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The applicability of three methods developed by finite element analysis (FEM) and proposed in the literature are studied on steel S355. Instrumented indentation tests using spherical indenters of radius 200 and 500 μ m are performed in the macro range at depths of more than 6 μ m. The results of the selected methods are compared with the tensile test. To evaluate the partially strongly varying results, the uncertainties of the calculated strain hardening exponent, n, and yield stress, Y, are estimated. Recommendations for an appropriated procedure of the indentation test are given. The machine compliance and the determination of the zero point of Depth play an essential role. If the certain conditions are considered, the instrumented indentation Tests can be used, in particular for investigations of specimens with inhomogeneous elastoplasticity.
Pollution through emission of toxic gases is an increasing problem for the environment. It affects similarly agricultural, industrial and urban areas. In future, environmental emissions in ambient air must be monitored at even lower concentrations as nowadays. One environmental relevant compound is ammonia and its conversion product ammonium that have strong negative impact on human health and ecosystems. Most ammonia measurements in ambient air are performed in the range below 1000 nmol·mol 1 and thus there is a need for reliable traceable ammonia gas standards and in addition in situ analytical procedures for monitoring (in ambient air to avoid that thresholds are exceeded). Therefore, the use of reference materials is necessary for development accompanying test or for calibration, e. g. of structure-integrated sensors and mobile multi-gas sensors.
The developed gas standard generator produces gas mixtures that comply with the metrological traceability for ammonia gas standards in the desired environmentally relevant measurement range. The method is based on the permeation of ammonia through a membrane at constant temperature and pressure. The resulting ammonia penetrant gas flow is then mixed with a carrier gas flow to generate a gas standard flow of known concentration. The dynamic rage is enlarged by using a two dilution steps. Depending on the permeation rate, generable molar fractions are possible in the range nmol·mol-1 to a few µmol·mol-1. We present the design of an ammonia gas standard generator and first results of the characterisation of its individual components supporting the uncertainty assessment according to GUM for stable gas concentrations in this range. The relative uncertainty of the generated ammonia gas standard is smaller than 4 % (k = 2).
Emissions of ammonia into the environment are mainly caused by agriculture, but also by combustion processes in waste and by road traffic. Even at low concentrations, this substance is not only an odour nuisance, but also a substance with ecological and climatic relevance. Therefore, BAM tested commercial electrochemical, and metal oxide based sensors, which have limited suitability for measuring in the environmental molar fraction range. Alternatively, own developments for the detection of ammonia in the trace range were implemented, wherein the analyte is measured by changing the fluorescence of a BODIPY dye at 550 nm by means of a portable fluorescence sensor directly from the gas phase. For the calibration of ammonia sensors and measuring instruments, a stationary system based on the mixture of certified test gases from pressure cylinders with calibrated mass flow controllers is available. A test gas generator was developed for on-site calibration and testing of sensors and measuring devices. The generation of ammonia-containing gases in the environmental relevant range of levels below 1000 nmol/mol is carried out by the permeation method according to ISO 6145-10. For the traceability of ammonia, standards are provided and further developed by the National Metrological Institutes and designated institutes. Metrological standards are based on SI units and are a basis for traceability of sensors or gas analysers.
Pollution through emission of toxic gases is an increasing problem for the environment. It affects similarly agricultural, industrial and urban areas. In future, environmental emissions in ambient air must be monitored at even lower concentrations as nowadays. One environmental relevant compound is ammonia and its conversion product ammonium that have strong negative impact on human health and ecosystems. Most ammonia measurements in ambient air are performed in the range below 1000 nmol·mol-1 and thus there is a need for reliable traceable ammonia gas standards and in addition in situ analytical procedures for monitoring (in ambient air to avoid that thresholds are exceeded). Therefore, the use of reference materials is necessary for development accompanying test or for calibration, e. g. of structure-integrated sensors and mobile multi-gas sensors.
The developed gas standard generator produces gas mixtures that comply with the metrological traceability for ammonia gas standards in the desired environmentally relevant measurement range. The method is based on the permeation of ammonia through a membrane at constant temperature and pressure. The resulting ammonia penetrant gas flow is then mixed with a carrier gas flow to generate a gas standard flow of known concentration. The dynamic rage is enlarged by using a two dilution steps. Depending on the permeation rate, generable molar fractions are possible in the range nmol·mol-1 to a few µmol·mol-1. We present the design of an ammonia gas standard generator and first results of the characterisation of its individual components supporting the uncertainty assessment according to GUM for stable gas concentrations in this range. The relative uncertainty of the generated ammonia gas standard is smaller than 4 % (k = 2).
In the near future, it will be important to adopt innovative approaches and technologies in order to further guarantee the reliability and availability of the highway network. New tools are therefore needed in order 'to obtain in-depth information about the condition of bridges and its development early enough before significant, precarious damage cases occur. In 2011, the research program "Intelligente Brücken (Smart Bridges)" was launched by the BASt together with the BMVI to evolve systems for information and holistic evaluation for bridge structures as a supplement to the current inspection-based maintenance management. Several projects dealt with the topic in the last few years and provided guidelines and a solid basis to move towards a first implementation considering the input of all research projects carried out so far.
To quantify the moisture in concrete, RFID based humidity sensors are embedded. Passive high frequency, ultra-high frequency RFID tags as well as active Bluetooth sensors are tested. After concreting, all sensors measure the corresponding relative humidity to monitor the concrete moisture. Two case studies are performed, embedding in an existing construction, i.e. the duraBASt test bridge, and embedding in cement based mortar in the laboratory. As basis for robust and long-life sensors in alkaline concrete, different casing materials are tested. Furthermore, signal strength measurements and their sensitivity to different moisture levels are performed.
Damages in infrastructure due to moisture amount to billions of Euros every year. For a more predictive structural health monitoring in civil engineering, the detection and monitoring of hazardous moisture in steel reinforced concrete constructions is of high interest. The sensors have to be wireless, elsewise they weaken the concrete cover of the rebars. The lifetime of such constructions is normally decades, thus the sensors have to be battery-free and fully passive. Considering these requirements, passive RFID-based sensors are developed. Communication and energy supply are realized wireless via the electromagnetic field of a RFID transmitter. The passive RFIDbased sensors are embedded into the concrete to enable the monitoring of moisture transport in porous materials. Results of the hydration process are shown.
In civil engineering, many structures are made of reinforced concrete. Most Degradation processes relevant to this material, e.g., corrosion, are related to an increased level of material moisture.
Therefore, moisture monitoring in reinforced concrete is regarded as a crucial method for structural health monitoring. In this study, passive radio frequency identification (RFID)-based sensors are embedded into the concrete. They are well suited for long-term operation over decades and are well protected against harsh environmental conditions. The energy supply and the data transfer of the humidity sensors are provided by RFID. The sensor casing materials are optimised to withstand the high alkaline environment in concrete, having pH values of more than 12. Membrane materials are also investigated to identify materials capable of enabling water vapour transport from the porous cement matrix to the embedded humidity sensor. By measuring the corresponding relative humidity with embedded passive RFID-based sensors, the cement hydration is monitored for 170 days.
Moreover, long-term moisture monitoring is performed for more than 1000 days. The Experiments show that embedded passive RFID-based sensors are highly suitable for long-term structural health monitoring in civil engineering.
A high-performance fiber Bragg grating-based (FBG) sensor device has been developed for the detection of small magnetic fields. Based on a smart multilayer jacket around the fibre over the physical length of the FBG, magnetic fields generated by rotating machine parts, power generators or power cable can be easily detected, analysed and evaluated. Consequently, this innovative, on-line and non-contact inspection method results in an increase in quality and reliability of high-performing machine parts, devices and cables. The basic physical principle is based on a magnetostrictive multilayer system that strains the high-resolution FBG element in presence of magnetic fields. Subsequently, a fixed relationship between induced magnetic field and wavelength change of the FBG element describes the characteristic sensitivity curve. Intensive tests regarding characterisation of this magnetic field FBG sensor have been carried out and its performance has been evaluated.
Sensors integrated into devices and structures provide essential data to control, optimize or manage machines and structural components. In the last years, processes, applications and machine parts became more and more intelligent. Consequently, the need for sensor validation increased significantly in order to rely on sensor data and measurement results.
Structure-integrated fibre optic strain sensors, such as fiber Bragg gratings (FBG), are of special interest in the composite manufacturing industry. This type of sensor makes it possible to gain information and to collect measurement data about entire production processes and whole life-time cycles of composite-made machine parts and structures. However, validation concepts and approaches for this type of sensors are barely reported in literature. Furthermore, all the reported activities have the drawback that the sensor diagnosis strategy is implemented as limited mathematical models and/or complex time-consuming spectral analysis tools which are applied in data post-processing loops. However, to automate sensor validation and to apply real-time and in-field sensor fault detection, it is necessary to acquire measurement data and information about the measurement reliability at the same time.
An auto-validation tool for the reliability quantification of materials integrated fiber Bragg grating (FBG) strain sensors have been developed and tested. The FBG strain sensor was jacketed with a magnetostrictive layer based on iron-nickel which, when excited by a specific magnetic field, adds an artificial strain to the sensor. The fixed relationship between magnetic induction and wavelength shift of the FBG strain sensor characterizes the bond strength and adhesion between the sensor and the surrounding structure. Due to an easily applicable magnetic field, it is possible to validate the sensor performance in a non-contact, fast way without disturbing the data-acquisition process.
