Analytische Chemie
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- Nano aerial robot (7)
- Mobile Robot Olfaction (5)
- Sensor network (5)
- Electronic nose (4)
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- Swarm (4)
- TDLAS (4)
- Environmental monitoring (3)
- Gas tomography (3)
- LoRaWAN (3)
Organisationseinheit der BAM
- 8.1 Sensorik, mess- und prüftechnische Verfahren (56) (entfernen)
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.
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.
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.
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.
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.
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.
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.
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.)
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.
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.
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 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 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 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.
Against the background of sustainable resource management and efficiency, wood-based materials are currently experiencing a revival and, among others, plywood, Laminated Veneer Lumber and glued laminated timber are becoming increasingly more important in the building sector. Even though these materials are so-called engineered products, the element wood is naturally grown with intrinsic variability in mechanical properties and requires professional handling on-site. Otherwise, load-bearing structures made of wood materials may entail certain risks. Critical situations can, in principle, be avoided by implementing a structural health monitoring system into components or structures made from wood material. The aim is to indicate accumulation of mechanical damage and to eliminate or at least significantly reduce the risk of unexpected failure. Toward this purpose, the failure behavior of several layered wood materials under quasi-static tension was investigated in laboratory-scale experiments by means of acoustic emission (AE) measurement. Based on spectral analysis and pattern recognition, two classes of AE signals are identified for each investigated lay-up that are characterized by either low or high frequency contents in the respective power spectra. AE activity and intensity of both signal classes are analyzed, striving for predictors appropriate for AE monitoring concepts.
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.
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.
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.
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 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.
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.
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.
Formic acid (FA) treatment as measure against the ectoparasitic mite, Varroa destructor, which infests the western honey bee, Apis mellifera, is usually performed twice a year. Although the therapeutic index is very narrow and the success of FA-treatment is highly dependent on various external factors, little is known about the local FA concentrations occuring in the hive. In this study we examined whether a commercially available odour measuring device (“electronic nose”) is suitable for measurements of high FA concentrations, as present during treatment. As measuring systems, two different setups were prepared for detection of FA concentrations in gas mixtures: A polymethyl methacrylate (PMMA) box was used to investigate whether the electronic nose is able to distinguish between different FA concentrations and a two-storied Segeberger hive to test under realistic conditions during bee-keeping.
In both experimental systems, the signals from the same sensor components (sensor type no. 1, 6, 7, 8 and 9) showed an increased sensitivity towards the presence of FA in the gas mixture. Principle component analysis (PCA) and linear discriminant analysis (LDA) allowed for identification of specific patterns in the measurement signals and showed clear correlations between the signals and the present FA concentration. These results indicate that the introduced commercial multi gas sensor system is suitable for detection of high FA concentrations, and therefore could be a starting point developing a detection method of FA. The future aim is to successfully monitor the efficiency and effectiveness of this anti-varroa-treatment.
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.
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.
Um ein tieferes Verständnis über die Schallemission bei der Entstehung und Ausbreitung von Rissen in Stahlrohrleitungen zu erlangen, wurde ein Stahlrohr der Güte S355J2H im Vierpunkt-Biegeversuch quasistatisch bis hin zum Wanddurchbruch (Leckage) belastet und mittels Schallemissionsmessung und Gleichstrompotentialmessung überwacht. Das Rohrsegment wurde durch einen 90°- Außenumfangskerb in der Mitte der Rohrlänge definiert vorgeschädigt, um davon ausgehend ein stabiles Risswachstum zu induzieren und die Analyse von Schallemission aus Rissereignissen, die am Kerb eintraten, sicherzustellen. Für die Schallemissionsmessung wurden vier Breitbandsensoren max. 105 mm vom Kerb entfernt montiert. Die Signalaufzeichnung erfolgte kontinuierlich und schwellwertunabhängig. Für die Gleichstrompotentialmessung wurde ein Gleichstrom von 300 A eingeleitet und der Potentialabfall über dem Kerb mit fünf Sonden entlang des Kerbs gemessen. Beide Messverfahren identifizieren die Rissinitiierung sowie Veränderungen im Risswachstum. Die detektierten Schallemissionsereignisse werden, unter Berücksichtigung spektraler Eigenschaften, mit fortschreitender Belastung und Rissentwicklung analysiert. Diese Studien wurden im Rahmen des interdisziplinären Forschungsprojekts AGIFAMOR, Aging infrastructure - Faseroptisches Monitoring von Rohrleitungen, an der BAM durchgeführt.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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 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.
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.
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.
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.
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.
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.
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.