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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
Use/distribution of cost-effective and biocompatible pieces of cellulose paper as passive optical chemosensors and readout by the camera system.
Modification of the paper surface using various chemically sensitive dyes (indicators) provides an optically detectable reaction and conclusions about the target substances and precise location.
Die zunehmende Bedeutung der luftgekoppelten Ultraschallprüfung (ACUT) in der zerstörungsfreien Prüfung (ZfP) unterstreicht die Notwendigkeit von standardisierten Abläufen und Methoden. Bei der ACUT bestehen grundlegende Unterschiede zur manuell durchgeführten Ultraschallprüfung mit Kontakttechnik oder zur automatisierten Tauchtechnik. Die Unterschiede bei der Bestimmung von Prüfkopfparametern für ACUT wurde von Herstellern, Forschungseinrichtungen und Anwendern bereits als wichtig erkannt, was sie veranlasst hat, im Rahmen des Unterausschusses Luftgekoppelte Ultraschallprüfung der DGZfP die Richtlinie US08 zur standardisierten Charakterisierung von luftgekoppelten Ultraschallwandlern zu erarbeiten. Darüber hinaus bestehen auch bei der Durchführung einer Messung grundlegende Unterschiede, die aktuell in einem Leitfaden zusammengetragen und definiert werden.
In diesem Beitrag wird ein Überblick über die geplanten Inhalte dieses Leitfadens gegeben. Insbesondere wird die Auswahl von Prüfparametern in Form von Frequenzen, Abständen und Positionierung sowie die Auswertung behandelt. Darüber hinaus werden die Ergebnisse eines Ringversuchs vorgestellt, welcher an einem eigens hierfür entwickelten und mit Defekten versehenem Prüfkörper, der sog. ACUT-Prüfplatte, durchgeführt wurde. In diesem Ringversuch werden unterschiedliche Messanordnungen, die mittels luftgekoppeltem Ultraschall möglich sind, anhand des erreichbaren Signal-Rausch-Verhältnisses sowie der messbaren Defektgröße quantifiziert. Zudem findet eine Abgrenzung zu weiteren gängigen Verfahren der ZfP statt. Anhand der hier vorgestellten Ergebnisse ist es möglich, die Anwendbarkeit des luftgekoppelten Ultraschalls unter Berücksichtigung unterschiedlicher Messanordnungen besser einzuschätzen.
Die größten Vorteile der luftgekoppelten Ultraschallprüfung sind: die berührungslose Prüfung und der Verzicht auf ein flüssiges Koppelmittel. Allerdings weisen die meisten luftgekoppelten Prüfszenarien ein sehr geringes Signal-zu-Rausch-Verhältnis (SNR) auf und die Pegel, die von luftgekoppelten Ultraschallwandlern realisiert werden, sind um mehrere Größenordnungen kleiner.
Da diese Herausforderung auch in anderen Disziplinen wie bspw. der Radartechnik existiert und dort ebenfalls eine entscheidende Rolle spielt, wurde die dort eingesetzte Pulskompression auf die physikalischen Gegebenheiten der luftgekoppelten Ultraschallprüfung angepasst und angewandt.
Dieser Beitrag präsentiert die Ergebnisse von zwei Versuchsaufbauten: 1) ein thermoakustischer Sender und ein optisches Mikrofon und 2) ein Paar Ferroelektret-Wandler als Sender und Empfänger. Aufgrund der physikalischen Randbedingungen wurden unipolare Kodierungen verwendet. Die Verwendung von unipolaren Kodes zur Modulation der Anregungssignale stellt dabei eine neue Methode dar, die so die Pulskompression für Ferroelektret- und thermoakustische Wandler ermöglichen soll. Die Anwendung der Pulskompression auf die Kombination aus thermoakustischem Sender und optischem Mikrofon konnte das Signal-zu-Rausch-Verhältnis um bis zu 15 dB und für die Ferroelektret-Wandler um bis zu 23 dB erhöhen.
Die größten Vorteile der luftgekoppelten Ultraschallprüfung sind: die berührungslose Prüfung und der Verzicht auf ein flüssiges Koppelmittel. Allerdings weisen die meisten luftgekoppelten Prüfszenarien ein sehr geringes Signal-zu-Rausch-Verhältnis (SNR) auf und die Pegel, die von luftgekoppelten Ultraschallwandlern realisiert werden, sind um mehrere Größenordnungen kleiner.
Da diese Herausforderung auch in anderen Disziplinen wie bspw. der Radartechnik existiert und dort ebenfalls eine entscheidende Rolle spielt, wurde die dort eingesetzte Pulskompression auf die physikalischen Gegebenheiten der luftgekoppelten Ultraschallprüfung angepasst und angewandt.
Dieser Beitrag präsentiert die Ergebnisse von zwei Versuchsaufbauten: 1) ein thermoakustischer Sender und ein optisches Mikrofon und 2) ein Paar Ferroelektret-Wandler als Sender und Empfänger. Aufgrund der physikalischen Randbedingungen wurden unipolare Kodierungen verwendet. Die Verwendung von unipolaren Kodes zur Modulation der Anregungssignale stellt dabei eine neue Methode dar, die so die Pulskompression für Ferroelektret- und thermoakustische Wandler ermöglichen soll. Die Anwendung der Pulskompression auf die Kombination aus thermoakustischem Sender und optischem Mikrofon konnte das Signal-zu-Rausch-Verhältnis um bis zu 15 dB und für die Ferroelektret-Wandler um bis zu 23 dB erhöhen.