A new concept for the self-diagnosis of embedded fiber Bragg grating (FBG) strain sensors was developed, simulated and experimentally tested. This concept is based on a magnetostrictive metallic layer directly coated on the fibre cladding over the grating segment of the FBG sensor, so that an on-demand external magnetic field in a millitesla scale can produce a controllable artificial strain as an indication signal for the remote optical interrogator. The relationship between the pre-defined magnetic field and its induced Bragg wavelength shift characterizes this validation concept. Any deviation of the local bonding state of the interfaces from the initial or/and any change of shear strain transferring mechanism from composite matrix to the optical fibre core will result in alterations in this sensitive relationship, and thus triggers an immediate alert for a further inspection. The finite element method is used to simulate the strain of this configuration as result of different values of the magnetic field in order to optimize the geometrical sensor parameters. The simulations are verified by experiments results. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thermogravimetry (TG), thermogravimetry coupled with mass spectroscopy (TG-MS) and thermogravimetry coupled with Fourier transform infrared spectroscopy (TG-FTIR) were used to characterise the thermo-oxidative behaviour of two intumescent coating materials. The temperature dependence, the corresponding volatile products and the amount of residue of the different processes were determined. Using both TG-MS and TG-FTIR results in an unambiguous interpretation of the volatile products. Characteristics such as the influence of endothermic reactions, the release of non-flammable gases, the dehydrogenation enhancing the char formation and the stability of the cellular char were discussed in detail. It was demonstrated, that TG, TG-MS and TG-FTIR are powerful methods to investigate mechanisms in intumescent coatings and that they are suitable methods in respect to quality assurance and unambiguous identification of such materials.
Nanocomposites of bisphenol A polycarbonate with 2, 4, 6, and 15 wt% multiwall carbon nanotubes (MWNT) and their use in fire retardancy are investigated. Their thermal behavior and pyrolysis are characterized using thermogravimetry, differential scanning calorimeter, oscillatory shear rheology, and dynamic mechanical analysis. The flammability is addressed using LOI and UL 94; the fire behavior, with a cone calorimeter using different irradiation. With increasing MWNT content the storage modulus is increased (10-20%) and melt viscosity increases by several orders of magnitude, particularly for low shear rates. The melt flow, dripping, and deformation during fire are hindered, which influences UL 94 and cone calorimeter results. The peak heat release rate is reduced up to 40-50% due to an improved barrier for small amounts (2 wt%) of MWNT and for low irradiation, whereas the effect is reduced for increasing irradiation and nearly vanishes for increasing filling. Adjuvant but also deleterious mechanisms result in the complex dependency on the MWNT content. Significant flame retardancy effects are specific and limited to only some fire properties. This study allows the materials' potential for implementation in different fire scenarios and tests to be assessed and provides insight into active mechanisms.
Barrier formation and increasing the melt viscosity are addressed as the two main general fire retardancy mechanisms of polymer nanocomposites. They result in specific impacts on fire properties that consequentially cause varying flame retardancy efficiency in different fire tests. The barrier formation retards mainly flame spread (peak of heat release rate) in developing fires, but does not reduce fire load (total heat evolved), ignitability or flammability (limiting oxygen index, UL 94). Furthermore, this flame retardancy effect increases with increasing irradiation and vanishes with decreasing irradiation. The increased melt viscosity prevents dripping, which is beneficial or disadvantageous depending on the fire test used. In some test, it become the dominant influence, transforming self-extinguishing samples into flammable materials or causing wicking. Advantages and the limits are sketched comprehensively for exploiting the main general fire retardancy mechanisms of polymer nanocomposites. It is concluded that barrier formation and changing the melt viscosity in nanocomposites are not sufficient for most applications, but must be accompanied by additional mechanisms in special systems or in combination with other flame retardants.
The cone calorimeter has become one of the most important and widely used instruments for the research and development of fire retarded polymeric materials. The paper addresses three important ways in which the principal setup influences the results factors which sometimes do not receive due consideration when drawing conclusions. The paper discusses in detail the impact on cone calorimeter results of the choice of external heat flux, the influence on the peak of heat release rate of sample thickness and thermal feedback from the back of the sample, and the influence on irradiance of the horizontal and vertical distances from the cone heater.
The exploration of condensed phase mechanisms such as charring and intumescence has been pushed forward in the last decades, since it is believed that focusing on these concepts will bring materials closer to an efficient and ecologically friendly fire retardancy. They promise to concentrate efficient fire retardancy at the key position between pyrolysis zone and gas phase. Examples of residue/char forming and intumescent materials are used to illustrate the influence of mass and heat barrier effects on the fire behavior of materials and general results are presented. A comprehensive understanding of the mechanisms and structure-property relationships in fire retardancy is presented.
Concept for investigating mechanical and thermal impacts on distributed subsurface gas monitoring
(2016)
A multifunctional sensor in line shape was developed and introduced in previous work for measuring of gas concentrations, temperature change, and strain. A current field study focuses on a spatially distributed monitoring of subsurface CO 2 gas storage sites in near real time.
Mechanical impacts, e.g., caused by construction work, denudation, and seismic activity, can affect the integrity of underground gas storage sites. Thermal or moisture impacts, e.g., caused by weather conditions, can influence the gas Distribution behavior. In this paper, we briefly describe the setup of a CO 2 injection soil test field. This setup contains actuating elements for the investigation of mechanical and thermal impacts on distributed subsurface gas monitoring. A concept is given for evaluating these impacts and first experimental results are presented.
A multifunctional sensor in line shape was developed and introduced in previous work for measuring of gas concentrations, temperature change, and strain. A current field study focuses on a spatially distributed monitoring of subsurface CO2 gas storage sites in near real time.
Mechanical impacts, e.g., caused by construction work, denudation, and seismic activity, can affect the integrity of underground gas storage sites. Thermal or moisture impacts, e.g., caused by weather conditions, can influence the gas distribution behavior. In this paper, we briefly describe the setup of a CO2 injection soil test field. This setup contains actuating elements for the investigation of mechanical and thermal impacts on distributed subsurface gas monitoring. A concept is given for evaluating these impacts and first experimental results are presented.
BAM Federal Institute for Materials Research and Testing, in cooperation with the company MeGaSen UG carries out a research project to enhance and validate an innovative approach for distributed subsurface monitoring of gas storage areas. The concept combines different measurement technologies to one multifunctional sensor: membrane-based gas measurement technology for in-situ monitoring of gases in soil and fiber optical sensing of temperature and strain (as a measure for structural change). Key aspect of the research project is the first-time validation of the system in an application relevant dimension. For this purpose a 20 x 20 m2 test field is build. A comprehensive validation of the system is carried out by systematic variation of different parameters like position-dependent gasinjection, temperature and mechanical impact.
A 400 m² soil test field with gas injection system was built up for the purpose of large-scale validation, optimization, and characterization of a novel comprehensive monitoring method for underground gas storage areas. The method combines gas sensing technology with linear form factor for in-situ monitoring of gases in soil with the mapping capabilities of Computed Tomography (CT) to reconstruct time-series of gas distribution maps based on samples of orthogonally-aligned linear gas sensors. Several injection experiments with carbon dioxide (CO2) at different days with varying boundary conditions indicates the potential of the method for, e.g., rapid leakage detection with respect to Carbon Capture and Storage (CCS) issues.
Leaking methane (CH4) from infrastructures, such as pipelines and landfills, is critical for the environment but can also pose a safety risk. To enable a fast detection and localization of these kind of leaks, we developed a novel robotic platform for aerial remote gas sensing. Spectroscopic measurement methods for remote sensing of selected gases lend themselves for use on mini-copters, which offer a number of advantages for inspection and surveillance over traditional methods. No direct contact with the target gas is needed and thus the influence of the aerial platform on the measured gas plume can be kept to a minimum. This allows to overcome one of the major issues with gas-sensitive mini-copters. On the other hand, remote gas sensors, most prominently Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensors have been too bulky given the payload and energy restrictions of mini-copters. Here, we present the Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), which combines a novel lightweight TDLAS sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile hexacopter. The proposed system can be deployed in scenarios that cannot be addressed by currently available robots and thus constitutes a significant step forward for the field of Mobile Robot Olfaction (MRO). It enables tomographic reconstruction of gas plumes and a localization of gas sources. We also present first results showing its performance under realistic conditions.
In this paper, we show that a micro unmanned aerial vehicle (UAV) equipped with commercially available gas sensors can address environmental monitoring and gas source localization (GSL) tasks. To account for the challenges of gas sensing under real-world conditions, we present a probabilistic approach for GSL that is based on a particle filter (PF). Simulation and real-world experiments demonstrate the suitability of this algorithm for micro UAV platforms.
In this paper, we show that a micro unmanned aerial vehicle (UAV) equipped with commercially available gas sensors can address environmental monitoring and gas source localization (GSL) tasks. To account for the challenges of gas sensing under real-world conditions, we present a probabilistic approach to GSL that is based on a particle filter (PF). Simulation and real-world experiments demonstrate the suitability of this algorithm for micro UAV platforms.
