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Air pollution within industrial scenarios is a major risk for workers, which is why detailed knowledge about the dispersion of dusts and gases is necessary. This paper introduces a system combining stationary low-cost and high-quality sensors, carried by ground robots and unmanned aerial vehicles. Based on these dense sampling capabilities, detailed distribution maps of dusts and gases will be created. This system enables various research opportunities, especially on the fields of distribution mapping and sensor planning. Standard approaches for distribution mapping can be enhanced with knowledge about the environment’s characteristics, while the effectiveness of new approaches, utilizing neural networks, can be further investigated. The influence of different sensor network setups on the predictive quality of distribution algorithms will be researched and metrics for the quantification of a sensor network’s quality will be investigated.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Im Rahmen des Projekts „Complex Fires – Auswirkung von Behälterversagen“ (CoFi-ABV) sollen die Auswirkungen des Versagens von Gasbehältern für alternative Treibstoffe in Fahrzeugen unter Berücksichtigung komplexer Brand- und Explosionsszenarien untersucht werden. Es wird der aktuelle Hintergrund des Forschungsvorhabens erläutert sowie die geplanten Untersuchungen und beabsichtigten Ergebnisse vorgestellt. Hauptbestandteil des Projekts ist eine Vielzahl von zerstörenden Großversuchen. Im Vorfeld dieser Großversuche werden zur Weiterentwicklung und Adaptierung von Messtechnik Versuche im kleineren Maßstab durchgeführt. Im Folgenden werden Teile dieser Ver-suchsaufbauten im „mid-scale“ sowie die dabei verwendete Messtechnik dargestellt. Weiterhin werden erste Ergebnisse aus Wärmeeintragsversuchen zur Quantifizierung verschiedener Unterfeuerungsmethoden für die zerstörenden Großversuche vorgestellt.
Commercial, off-the shelf propane cylinders are subjected to high safety regulations. Furthermore, those cylinders are equipped with safety devices like pressure relief valves (PRV). Despite these regulations and safety measures, a failure of the Container is possible if exposed to an intense fire. The result of this is severe hazard for users, rescue forces and infrastructure. Within the framework of a destructive test series, 15 identical propane cylinders, without pressure relief devices, were exposed to an intensive fire in horizontal Position until failure. Each cylinder was filled with a mass of m =11 kg of liquid propane. Three different fire sources were used (wood, petrol, propane). The experiments revealed the failure of all cylinders in a time period t < 155 s. The failure lead to a fragmentation into several major parts with throwing distances of up to l =262 m. In all trials, the temperature of the cylinder wall (top, side, bottom), of the liquid phase inside and of the surrounding fire (top, side, bottom) was recorded. In addition, the inner cylinder pressure and the induced overpressure of the blast wave after the failure were recorded. Overpressures of up to p=0.27 bar were recorded close to the cylinder (l =5 m). AM tests were documented hy video from several positions (general view, close-up, high-speed 5000 fps). This test series creates the basis for further experimental studies in the field of alternative fuels for vehicles. The aim of this test series is to assess and analyse the consequences of the failure of gas vessels (for LPG, CNG, CGH2) in the aftermath of severe incidents.
Commercial, off-the shelf propane cylinders are subjected to high safety regulations. Furthermore, those cylinders are equipped with safety devices like pressure relief valves (PRV). Despite these regulations and safety measures, a failure of the container is possible if exposed to an intense fire. The result of this is severe hazard for users, rescue forces and infrastructure. Within the framework of a destructive test series, 15 identical propane cylinders, without pressure relief devices, were exposed to an intensive fire in horizontal position until failure. Each cylinder was filled with a mass of m =11 kg of liquid propane. Three different fire sources were used (wood, petrol, propane). The experiments revealed the failure of all cylinders in a time period t < 155 s. The failure lead to a fragmentation into several major parts with throwing distances of up to l =262 m. In all trials, the temperature of the cylinder wall (top, side, bottom), of the liquid phase inside and of the surrounding fire (top, side, bottom) was recorded. In addition, the inner cylinder pressure and the induced overpressure of the blast wave after the failure were recorded. Overpressures of up to p=0.27 bar were recorded close to the cylinder (l =5 m). All tests were documented by video from several positions (general view, close-up, high-speed 5000 fps). This test series creates the basis for further experimental studies in the field of alternative fuels for vehicles. The aim of this test series is to assess and analyse the consequences of the failure of gas vessels (for LPG, CNG, CGH2) in the aftermath of severe incidents.
