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Organisationseinheit der BAM
- 8.1 Sensorik, mess- und prüftechnische Verfahren (71) (entfernen)
Implementation and validation of robot-enabled embedded sensors for structural health monitoring
(2024)
In the past decades, structural health monitoring (SHM) has matured into a viable supplement to regular inspections, facilitating the execution of repair and maintenance work in the early stages of structural damage. With the advent of wireless technologies and advancements in information and communication technologies, civil infrastructure has been increasingly instrumented with wireless sensor nodes to record, analyze, and communicate data relevant to SHM. A promising method for SHM is to embed sensors directly into concrete for recording SHM data from inside structural elements. In this paper, a sensor system for embedment into concrete is proposed, able to assess SHM data recorded from concrete. Power is supplied to the sensors on-demand by quadruped robots, which also collect the SHM data via radio-frequency identification (RFID), providing an automated and efficient SHM process. In laboratory experiments, the capability of the sensor system of automatically collecting the SHM data using quadruped robots is validated. In summary, the integration of RFID technology and robot-based inspection presented in this study demonstrates a vital approach to evolve current SHM practices towards more digitalized and automated SHM.
We introduce a passive smart dust concept as a novel solution for environmental monitoring. Utilizing chemical reagents like colorimetric indicators and other chemosensors, these particles detect varying environmental conditions. We developed paper-based sensors that are both cost-effective and eco-friendly. In practical tests, these sensors, dispersed over a designated area, successfully identified hazardous substances by changing their color when exposed to acids or bases. This color change was remotely detectable using a drone-mounted color camera. The data thus obtained was processed through specialized software, accurately pinpointing areas of contamination. This method proves the efficacy and scalability of passive smart dust technology for real-time, environmentally sustainable remote sensing of hazardous materials
This paper explores combining a gimbal-mounted tunable diode laser absorption spectroscopy (TDLAS) sensor and a video camera to create a virtual gas camera for methane leak detection. This provides a low-to-zero-cost extension of typical TDLAS gas tomography systems. A prototype setup mounted on a ground robot is evaluated. Results acquired using a simulated methane leak show the feasibility of the virtual gas camera, accurately detecting methane leaks by overlaying concentrations onto a visual image. While the acquisition time is significantly longer than for traditional gas cameras, potential enhancements are discussed. The study concludes that the virtual gas camera is feasible and useful, despite its longer acquisition time. It serves as a valuable software-only addition to typical TDLAS gas tomography systems, offering quickly-available on-site data augmentation for visual leak assessment at low-to-zero cost.
This paper outlines significant advancements in our previously developed aerial gas tomography system, now optimized to reconstruct 2D tomographic slices of gas plumes with enhanced precision in outdoor environments. The core of our system is an aerial robot equipped with a custom-built 3-axis aerial gimbal, a Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor for CH4 measurements, a laser rangefinder, and a wide-angle camera, combined with a state-of-the-art gas tomography algorithm. In real-world experiments, we sent the aerial robot along gate-shaped flight patterns over a semi-controlled environment with a static-like gas plume, providing a welldefined ground truth for system evaluation. The reconstructed cross-sectional 2D images closely matched the known ground truth concentration, confirming the system’s high accuracy and reliability. The demonstrated system’s capabilities open doors for potential applications in environmental monitoring and industrial safety, though further testing is planned to ascertain the system’s operational boundaries fully.
Gas Distribution Mapping (GDM) is essential in monitoring hazardous environments, where uneven sampling and spatial sparsity of data present significant challenges. Traditional methods for GDM often fall short in accuracy and expressiveness. Modern learning-based approaches employing Convolutional Neural Networks (CNNs) require regular-sized input data, limiting their adaptability to irregular and sparse datasets typically encountered in GDM. This study addresses these shortcomings by showcasing Graph Neural Networks (GNNs) for learningbased GDM on irregular and spatially sparse sensor data. Our Radius-Based, Bi-Directionally connected GNN (RABI-GNN) was trained on a synthetic gas distribution dataset on which it outperforms our previous CNN-based model while overcoming its constraints. We demonstrate the flexibility of RABI-GNN by applying it to real-world data obtained in an industrial steel factory, highlighting promising opportunities for more accurate GDM models.
Robotic Measurement System Concept for Greenhouse Gas Tomography in Wastewater Treatment Plants
(2023)
This paper introduces a conceptual framework for a robotic greenhouse gas (GHG) measurement system designed for wastewater treatment plants (WWTPs). The emphasis is on accurate gas tomography measurement of emissions, crucial for national emission assessments. The proposed system is movable, semi-autonomous, and employs a combination of ground and air robots equipped with integral remote gas sensors and in-situ sensors. Employing a two/two configuration ensures comprehensive coverage of WWTPs, overcoming obstacles. The system concept lays the foundation for future implementation and evaluation, addressing the need for enhanced understanding of GHG emissions from WWTPs.
Gas source localization (GSL) helps mitigate the impact of industrial accidents and natural disasters. While GSL may be dangerous and time-consuming when performed by humans, swarms of agile and inexpensive nano aerial robots may increase the safety and efficiency of gas source localizations. Since the small payloads of nano aerial robots limit the sensing and computing resources, strategies adapted from biological swarms, such as colonies of social insects, are used to coordinate robot swarms. Most swarm GSL strategies are based on the assumption that the maxima of gas concentrations are sufficiently close to the gas sources. However, prior studies have indicated that the occurrence of “bouts”, a metric for the intermittency of gas distributions, may advantageously be used as a more accurate gas source proximity indicator. This paper presents a swarm GSL strategy employing bouts as source proximity indicators and a bio-inspired pheromone system for communication. Nano aerial robots, deployed in this study, act as agents and emit pheromone markers in an artificial environment upon detecting bouts. Leveraging the concept of artificial potential fields, the agents switch between exploiting the knowledge of the swarm by following pheromone gradients and exploring the search space by targeting a random point. The agents are repelled by each other and by walls to avoid collisions. The swarm GSL strategy is implemented into three nano aerial robots and validated in a real-world experiment in an indoor environment with a single gas source. The results indicate that the the swarm GSL strategy presented in this paper is capable of GSL in indoor environments and that the intermittency of gas distributions is a better source proximity indicator than the mean concentration.