A monitoring method is introduced that creates twodimensional (2D) maps of the soil gas distribution. The method combines linear gas sensing technology for in-situ monitoring of gases in soil with the mapping capabilities of Computed Tomography (CT) to reconstruct spatial and temporal resolved gas distribution maps. A weighted iterative algebraic reconstruction method based on Maximum Likelihood with Expectation Maximization (MLEM) in combination with a source-by-source reconstruction approach is introduced that works with a sparse setup of orthogonally-aligned linear gas sensors. The reconstruction method successfully reduces artifact production, especially when multiple gas sources are present, allowing the discrimination between true and non-existing so-called ghost source locations. Experimental validation by controlled field experiments indicates the high potential of the proposed method for rapid gas leak localization and quantification with respect to Pipeline or underground gas storage issues.
A 400 m² soil test field with gas injection system was built up, which enables an experimental validation of linear gas sensors for specific applications and gases in an application-relevant scale. Several injection and soil watering experiments with carbon dioxide (CO2) at different days with varying boundary conditions were performed indicating the potential of the method for, e.g., rapid leakage detection with respect to Carbon Capture and Storage (CCS) issues.
This work presents first results from repetitive CO2 injection experiments performed on a recently built-up 400 m² soil test field with gas injection system. The test field contains 48 membrane-based linear gas sensors that were installed in several depths of the test field. Sensors for measuring meteorological parameters (e.g., wind / rain) and the parameters soil temperature, soil moisture, and groundwater level were installed additionally.
A 400 m2 soil test field with gas injection system was built up, which enables an experimental validation of linear membrane-based gas sensors – a sensor technology which was developed based on the selective permeation of gases through membranes. Several soil watering and injection experiments with carbon dioxide at different days with varying boundary conditions were performed showing that the sensor behaves mostly insensitive to the environmental conditions investigated, i.e., barometric pressure fluctuations, soil temperature, air temperature and humidity, sun duration, and wind speed. Furthermore, depending on water infiltration, a gas phase displacement could be observed in-situ based on the changed measurement signal. The results of the validation experiments highlight the potential of the method for rapid leak detection and localization qualifying the sensor particularly for safety applications, e.g., in underground gas storage areas.
One of the main unsolved issues of under-ground storages for, e.g., CO2, H2, and natural gas is the comprehensive surveillance of these areas with reasonable effort and costs. Conventional sensors (e.g., soil air probes or borehole probes), however, can only be used for punctual or locally limited measurements; further their application can cause structural influences (invasive application).
In this paper, we describe in detail the setup of a CO2 injection soil test field. This test field will be used to enhance and validate an innovative ap-proach for distributed subsurface monitoring of gas storage areas. To the author’s knowledge, this is the first time that, for this purpose, a test field is built in an application relevant scale.
In this paper, we present and validate the concept of an autonomous aerial robot to reconstruct tomographic 2D slices of gas plumes in outdoor environments. Our platform, the so-called Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), combines a lightweight Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor with a 3-axis aerial stabilization gimbal for aiming at a versatile octocopter. While the TDLAS sensor provides integral gas concentration measurements, it does not measure the distance traveled by the laser diode’s beam nor the distribution of gas along the optical path. Thus, we complement the set-up with a laser rangefinder and apply principles of Computed Tomography (CT) to create a model of the spatial gas distribution from a set of integral concentration measurements. To allow for a fundamental ground truth evaluation of the applied gas tomography algorithm, we set up a unique outdoor test environment based on two 3D ultrasonic anemometers and a distributed array of 10 infrared gas transmitters. We present results showing its performance characteristics and 2D plume reconstruction capabilities under realistic conditions. The proposed system can be deployed in scenarios that cannot be addressed by currently available robots and thus constitutes a significant step forward for the field of Mobile Robot Olfaction (MRO).
Leaking methane (CH4) from infrastructures, such as pipelines and landfills, is critical for the environment but can also pose a safety risk. To enable a fast detection and localization of these kind of leaks, we developed a novel robotic platform for aerial remote gas sensing. Spectroscopic measurement methods for remote sensing of selected gases lend themselves for use on mini-copters, which offer a number of advantages for inspection and surveillance over traditional methods. No direct contact with the target gas is needed and thus the influence of the aerial platform on the measured gas plume can be kept to a minimum. This allows to overcome one of the major issues with gas-sensitive mini-copters. On the other hand, remote gas sensors, most prominently Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensors have been too bulky given the payload and energy restrictions of mini-copters. Here, we present the Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), which combines a novel lightweight TDLAS sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile hexacopter. The proposed system can be deployed in scenarios that cannot be addressed by currently available robots and thus constitutes a significant step forward for the field of Mobile Robot Olfaction (MRO). It enables tomographic reconstruction of gas plumes and a localization of gas sources. We also present first results showing its performance under realistic conditions.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.
In this paper, we present an autonomous aerial robot to reconstruct tomographic 2D slices of gas plumes in outdoor environments. Our platform, the so-called Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS) combines a lightweight Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile octocopter. The TDLAS sensor provides integral gas concentration measurements but no information regarding the distance traveled by the laser diode's beam or the distribution of the gas along the optical path. We complemented the set-up with a laser rangefinder and apply principles of Computed Tomography (CT) to create a model of the spatial gas distribution from these integral concentration measurements. To allow for a rudimentary ground truth evaluation of the applied gas tomography algorithm, we set up a unique outdoor test environment based on two 3D ultrasonic anemometers and a distributed array of 10 infrared gas transmitters. We present first results showing the 2D plume reconstruction capabilities of the system under realistic conditions.
In this paper, we introduce a nano aerial robot swarm for indoor air quality monitoring applications such as occupational health and safety of (industrial) workplaces. The concept combines a robotic swarm composing of nano Unmanned Aerial Vehicles (nano UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight metal oxide gas sensors for measuring the Total Volatile Organic Compound (TVOC) in ppb and estimating the eCO2 (equivalent calculated carbon-dioxide) concentration in ppm. TVOC is a measure for the indoor air quality. An indoor localization and positioning system will be used to estimate the absolute 3D position of the swarm like GPS. Based on this novel indoor air quality monitoring concept, the development and validation of new algorithms in the field of Mobile Robot Olfaction (MRO) are planned, namely gas source localization and gas distribution mapping. A test scenario will be built up to validate and optimize the gas-sensitive nano aerial robot swarm for the intended applications.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.
In this paper, we introduce a nano aerial robot swarm for Indoor Air Quality (IAQ) monitoring applications such as occupational health and safety of (industrial) workplaces. The robotic swarm is composed of nano Unmanned Aerial Vehicles (UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight Metal Oxide (MOX) gas sensors for measuring the Total Volatile Organic Compound (TVOC), which is a measure for IAQ. An indoor localization and positioning system is used to estimate the absolute 3D position of the swarm similar to GPS. A test scenario was built up to validate and optimize the swarm for the intended applications. Besides calibration of the IAQ sensors, we performed experiments to investigate the influence of the rotor downwash on the gas measurements at different altitudes and compared them with stationary measurements. Moreover, we did a first evaluation of the gas distribution mapping performance. Based on this novel IAQ monitoring concept, new algorithms in the field of Mobile Robot Olfaction (MRO) are planned to be developed exploiting the abilities of an aerial robotic swarm.
In this paper, we introduce a nano aerial robot swarm for Indoor Air Quality (IAQ) monitoring applications such as occupational health and safety of (industrial) workplaces. The robotic swarm is composed of nano Unmanned Aerial Vehicles (UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight Metal Oxide (MOX) gas sensors for measuring the Total Volatile Organic Compound (TVOC), which is a measure for IAQ. An indoor localization and positioning system is used to estimate the absolute 3D position of the swarm similar to GPS. A test scenario was built up to validate and optimize the swarm for the intended applications. Besides calibration of the IAQ sensors, we performed experiments to investigate the influence of the rotor downwash on the gas measurements at different altitudes and compared them with stationary measurements. Moreover, we did a first evaluation of the gas distribution mapping performance. Based on this novel IAQ monitoring concept, new algorithms in the field of Mobile Robot Olfaction (MRO) are planned to be developed exploiting the abilities of an aerial robotic swarm.
This paper presents first advances in the area of aerial chemical trail following. For that purpose, we equipped a palm-size aerial robot, based on the Crazyflie 2.0 quadrocopter, with a small lightweight metal oxide gas sensor for measuring evaporated ethanol from chemical trails. To detect and localize a 5 cm wide chemical trail, a detection criterion was developed that uses only relative changes in the transient phase of the sensor response. The reduction in signal strength dependence improves the robustness of its application. We tested our setup in first crossing-trail experiments showing that our flying ant robot can correlate an odor hit with the chemical trail within 0.14 m. Principally, this could enable aerial chemical trail following in the future.
This paper presents first advances in the area of aerial chemical trail following. For that purpose, we equipped a palm-size aerial robot, based on the Crazyflie 2.0 quadrocopter, with a small lightweight metal oxide gas sensor for measuring evaporated ethanol from chemical trails. To detect and localize the chemical trail, a novel detection criterion was developed that uses only relative changes in the transient phase of the sensor response, making it more robust in its application. We tested our setup in first crossing-trail experiments showing that our flying ant robot is able to correlate an odor hit with the chemical trail within 0.14 m. Principally, this could enable aerial chemical trail following in the future.