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.
This study explores the acceleration of material design in the concrete industry, focusing on improving carbonation resistance, a key factor in the durability of concrete structures. Traditional tests for carbonation resistance are lengthy, but with the construction industry aiming for sustainable production, finding a balance between carbonation resistance and CO2 footprint is crucial. Our research employs two innovative methods: 1. Applying the Sequential Learning App for Materials Discovery (SLAMD), an AI materials design framework, to an extensive dataset of real-world concrete compositions to selectively test materials that meet market demands: maximum durability, optimal eco-durability, and the best cost-durability trade-off. 2. Investigating 1H Nuclear Magnetic Resonance (NMR) relaxometry as a quick alternative for characterizing carbonation behavior, as it saves time compared to traditional tests and assesses the complete material's pore space. Specific NMR features are then integrated into the material design model, with the model's performance compared against traditional approaches. The results of our study are compelling, demonstrating that materials can be precisely tailored to meet specific requirements with minimal data points. This marks a significant stride in the concrete industry, indicating that NMR-based, low-fidelity surrogate characterizations, combined with a focused, data-driven design approach, can substantially accelerate the development of durable, sustainable concrete mixtures.
Infrared thermography using a focused (spot or line) beam has proved to be effective for detection of surface breaking cracks on planar samples. In this work, we use the same principle, but applied to complex shaped components, like a rail section, a gear, and a gas turbine blade. We use a six-axis robot arm to move the sample in front of our thermographic setup. Several scanning paths and thermographic parameters are explored: scanning speed, density of points in each scanning slice, laser power and camera frame-rate. Additionally, we explore semi-automatic evaluation algorithms for crack detection, as well as 2D-to-3D registration of the found indications.
Related work
Laboratory Study:
Combining Signal Features of Ground-Penetrating Radar to Classify Moisture Damage in Layered Building Floors
https://doi.org/10.3390/app11198820
On-Site Study:
TBA
Doctoral Thesis:
Non-destructive classification of moisture deterioration in layered building floors using ground penetrating radar
https://doi.org/10.14279/depositonce-19306
Measurement Parameters
The GPR measurements were carried out with the SIR 20 from GSSI and a 2 GHz antenna pair (bandwidth 1 GHz to 3 GHz) in common-offset configuration. Each B-Scan consists of N A-Scans, each including 512 samples of a 11 ns time window. Survey lines were recorded with 250 A-Scans/ meter, which equals a 4 mm spacing between each A-Scan No Gains were applied.
Folder Description:
Lab_dry, Lab_insulDamage, Lab_screedDamage
- each contain 168 Measurements (B-Scans) in .csv on 84 dry floors, floors with insulation damage and screed damage.
- each floor setup was measured twice on two orthogonal survey lines, indicated by _Line1_ and _Line2_ in the file name.
- the file names encode the building floor setup e.g. CT50XP100 describes a 50 mm cement screed with 100 mm extruded polystyrene below
- the material codes are
CT: cement screed, CA: anhydrite screed, EP: expanded polystyrene, XP: extruded polystyrene, GW: glass wool, PS: perlites
further information can be found in the publication https://doi.org/10.3390/app11198820
OnSite_
- 5 folders containing B-Scans on 5 different practical moisture damages
- the building floor setup is encoded according to the lab with an additional measurement point numbering at the start and a damage case annotation at the end of the file name with _dry, _insulationDamage and_screedDamage
File Description:
B-Scans, Measurement files - no header
- dimension: 512 x N data point with N beeing the number of A-Scans including 512 samples of a 11 ns time window.
- survey lines were recorded with 250 A-Scans/ meter, which equals a 4 mm spacing between each A-Scan
Moisture References
- Moist_Reference of On-Site Locations include the columns MeasPoint: Measurement point, wt%Screed: moisture content of screed layer in mass percent; wt%Insul: moisture content of insulation layer in mass percent. References were obtained by drilling cores with 68 mm diameter in the center of each survey line.
- Moist_Reference_Screed of Lab data include the columns Screed: Screed material and thickness in mm, wt%Screed moisture content of screed layer in mass percent
- Moist Reference_Insul of Lab data include the columns Insulation: Insulation material and thickness in mm, water addition in l: water added to the insulation layer in liters, V%Insulation: water added to the insulation layer in volume percent, RH%: resulting relative humidy in the insulation layer during measurement. These References are only avaible for Lab measurements on insulation damages.
Nondestructive testing of gas turbine blades is essential for their maintenance and service process which is critical to ensure both safety and efficiency of these highly stressed parts. In this presentation, a novel ultrasonic testing method is explored in order to acquire part thickness information in the turbine blade’s airfoil. In established industry processes, the measurements are mainly carried out manually and only at a few specific positions of the inspected parts. The proposed method scans the part using a robot arm guiding an ultrasonic array sensor. For ultrasonic coupling to the complex-shaped surface geometry, the inspected part and sensor are immersed into water. A two-step TFM[1, 2] (Total Focusing Method) approach is used to reconstruct the outer and inner surfaces subsequently from the ultrasonic raw data, which are acquired using the FMC[3] (Full Matrix Capture) measurement principle. For each sensor position, the location and geometry of the outer surface is first identified and then used to create an image of an area inside the material. From that image, the inner surface is reconstructed. Finally, part thickness information is deducted from merging location data of inner and outer surface. The result is a high resolution, high precision mapping of the inspected part’s wall thickness.