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.
Since several years, magnetic sensor elements are available in fully flexible architectures that often reveal identical sensing properties, compared to their rigid counterparts, while being bent severely and repeatedly. Nowadays, a variety of magnetic senor principles, including well known Hall, AMR and GMR but also more exotic PHE and AHE sensors were demonstrated on such flexible platforms. The novel properties of being thin, lightweight, shapeable, and wearable enable magnetic sensory systems to be utilized in vicinities and conditions that are inaccessible for rigid and microchip-based sensors.
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.
Setting up sensors for the purpose of environmental monitoring should be a matter of days, but often drags over weeks or even months, preventing scientists from doing real research. Additionally, the newly developed hardware and software solutions are often reinventing existing wheels. In this short paper, we revisit the design of our environmental sensing node that has been monitoring industrial areas over a span of two years. We share our findings and lessons learned. Based on this, we outline how a new generation of sensing node(s) can look like.
Multi-sensory monitoring and ultrasound for quality assurance at underground sealing structures
(2023)
Within the safety concepts of underground disposal sites of nuclear waste, engineered barriers play an important role. As these sealing structures have high demands concerning integrity, we aim at advancing the available construction materials, monitoring, and inspection techniques within the project SealWasteSafe. A specifically developed alkali-activated material is compared to classical salt concrete. A comprehensive multi-sensory monitoring scheme is used at 150-340 l specimens to monitor setting and hardening of both materials. All sensors are demonstrated to resist the highly alkaline environments. Besides cabled and wireless temperature and humidity of the materials, strain variations using fibre optic sensors and acoustic emissions are recorded over periods of at least 28 days, partly for more than eight months. After hardening of the specimens, further nondestructive evaluations using ultrasonic echo and thermographic measurements are conducted.
Preliminary results proof the suitability of the tested sensors and clearly highlight differences between the tested materials. Particularly, the newly developed alkali-activated material shows lower acoustic emission activity indicating less cracking activity. Additionally, unique ultrasonic methods will enable better images of potential internal objects and cracks at in-situ sealing structures. A largescale ultrasonic system is optimised to reliably detect objects at a depth exceeding 9 m while still obtaining a good resolution. Modelling studies show the potential of further increasing the distance between individual transducer arrays. Additionally, a new ultrasonic borehole probe using phased arrays allowing for beam focussing is constructed and tested. Laboratory measurements at a halfcylindrical concrete specimen coincide well with the previous modelling. In total, the presented safe materials, detailed monitoring approaches and ultrasonic quality assurance methods will help to obtain safe sealing structures within salt as a host rock. The concepts can partly be transferred to sealing structures in alternative host rocks and will also be valuable for non-nuclear waste repositories.
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 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.
Simulating a Gas Source Localization Algorithm with Gas Dispersion Produced by Recorded Outdoor Wind
(2023)
This paper reports the use of the first gas dispersion simulator capable of introducing large wind fluctuations into simulations. The proposed simulator enables testing of a modification made to a gas source localization algorithm in a realistic scenario in order to study how the change affects it. Gas source localization in an outdoor environment is a challenging task mainly due to the complexity of the gas spread caused by the unpredictable nature of constantly changing wind. Therefore, a novel use of outdoor wind in developing a gas source localization system by simulation is presented in this paper. To consider the characteristic of sudden but large and unpredictable changes in wind direction, we propose to use recorded outdoor wind to simulate a realistic outdoor gas dispersion which has been done for the first time to the best of our knowledge. With the use of this simulator, we have tested a modification to a mobile robot-based gas source localization algorithm. Multiple simulations of the modified and the original particle filter-based algorithm have been done to study the effect of the tested modification. The results showed that a small difference in the algorithm can greatly impact the results. From this study, we show that the use of simulation consisting of the necessary traits to evaluate outdoor gas source localization, has the potential to accelerate the development of a reliable localization system.
To better understand the dynamics in hazardous environments, gas distribution mapping aims to map the gas concentration levels of a specified area precisely. Sampling is typically carried out in a spatially sparse manner, either with a mobile robot or a sensor network and concentration values between known data points have to be interpolated. In this paper, we investigate sequential deep learning models that are able to map the gas distribution based on a multiple time step input from a sensor network. We propose a novel hybrid convolutional LSTM - transpose convolutional structure that we train with synthetic gas distribution data. Our results show that learning the spatial and temporal correlation of gas plume patterns outperforms a non-sequential neural network model.
Remote sensing of hazardous substances is a key task that can be achieved with the help of remotely operated platforms equipped with specific sensors. A huge variety of methods and used vehicles have been developed for different purposes in recent years. The term smart dust refers to a science fiction novel and develop shortly after into a research proposal at UC Berkley funded by DARPA. Subsequently, the topic gained attraction but was overall considered as to complex for the technologies available at that time. In the launched passive smart dust project, we shift to a simple “chemical intelligent” passive sensor particle on the ground combined a read-out active sensor attached to an Unmanned Aerial Vehicle (UAV). The reactive particle surface can be preadjusted in the lab for exact desired properties regarding certain reactions to hazardous substances.