In Deutschland gibt es eine große Anzahl von Kraftfahrzeugen, die mit alternativen Antrieben (z. B. LPG (Liquefied Petroleum Gas), CNG (Compressed Natural Gas)) ausgerüstet sind. In zahlreichen Großversuchsserien untersucht die Bundesanstalt für Materialforschung und -prüfung (BAM) im Rahmen des internen Forschungsprojekts CoFi-ABV (Complex Fires – Auswirkungen von Behälterversagen) die Auswirkungen beim Versagen der Treibstoffbehälter dieser alternativen Antriebe. Ziel dieser Untersuchungen ist eine ganzheitliche Auswirkungsbetrachtung, um die Risiken für Feuerwehren und Rettungskräfte besser abschätzen zu können. Im Vorfeld zu den Versuchen für LPG- und CNG-Tanks wurden in einer weiteren Versuchsserie 15handelsübliche 11-kg-Propangasflaschen ohne Sicherheitseinrichtung unterfeuert. Alle 15 Behälter haben – wie zu erwarten war – versagt. Neben den Zustandsdaten des Behälters zum Versagenszeitpunkt (Temperatur des Behältermantels, Innendruck und -temperatur) wurden die Auswirkungen auf die Umgebung hinsichtlich Druckwirkung und Fragmentierung (Anzahl, Masse, Distanz, Richtung) dokumentiert.
In einer Großversuchsserie wurden auf dem BAM-TTS 15 11-kg-Propangasflaschen ohne Sicherheitseinrichtung mit drei verschiedenen Methoden (Holz, Benzinpool, Gas) unterfeuert. Der Beitrag beschreibt die dokumentierten Auswirkungen (z. B. Fragmentierung, Überdruck), die Art des Versagens sowie den Behälterzustand zum Zeitpunkt des Versagens.
In case of a vehicle fire, an installed LPG (liquefied petroleum gas) tank with a malfunctioning safety device poses severe hazards. To investigate the consequences in case of tank failure, we conducted 16 tests with toroidal shaped LPG vehicle tanks. Three tanks were used for a Hydraulic Burst Test under standard conditions. Another three tanks were equipped with a statutory safety device and were subjected to a gasoline pool fire. The safety device prevented tank failure, as intended. To generate a statistically valid dataset on tank failure, ten tanks without safety devices were exposed to a gasoline pool fire. Five tanks were filled to a level of 20 %; the re-maining five were filled to a level of 100 %. In order to gain information on the heating process, three tem-perature readings at the tank surface, and three nearby flame temperatures were recorded. At distances of l = (7; 9; 11) m to the tank, the overpressure of the shock wave induced by the tank failure and the unsteady tem-peratures were measured. All ten tanks failed within a time of t < 5 min in a BLEVE (boiling liquid expanding vapor explosion). Seven of these resulted directly in a catastrophic failure. The other three resulted in partial failure followed by catastrophic failure. A near field overpressure at a distance of l = 7 m of up to p = 0.27 bar was measured. All ten tests showed massive fragmentation of the tank mantle. In total, 50 fragments were found. These 50 fragments make-up 88.6 % of the original tank mass. Each fragment was georeferenced and weighed. Fragment throwing distances of l > 250 m occurred. For the tanks with a fill level of 20 %, the average number of fragments was twice as high as it was for the tanks that were filled completely.
Compressed natural gas (CNG) is a widely used automotive fuel in a variety of countries. In case of a vehicle fire where the safety device also malfunctions, a failure of the CNG automotive cylinder could occur. Such a cylinder failure is associated with severe hazards for the surrounding environment. Firstly, a comprehensive analysis is given below, summarizing various accidents involving CNG automotive cylinders and their consequences. In an extensive experimental program, 21 CNG automotive cylinders with no safety device were tested. Of the 21, burst tests were carried out on 5 Type III and 5 Type IV cylinders. Furthermore, fire tests with 8 Type III and 3 Type IV cylinders were conducted. Apart from cylinder pressure, inner temperature and cylinder mantle temperature, the periphery consequences, such as nearfield blast pressure and fragmentation are documented. The maximum measured overpressure due to a Type III cylinder failure was p = 0.41 bar. Each traceable fragment was georeferenced. All-in-all, fragment throw distances of d > 300 m could be observed. As one key result, it can be stated that the tested Type IV CNG cylinders showed less critical failure behavior then the Type III cylinders under fire impingement.
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.
Pollution through emission of toxic gases is an increasing problem for the environment. It affects similarly agricultural, industrial and urban areas. In future, environmental emissions in ambient air must be monitored at even lower concentrations as nowadays. One environmental relevant compound is ammonia and its conversion product ammonium that have strong negative impact on human health and ecosystems. Most ammonia measurements in ambient air are performed in the range below 1000 nmol·mol 1 and thus there is a need for reliable traceable ammonia gas standards and in addition in situ analytical procedures for monitoring (in ambient air to avoid that thresholds are exceeded). Therefore, the use of reference materials is necessary for development accompanying test or for calibration, e. g. of structure-integrated sensors and mobile multi-gas sensors.
The developed gas standard generator produces gas mixtures that comply with the metrological traceability for ammonia gas standards in the desired environmentally relevant measurement range. The method is based on the permeation of ammonia through a membrane at constant temperature and pressure. The resulting ammonia penetrant gas flow is then mixed with a carrier gas flow to generate a gas standard flow of known concentration. The dynamic rage is enlarged by using a two dilution steps. Depending on the permeation rate, generable molar fractions are possible in the range nmol·mol-1 to a few µmol·mol-1. We present the design of an ammonia gas standard generator and first results of the characterisation of its individual components supporting the uncertainty assessment according to GUM for stable gas concentrations in this range. The relative uncertainty of the generated ammonia gas standard is smaller than 4 % (k = 2).