This seminar series comprises three lectures on drones and ground robots capable of sensing chemical substances and two accompanying hands-on workshops on nano drones equipped with chemical sensors. In the first lecture, Dr. Neumann will talk on a summary of aerial robot olfaction and his research. In the second and third lectures, more details of the nano drones equipped with chemical sensors will be provided, and the participants can get hands on experience of the nano
drones in the accompanying workshops. The lectures will be given in English. This seminar series is supported by FY2023 Researcher Exchanges Program in UEC.
This seminar series comprises three lectures on drones and ground robots capable of sensing chemical substances and two accompanying hands-on workshops on nano drones equipped with chemical sensors. In the first lecture, Dr. Neumann will talk on a summary of aerial robot olfaction and his research. In the second and third lectures, more details of the nano drones equipped with chemical sensors will be provided, and the participants can get hands on experience of the nano
drones in the accompanying workshops. The lectures will be given in English. This seminar series is supported by FY2023 Researcher Exchanges Program in UEC.
This seminar series comprises three lectures on drones and ground robots capable of sensing chemical substances and two accompanying hands-on workshops on nano drones equipped with chemical sensors. In the first lecture, Dr. Neumann will talk on a summary of aerial robot olfaction and his research. In the second and third lectures, more details of the nano drones equipped with chemical sensors will be provided, and the participants can get hands on experience of the nano drones in the accompanying workshops. The lectures will be given in English. This seminar series is supported by FY2023 Researcher Exchanges Program in UEC.
LIBS‐ConSort: Development of a sensor‐based sorting method for construction and demolition waste
(2023)
AbstractA joint project of partners from industry and research institutions approaches the challenge of construction and demolition waste (CDW) sorting by investigating and testing the combination of laser‐induced breakdown spectroscopy (LIBS) with near‐infrared (NIR) spectroscopy and visual imaging. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3‐cotaining building materials (gypsum, aerated concrete, etc.)Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic / technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.The objective of this paper is to present current progress and results of the test stand development combining LIBS with NIR spectroscopy and visual imaging. In the future, this laboratory prototype will serve as a fully automated measurement setup to allow real‐time classification of CDW on a conveyor belt.
Digital twin for hydrogen refueling stations: An analytical study for safe and efficient operations
(2023)
This analytical overview is the initial study in developing the digital sensors twin for the hydrogen refueling station. The research includes a comprehensive analysis of the current literature, refueling protocol, standards, mathematical model, simulation model, and trends in digital twins and H2 technologies. Furthermore, this study has explored the various HRS attributes, such as leakage, temperature, pressure, and hydrogen flow, and identified different use cases of the hydrogen fuel station to build a digital sensor twin. Various real gas equations, such as the Van der Waals and Able-Noble equation of state (EOS), are applied to analyze the key factors and parameters affecting hydrogen and the MATLAB simulation model to validate the key elements and parameters. This study also focuses on identifying and addressing research gaps in hydrogen technology, contributing to advancing hydrogen infrastructure, and supporting the global transition to cleaner energy solutions.
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.
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.
In construction and demolition waste (CDW) recycling, the preference to date has been to apply simple but proven techniques to sort and process large quantities of construction rubble in a short time. This contrasts with the increasingly complex composite materials and structures in the mineral building materials industry. An automated, sensor-based sorting of these building materials could complement or replace the practice of manual sorting to improve processing speed, recycling rates, sorting quality, and prevailing health conditions for the executing staff.
A joint project of partners from industry and research institutions approaches this task by investigating and testing the combination of laser-induced breakdown spectroscopy (LIBS) with near-infrared (NIR) spectroscopy and visual imaging. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of CDW, and may enable the detection and separation of impurities such as SO3-cotaining building materials (gypsum, aerated concrete, etc.)
We present current advances and results about the methodological development combining LIBS with NIR spectroscopy and visual imaging. Here, applying data fusion proves itself beneficial to improve recognition rates. In the future, a laboratory prototype will serve as a fully automated measurement setup to allow real-time classification of CDW on a conveyor belt.