Moreover, the aimed interaction with the active sensor can be modified. Planed applications allow for different materials e.g., for short time measurement, being ecologically degradable, or weather stable for long time monitoring.
Occupational health is an important topic, especially in industry, where workers are exposed to airborne by-products (e.g., dust particles and gases). Therefore, continuous monitoring of the air quality in industrial environments is crucial to meet safety standards. For practical and economic reasons, high-quality, costly measurements are currently only carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only.
The project “Robot-assisted Environmental Monitoring for Air Quality Assessment in Industrial Scenarios” (RASEM) addresses this issue by bringing together the benefits of both – low- and high-cost – measuring technologies enabling costefficient long-term air quality monitoring in realtime: A stationary network of low-cost sensors that is augmented by mobile units carrying high-quality sensors. By mapping the distribution of gases and particles in industrial environments with the proposed RASEM system, measures can be identified to improve on-site working conditions much faster than using traditional methods.
In this paper, we detail the technical aspects of RASEM and introduce the mobile platforms used.
The Sharp GP2Y1010AU0F is a widely used low-cost dust sensor, but despite its popularity, the manufacturer provides little information on the sensor. We installed 16 sensing nodes with Sharp dust sensors in a hot rolling mill of a steel factory. Our analysis shows a clear correlation between sensor drift and accumulated production of the steel factory. An eye should be kept on the long-term drift of the sensors to prevent early saturation. Two of 16 sensors experienced full saturation, each after around eight and ten months of operation.
The project "SealWasteSafe" of the Bundesanstalt für Materialforschung und -prüfung (BAM, Berlin) deals with sealing structures applied for underground disposal of nuclear waste from two perspectives: (1) material improvement for application in sealing constructions and (2) feasibility study regarding multi-sensor approaches to ensure quality assurance and long-term monitoring.
One specimen of 150 l made of alkali-activated material, which was found innovative and suitable for sealing constructions based on preliminary laboratory studies, and, for comparison purpose, another one made of salt concrete, are manufactured with an integrated multi-sensory setup for quality assurance and long-term-monitoring. The specimens were left in their cast form and additionally thermally insulated to simulate the situation in the repository. The multi-sensory concept comprises RFID technology embedded in the specimens suppling material temperature and moisture measurements, integrated fibre optic sensing allowing strain measurement and acoustic emission testing for monitoring possible crack formation. Overall, the suitability and the functionality of the sensors embedded into and attached to strongly alkaline (pH > 13 for the AAM) and salt corrosive (NaCl) environment was proven for the first 672 h.
First temperature measurement based on RFID succeeded after 626 h for the alkali-activated material and after 192 h for the conventional salt concrete. Strain measurement based on distributed fibre optic sensing turned out the alkali-activated material with > 1 mm m-1 undergoing approximately twice the compression strain as the salt concrete with strains < 0.5 mm m-1. In contrast, the acoustic emission first and single hits representing crack formation in numbers, was found for alkali-activated material half of that detected at the salt concrete.
Gas distribution mapping is important to have an accurate understanding of gas concentration levels in hazardous environments. A major problem is that in-situ gas sensors are only able to measure concentrations at their specific location. The gas distribution in-between the sampling locations must therefore be modeled. In this research, we interpret the task of spatial interpolation between sparsely distributed sensors as a task of enhancing an image's resolution, namely super-resolution. Because autoencoders are proven to perform well for this super-resolution task, we trained a convolutional encoder-decoder neural network to map the gas distribution over a spatially sparse sensor network. Due to the difficulty to collect real-world gas distribution data and missing ground truth, we used synthetic data generated with a gas distribution simulator for training and evaluation of the model. Our results show that the neural network was able to learn the behavior of gas plumes and outperforms simpler interpolation techniques.
Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or poorly accessible areas. A challenging task however, is the generation of three-dimensional distribution maps from these spatially sparse gas measurements. To obtain high-quality reconstructions, the choice of optimal measuring poses is of great importance. Remote gas sensors, that are commonly used in Robot Assisted Gas Tomography (RAGT), require reflecting surfaces within the sensor’s range, limiting the possible sensing geometries, regardless of whether the robots are ground-based or airborne. By combining ground and aerial robots into a heterogeneous swarm whose agents are equipped with reflectors and remote gas sensors, remote inter-robot gas measurements become available, taking RAGT to the next dimension – releasing those constraints. In this paper, we demonstrate the feasibility of drone-to-drone measurements under realistic conditions and highlight the resulting opportunities.
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.
Vor allem in den letzten Jahren ist das Interesse der Industrie an der additiven Fertigung deutlich gestiegen. Die Vorteile dieser Verfahren sind zahlreich und ermöglichen eine ressourcenschonende, kundenorientierte Fertigung von Bauteilen, welche zur stetigen Entwicklung neue Anwendungsbereiche und Werkstoffe führen. Aufgrund der steigenden Anwendungsfälle, nimmt auch der Wunsch nach Betriebssicherheit unabhängig von anschließenden kostenintensiven zerstörenden und zerstörungsfreien Prüfverfahren zu. Zu diesem Zweck werden im Rahmen des von der BAM durchgeführten Themenfeldprojektes „Prozessmonitoring in Additive Manufacturing“ verschiedenste Verfahren auf ihre Tauglichkeit für den in-situ Einsatz bei der Prozessüberwachung in der additiven Fertigung untersucht. Hier werden drei dieser in-situ Verfahren, die Thermografie, die optische Emissionsspektroskopie und die Schallmissionsanalyse für den Einsatz beim Laser-Pulver-Auftragschweißen betrachtet.
