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Paper des Monats
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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 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.
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).
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.
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 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.
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.
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 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.
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.
Strain and acceleration measurement during high dynamic drop tests, e.g., of containments for dangerous goods is performed using high speed multichannel measuring systems. So far established and operated systems need a cable connection of every strain gauge and acceleration sensor with the measuring device, often counting up to a number of more than 100 cables, corresponding to the number of applied sensors. The result is a massive cable harness consisting of all single cables, which is difficult to handle and causes a number of practical problems. An innovative approach is proposed by using a single cable measuring system, consisting of measuring modules with data bus connection and local data acquisition. Promising results were presented in a previous study. This paper follows up with additional results from full-scale testing of a further enhanced single cable system for the application in drop tests.
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.
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 combination of RFID tags and energy efficient sensors offers promising potential for identification, diagnosis, and monitoring applications - particularly when it comes to objacts, which require continuous observation and which are difficult to access with conventional tools. This paper presents two examples as an outlook for RFID sensor systems in embedded structures and in mobile applications.
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 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.
The combination of different types of sensors to multi-sensor devices offers excellent potential for monitoring applications. This should be demonstrated by means of four different examples of actual developments carried out by Federal Institute for Materials Research and Testing (BAM): monitoring and indoor localization of relief forces, a micro-drone for gas measurement in hazardous scenarios, sensor-enabled radio-frequency identification (RFID) tags for safeguard of dangerous goods, and a multifunctional sensor for spatially resolved under-surface monitoring of gas storage areas. Objective of the presented projects is to increase the personal and technical safety in hazardous scenarios. These examples should point to application specific challenges for the applied components and infrastructure, and it should emphasize the potential of multi-sensor systems and sensor data fusion.
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.
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.