Fused filament fabrication (FFF) on desktop 3D printers is a material extrusion-based technique often used by educational institutions, small enterprises and private households. Polymeric filaments are melted and extruded through a heated nozzle to form a 3D object in layers. The extrusion temperature is therefore a key parameter for a successful print job, but also one of the main driving factors for the emission of harmful air pollutants, namely ultrafine particles and volatile organic gases, which are formed by thermal stress on the polymeric feedstock. The awareness of potential health risks has increased the number of emission studies in the past years. However, the multiplicity of study designs makes an objective comparison of emission data challenging because printer hardware factors such as the actual extruder temperature (TE) and also feedstockspecific emissions are not considered. We assume that across the market of commercial low- and mid-price FFF printers substantial deviations between actual and set extruder temperatures exist, which have a strong effect on the emissions and hence may bias the findings of exposure studies. In our last publication, we presented a standardized feedstock-specific emission test method and showed that for each investigated feedstock an increase in actual extruder temperature was accompanied by an increase in particle emissions (Tang and Seeger, 2022). Therefore, any systematic discrepancy between set and actual extruder temperature matters. In this study, we used a thermocouple and an infrared camera to measure the actual extruder temperatures at different heights. We found significant under- and overestimation of the actual extruder temperatures by the respective set temperatures in three commercial printers. This caused a broad variation of the measured total numbers of emitted particles (TP), even when the same feedstock was operated. For the determination of TP, we followed the DE-UZ 219 test guideline. In a second round we repeated the tests with all printers adjusted to exactly the same extruder temperatures, i.e., to TE=230°C for ABS and TE=210°C for PLA. All measurements were conducted in a 1 m³ emission test chamber. Particle emissions in the size range between 4 nm and 20 μm were detected. Printing on three different printer models without temperature adjustment resulted for each of the investigated feedstocks in a variation in TP of around two orders of magnitude. After temperature adjustment, this was substantially reduced to approx. one order of magnitude and hence minimizes the bias of printer hardware on the emissions. Our findings suggest that adjustment of the extruder temperature should be mandatory in emission testing standards. It also poses a more accurate benchmark and provides more reliable emission data for evaluation of indoor air quality or for health risk assessments. In addition, a proper temperature setting is in the interest of the user. Some commercial FFF printers may have a higher actual extruder temperature than displayed and unintended overheating may not only impair the print quality but may cause unnecessarily increased exposure to particle emissions.
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 cost-efficient 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 presentation, we detail the technical aspects of RASEM and introduce the mobile platforms used.
Wavelength scanning coherent optical time domain reflectometer (WS-COTDR) is a good candidate to spatially resolve the environmental information at comparatively low frequency. This paper reveals it can also work as a traditional optical time domain reflectometer (OTDR) to identify Fresnel reflection by averaging the obtained signal over the wavelength scanning range. Simultaneous distributed vibration sensing and a traditional OTDR measurement are experimentally demonstrated using the WS-COTDR system.
Wavelength scanning coherent optical time domain reflectometer (WS-COTDR) is a good candidate to spatially resolve the environmental information at comparatively low frequency. This paper reveals it can also work as a traditional optical time domain reflectometer (OTDR) to identify Fresnel reflection by averaging the obtained signal over the wavelength scanning range. Simultaneous distributed vibration sensing and a traditional OTDR measurement are experimentally demonstrated using the WS-COTDR system.
Fused filament fabrication (FFF) is a material extrusion-based technique often used in desktop 3D printers. Polymeric filaments are melted and are extruded through a heated nozzle to form a 3D object in layers. The extruder temperature is therefore a key parameter for a successful print job but also one of the main emission driving factors as harmful pollutants (e.g., ultrafine particles) are formed by thermal polymer degradation. The awareness of potential health risks has increased the number of emission studies in the past years. However, studies usually refer their calculated emission data to the printer set extruder temperature for comparison purposes. In this study, we used a thermocouple and an infrared camera to measure the actual extruder temperature and found significant temperature deviations to the displayed set temperature among printer models. Our result shows that printing the same filament feedstocks with three different printer models and with identical printer set temperature resulted in a variation in particle emission of around two orders of magnitude. A temperature adjustment has reduced the variation to approx. one order of magnitude. Thus, it is necessary to refer the measured emission data to the actual extruder temperature as it poses a more accurate comparison parameter for evaluation of the indoor air quality in user scenarios or for health risk assessments.
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 our current research project „Reincarnate“ we aim to anchor the idea of the circular economy in the European construction industry and significantly extend the life cycle of buildings, construction products and materials through innovative solutions. On the long term, this is an approach reduce construction waste by 80 percent and the CO2 footprint of the construction sector by 70 percent."
This project has received funding from the European Union’s Horizon Europe research and innovation programme and will take you on a tour on what are the drivers, what is the goal, who are the partners and how we want to make the world a better place!
Vorstellung der Themen der Nachwuchsgruppe "Materialcharakterisierung und -informatik für die Nachhaltigkeit im Bauwesen" von Prof. Sabine Kruschwitz (TU Berlin und BAM)
Simulating a Gas Source Localization Algorithm with Gas Dispersion Produced by Recorded Outdoor Wind
(2022)
This presentation reports the use of the first gas dispersion simulator capable of generating large wind fluctuation, to test a modification to a gas source localization algorithm and study how the change affects it. Gas source localization at an outdoor environment is a challenging task mainly due to the complexity of the spreading gas 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 will be shared. To consider the characteristic of sudden but large and unpredictable changes in wind direction, recorded outdoor wind was used to simulate a realistic outdoor gas dispersion which has been done for the first time. With the use of this simulator, a modification to a mobile robot-based gas source localization algorithm was evaluated. Multiple simulations of the modified and the original algorithm were 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 consider 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.
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.
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.
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 cost-efficient 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 presentation, we detail the technical aspects of RASEM and introduce the mobile platforms used.
Flexible, niedrigdichte Schäume aus Biokunststoffen im Extrusionsverfahren herzustellen war bisher industriell noch nicht möglich. Im Verarbeitungstechnikum Biopolymere des Fraunhofer IAP wurde in einem Projekt die Eignung von PBS-basierten Biokunststofftypen für Schaumanwendungen erforscht und weiterentwickelt.
Closed material cycles and unmixed material fractions are required to achieve high recovery and recycling rates in the building industry. The growing diversity of construction and demolition waste is leading to increasing difficulties in separating the individual materials. Manual sorting involves many risks and dangers for the executing staff and is merely based on obvious, visually detectable differences for separation. An automated, sensor-based sorting of these building materials could complement or replace this practice to improve processing speed, recycling rates, sorting quality, and prevailing health conditions.