Wireless sensor networks provide occupational health experts with valuable information about the distribution of air pollutants in an environment. However, especially low-cost sensors may produce faulty measurements or fail completely. Consequently, not only spatial coverage but also redundancy should be a design criterion for the deployment of a sensor network. For a sensor network deployed in a steel factory, we analyze the correlations between sensors and build machine learning forecasting models, to investigate how well the sensor network can compensate for the outage of sensors. While our results show promising prediction quality of the models, they also indicate the presence of spatially very limited events. We, therefore, conclude that initial measurements with, e.g., mobile units, could help to identify important locations to design redundant sensor networks.
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.
The best-known discretization methods for solving engineering problems formulated as partial differential equations are finite difference method (FDM), finite element method (FEM) and finite volume method (FVM). While the finite volume method is used in fluid mechanics, the finite element method is predominant in solid state mechanics. At first glance, FVM and FEM are two highly specialized methods. However, both methods can solve problems of both solid mechanics and fluid mechanics well. Since experimental mechanics deals not only with solid state physics but also with fluid mechanics problems, we want to understand FVM in the sense of FEM in this work. In the long term, we want to use the variational calculus to unify many important numerical methods in engineering science into a common framework. In this way, we expect that experiences can be better exchanged between different engineering sciences and thus innovations in the field of experimental mechanics can be advanced. But in this work, we limit ourselves to the understanding of the FVM with the help of the variational calculus already known in FEM. We use a simple 1D Poisson equation to clarify the point. First, we briefly summarize the FVM and FEM. Then we will deal with the actual topic of this paper, as we establish the FEM and the FVM on a common basis by variation formulation. It is shown here that the FVM can be understood in terms of the finite element method with the so-called Galerkin-Petrov approach.
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.
Von den Zellulosefibrillen über die Zellwand und die Anordnung der Früh- und Spätholzzellen in einem Jahrring bis hin zum Balken von Natur aus ist Holz ein optimierter Hochleistungswerkstoff, der Handwerker, Architekten, Ingenieure und Wissenschaftler fasziniert und begeistert. Im digitalen Zeitalter werden neben Standard-Laborexperimenten zunehmend Modelle und Simulationen eingesetzt, um das Verhalten des Materials unter verschiedenen Belastungen besser zu verstehen und vorherzusagen. Dazu werden Zahlenwerte von Verformungen im subzellulären Maßstab benötigt, die nun in Experimenten an der TOMCAT-Beamline (TOmographic Microscopy and Coherent rAdiology ExperimenTs) der SLS (Swiss Light Source) gewonnen werden konnten: Holzproben aus Fichte ( Picea abies Karst.) mit einem Prüfquerschnitt von mindestens 1 mm² auf Zug oder Druck beansprucht. Die strukturellen Veränderungen auf Zellebene wurden mittels Computertomographie erfasst. Für die nachträgliche Analyse der 3D-Mikrostruktur von Holz wurde ein Ansatz entwickelt, der es ermöglicht, einzelne Zellen, die in mehreren Tomogrammen unterschiedlicher Belastungszustände erfasst wurden, zu verfolgen. Dabei wurden die Zellgeometrien und das subzelluläre Deformationsverhalten quantifiziert. Unter Zugbelastung beispielsweise verengt sich die Zellwanddicke um ca. 0,8%, das sind bei der gemessenen mittleren Zellwanddicke von 3,5 µm ca. 28 nm. Diese und andere Erkenntnisse liefern nun einen direkten numerischen Zusammenhang zwischen Verformungen der Holzmikrostruktur und dem daraus resultierenden makroskopischen Verhalten.
The internal project "SealWasteSafe" of the Federal Institute for Materials Research and Testing is dedicated to the further improvement in the construction of sealing systems for underground repositories of radioactive waste. Particularly, a multi-sensory concept is developed to ensure quality assurance and continuous long-term monitoring on the engineered barriers. Therefore, beside other measures, the temperature and equilibrium moisture of the construction shall be monitored and respective multi-sensoric monitoring concepts are tested first on the laboratory scale. One focus in this project is on embedded application in alkali-activated mortars (AAM), which results in special requirements for the resistance of the sensors to strongly alkaline environments with up to pH 14. In addition, the ingress of water along cables or at sensor positions is critical for sensors embedded in concrete, as the cable access of the sensor housing is a major weak point. It is therefore advisable to equip wireless high frequent radio frequency identification-based sensors, so called HF RFID sensors (short: RFID), that do not require cable access and thus have a stable and leak-proof sensor housing for long-term monitoring. In this contribution, the results from temperature, moisture and transmitted power monitoring of a AAM and a M2 specimens by means of HF RFID sensor systems are presented.
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.
Development of a Low-Cost Sensing Node with Active Ventilation Fan for Air Pollution Monitoring
(2021)
A fully designed low-cost sensing node for air pollution monitoring and calibration results for several low-cost gas sensors are presented. As the state of the art is lacking information on the importance of an active ventilation system, the effect of an active fan is compared to the passive ventilation of a lamellar structured casing. Measurements obtained in an urban outdoor environment show that readings of the low-cost dust sensor (Sharp GP2Y1010AU0F) are distorted by the active ventilation system. While this behavior requires further research, a correlation with temperature and humidity inside the node shown.
In the present paper the development of a semi-automated device for long-term monitoring of gaseous ammonia is described. A sensor material was produced that changes its optical properties in the pres-ence of low concentrations of ammonia in air. The implementation into an electronic device enables precise, simple, economic and fast monitoring of low concentrations of harmful gases, like ammonia, and hence can help to improve the climate monitoring in livestock housing, barns or stables.
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.
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.
The present paper describes the development of a sensor material that changes its fluorescence in the presence of gaseous ammonia in a relevant concentration range. The implementation into a semi-automatic gas measurement device enables low-cost, precise, simple and fast monitoring of low con-centrations of harmful gases, like ammonia, and hence can help to improve the climate monitoring in livestock housing, barns or stables.