This paper presents first advances in the area of aerial chemical trail following. For that purpose, we equipped a palm-size aerial robot, based on the Crazyflie 2.0 quadrocopter, with a small lightweight metal oxide gas sensor for measuring evaporated ethanol from chemical trails. To detect and localize the chemical trail, a novel detection criterion was developed that uses only relative changes in the transient phase of the sensor response, making it more robust in its application. We tested our setup in first crossing-trail experiments showing that our flying ant robot is able to correlate an odor hit with the chemical trail within 0.14 m. Principally, this could enable aerial chemical trail following in the future.
One challenge associated with navigating a nano aerial robot swarm indoors in unstructured environments is, i.a., the limited air space. To avoid an over-regulation of the available indoor air space (e.g., prohibit copters to fly above each other), a safety region around each copter must be defined. In this paper, we investigate the impact of the downwash of a nano-drone on the stability of another nearby nano-drone. In the experiments, we found out that this downwash has a negative influence of a second nano-drone in a distance of around 1 m vertically and 0.2 m horizontally. Based on the obtained data, we developed a model describing the above-mentioned safety region to enable a safe operation of the swarm in these environments with fewer constraints.
Using a swarm of copter-based gas-sensitive aerial nano robots for monitoring indoor air quality is challenging due to, e.g., limited air space in buildings. To avoid an over-regulation of the available indoor air space (e.g., prohibit copters to fly above each other), a safety region around each copter must be defined to guarantee a safe operation of the swarm.
The key contributions of this paper are the realization of experiments that investigate the influence of the rotor downwash on flying vertically displaced nano robots and the development of a model describing the above-mentioned safety region.
Monitoring and maintenance of civil infrastructure are of great importance, as any undetected damage can cause high repair costs, unintended deadtime, or endanger structural integrity. The inspection of large concrete structures such as bridges and parking lots is particularly challenging and time-consuming. Traditional methods are mostly manual and involve mapping a grid of measurement lines to record the position of each measurement. Current semi-automated methods, on the other hand, use GPS or tachymeters for localization but still require trained personnel to operate. An entirely automated approach using mobile robots would be more cost- and time-efficient. While there have been developments in using GPS-enabled mobile robots for bridge inspection, the weak signal strength in indoor areas poses a challenge for the automated inspection of structures such as parking lots. This paper aims to develop a solution for the automated inspection of large indoor concrete structures by addressing the problem of robot localization in indoor spaces and the automated measurement of concrete cover and rebar detection.
Gas sensors in linear form based on the measuring principle of gas selective permeability through a membrane were developed and introduced for the detection and quantification of gas concentrations. A current field study focuses on measuring CO2 concentrations for a spatially distributed monitoring of subsurface CO2 gas storage sites in near real time. A 400 m(2) test site and a corresponding laboratory system were built up to characterize, validate, and optimize the sensor. A calibration routine was developed, which can be applied subsequently to underground installation. First measurement results indicate the potential of the method.
Gas sensors in linear form based on the measuring principle of gas selective permeability through a membrane were developed and introduced for the detection and quantification of gas concentrations. A current field study focuses on measuring CO2 concentrations for a spatially distributed monitoring of subsurface CO2 gas storage sites in near real time. A 400 m² test site and a corresponding laboratory system were built up to characterize, validate, and optimize the sensor. A calibration routine was developed, which can be applied subsequently to underground installation. First measurement results indicate the potential of the method.
Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms
(2013)
Gas source localization (GSL) with mobile robots is a challenging task due to the unpredictable nature of gas dispersion, the limitations of the currents sensing technologies, and the mobility constraints of ground-based robots. This work proposes an integral solution for the GSL task, including source declaration. We present a novel pseudo-gradient-based plume tracking algorithm and a particle filter-based source declaration approach, and apply it on a gas-sensitive micro-drone. We compare the performance of the proposed system in simulations and real-world experiments against two commonly used tracking algorithms adapted for aerial exploration missions.
Insect behavior is a common source of inspiration for roboticists and computer scientists when designing gas-sensitive mobile robots. More specifically, tracking airborne odor plumes, and localization of distant gas sources are abilities that suit practical applications such as leak localization and emission monitoring. Gas sensing with mobile robots has been mostly addressed with ground-based platforms and under simplified conditions and thus, there exist a significant gap between the outstanding insect abilities and state-of-the-art robotics systems. As a step toward practical applications, we evaluated the performance of three biologically inspired plume tracking algorithms. The evaluation is carried out not only with computer simulations, but also with real-world experiments in which, a quadrocopter-based micro Unmanned Aerial Vehicle autonomously follows a methane trail toward the emitting source. Compared to ground robots, micro UAVs bring several advantages such as their superior steering capabilities and fewer mobility restrictions in complex terrains. The experimental evaluation shows that, under certain environmental conditions, insect like behavior in gas-sensitive UAVs is feasible in real-world environments.
Insect behavior is a common source of inspiration for roboticists and computer scientists when designing gas-sensitive mobile robots. More specifically, tracking airborne odor plumes and localization of distant gas sources are abilities that suit practical applications such as leak localization and emission monitoring. Gas sensing with mobile robots has been mostly addressed with ground-based platforms and under simplified conditions and thus, there exist a significant gap between the outstanding insect abilities and state of the art robotics systems. As a step towards practical applications, we evaluated the performance of three biologically inspired plume tracking algorithms. The evaluation is carried out not only with computer simulations, but also with real-world experiments in which, a quadrocopter-based micro Unmanned Aerial Vehicle autonomously follows a methane trail towards the emitting source. Compared to ground robots, micro UAVs bring several advantages such as their superior steering capabilities and fewer mobility restrictions in complex terrains. The experimental evaluation shows that, under certain environmental conditions, insect like behavior in gas-sensitive UAVs is feasible in real world environments.
BAM Federal Institute for Materials Research and Testing, in cooperation with the AirRobot GmbH & Co. KG company, has developed a flying remote-controlled measuring system. The system is capable of operating in a variety of scenarios of gas emissions, e.g. exhaust gas from chimneys, flue gas in a fire, gas emissions in the case of an accident of chemical or hazardous goods or in the case of a terrorist act involving toxic gases. Thus it can measure the gas concentration in the immediate vicinity of the object which causes the emission. A further stage of extension is to enhance the system for plume tracking and identification of sources of hazardous gases.
A monitoring method is introduced that creates, in near real-time, two-dimensional (2D) maps of the soil gas distribution. The method combines linear gas sensing technology for in-situ monitoring of gases in soil with the mapping capabilities of Computed Tomography (CT) to reconstruct spatial and temporal resolved gas distribution maps. A weighted iterative algebraic reconstruction method based on Maximum Likelihood with Expectation Maximization (MLEM) in combination with a source-by-source reconstruction approach is introduced that works with a sparse setup of orthogonally-aligned linear gas sensors. The reconstruction method successfully reduces artifact production, especially when multiple gas sources are present, allowing the discrimination between true and non-existing so-called ghost source locations. A first experimental test indicates the high potential of the proposed method for, e.g., rapid gas leak localization.
Real-time wind estimation on a micro unmanned aerial vehicle using its inertial measurement unit
(2015)
This paper presents an approach for a quadrocoper-based micro unmanned aerial vehicle (UAV) that estimates the wind vector (speed and direction) in real-time based on measurement data of its on-board sensors only. This method does not need any additional airspeed sensor or dedicated anemometer, and thus the micro UAV's valuable payload remains free for other sensors. Wind tunnel and field tests were used to evaluate the performance of the approach. In order to quantify its accuracy, experiments are presented where data was collected with an anemometer placed in an open field with the micro UAV in flight following a predefined trajectory around the anemometer and hovering at a defined position close to it.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.
Leaking methane (CH4) from infrastructures, such as pipelines and landfills, is critical for the environment but can also pose a safety risk. To enable a fast detection and localization of These kind of leaks, we developed a novel robotic platform for aerial remote gas sensing - the so-called Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS).
Monitoring and maintenance of civil infrastructure are of great importance, as any undetected damage can cause high repair costs, unintended deadtime, or endanger structural integrity. The inspection of large concrete structures such as bridges and parking lots is particularly challenging and time-consuming. Traditional methods are mostly manual and involve mapping a grid of measurement lines to record the position of each measurement. Current semi-automated methods, on the other hand, use GPS or tachymeters for localization but still require trained personnel to operate. An entirely automated approach using mobile robots would be more cost- and time-efficient. While there have been developments in using GPS-enabled mobile robots for bridge inspection, the weak signal strength in indoor areas poses a challenge for the automated inspection of structures such as parking lots. This paper aims to develop a solution for the automated inspection of large indoor concrete structures by addressing the problem of robot localization in indoor spaces and the automated measurement of concrete cover and rebar detection.
This paper presents a sampling strategy for mobile gas sensors. Sampling points are selected using a modified artificial potential field (APF) approach, which balances multiple criteria to direct sensor measurements towards locations of high mean concentration, high concentration variance and areas for which the uncertainty about the gas distribution model is still large. By selecting in each step the most often suggested close-by measurement location, the proposed approach introduces a locality constraint that allows planning suitable paths for mobile gas sensors. Initial results in simulation and in real-world experiments with a gas-sensitive micro-drone demonstrate the suitability of the proposed sampling strategy for gas distribution mapping and its use for gas source localization.