A joint project of partners from industry and research institutions approaches this task by investigating and testing the combination of laser-induced breakdown spectroscopy (LIBS) and visual (VIS)/ near-infrared (NIR) spectroscopy. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3-containing building materials (gypsum, aerated concrete, etc.). Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic/technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.
First LIBS measurements show promising results in distinguishing various material types. A meaningful validation shall be achieved with further practical samples. Future works will investigate the combination of LIBS and VIS/NIR spectroscopy in a fully automated measurement setup with conveyor belt speeds of 3 m/s.
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.
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.
This paper presents first advances in the area of aerial chemical trail following. For that purpose, we equipped a palm-size aerial robot, based on the Crazyflie 2.0 quadrocopter, with a small lightweight metal oxide gas sensor for measuring evaporated ethanol from chemical trails. To detect and localize a 5 cm wide chemical trail, a detection criterion was developed that uses only relative changes in the transient phase of the sensor response. The reduction in signal strength dependence improves the robustness of its application. We tested our setup in first crossing-trail experiments showing that our flying ant robot can correlate an odor hit with the chemical trail within 0.14 m. Principally, this could enable aerial chemical trail following in the future.
This poster presents first advances in the area of aerial chemical trail following. For that purpose, we equipped a palm-size aerial robot, based on the Crazyflie 2.0 quadrocopter, with a small lightweight metal oxide gas sensor for measuring evaporated ethanol from chemical trails. To detect and localize the chemical trail, a novel detection criterion was developed that uses only relative changes in the transient phase of the sensor response, making it more robust in its application. We tested our setup in first crossing-trail experiments showing that our flying ant robot is able to correlate an odor hit with the chemical trail within 0.14 m. Principally, this could enable aerial chemical trail following in the future.
This paper presents first advances in the area of aerial chemical trail following. For that purpose, we equipped a palm-size aerial robot, based on the Crazyflie 2.0 quadrocopter, with a small lightweight metal oxide gas sensor for measuring evaporated ethanol from chemical trails. To detect and localize the chemical trail, a novel detection criterion was developed that uses only relative changes in the transient phase of the sensor response, making it more robust in its application. We tested our setup in first crossing-trail experiments showing that our flying ant robot is able to correlate an odor hit with the chemical trail within 0.14 m. Principally, this could enable aerial chemical trail following in the future.
This paper presents first advances in the area of aerial chemical trail following. For that purpose, we equipped a palm-size aerial robot, based on the Crazyflie 2.0 quadrocopter, with a small lightweight metal oxide gas sensor for measuring evaporated ethanol from chemical trails. To detect and localize the chemical trail, a novel detection criterion was developed that uses only relative changes in the transient phase of the sensor response, making it more robust in its application. We tested our setup in first crossing-trail experiments showing that our flying ant robot is able to correlate an odor hit with the chemical trail within 0.14 m. Principally, this could enable aerial chemical trail following in the future.
This poster presentation presents first advances in the area of aerial chemical trail following. For that purpose, we equipped a palm-size aerial robot, based on the Crazyflie 2.0 quadrocopter, with a small lightweight metal oxide gas sensor for measuring evaporated ethanol from chemical trails. To detect and localize the chemical trail, a novel detection criterion was developed that uses only relative changes in the transient phase of the sensor response, making it more robust in its application. We tested our setup in first crossing-trail experiments showing that our flying ant robot is able to correlate an odor hit with the chemical trail within 0.14 m. Principally, this could enable aerial chemical trail following in the future.
This 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.
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.
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.
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.
In this study, nanoscopic particles of magnesium Fluoride (MgF2) and calcium fluoride (CaF2) also known as nano metal fluorides (NMFs), were evaluated for their potential to improve wood durability. Even though these fluorides are sparingly soluble, their synthesis in the form of nano-sized particles turns them into promising candidates for wood preservation. Their distinct property of low-water solubility is proposed to maintain long-lasting protection of treated wood by reducing the leaching of fluoride. Analytical methods were used to characterize the synthesized NMFs and their distribution in treated wood specimens. Transmission electron microscopy images showed that these fluoride particles are smaller than 10 nm. In nano metal fluoride (NMF) treated specimens, aggregates of these particles are uniformly distributed in the wood matrix as confirmed with scanning electron microscopy images and their corresponding energy-dispersive X-ray spectroscopy maps. The fluoride aggregates form a protective layer around the tracheid walls and block the bordered pits, thus reducing the possible flow path for water absorption into wood. This is reflected in the reduced swelling and increased hydrophobicity of wood treated with NMFs. The biocidal efficacy of NMFs was tested against brown-rot fungi (Coniophora puteanaand Rhodonia placenta), white-rot fungus (Trametes versicolor), and termites (Coptotermes formosanus). The fungal and termite tests were performed in accordance with the EN 113 (1996) and EN 117 (2012) standards, respectively. Prior to fungal tests, the NMF treated wood specimens were leached according to the EN 84 (1997)standard. Compared to untreated specimens, the NMF treated wood specimens have a higher resistance to decay caused by brown-rot fungi, white-rot fungus, and termites. Although all NMF treatments in wood reduce the mass loss caused by fungal decay, only the combined treatment of MgF2 and CaF2 has efficacy against both brown-rot fungi and white-rot fungus. Similarly, wood treated with the combined NMF formulation is the least susceptible to attack by C. formosanus.It is proposed that combining MgF2 and CaF2changes their overall solubility to promote the release of fluoride ions at the optimal concentration needed for biocidal efficacy against fungi and termites. In this thesis, it was proven that even after leaching, sufficient fluoride was present to protect NMF treated wood from fungal decay. This shows that NMFs are robust enough for above ground contact outdoor applications of wood, where permanent wetness cannot be avoided according to Use Class 3.2, as per the EN 335 (2013) standard. Also, they pose a low risk to human health and the environment because they are sparingly soluble. Since NMFs significantly reduce the decay of wood, the CO2 fixed in it will be retained for longer than in unpreserved wood. Overall, the novel results of this study show the potential of NMFs to increase the service life of building materials made from non-durable wood.