The vulnerability of low-quality concrete of some bridges to ageing and deterioration while they are exposed to environmental conditions during their service life, influence of growing population and climate changes, is a well-known effect and requires survey. For survey, the development of a low cost, cost-efficient sensor network to be embedded for continuous or attached to the surface for periodic monitoring is essential.
Changing ground water conditions, flood or even leakage in fresh or disposal of waste water can lead to in-creased moisture content in building materials and structural elements as walls or floors. Moisture allows the transport of other adverse chemicals that might reduce the durability of structures. The paper presents a feasibility study about the capability of microwave modules as bluetooth® or ZigBee with frequency range at 2,4 GHz to create advanced Wireless Sensor Networks (WSN) for estimation and visualization of moisture distribution in infrastructure assets. It was found that the value of the received signal strength indication (RSSI) depends on the moisture content and can be the basis for the moisture distribution inside a massive structure.
The microwave modules may be used to compose networks outside and inside of building materials or structural elements. The higher the number of connections between BLE modules, the more precise and the more distant information can be obtained from the network. Mesh networking was applied to increase the quantitative information.
Occupational health is an important topic, especially in industry, where workers are exposed to airborne by-products (e.g., dust particles and gases). Therefore, continuous monitoring of the air quality in industrial environments is crucial to meet safety standards. For practical and economic reasons, high-quality, costly measurements are currently only carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only.
Recent developments in sensor technology enable cost-efficient gas monitoring in real-time for long-term intervals. This knowledge of contaminant distribution inside the industrial environment would provide means for better and more economic control of air impurities, e.g., the possibility to regulate the workspace’s ventilation exhaust locations, can reduce the concentration of airborne contaminants by 50%.
This paper describes a concept proposed in the project “Robot-assisted Environmental Monitoring for Air Quality Assessment in Industrial Scenarios“ (RASEM). RASEM aims to bring together the benefits of both – low- and high-cost – measuring technologies: A stationary network of low-cost sensors shall be augmented by mobile units carrying high-quality sensors. Additionally, RASEM will develop procedures and algorithms to map the distribution of gases and particles in industrial environments.
Die Varroose gilt weltweit als eine der bedeutendsten Erkrankungen der westlichen Honigbiene, Apis mellifera. Verursacht wird sie durch den Ektoparasiten Varroa destructor, der durch Saugen der Hämolymphe und Virenübertragung sowohl die Bienenbrut als auch die adulten Individuen schädigt.
Ohne imkerliche Unterstützung gehen betroffene Bienenvölker in der Regel innerhalb von drei Jahren ein. Als bewährte, häufige Behandlung wird flächendeckend 60%ige Ameisensäure (AS) - im Bienenstock appliziert über verschiedene Verdampfungssysteme - eingesetzt. Sie wirkt als einziger zugelassener Stoff gegen die Varroamilbe auch in die verdeckelte Brut hinein und birgt kein Risiko der Resistenzentwicklung.
Allerdings ist das therapeutische Fenster, der Bereich zwischen Milbenabtötung und Bienenschädigung, relativ schmal und die tatsächliche AS-Konzentration im Bienenstock stark abhängig von äußeren Einflussfaktoren, wie Temperatur, Luftfeuchte oder Applikationsart.
Eine Bestimmung der exakten AS-Konzentration im Bienenstock ist also notwendig, um einerseits das Wirkungsoptimum zu bestimmen und andererseits bei Übersteigen der Maximalkonzentrationen mit Folge-Schädigung der Bienen, ein rechtzeitiges Eingreifen der Imker zu ermöglichen.
For a better understanding of the damage of glued wood tensile tests on miniature specimens made of glued spruce wood with acoustic emission and in-situ synchrotron-based X-ray computer microtomography has been monitored. As adhesive, urea-formaldehyde resin was used. For comparison purposes, tensile tests were carried out on solid wood and bonded miniature tensile shear samples with acoustic emission. The acoustic emission signals of all experiments were with classified pattern recognition. This resulted in two classes of signals for each two frequency peaks. In one class was the low-frequency, in the other the higher frequency peak of higher intensity, but this essentially independent from the structure (solid wood or plywood) and the size scale of the test specimens. The influence of the adhesive layers was determined on plywood test specimens in laboratory scale and on miniature test specimens with an adhesive layer and selected fiber orientations examined. This gave evidence that the sound emission signals from the failure of the adhesive layer presumably of the class with low frequency signals peak in the range of services can be assigned.
Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or hardly accessible areas. A challenging task, however, is the generation of threedimensional distribution maps from these gas measurements.
Suitable reconstruction algorithms can be adapted, for instance, from the field of computed tomography (CT), but both their performance and strategies for selecting optimal measuring poses must be evaluated. For this purpose simulations are used, since, in contrast to field tests, they allow repeatable conditions. Although several simulation tools exist, they lack realistic models of remote gas sensors. Recently, we introduced a model for a Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor taking into account the conical shape of its laser beam. However, the novel model has not yet been validated with experiments. In this paper, we compare our model with a real sensor device and show that the assumptions made hold.
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.
By means of a small-scale truss bridge, the ability of the Measurement- and Model-based Structural Analysis to detect and localize damage was examined. Although there was no noteworthy difficulty in detecting damage, it turned out that damage localization responds sensitively to systematic influences, i.e. non-modelled properties of the mechanical model. Therefore, another experiment is being conducted to re-examine the Measurement- and Model-based Structural Analysis. For this purpose, the bending test is carried out as it has been already theoretically respectively numerically discussed. In this attempt, the systematic influences such as residual stress are kept as low as possible.