This article presents the development and validation of an autonomous, gas sensitive microdrone that is capable of estimating the wind vector in real time using only the onboard control unit of the microdrone and performing gas distribution mapping (DM). Two different sampling approaches are suggested to address this problem. On the one hand, a predefined trajectory is used to explore the target area with the microdrone in a real-world gas DM experiment. As an alternative sampling approach, we introduce an adaptive strategy that suggests next sampling points based on an artificial potential field (APF). Initial results in real-world experiments demonstrate the capability of the proposed adaptive sampling strategy for gas DM and its use for gas source localization.
Carbon capture & storage (CCS) is one of the most promising technologies for greenhouse gas (GHG) management. However, an unsolved issue of CCS is the development of appropriate long-term monitoring systems for leak detection of the stored CO2. To complement already existing monitoring infrastructure for CO2 storage areas, and to increase the granularity of gas concentration measurements, a quickly deployable, mobile measurement device is needed. In this paper, we present an autonomous gas-sensitive micro-drone, which can be used to monitor GHG emissions, more specifically, CO2. Two different measurement strategies are proposed to address this task. First, the use of predefined sensing trajectories is evaluated for the task of gas distribution mapping using the micro-drone. Alternatively, we present an adaptive strategy, which suggests sampling points based on an artificial potential field (APF). The results of real-world experiments demonstrate the feasibility of using gas-sensitive micro-drones for GHG monitoring missions. Thus, we suggest a multi-layered surveillance system for CO2 storage areas.
QI-Digital is a joined project aiming at digitalising Quality Infrastructure (QI) processes involving standardization, conformity assessment, accreditation, metrology, and market surveillance [1]. Federal institute of material research and testing (BAM) is working on the creation of a digital calibration certifi-cate (DCC) to achieve digital metrological traceability and conformity assessment. The utilisation of machine readable and executable DCCs in the XML format is demonstrated on an example of a tem-perature measurement at a hydrogen refueling station. The certificates will be retrieved and analysed automatically at a Process Control System or at a Digital Twin.
Die Optimierung und Validierung des digitalen Wasserstofftankstellenmanagements mit Sensortechnologien ist das übergeordnete Ziel des Teilprojekts Digitale Qualitätsinfrastruktur mit Sensortechnologien (QIST) am Use Case H2, im Rahmen der digitalen Qualitätsinfrastruktur (QI digital[1]). Hierfür sollen u.a. Sensornetzwerke mit digital-gestützten Auswertungsstrategien intelligent gestaltet werden (Stichwort KI bzw. digitaler Zwilling). Verschiedene, sich ergänzende Sensoren, Systemkomponenten und KI-Methoden stehen als Bausteine intelligenter Sensorsysteme zur Verfügung, mit dem Zweck, die physikalischen und chemischen Parameter an und in Anlagen umfassend und effizient zu überwachen sowie Fehlfunktionen zuverlässig zu detektieren und zu interpretieren, Abbildung 1.
Konkrete Arbeitsschritte sind, nach dem Aufbau der Versuchsplattform „Wasserstofftankstelle“, die Instrumentierung von Sensorik und deren digitale Integration in das Tankstellenmanagementsystem sowie die Validierung im Realbetrieb. Die somit erzielten Messergebisse sowie die Messunsicherheiten, Historien und Verfahren werden in digitaler Form aufbereitet, gespeichert und fortlaufend in die KI-basierte Datenauswertung einbezogen, inkl. der Anbindung an die metrologische Rückführungskette.
Ziele sind:
• Einführung eines neuen messtechnischen Ansatzes und eines digitalen Zwillings für den Anwendungsfall "Wasserstofftankstelle" auf Basis der H2-Sensorik sowie der Zustandsgrößen Druck und Temperatur
• Qualitätssicherung durch Applikationen zuverlässiger Gassensorik, Manometer und Thermometer sowie KI-Methoden zur Prozesskontrolle und Detektion von Fehlfunktionen
• Nutzung von digitalen Kalibrierscheinen (DCCs) insbesondere für die Messgröße Temperatur zur Realisierung der metrologischen Rückführung in einer digitalen Qualitätsinfrastruktur
BAM is the German Federal Institute for Materials Research and Testing and the competent authority for mechanical and thermal safety assessment of transport packages for spent fuel and high level waste. In context with safety assessment of RAM packages BAM performed numerous drop tests in the last decades. The tests were mostly accompanied by extensive and various measurement techniques especially by instrumented measurements with strain gages and accelerometers. The procedure of drop testing and the resulting measurement analysis are the main methods to evaluate the safety against mechanical test conditions. Measurement techniques are dedicated to answer questions in regard to the structural integrity of a RAM package, the mechanical behavior of the prototype as well as of its content under impact conditions.
Test results like deceleration-time functions constitute a main basis for the validation of assumptions in the safety analysis and for the evaluation of numerical calculations. In this context the adequate selection of accelerometers and measurement systems for the performance of drop tests is important. Therefore it is not only necessary to find suitable positions for the accelerometers at the test specimens, but also to consider technical boundary conditions as e.g. temperature.
BAM is the German Federal Institute for Materials Research and Testing and the competent authority for mechanical and thermal safety assessment of transport packages for spent fuel and high level waste. In context with safety assessment of RAM packages BAM performed numerous drop tests in the last decades. The tests were mostly accompanied by extensive and various measurement techniques especially by instrumented measurements with strain gages and accelerometers.
The procedure of drop testing and the resulting measurement analysis are the main methods to evaluate the safety against mechanical test conditions. Measurement techniques are dedicated to answer questions in regard to the structural integrity of a RAM package, the mechanical behavior of the prototype as well as of its content under impact conditions.
Test results like deceleration-time functions constitute a main basis for the validation of assumptions in the safety analysis and for the evaluation of numerical calculations. In this context the adequate selection of accelerometers and measurement systems for the performance of drop tests is important. Therefore it is not only necessary to find suitable positions for the accelerometers at the test specimens, but also to consider technical boundary conditions as e.g. temperature.
Wastewater contains harmful chemicals and heavy metals that are known to cause various environmental and health problems. Therefore, the water quality control using sensitive, simple, fast, accurate, and portable tools is of great importance. This study aimed to evaluate the pollution parameters of wastewaters collected at different treatment stages from a wastewater treatment plant (WWTP) that treats domestic and industrial wastewaters by using an electronic nose (E-nose) and a voltammetric electronic tongue (E-tongue) combined with chemometric techniques. Water and wastewater pollution parameters determination were performed using inductively coupled plasma optical emission spectrometry for the determination of cations, and anions by using ion chromatography. Chemometric techniques, such as Principal Component Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to process the E-nose and E-tongue datasets to describe the similarities between the samples. In addition, Partial Least Squares Regression (PLSR) model was constructed using electronic sensing data to simultaneously predict the concentration values of physicochemical parameters. The obtained correlation coefficient, for training and testing sets, is higher than 0.91 for the prediction of the concentration of all physicochemical parameters, except for iron (Fe) which remains 0.84. These results suggest that simple, portable, and inexpensive tools such as electronic nose and tongue are suitable for wastewater analysis.
This work focuses on the design and fabrication of low-cost and fast-response of an electronic nose (E-nose) based on semiconductor gas sensors, for discriminating some synthetic gases such as ammonia (NH3), ethanol (C2H5OH), and hydrogen sulfide (H2S). Additionally, the capability of separating different concentration levels of each considered gases was checked. Dataset treatment of E-nose by using Principal Component Analysis (PCA) showed a good discrimination of the different synthetic gases. Furthermore, perfect classification was reached of different concentration levels of the analysed gases by using Discriminant Function Analysis (DFA). In the light of these results, it could be stated that the developed E-nose system constitutes an inexpensive, rapid, simple to use, and efficient tool for synthetic gases detection.
In this study, the ability of an electronic nose developed to analyze and monitor odor emissions from three poultry farms located in Meknes (Morocco) and Berlin (Germany) was evaluated. Indeed, the potentiality of the electronic nose (e-nose) to differentiate the concentration fractions of hydrogen sulfide, ammonia, and ethanol was investigated. Furthermore, the impact change of relative humidity values (from 15% to 67%) on the responses of the gas sensors was reported and revealed that the effect remained less than 0.6%. Furthermore, the relevant results confirmed that the developed e-nose system was able to perfectly classify and monitor the odorous air of poultry farms.
In this work, we demonstrate the ability of an electronic nose system based on an array of six-semiconductor gas sensors for outdoor air quality monitoring over a day at a traffic road in downtown of Meknes city (Morocco). The response of the sensor array reaches its maximum in the evening of the investigated day which may due to high vehicular traffic or/and human habits resulting in elevated concentrations of pollutants. Dataset treatment by Principal Component Analysis and Discriminant Function Analysis shows a good discrimination between samples collected at different times of the day. Moreover, Support Vector Machines were used and reached a classification success rate of 97.5 %. Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS) technique was used to validate the developed e-nose system by identifying the composition of the analyzed air samples. The discrimination obtained by e-nose system was in good agreement with the TD-GC-MS results. This study demonstrates the usefulness of TD-GC-MS and e-nose, providing high accuracy in discriminating outdoor air samples collected at different times. This demonstrates the potential of using the e-nose as a rapid, easy to use and inexpensive environmental monitoring system.