Frass (fine powdery refuse or fragile perforated wood produced by the activity of boring insects) of larvae of the European house borer (EHB) and of drywood termites was tested as a natural and novel feedstock for 3D-printing of wood-based materials. Small particles produced by the drywood termite Incisitermes marginipennis and the EHB Hylotrupes bajulus during feeding in construction timber, were used. Frass is a powdery material of particularly consistent quality that is essentially biologically processed wood mixed with debris of wood and faeces. The filigree-like particles flow easily permitting the build-up of woodbased structures in a layer wise fashion using the Binder Jetting printing process. The Quality of powders produced by different insect species was compared along with the processing steps and properties of the printed parts. Drywood termite frass with a Hausner Ratio HR = 1.1 with ρBulk = 0.67 g/cm3 and ρTap = 0.74 g/cm3 was perfectly suited to deposition of uniformly packed layers in 3D printing. We suggest that a variety of naturally available feedstocks could be used in environmentally responsible approaches to scientific material sciences/additive manufacturing.
Fluorides are well-known as wood preservatives. One of the limitations of fluoride-based wood preservatives is their high leachability. Alternative to current fluoride salts such as NaF used in wood protection are low water-soluble fluorides. However, impregnation of low water-soluble fluorides into wood poses a challenge. To address this challenge, low water-soluble fluorides like calcium fluoride (CaF2) and magnesium fluoride (MgF2) were synthesized as nanoparticles via the fluorolytic sol−gel synthesis and then impregnated into wood specimens. In this study, the toxicity of nano metal fluorides was assessed by termite mortality, mass loss and visual analysis of treated specimens after eight weeks of exposure to termites, Coptotermes formosanus. Nano metal fluorides with sol concentrations of 0.5 M and higher were found to be effective against termites resulting in 100% termite mortality and significantly inhibited termite feeding. Among the formulations tested, the least damage was found for specimens treated with combinations of CaF2 and MgF2 with an average mass loss less than 1% and visual rating of “1”. These results demonstrate the efficacy of low water-soluble nano metal fluorides to protect wood from termite attack.
Precise knowledge about the distribution of air pollutants is necessary to develop plausible occupational health measures. Combinatory systems, consisting of mobile robots and stationary sensors, can be effective solutions for the coverage of large measurement areas. However, further research is needed to fully understand their performance in comparison to traditional sensing strategies. Therefore, multiple sensor networks layouts will be set up in a simulation environment as well as in real industrial environments. Models for distribution mapping will be developed and evaluated to investigate the performance and opportunities of hybrid-mobility sensor networks for the task of distribution mapping.
Air pollution in industrial environments is a major risk. Precise knowledge about the distribution of air pollutants is necessary to develop plausible occupational health measures. Combinatory systems, consisting of mobile robots and stationary sensors, can be effective solutions for the coverage of large measurement areas.
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.
One challenge associated with navigating a nano aerial robot swarm indoors in unstructured environments is, i.a., the limited air space. To avoid an over-regulation of the available indoor air space (e.g., prohibit copters to fly above each other), a safety region around each copter must be defined. In this paper, we investigate the impact of the downwash of a nano-drone on the stability of another nearby nano-drone. In the experiments, we found out that this downwash has a negative influence of a second nano-drone in a distance of around 1 m vertically and 0.2 m horizontally. Based on the obtained data, we developed a model describing the above-mentioned safety region to enable a safe operation of the swarm in these environments with fewer constraints.
Der Vortrag gibt Beispiele dafür, wie Drohnen sinnvoll im zivilen Bereich eingesetzt werden können. Insbesondere werden die Lokalisierung von Gasemissionsquellen und die Erstellung von Gasverteilungskarten vorgestellt.
The Motivation of RASEM (Robot-assisted Environmental Monitoring):
Monitoring of the air quality in industrial environments is inevitable to meet safety Standards.
Because of economic and practical reasons, measurements are carried out sparsely in terms of time and space.
Newest developments on the field of low cost sensor technology enable cost efficient long term monitoring of gases and dust
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.
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.
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.
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. Here we present a concept of how an existing simulator can be extended to handle both indoor and large outdoor scenarios.
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 poster 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.
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.
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).
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.
19th and 20th centuries glass paint layers consist of a colour body and a colourless lead silicate flux, in which borax or boric acid was added as further component to improve the paint ability and to reduce the firing temperature for multiple layers of paint. Model glasses were used in laboratory tests to investigate the stability of glass paints with additions of boron oxide. To determine boron in paint layers, a LIBS-system with pulsed NdYAG-laser was used.