The development of algorithms for mapping gas distributions and localising gas sources is a challenging task, because gas dispersion is a highly dynamic process and it is impossible to capture ground truth data. Fluid-mechanical simulations are a suitable way to support the development of these algorithms. Several tools for gas dispersion simulation have been developed, but they are not suitable for simulations of large outdoor environments. In this paper, we present a concept of how an existing simulator can be extended to handle both indoor and large outdoor scenarios.
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.
Remote gas sensors like those based on the Tunable Diode Laser Absorption Spectroscopy (TDLAS) enable mobile robots to scan huge areas for gas concentrations in reasonable time and are therefore well suited for tasks such as gas emission surveillance and environmental monitoring. A further advantage of remote sensors is that the gas distribution is not disturbed by the sensing platform itself if the measurements are carried out from a sufficient distance, which is particularly interesting when a rotary-wing platform is used. Since there is no possibility to obtain ground truth measurements of gas distributions, simulations are used to develop and evaluate suitable olfaction algorithms. For this purpose several models of in-situ gas sensors have been developed, but models of remote gas sensors are missing. In this paper we present two novel 3D ray-tracer-based TDLAS sensor models. While the first model simplifies the laser beam as a line, the second model takes the conical shape of the beam into account. Using a simulated gas plume, we compare the line model with the cone model in terms of accuracy and computational cost and show that the results generated by the cone model can differ significantly from those of the line model.
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 presentation gives an introduction to the gas-sensitive aerial robots developed at BAM, including various application examples in the field of mobile robot olfaction: gas source localization and gas distribution mapping.
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 work presents the testing of a developed elec¬tronic nose for outdoor odour nuisance monitoring. The sensor system consists of a sampling system, a measuring cell equipped with commercially available low-cost gas sensor elements and a data acquisition system. The sensor testing showed that the developed prototype is able to distinguish, identify and partially quantify individual odorous substances like ethanol, ammonia and hydrogen sulphide. Ethanol and ammonia could even be detected below or near their odour threshold.
Within the presented research project, experimental and numerical investigations were performed to develop a thin-shelled, modular, mobile element system made of a micro-reinforced ultra-high-performance ductile concrete (DUCON®). Material parameters were experimentally determined to adapt the material model within the numerical analysis applying the Drucker-Prager relationship. Afterwards, for validation of the numerical models, quasi-static and high-velocity impact tests were performed on plate-like structures. Finally, a suitable geometry of transportable barrier elements will be designed, which provides a maximum of resistance against impact by a minimum of weight and a maximum of mobility.
Der Beitrag präsentiert die erarbeiteten technischen Richtlinien zur Anwendung und Prüfung von Multigassensoren innerhalb der Richtlinienreihe VDI/VDE 3518 sowie in diesem Zusammenhang die Möglichkeiten der Sensorprüfung im akkreditierten Prüflabor des Fachbereichs 8.1 der BAM. Im Speziellen wird das in Kürze veröffentlichte Blatt 3 der Richtlinienreihe vorgestellt, das Bezug auf Multigassensoren für geruchsbezogene Messungen mit elektronischen Nasen nimmt.
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.)
The feasibility study „AGIFAMOR. Ageing infrastructures – distributed acoustic monitoring of pipes” is an interdisciplinary research project at BAM internally financed from 2015 to 2018. Therefore, the quite young fibre optic sensing technology of distributed acoustic sensing (DAS) was investigated to possibly be extended towards a global condition monitoring system for pipelines operating in real time.
DAS is a highly dynamic fibre optic sensing technology based on the method of coherent optical time domain reflectometry (C-OTDR). DAS allows capturing strain changes in the range of kHz. For the experimental work, the most suitable application yielding an optimum sensitivity was proven by wrapping a standard single-mode silica fibre around the pipe.
The DAS sensitivity was investigated regarding the detection of 1) incidents that initiate propagation of acoustic waves in the pipe wall, 2) changes inside the pipeline causing altered flow and 3) damage development in the pipe wall. Therefore, several testing setups in laboratory as well as in real scale were realized. For comparison purposes, experiments were accompanied by acoustic emission analyses and by measurements with accelerometers.
DAS was found to be very sensitive to gas ignition and its propagation across the pipe. Furthermore, the ability of DAS to detect and localize acoustic signals associated with pipeline leakage was demonstrated. The detection of crack formation and propagation within the pipe wall by means of DAS was studied during bending tests on several pipe segments, but was not proven so far with certainty. As expected, these studies turned out as the most difficult challenge due to the random occurrence and transient nature of microscopic damage phenomena.
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.
Damage mechanisms analysis of reinforced concrete beams in bending using non-destructive testing
(2019)
Beams that are loaded in transverse direction are one of the main structural elements used in reinforced concrete structures. Bending beams are used, for example, in bridge girders or joists. The strength related failure modes at maximum loading can be divided into bending and shear failure that could occur with or without indication. Conventional design concepts used in practice for designing structural elements subjected to bending aim at failure modes with sufficient indication (e.g. large deflections or cracks), as it occurs in the case of secondary flexure-compression-failure. These indicators can also be used to identify structural changes of civil infrastructure systems (e.g. bridges) using non-destructive testing methods for Structural Health Monitoring (SHM). However, profound knowledge on the determining failure modes of bending beams is required for the reliable application of structural health monitoring. Therefore, resulting effects of different thermal and mechanical loads on the response of a structure are investigated by means of a bridge demonstrator. The results of this investigation are used for developing a monitoring system. Different non-destructive testing (NDT) methods have been used for analyzing the deformation behavior of a reinforced concrete beam in bending. The suitability of the different measuring techniques will be discussed by means of the obtained experimental results. For this purpose, the deformation behavior of a reinforced concrete beam having a span of 2.75 m was investigated in a four-point bending flexural test at laboratory scale. The focus is on the characterization of determining failure modes by the NDT methods and the comparison with classical measuring techniques (e.g. deformation measurements by displacement transducers). The bending tests have been accompanied by Acoustic Emission analysis (AE), optical deformation measurements using Stereophotogrammetry (SP) and Digital Image Correlation (DIC). The conducted tests have shown that the three-dimensional detection of deformations and resulting strains with optical techniques is beneficial for analyzing the damage mechanism of loaded structures and related crack formation and propagation. Optical techniques can be supplemented by acoustic emission testing which gives detailed information on crack formation and progressing damage. The combination of both techniques offers the application as efficient monitoring system for larger structures.