The presence of wastewater and air pollution has become an important risk factor for citizens, not only in terms of problems related to health risks, but also because of its negative impact on the country's image. For this reason, malodorous emission monitoring and control techniques are in high demand in urban areas and industries. The aim of this work is first to build an electronic nose (e-nose) and a Voltammetric Electronic tongue (VE-tongue) in order to study their ability to discriminate between polluted and clean environmental samples. Secondly, Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS), and Solid Phase Micro Extraction-Gas Chromatography–Mass Spectrometry (SPME-GC-MS) are utilized to explain this discrimination by identifying specific compounds from these samples. Indeed, the e-nose, consisted of metal oxide semiconductor gas sensors, is used for the assessment of the studied odorous air and headspace samples from water and wastewater sites. Moreover, the VE-tongue, based on metal electrodes, is utilized to determine the patterns of the sensor array responses, which serve as fingerprints profiles of the analyzed liquid samples. Chemometric tools, such as Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Support Vector Machines (SVMs) are operated for the processing of data from the e-nose and the VE-tongue. By using the both systems, the analyses of headspace and liquid samples from the seven sites allow better discrimination. To explain the cause of the obtained discrimination, TD-GC-MS and SPME-GC-MS analyses are well performed to identify compounds related sites. According to these outcomes, the proposed e-nose and VE-tongue are proved to be rapid and valuable tools for analysis of environmental polluted matrices.
Poor air quality, particularly in urban areas, causes various diseases and degrades living standards. Air Quality could be affected by emissions of odor, Volatile Organic Compounds (VOCs), and other gases. Therefore, assessment and monitoring of odorous air quality using sensitive, simple, rapid, accurate and portable tools is very important for public health. This study aimed to characterize odor emissions to detect malfunctions in facilities and to prevent air pollution and olfactory nuisance in the environment. A gas chromatographic method, in conjunction with sensorial analysis were performed for odorous air samples analysis collected from neighborhood of Meknes city (Morocco). Advanced multivariate statistical approaches, such as Principal Components Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to describe samples similarities. The electronic nose (e-nose) data processing exhibits a satisfactory discrimination between the odorous air samples. Twenty-four VOCs with known molecular formulas were identified with Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS). A validated Partial Least Square (PLS) model foresees good calibration between e-nose measurement and TD-GCMS analysis. The finding indicates that TD-GC–MS approach in conjunction with e-nose unit could be suitable tool for environmental measurement-based odor emissions.
Over decades, the German Federal Institute for Materials Research and Testing (BAM) has established a sophisticated calibration laboratory for force, temperature and electrical quantities. Since more than 15 years it is accredited, currently by the national accreditation body (DAkkS), and offers its service also to external entities on a global scale. As a public provider, we are furthermore committed to research and development activities that demand measurements with highest quality and low level of uncertainties. Two R&D examples are highlighted within this contribution.
With the reduction of large oil spills because of stricter regulations and safety measures, the question of how to manage smaller oil spills arises. Few on-site analytical tools are available for first responders or other law enforcement personnel to rapidly test for crude oil in the early management of localized polluted areas. The approach reported here relies on well-described computer-assisted multivariate data analysis of the intrinsic fluorescence fingerprints of crude oils to build a multivariate model for the rapid classification of crude oils and the prediction of their properties. Thanks to a dedicated robust portable reader, the method allowed classification and accurate prediction of various properties of crude oil samples like density (according to API, the American Petroleum Institute and viscosity as well as composition parameters such as volume fractions of paraffins or aromatics. In this way, autonomous operation in on-site or in-the-field applications becomes possible based on the direct (undiluted and untreated) measurement of samples and a rapid, tablet-operated readout system to yield a robust and simple analytical test with superior performance. Testing in real-life scenarios allowed the successful classification and prediction of a number of oil spill samples as well as weathered samples that closely resemble samples collected by first responders.
Contamination of natural bodies of water or soil with oils and lubricants (or generally, hydrocarbon derivatives such as petrol, fuels, and others) is a commonly found phenomenon around the world due to the extensive production, transfer, and use of fossil fuels. In this work, we develop a simple system for the on-field detection of total petroleum hydrocarbons (TPHs) in water and soil. The test is based on the measurement of the fluorescence signal emitted by the molecular rotor 2-[ethyl[4-[2-(4-nitrophenyl)ethenyl]phenyl]amino]ethanol (4-DNS-OH). This dye is embedded in a hydrophobic polymeric matrix (polyvinylidene fluoride), avoiding interactions with water and providing a robust support for use in a test strip fashion. Together with the strips, an embedded optical system was designed for fluorescence signal read-out, featuring a Bluetooth low-energy connection to a commercial tablet device for data processing and analysis. This system works for the detection and quantification of TPHs in water and soil through a simple extraction protocol using a cycloalkane solvent with a limit of detection of 6 ppm. Assays in surface and sea waters were conclusive, proving the feasibility of the method for in-the-field operation.
Geogenic gases such as CH4 or CO2 from natural sources, gases (CCS-CO2, H2, Natural
gas, City gas …) from a geological repository, or a leaking gas pipeline can present serious
risks in industrial and urban areas where the density of infrastructural elements increases as
well as above and below ground. To extend the lead time for risk treatment in such critical
regions, reliable detection of gases within the shallow subsurface is required to observe
critical gas accumulations before degassing into the atmosphere.
A near real-time monitoring approach is introduced to determine the volumetric expansion of
such a gas escaping from a leak in the subsurface. Considering the pressure relaxation with
the ambient air pressure, the approach enables the forecasting of the final size of a
pressurized gas body in terms of characteristic lengths. According to theoretical basics, such
a characteristic length, which allows to perform a gas (safety) measurement based on a
purely geometrical measure, behaves independently of subsurface properties, i.e., it enables
a reliable quantification of the escaping gas, irrespective of its heterogeneous flow path
distribution. A field test for a 10 l/min pinhole leakage of CO2 injected in an unsaturated Chernozemic soil (agricultural test field Bad Lauchstädt)that was equipped with linear gas sensors demonstrates the lateral-vertical volumetric gas expansion along the environment of these gas sensors, and confirms the applicability of the new characteristic length approach.
Comprehensive monitoring of pipelines over their full length is technically difficult and expensive. Considering a cost-benefit ratio it is reasonable to implement monitoring solutions in pipeline segments, which bear a high risk potential, like residential areas, construction sites, slopes, street or river crossings. Still such segments can measure up to several hundred meters in length, demanding for monitoring solutions that extend along such distances and enable fast response. Point wise sensing and periodical surveillance have clear drawbacks, particularly regarding early damage detection. Fibre optic sensors enable distributed sensing of temperature and strain, but they offer very limited possibilities for measuring gas concentrations. Linear membrane-based gas sensors enable the monitoring of gas concentrations alongside a pipeline. Such line-sensors are implemented in form of flexible tubes and can be arranged inside or outside the pipeline (also underwater or within the subsurface), corresponding to the technical requirements. The measuring method combines the gas specific diffusion rates through a membrane with Dalton’s law of partial pressures and enables the calculation of gas concentrations or the detection of a change of the gas composition. The objective is to detect gas leakages fast and with high reliability. Furthermore, the calibrated system enables to estimate the spatial extent of a leakage. So far the gas concentration measurement is tested for oxygen, carbon dioxide, methane; further gases should follow, e.g. hydrogen, carbon monoxide or mixtures like natural gas. The paper introduces in the different operating modes of line-sensors. A near real-time approach will be demonstrated to quantify the impact of a gas leak on the near environment. This approach is based on a critical length describing the expansion of the leaking gas.
Geogenic gases from natural sources, carbon dioxide (CO2) from a geological repository (carbon capture and storage - CCS) or a leaking gas pipeline can present serious risks in industrial and urban areas. To extend the lead time for risk treatment in such critical regions, reliable detection of gases within the shallow subsurface is required to observe critical gas accumulations before degassing into the atmosphere.
A near real-time monitoring approach is introduced to determine the volumetric expansion of a leakinggas in the subsurface. Considering the pressure relaxation with the ambient air pressure, the approach enables the forecasting of the final size of a pressurized gas body in terms of characteristic lengths. According to theoretical basics, such a characteristic length, which enables us to perform a gas (safety) measurement based on a purely geometrical measure, behaves independently of subsurface properties,i.e., it enables a reliable quantification of the escaping gas irrespective of its heterogeneous or changingflow path distribution. A field test for a 10 l/min pinhole leakage injected into a 10 m long, 0.4 m wide, 0.95 m deep soil-filled trench that was equipped with linear sensors shows the lateral-vertical volumetric gas expansion along these sensors, and demonstrates the applicability of the characteristic length approach.
The Split Hopkinson Pressure Bar (SHPB) or
Kolsky Bar is known as a method for analysing
mechanical properties of a material under dynamic
load. Referring to the name it is a splitted
Hopkinson Pressure Bar. The Hopkinson Bar is
related to its inventor Bertram Hopkinson (1914).
He used it to analyze stone samples under dynamic
load. Later his construction was improved by
Davies (1948) [1] and Kolsky (1949) [2], who had
the idea to split the bar and put a sample in
between.
