Ingenieurwissenschaften und zugeordnete Tätigkeiten
Filtern
Dokumenttyp
- Vortrag (2)
- Beitrag zu einem Tagungsband (1)
- Posterpräsentation (1)
Referierte Publikation
- nein (4)
Schlagworte
- Gas Tomography (2)
- Mobile Robotic Olfaction (2)
- Plume (2)
- TDLAS (2)
- Aerial Robot (1)
- Gas Camera (1)
- Gastomographie (1)
- Indoor Localization (1)
- Mobile Robot (1)
- Mobile Sensorik (1)
Organisationseinheit der BAM
- 8 Zerstörungsfreie Prüfung (4) (entfernen)
Ziel des FuE-Vorhabens ist die Entwicklung, Aufbau und Validierung eines gasto-mographischen Messsystems basierend auf stationärer und mobiler Sensorik zum Emissionsmonitoring in kommunalen Kläranlagen. Die Gastomographie basiert hierbei im Wesentlichen auf, aus unterschiedlichen Sichtwinkeln aufgenommenen, integralen Konzentrationsmessungen, anhand derer eine Rekonstruktion der Gasverteilung erfolgt. Das FuE-Projekt kombiniert hierfür stationäre Sensornetzwerke mit luftgestützten und bodengebundenen Robotersystemen in einem System. Letztere werden mit Reflektoren und/oder Gasdetektoren ausgestattet. Hierfür werden Open-Path-Gasmesstechnik basierend auf Tunable Diode Laser Ab-sorption Spectroscopy (TDLAS, primär CH4 in ppm·m) und In-situ-Gassensorik (CH4, ppm) auf Basis von z.B. Infrarot eingesetzt. Dies sind zwei komplementäre Methoden der Gasmessung: Die In-situ-Gassensorik ermöglicht Punktmessungen, wohingegen TDLAS-Sensoren Gaskonzentrationen integral über offene Messstre-cken von bis zu 60 m gegen Oberflächen messen. Die In-situ-Gassensorik wird für Referenzmessungen und ggf. zur Erhöhung der Rekonstruktionsqualität zum Ein-satz kommen. Die wesentlichen Neuheiten des Projekts sind:
• 2D-Gastomographie auf Basis eines mit TDLAS-basierter Open-Path-Gasmesstechnik und Reflektoren ausgestatteten heterogenen Messsystems.
• CT-basierte Rekonstruktionsalgorithmen, adaptiert an die komplexen Rahmenbedingungen.
• Validierung des Messsystems anhand realer Messungen auf Kläranlagen.
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.
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.
Monitoring and maintenance of civil infrastructure are of great importance, as any undetected damage can cause high repair costs, unintended deadtime, or endanger structural integrity. The inspection of large concrete structures such as bridges and parking lots is particularly challenging and time-consuming. Traditional methods are mostly manual and involve mapping a grid of measurement lines to record the position of each measurement. Current semi-automated methods, on the other hand, use GPS or tachymeters for localization but still require trained personnel to operate. An entirely automated approach using mobile robots would be more cost- and time-efficient. While there have been developments in using GPS-enabled mobile robots for bridge inspection, the weak signal strength in indoor areas poses a challenge for the automated inspection of structures such as parking lots. This paper aims to develop a solution for the automated inspection of large indoor concrete structures by addressing the problem of robot localization in indoor spaces and the automated measurement of concrete cover and rebar detection.