In this paper, we introduce a nano aerial robot swarm for Indoor Air Quality (IAQ) monitoring applications such as occupational health and safety of (industrial) workplaces. The robotic swarm is composed of nano Unmanned Aerial Vehicles (UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight Metal Oxide (MOX) gas sensors for measuring the Total Volatile Organic Compound (TVOC), which is a measure for IAQ. An indoor localization and positioning system is used to estimate the absolute 3D position of the swarm similar to GPS. A test scenario was built up to validate and optimize the swarm for the intended applications. Besides calibration of the IAQ sensors, we performed experiments to investigate the influence of the rotor downwash on the gas measurements at different altitudes and compared them with stationary measurements. Moreover, we did a first evaluation of the gas distribution mapping performance. Based on this novel IAQ monitoring concept, new algorithms in the field of Mobile Robot Olfaction (MRO) are planned to be developed exploiting the abilities of an aerial robotic swarm.
In this paper, we introduce a nano aerial robot swarm for Indoor Air Quality (IAQ) monitoring applications such as occupational health and safety of (industrial) workplaces. The robotic swarm is composed of nano Unmanned Aerial Vehicles (UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight Metal Oxide (MOX) gas sensors for measuring the Total Volatile Organic Compound (TVOC), which is a measure for IAQ. An indoor localization and positioning system is used to estimate the absolute 3D position of the swarm similar to GPS. A test scenario was built up to validate and optimize the swarm for the intended applications. Besides calibration of the IAQ sensors, we performed experiments to investigate the influence of the rotor downwash on the gas measurements at different altitudes and compared them with stationary measurements. Moreover, we did a first evaluation of the gas distribution mapping performance. Based on this novel IAQ monitoring concept, new algorithms in the field of Mobile Robot Olfaction (MRO) are planned to be developed exploiting the abilities of an aerial robotic swarm.
In mobile robot applications, some sensors such as open-path gas detectors or laser rangefinders need to be aimed at specific targets in order to get the desired measurements. To do this in a fast and elegant manner, we present a spherical parallel manipulator with three degrees of freedom. Compared to typical serial manipulators, it offers superior dynamics and structural stiffness, which are important parameters for this type of task. We present the mechanical design and derive kinematic equations both to compute set-points for the desired orientation and to estimate the current state of the system. A PID controller is used to generate control signals.
The impact of fracture geometry and aperture distribution on fluid movement and on non-reactive solute transport was investigated experimentally and numerically in single fractures. For this purpose a hydrothermally altered and an unaltered granite drill core with axial fractures were investigated. Using three injection and three extraction locations at top and bottom of the fractured cores, different dipole flow fields were examined. The conservative tracer (Amino-G) breakthrough curves were measured using fluorescence spectroscopy. Based on 3-D digital data obtained by micro-computed tomography 2.5-D numerical models were generated for both fractures by mapping the measured aperture distributions to the 2-D fracture geometries (x-y plane). Fluid flow and tracer transport were simulated using COMSOL Multiphysics®.
By means of numerical simulations and tomographic imaging experimentally observed breakthrough curves can be understood and qualitatively reproduced. The experiments and simulations suggest that fluid flow in the altered fracture is governed by the 2-D fracture geometry in the x-y plane, while fluid flow in the unaltered fracture seems to be controlled by the aperture distribution. Moreover, we demonstrate that in our case simplified parallel-plate models fail to describe the experimental findings and that pronounced tailings can be attributed to complex internal heterogeneities. The results presented, implicate the necessity to incorporate complex domain geometries governing fluid flow and mass transport into transport modeling.
In this paper, we present an autonomous aerial robot to reconstruct tomographic 2D slices of gas plumes in outdoor environments. Our platform, the so-called Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS) combines a lightweight Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile octocopter. The TDLAS sensor provides integral gas concentration measurements but no information regarding the distance traveled by the laser diode's beam or the distribution of the gas along the optical path. We complemented the set-up with a laser rangefinder and apply principles of Computed Tomography (CT) to create a model of the spatial gas distribution from these integral concentration measurements. To allow for a rudimentary ground truth evaluation of the applied gas tomography algorithm, we set up a unique outdoor test environment based on two 3D ultrasonic anemometers and a distributed array of 10 infrared gas transmitters. We present first results showing the 2D plume reconstruction capabilities of the system under realistic conditions.
In 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.
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.
This work presents the testing of a developed electronic 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.
For several applications involving multirotor aircraft, it is crucial to know both the direction and speed of the ambient wind. In this paper, an approach to wind vector estimation based on an equilibrium of the principal forces acting on the aircraft is shown. As the thrust force generated by the rotors depends on their rotational speed, a sensor to measure this quantity is required. Two concepts for such a sensor are presented: One is based on tapping the signal carrying the speed setpoint for the motor controllers, the other one uses phototransistors placed underneath the rotor blades. While some complications were encountered with the first approach, the second yields accurate measurement data. This is shown by an experiment comparing the proposed speed sensor to a commercial non-contact tachometer.
Wyciek metanu (CH4) z infrastruktury takiej jak rurociągi czy zbiorniki magazynowe ma kluczowe znaczenie dla środowiska oraz stwarza zagrożenie dla bezpieczeństwa ludzi i mienia. Obecnie, po okresie bezawaryjnej eksploatacji, można zaobserwować wzrost liczby incydentów spowodowanych nieszczelnościami rurociągów przesyłowych.