Moisture content and water activity are important parameters for quality characterization of products like bulk materials, powders, granules. Thus, an exact determination is necessarily required in a wide range of industrial applications. Moisture of materials is the content of non-chemically bound water in a solid or liquid. Water activity (aW) is a characteristic/parameter of the non-chemically bound ("free") water in materials and is measured as humidity over a solid/liquid surface at constant temperature (equilibrium moisture content). It is an important parameter to characterize the quality of e. g. pharmaceutical and food products. In our contribution, we present the developed MOISHUM device for staged determination of water activity and moisture content of liquid and solid materials.
In robotic applications, it is often necessary to orient a sensor quickly. Spherical parallel manipulators (SPM) are well suited for this purpose since they offer superior dynamics and structural stiffness as compared to serial manipulators. To control them, however, the kinematic equations have to be known. In this paper, a SPM with three degrees of freedom and the kinematic equations describing its mechanical properties are presented.
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.
To examine the capability to detect and localise damage using the Measurement- and Model-based Structural Analysis (MeMoS), a small-scale truss bridge (1520 mm × 720 mm × 720 mm) made of aluminium profiles is built as a test specimen for this purpose. The truss frame of the test bridge is made of aluminium profiles with a sophisticated design of the cross-sectional area. In comparison, with solid profiles, only a fraction of the material is needed to produce the profiles, while their bending resistance decreases slightly. The profiles are built into a truss frame by connecting them by means of fastening sets made of steel. The bridge model is mounted on four steel bearings which each of them consist of a cylinder arranged between two plates. Fixed bearings are made by holding onto one end of the bridge. The bridge is subjected by an external load by placing a heavy object beneath it. At the same time, measurements can be conducted below the bridge. Therefore, the bridge specimen is elevated by attaching it on a pedestal with four columns. Damages can be induced by loosening the fastening pieces.
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.
Four-point bending tests were carried out to analyze the acoustic characteristics of damage development in pipe segments made of steel, grade S355J2H, being 2.5 m long with an outer diameter of 168 mm and 16 mm wall thickness. To induce stable crack growth, the pipe segments were pre-damaged by a 90°circumferential notch in the middle of the pipe length. While the pipe was quasi-statically loaded, microscopic damage and plastic deformation accumulated to form a macroscopic crack that grew through the pipe wall until leakage. For acoustic emission (AE) monitoring, four broadband sensors of type VS 900 M were mounted close to the notch. Continuous AE signal detection was performed by the non-threshold method. Advantages and disadvantages of the non-threshold AE monitoring compared to a commonly employed method analyzing only signals exceeding a predefined threshold are discussed. The results of AE analysis are compared to additional information on the crack growth detected by the direct current potential drop (DCPD) technique. These studies were carried out in the course of the interdisciplinary research project AGIFAMOR, Ageing infrastructures - distributed acoustic monitoring of pipes at BAM.
Planar coulometric sensors were investigated in humidified synthetic air at various absolute gas pressures, i. e. 2 bar, 5, bar, 10 bar, and 15 bar. Humidified gas flow at adjusted gas pressure was split into two flows, one passed a coulometric sensor and the other one passed a reference hygrometer after decompression. Both signals were recorded and then compared after calculation of resulting frost point temperature. Calculation is based on a calibration function obtained at ambient pressure. Comparison showed that an increasing pressure resulted in a higher derivation between sensor signal (calculated frost point temperature) and reference frost point temperature. At an absolute pressure of 2 bar the differences were minor in consideration of the uncertainty, however at 15 bar the differences were 6.77 K. Nevertheless, it was possible to measure the gas humidity at higher pressure with coulometric trace humidity sensors.
Es wird ein vereinfachtes Verfahren für die Bestimmung und Implementierung der Maschinennachgiebigkeit bei der Verwendung eines sphärischen Indenters dargestellt. Die Maschinennachgiebigkeit wird bei deutlicher Kraftabhängigkeit als Funktion der Kraft in die Auswertung implementiert. Als sensitiver Kennwert dient der aus der instrumentierten Eindringprüfung an Härtevergleichsplatten ermittelte Eindringmodul.
Temperature characteristics of a piezoresistive accelerometer for high impact shock application
(2018)
This study presents the characterization of a piezoresistive accelerometer damped with silicon oil for the application in drop tests carried out at BAM. Experiments were performed with the Hopkinson Bar method in close correlation to the real-world application conditions. The results point out certain limitations regarding the temperature influence and the frequency response. Additional experiments were performed with a gas damped type of piezoresistive accelerometer, which has superior specifications, particularly for low temperatures. The results allow for a comparison.