The technique is used to measure a lot of
different mechanical properties of a material e.g.
the dynamic Youngs modulus, deformation
behaviour or to chart the dynamic stress-strain
diagram. Further applications are the measurement
of the elastic wave and the analysis of the
propagation of the wave [2]. In the last years there
was still an interest in measuring dynamic
properties with a SHPB. Nevertheless no
comprehensive validation of the system exists.
Another problem is that the stress and the strain in
the sample are only calculated with simplified
estimations.
The aim of this paper is to give a first
impression of important points validating the
system. On account of different setups of the
SHPB a validation of the used system is necessary.
Hence it is important to look at the theory. Further
in this paper the measurement results will be
shown in a strain over time diagram.
In this study a method for early damage detection is investigated based on the directed excitation and measuring of Lamb waves (guided waves). The objective is to make a statement about the practicability of a Lamb wave generator (LWG) and about the application relevant parameters (specimen materials and dimensions, wave characteristics, excitation, transmission und reflection). Guided waves enable an effective differentiation of structural and defective indications as well as a classification of different defect types. For the investigations, a LWG was developed which combines the advantages of the single excitation of a piezoelectric actuator and the possibility of a group excitation. Algorithms were developed to identify and analyze damage patterns (cracks, wholes, weakening).
Sensor based person tracking is a challenging
topic. The main objective is positioning in areas without
GPS connection, i.e. indoors. A research project is carried
out at BAM, Federal Institute for Materials Research and
Testing, to develop and to validate a multi-sensor system for
3D localization. It combines body motion sensing and a
guard system for the tracking and recording of the status of
persons. The so named BodyGuard system was designed for
sensor-based monitoring and radio-based transmission of
the movement of a person. Algorithms were developed to
transform the sensor data into a spatial coordinate. This
paper describes how the BodyGuard system operates, which
main components were used in the system, how the
individual sensor data are converted into 3D motion data,
with which algorithms the individual sensors are processed,
how individual errors are compensated and how the sensor
data are merged into a 3D Model. Final objective of the
BodyGuard system is to determine the exact location of a
person in a building, e.g. during fire-fighting operations.
A multi-sensor system for 3D localization was developed and named BodyGuard. It combines body movement sensing and a guard system for the tracking and recording of the status of persons. BodyGuard was designed to monitor and transmit the movement of a person radio-based and to transform that data into a spatial coordinate. This paper describes how the BodyGuard system works, what components the system consists of, how the individual sensor data is converted into 3D motion data, with which algorithms the individual sensors are processed, how individual errors are compensated and how the sensor data are fused into a 3D Model.
Fiber optic sensors have gained increasing importance in recent years and are well established in many areas of industrial applications. In this paper, we introduce a concept of a self-diagnostic fiber optic sensor. The presented sensor is to resolve the problems of embedded fiber optic sensors in complex structures and to enable the validation under operational conditions. For this purpose, different magnetostrictive coated fiber optic sensors were developed and various experiments were performed to verify their mode of Operation and to determine the respective reproducibility. The measuring principle is illustrated by obtained experimental results, which showed a change in wavelength from 1 pm at a magnetic field strength change of 0.25 mT.
In addition, the temperature characteristics of the implemented magnetostrictive sensor were analyzed and an experimental factor of 1.5 compared to a reference fiber optic sensor was determined.
Fiber optic sensors have gained increasing importance in recent years and are well established in many areas of industrial applications. In this paper, we introduce a concept of a self-diagnostic fiber optic sensor. The presented sensor is to resolve the problems of embedded fiber optic sensors in complex structures and to enable the validation under operational conditions. For this purpose, different magnetostrictive coated fiber optic sensors were developed and various experiments were performed to verify their mode of operation and to determine the respective reproducibility. The measuring principle is illustrated by obtained experimental results, which showed a change in wavelength from 1 pm at a magnetic field strength change of 0.25 mT. In addition, the temperature characteristics of the implemented magnetostrictive sensor were analyzed and an experimental factor of 1.5 compared to a reference fiber optic sensor was determined.
Damage to buildings occurs if a construction component fails. The result is a partial or total collapse which can be dangerous for people for example if it's a bridge or a large hall. The collapse of the terminal building at the Airport Charles de Gaulle in Paris and the damage at the historic City Archives of Cologne are typical examples of such accidents. Another problem is the contradiction of the increasing volume of traffic (particularly heavy traffic) and the great age of bridges. The probability increases that the load-bearing capacity of a bridge decreases. For example the collapses of the Mississippi Bridge and of the Inntal Motorway Bridge can be seen as results. Therefore it is necessary to control endangered structures during their life span.
In order to prevent these kinds of accidents, the Federal Institute for Materials Research and Testing developed a radio-based, self-configuring measuring system in cooperation with the ScatterWeb Company, Berlin (Germany). This measuring system consists of identically designed sensor modules which are self-sustaining, wireless, act as transmitters and receivers and are equipped with a special sensor technology for long-term monitoring of buildings or engineering facilities. The sensor unit uses strain gauges for stress analysis and contains interfaces for additional sensors. The system in particular applies to buildings and structures for transport and traffic and large-scale industrial facilities, where a subsequent wiring installation is difficult or impossible.
In this work an air-based sensor network for the localization of persons at extensive areas is presented. The developed network consists of a localization device which the person is wearing (BodyGuard-System), a mobile relay station in the air, and a base station. All three parts communicate with the same radio chip. The BodyGuard-System is an inertial navigation system which was developed for localization in difficult environments with high accuracy and low measurement uncertainty. To increase the range of the system, a multi-hop network was built up. The measured data of the BodyGuard-System and the mobile relay station is visualized on a PC in the base station. This multi-hop network is necessary for example for fire department missions.
In many cases, science falls back on self-developed prototype systems, which are used and developed for the measurement and execution of the tasks. About 80 % of the development is based on the same hardware design, which is used in only one application scenario and then discarded. For the most part, there are also uncalibrated sensors, since it is costly to calibrate a complicated sensor measurement system or the entire measurement chain since access to the sensor systems is not always available. This paper describes a conceptual design to implement a versatile sensor system with the motivation to fuse the data recording and data reception, which can cover large areas with the help of LoRaWAN (Long Range Wide Area Network) technology. To overcome disadvantages of LoRaWAN, namely the slow data rates, the proposed sensor system can also cover smaller areas with the widespread WiFi technology. An enormous advantage over individual complete systems in the form of a prototype, is the rapid expansion, uncomplicated calibration of the individual sensors and the ecological relief.
A modular design is used, where individual stacks with sensors and peripherals can be added separately. The stacks are standalone low-power systems and can be calibrated, maintained, and replaced separately and do not require the entire measurement chain. The measured and sent values are stored locally on the main stack and sent to the data collector (gateway) and evaluated by means of the automated selection between WiFi and LoRaWAN.
This project addresses the application of safe and healthy workplaces in offices, chemical laboratories and other workplaces where indoor air quality plays an important role. The LoRaWAN (Long Range Wide Area Network) is used as a communication interface to make sensor data globally accessible.
The objectives of the project are to create a sensor node and an online and offline system that collects the data from the sensor nodes and stores it on a local server, in a cloud, and also locally on the node to prevent communication failures. An important point in this project is the development of the sensor nodes and the placement of these in the premises, thus no development work is involved in Building the infrastructure.
Increasing traffic volume on the one hand and ageing infrastructure on the other hand have created many new challenges for maintenance and structural health monitoring of roads and bridges. In the past, many bridges and road structures have been neglected, often resulting in traffic congestion, road closure, and increased repair costs.
This research is concerned with the development of a system to improve the challenge of maintenance and early detection of damage, particularly moisture penetration and corrosion of steel reinforced concrete components. The objective is to develop a method that will also work after 30 years and longer. Many new IoT solutions are equipped with internal energy storage elements (accumulators or batteries) which are inappropriate here, since most relevant signs of concrete degradation occur after decades, where the functioning of such elements are more than questionable. The presented technology approach uses radio-frequency identification (RFID) and enables connectivity to sensors. It offers the advantage of an passive, completely independent energy supply without any energy storage components.
Since the system should be permanently embedded in concrete, it is crucial to develop a long-term stable device which is adapted to the environmental influences of the structure, e.g., long-term resistance in very alkaline environment of pH 13. In numerous experiments, the robustness of the system was tested and evaluated. Various tests with encapsulations to protect the electronics were performed, and for long-term validation different concrete specimens were instrumented with RFID-sensor-systems. Their operating time is now around two years and investigations for signs of fatigue and damage to the encapsulation and the electronics are ongoing.
Increasing traffic volume on the one hand and ageing infrastructure on the other hand have created many new challenges for maintenance and structural health monitoring of roads and bridges. In the past, many bridges and road structures have been neglected, often resulting in traffic congestion, road closure, and increased repair costs.
This research is concerned with the development of a system to improve the challenge of maintenance and early detection of damage, particularly moisture penetration and corrosion of steel reinforced concrete components. The objective is to develop a method that will also work after 30 years and longer. Many new IoT solutions are equipped with internal energy storage elements (accumulators or batteries) which are inappropriate here, since most relevant signs of concrete degradation occur after decades, where the functioning of such elements are more than questionable. The presented technology approach uses radio-frequency identification (RFID) and enables connectivity to sensors. It offers the advantage of an passive, completely independent energy supply without any energy storage components.
