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Erscheinungsjahr
- 2013 (9) (entfernen)
Dokumenttyp
Schlagworte
- Autonomous micro UAV (2)
- Chemical and wind sensing (2)
- Data-fusion (2)
- Gas source localization (2)
- Gas storage areas (2)
- Hazardous scenarios (2)
- Membrane-based gas sensing (2)
- Mikrodrohne (2)
- Particle filter (2)
- Subsurface monitoring (2)
One of the main unsolved issues of CCS is the comprehensive surveillance of CO2 storage areas with reasonable effort and costs. This study presents an approach for distributed subsurface monitoring of gas storage areas. The concept combines different measurement technologies to one multifunctional sensor: membrane based measurement technology for in situ monitoring of gases in soil and fibre optical sensing of temperature and strain (as a measure for structural change). A test field of application-relevant dimensions is built up to validate and optimize the technology.
Carbon capture & storage (CCS) is one of the most promising technologies for greenhouse gas (GHG) management. However, an unsolved issue of CCS is the development of appropriate long-term monitoring systems for leak detection of the stored CO2. To complement already existing monitoring infrastructure for CO2 storage areas, and to increase the granularity of gas concentration measurements, a quickly deployable, mobile measurement device is needed. In this paper, we present an autonomous gas-sensitive micro-drone, which can be used to monitor GHG emissions, more specifically, CO2. Two different measurement strategies are proposed to address this task. First, the use of predefined sensing trajectories is evaluated for the task of gas distribution mapping using the micro-drone. Alternatively, we present an adaptive strategy, which suggests sampling points based on an artificial potential field (APF). The results of real-world experiments demonstrate the feasibility of using gas-sensitive micro-drones for GHG monitoring missions. Thus, we suggest a multi-layered surveillance system for CO2 storage areas.
In this paper, we show that a micro unmanned aerial vehicle (UAV) equipped with commercially available gas sensors can address environmental monitoring and gas source localization (GSL) tasks. To account for the challenges of gas sensing under real-world conditions, we present a probabilistic approach for GSL that is based on a particle filter (PF). Simulation and real-world experiments demonstrate the suitability of this algorithm for micro UAV platforms.
Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms
(2013)
Gas source localization (GSL) with mobile robots is a challenging task due to the unpredictable nature of gas dispersion, the limitations of the currents sensing technologies, and the mobility constraints of ground-based robots. This work proposes an integral solution for the GSL task, including source declaration. We present a novel pseudo-gradient-based plume tracking algorithm and a particle filter-based source declaration approach, and apply it on a gas-sensitive micro-drone. We compare the performance of the proposed system in simulations and real-world experiments against two commonly used tracking algorithms adapted for aerial exploration missions.
BAM Federal Institute for Materials Research and Testing, in cooperation with the company MeGaSen UG carries out a research project to enhance and validate an innovative approach for distributed subsurface monitoring of gas storage areas. The concept combines different measurement technologies to one multifunctional sensor: membrane-based gas measurement technology for in-situ monitoring of gases in soil and fiber optical sensing of temperature and strain (as a measure for structural change). Key aspect of the research project is the first-time validation of the system in an application relevant dimension. For this purpose a 20 x 20 m2 test field is build. A comprehensive validation of the system is carried out by systematic variation of different parameters like position-dependent gasinjection, temperature and mechanical impact.