Ionische Flüssigkeiten als neuartige Sensorbeschichtung für coulometrische Spurenfeuchtesensoren
(2018)
Die Arbeit präsentiert erste Messungen mit coulometrischen Sensoren, die mit einer ionischen Flüssigkeit beschichtet sind. Diese Sensoren werden in der Industrie verwendet, um die Spurenfeuchte in unterschiedlichen Gasen zu messen. Normalerweise erfolgt eine Beschichtung der Sensoren mit Phosphorpentoxid und dessen Hydrolyseprodukte. In dieser Arbeit wurde stattdessen eine hygroskopische ionische Flüssigkeit benutzt. Die generierte Gasfeuchte für die Untersuchungen betrug bezogen auf die Frostpunkttemperatur -80 °C bis -30 °C, was gleichbedeutend mit einem Wasserdampf-Stoffmengenanteil von 0,5 μmol·mol-1 bis 376 μmol·mol-1 ist. Zusätzlich zu der Messung mit coulometrischen Sensoren erfolgte eine Referenzmessung der Gasfeuchte mittels eines Taupunkthygrometers. Erste Ergebnisse haben gezeigt, dass es möglich ist mit dieser Art der Beschichtung unterschiedliche Gasfeuchten zu messen. Aber es ergaben sich trotz gleicher Feuchte unterschiedliche Signalintensitäten bei den benutzen Sensoren und es zeigte sich eine Drift des Sensorsignales.
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.
This work presents a first attempt to use ionic liquids as a new coating for planar coulometric sensors. These sensors are used for the measurement of trace humidity in various gases. Usually, the coating of the sensors is tetraphosphorus decaoxide and its hydrolysis products. Instead, a hygroscopic ionic liquid was used as sensor coating in this work. Generated frost point temperatures tf in the gas ranged from -80 °C to -30 °C, which is equivalent to vapour mole fractions xv from 0.5 μmol·mol-1 to 376 μmol·mol-1. In addition to the coulometric sensors, the generated humidity is determined by a precision dew point hygrometer as reference. First results show that it is possible to measure humidity with ionic liquid based coulometric sensors.
In Glasfasern eingeschriebene Bragg-Gitter (FBG: fibre-based Bragg gratings) sind über die Verschiebung der Bragg-Wellenlänge in der Lage, Stauchungen und Dehnungen von Glasfasern hochgenau zu erfassen. In Kompositwerkstoffe eingebettete faseroptische Sensoren können Bauteile bezüglich ihrer mechanischen Integrität überwachen und früh-zeitig Informationen über Materialveränderungen gewinnen.
Um die Zuverlässigkeit eines solchen Sensors zu gewährleisten, ist es wichtig, die korrekte Funktion des Sensors im Verbund mit der Werkstoff-Matrix on-line und in-situ sicherzu-stellen. Im Rahmen des DFG-Projekts FAMOS² (FAser-basierter Magneto-Optischer SchichtSensor) wurde ein selbstdiagnosefähiger Schichtsensor entwickelt, der mit Hilfe von magnetostriktiven Aktorschichten aus Nickel bzw. Eisen-Nickel validiert werden kann.
Der FAMOS²-Schichtsensor wird durch ein PVD (physical vapour deposition)/ECD (electro-chemical deposition) Hybridschichtsystem realisiert, das auf dem Fasermantel im Bereich des FBG haftfest, homogen und langzeitfunktional abzuscheiden ist. Dabei wird in einem ersten Schritt ein etwa 100 Nanometer dünnes PVD-Schichtsystem aus Chrom und Kupfer als Haftvermittler auf der Glasfaser bzw. als leitfähige Startschicht für den nachfolgenden ECD-Prozess abgeschieden. Um eine rotationssymmetrische Schich-tabscheidung zu gewährleisten, erfolgt während der PVD-Beschichtung eine Rotation der Glasfasern. In einem zweiten Schritt wird dann unter Verwendung eines klassischen Watts-Elektrolyten in einer speziell entwickelten ebenfalls rotationssymmetrisch aufgebau-ten ECD-Durchströmungszelle dann die etwa 30 Mikrometer dicke, magnetostriktive Ak-torschicht auf dem PVD-Schichtsystem abgeschieden, im Vergleich sowohl reine Nickel-Schichten als auch Nickel-Eisen-Schichten.
Ein äußeres Magnetfeld dehnt die magnetostriktive Aktorschicht und damit auch die Faser reversibel. Diese Dehnung führt zu einer Verschiebung der Bragg-Wellenlänge, welche direkt mit der Stärke eines zu messenden oder zu Validierungszwecken vorgegebenen Magnetfeldes korreliert. Die Anpassung der Beschichtungsverfahren an die Fasergeome-trie und die mechanischen Eigenschaften der Hybridschichten werden hinsichtlich der me-chanischen Integrität des faseroptischen Sensors diskutiert und der Nachweis der Selbst-diagnosefähigkeit erbracht.
The monitoring of oil and gas pipelines by means of distributed fibre optic sensors is becoming common. The most recent development in the field of fibre optic sensing is the distributed acoustic sensing (DAS), which allows to detect and to localize third party threats to pipelines. For this purpose, fibre optic telecommunication cables located close to the pipelines are usually used. However, DAS carries a far greater potential for continuous condition monitoring of pipelines.
The interdisciplinary research project AGIFAMOR (Ageing Infrastructures – Fibre Optic Monitoring of Pipes) at BAM investigates a new technical approach to extend the application field of DAS towards the detection and localization of acoustic signals that indicate critical alterations and certain damage scenarios originated from within the pipeline or the pipe wall. Therefore, the optical fibre sensors are applied onto the pipe itself and the application procedure towards an optimal acoustic signal transduction is optimized.
A number of laboratory scale experiments were performed focusing on the signal transmission of acoustic signals as well as the detection of damages in the pipe wall by means of DAS. Furthermore, real-scale tests on a pipeline DN100 of 38m length have been carried out at the BAM test site for technical safety (BAM-TTS) to study the detection and localization of leaks and of changing flow profiles due to corrosion or sedimentation processes.