Since the system should be permanently embedded in concrete, it is crucial to develop a long-term stable device which is adapted to the environmental influences of the structure, e.g., long-term resistance in very alkaline environment of pH 13. In numerous experiments, the robustness of the system was tested and evaluated. Various tests with encapsulations to protect the electronics were performed, and for long-term validation different concrete specimens were instrumented with RFID-sensor-systems. Their operating time is now around two years and investigations for signs of fatigue and damage to the encapsulation and the electronics are ongoing.
Structural Health Monitoring (SHM) is an important part of buildings surveillance and maintenance to detect material failure as early as possible and to contribute in protection of structures and their users.
The implementation of Radio Frequency Identification (RFID) sensor systems without cable connection and battery into building components offers innovative possibilities to enable long-term in-situ SHM of addressed structures, bridges. The objectives of the presented study are complete embedding of RFID sensors systems in concrete, full passive communication with the systems, at best for the whole life span of structures. One challenge for this task is the highly alkaline environment in concrete, which requires non-degrading and robust encapsulation. Further Requirements are passive communication and energy supply, appropriate antenna design, placement and fixation in concrete, and the selection and implementation of sensors and connections. The concept is to develop and optimize a simple and robust system, which meets the requirements, as well as comprehensive validation in concrete specimen and real world applications. Two different systems were developed (HF and UHF RFID, respectively).
First tasks were the implementation of analog sensors using the superposition principle for the signal adaption. Investigation of suitable materials for robust encapsulation and sensor protection against basic environments.
Four materials were investigated in pH 13 solution for 14 days
- 3D-Printer-Polymer was completely resolved
- PVC has no noticeable decrease in weight
- (VitaPro) glass filter for the sensor protector, has weight loss 2.7 %
- The epoxy resin has increased by 1.8 % due to moisture expansion
Different concrete samples were prepared for the validation of the systems.
RFID sensors were embedded in different integration depths. Investigate the energy- and data transfer through concrete, also with varying moisture content. Additionally, signal strength data was used to optimize and validate the antenna characteristics in concrete. Next steps are to guarantee a sufficient energy supply for UHF RFID systems embedded in different concrete mixtures and further embedding the HF and UHF RFID systems in real bridges and buildings to validate the long term monitoring.
Structural Health Monitoring (SHM) is an important topic for Industry 4.0. More and more systems are embedded in different materials and are connected to each other. To embed sensors for a long time in concrete, an exact preparation is required. In this paper, we identify Radio-Frequency Identification (RFID) as promising technology for monitoring of concrete structures. This paper present the concept for long term monitoring, defines the requirements and shows first development steps, for example, the system design, the possibilities of sensor connection, and an encapsulation for embedding in concrete.
One of the more difficult tasks for structural health monitoring is the continuous evaluation of the stability and load capacity of the building materials. This knowledge can be won, e.g., by taking material samples at the examining place with the drawback of partly destroying the structure. To avoid this, modern sensor and communication technologies offer promising methods for non-destructive testing. To address the tasks for monitoring of concrete structures, in the presented study, different sensors were combined with RFID transponders and embedded in concrete components.
Structural Health Monitoring (SHM) has become very important in today's rapidly developing time. High buildings, large bridges and complex technical structures need to be monitored continuously and this over long periods.
Visual monitoring cannot evaluate the internal condition of building structures. Thus, material embedded sensors are needed. Cable connection of these sensors pose the disadvantage of weak spots and water intrusion. For concrete embedded sensors the use of batteries is not convenient, because of limited lifetime, difficult charging, and generation of electrical waste.. Hence, monitoring should be implemented preferentially with firmly embedded passive RFID sensor modules. However, since the concrete structure forms an electromagnetically reflective and absorbing barrier, only limited energy can be transmitted to the module. This project requires a highly energy-saving system, which can record different sensor parameters at critical points.
This paper is a further research on the topic of the complete embedding of radio frequency identification (RFID) sensors in concrete. The focus is on the antenna of the transponder. Earlier investigations of different RFID technologies, embedded in concrete, showed a difference in energy transmission. The transmission through concrete at ultra high frequency (UHF), in spite of the large signal range, does not match the targeted application specific task. Therefore, the antenna characteristics have been examined more closely. The antenna is an important component for the application of RFID. Through the antenna, energy and data transfer takes place, so it is important to design an optimal antenna to accomplish a maximum embedding depths in concrete. To identify the optimal antenna geometry, different UHF antenna types were selected and investigated. An experimental comparison was performed to gain more information about the damping behavior and antenna characteristics in concrete.
This paper deals with the development and investi-gation of a volatile organic compound (VOC) system for differ-ent scenarios. The integrated multi-sensor unit can detect dif-ferent gases through the integrated 3-fold VOC sensor, where-by a continuous measurement takes place. The system-integrated flow control, with pump and flow sensor, allows the gas molecules to be transported directly to the VOC sensor. The entire measurement is permanently stored on an integrat-ed Secure Digital (SD) card. If the previously determined limit range is exceeded, an alarm is generated. Due to the combina-tion of different components, numerous applications are possi-ble. The system is the first step or a tool towards further devel-opments in the field of gas sensors and is primarily used for the validation of chemically based gas sensors, and it is still largely extended by application-specific influences.
This paper describes a wireless mobile prototype able to perform optical measurements by means of a miniatur-ized spectrometer for low light analysis, e.g. fluorescent sensors. Evaluations, calculations, calibration management and result display are performed by a computer or a standard tablet. The device was designed primarily to detect traces of oil in drinking or ground water and for the analyses of crude oils. However, it can also address a wide range of fluorescent sensors. The fast and user-friendly inspection of water quality or oil properties, as well as the adaptability and mobility, make the device attractive for a variety of users. Further application areas could be easily imple-mented by adapting the optics and the software (database, data processing and calibration plots, etc.)
Design and Implementation of Smart Multisensor Monitoring System for Safe Workplaces with LoRaWAN
(2020)
This project addresses the application of safe workplaces in offices and chemical laboratories where indoor air quality plays an important role. The LoRaWAN (Long Range Wide Area Network) is used as a communication interface to make important sensor data globally accessible. The goal of the development is to create a sensor node and an online and offline solution that collects the data from the sensor nodes and stores it on a local server or in a cloud. In cooperation with the companies WISTA GmbH and IONOS, a test sensor network is going to be established in the Berlin-Adlershof area.
This paper describes the development of a semi-automatic gas measurement device presenting potentially a broad range of applications, noteworthy in the agricultural sector. Non-reversible fluorescent molecular sensors were designed and syn-thesized. Upon, integration into a hydrogel matrix with an optimal ratio of co-solvents, the sensors reacting selectively to ammonia were illuminated by excitation light to produce a concentration-correlated fluorescence emission. An automated mechanical-elec-trical device initiates a given gas mixture and thus simulates con-centrations similar to a threshold value. The aim of this project is to develop a sensor or a low-cost method which can monitor low concentrations of harmful gases and aid in their elimination or regulation in livestock housing, barns or stables.
Innovation is the catalyst for the technology of the future. It is important to develop new and better technologies that can continuously monitor the environmental impact, e.g., for air quality control or emission detection. In the recently at BAM developed Universal Pump Sensor Control (UPSC3) module, different components and sensors are fused. The combination of the individual components makes the UPSC3 module an excellent monitoring and reference system for the development and characterization of gas specific sensors. Measurements over long periods are possible, for mixed gas loads or for certain gas measurements. The system is part of a mobile sensor network of several sensor units, which can also be used as standalone systems.
The motivation and objective of this research is to develop gas sensors based on fluorescence detection with range of ppm / ppb. For this task a reference system is required, which contains volatile organic compound (VOC) sensors for reference data from different scenarios. The integrated multi-sensor unit can measure different gases through the integrated 3-fold VOC sensor, which can be adapted to the addressed scenario. . The system-integrated flow control, with pump and flow sensor, allows the gas molecules to be transported directly to the VOC sensor. The entire measurement is permanently stored on an integrated memory card. If the previously determined limit range is exceeded, an alarm is generated. The system is an important tool towards further developments in the field of gas sensors and is primarily used for the validation of chemically based gas sensors.
Piezoresistive accelerometers use a strainsensing element, generally made of semiconductor material, e.g., silicon to convert the mechanical motion into an electrical signal. This element is usually designed in form of a cantilever beam loaded with a mass. Acceleration causes bending
of the beam, which produces a change of electrical resistance proportional to the applied acceleration.
Main advantages of piezoresistive accelerometers in comparison to other types, e.g., piezoelectric and capacitive, is their robust and highly dynamic behavior, which qualifies them for application in high impact shock applications. Mechanical damping is typically implemented with silicon oil in a way that the output signal is undistorted over a wide frequency range. These characteristics principally qualify them for the application in drop tests carried out at BAM, for which they are calibrated over the frequency range from 1 to 4 kHz. However, using silicon oil for damping, has the drawback of temperature dependent change of its viscosity, leading to temperature dependent deviation of the accelerometer’s sensitivity. This study presents experimental results of the temperature behavior of a piezoresistive accelerometer with a dynamic range up to ±5000 g.
This type of accelerometer is applied for drop tests which are partially performed at temperatures of -40 or +100 °C.