W Polsce szczególnie problematyczne okazują się gazociągi, które powstały dekady temu. W tamtym czasie normy techniczne i przepisy budowlane były łagodniejsze niż obecnie obowiązujące. Integralność tych gazociągów jest trudna do skontrolowania, gdyż na etapie budowy nie zostały one przystosowane do badania tłokami pomiarowymi. Aby sprostać temu wyzwaniu, UDT poszukuje metod umożliwiających szybkie i niezawodne wykrywanie oraz lokalizowanie nieszczelności gazociągów na duże odległości.
Leaking methane (CH4) from infrastructures, like pipelines, industrial complexes and landfills, or accidental hazardous goods transports is critical for the environment, but can also pose a risk to human life. To enable a fast detection and localisation of these kind of leaks, we developed a novel robotic platform for aerial remote gas sensing. The platform combines an unmanned micro aircraft (UAV), a 3-axis aerial stabilisation gimbal and an open-path gas detector based on the tunable diode laser absorption spectroscopy (TDLAS).
An unmanned micro aircraft (UAV) is equipped with an open-path gas detector to localise gas sources and to generate gas distribution maps. The gas detector is based on the tunable diode laser absorption spectroscopy (TDLAS) and attached to a 3-axis aerial stabilisation gimbal. Sensor validation experiments and first gas tomography reconstructions are shown.
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.)
This paper describes a wireless mobile prototype able to perform optical measurements by means of a miniaturized 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 implemented 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.
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.
Leaking methane (CH4) from infrastructures, such as pipelines and landfills, is critical for the environment but can also pose a safety risk. To enable a fast detection and localization of These kind of leaks, we developed a novel robotic platform for aerial remote gas sensing - the so-called Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS).
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 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 industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.
Leaking methane from infrastructures, such as pipelines and landfills, is critical for the environment but can also pose a safety risk. To enable a fast detection and localization of these kind of leaks, BAM developed a novel robotic platform for aerial remote gas sensing. Spectroscopic measurement methods for remote sensing of selected gases lend themselves for use on mini-copters, which offer a number of advantages for inspection and surveillance over traditional methods. No direct contact with the target gas is needed and thus the influence of the copter downwash on the measured gas plume can be kept to a minimum. This allows to overcome one of the major issues with gas-sensitive mini-copters. On the other hand, remote gas sensors, most prominently Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensors have been too bulky given the payload and energy restrictions of mini-copters. Here, we present the Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), which combines a novel lightweight TDLAS sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile multicopter. The proposed system can be deployed in scenarios that cannot be addressed by currently available systems and thus constitutes a significant step forward for the field of Mobile Robot Olfaction (MRO). It enables tomographic reconstruction of gas plumes and a localization of gas sources. We also present first results showing its performance under realistic conditions.
Fluorometric sensing is a versatile approach for trace analysis outside of the laboratory, requiring suitable sensor materials and their integration into sensing devices. The versatility of fluorophores as probes, especially in terms of the possibility to tailor their optical as well as their recognition properties by synthetic modifications in a wide range, renders them as superior active component for the preparation of optical sensing devices. Recent works at BAM in this field include, for example, the detection of nerve gas agents, illustrating impressively the aforementioned benefits of fluorophores in optical sensing applications.
In the interdisciplinary project presented here, we target hazardous gases such as ammonia, benzene, and hydrogen sulfide, next to others, which pose a major threat to human health and environmental safety and for which the availability of a sensitive and reliable detection method is highly desirable. The dyes presented follow a “turn-on” fluorescence schematic, which allows for the selective and sensitive detection of the respective gaseous analyte. The immobilization of the probe in polymeric matrices is then the next step toward the fabrication of a prototype device for molecular sensing. Further steps in the project include the assembly of instruments for test-atmosphere generation, the referencing of the sensor system, development and implementation of an optical setup, and the testing of the prototype device under laboratory conditions and in the field.
In this presentation, we give an overview over the recent developments on this topic in our groups. Highlights are hydrogen sulfide sensitive, BODIPY based transition metal complexes, which allow for a sensitive as well as selective detection of the toxic gas. In addition, we present a novel class of highly substituted BODIPY derivatives – pocket-BODIPYs – which are of a synthetically high versatility and can readily be modified to create pockets in the periphery of the molecule of defined geometries. This is illustrated on the successful encapsulation of benzene by a pocket-BODIPY derivative, confirmed by X-ray crystallographic analysis as well as by further spectroscopic and analytical methods.
The presentation gives a brief overview of the main goals, the used methods and the first results of the PMARS OdourSense project. In cooperation with the Moulay Ismaïl University in Meknès (Morocco), a multi-gas sensor system for odour nuisance monitoring in outdoor air and a method for testing/calibration of such devices are being developed in this project.
Wood treated with nano metal fluorides is found to resist fungal decay. Sol−gel synthesis was used to synthesize MgF2 and CaF2 nanoparticles. Electron microscopy images confirmed the localization of MgF2 and CaF2 nanoparticles in wood. Efficacy of nano metal fluoride-treated wood was tested against brown-rot fungi Coniophora puteana and Rhodonia placenta. Untreated wood specimens had higher
mass losses (∼30%) compared to treated specimens, which had average mass loss of 2% against C. puteana and 14% against R. placenta, respectively. Nano metal fluorides provide a viable alternative to current wood preservatives.