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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.
Multichannel measuring systems are used to measure strains and accelerations during drop tests of containments for dangerous goods. Conventional systems require cabling of each sensor and co-falling of the cable harness, causing problems in the test preparation and execution. Promising results of a single cable measuring system, consisting of measuring modules with data bus connection and local data acquisition were presented in a previous study. This paper follows up with results from laboratory and full-scale testing of an further enhanced single cable system for the application in drop tests.----------------------------------------------------------------------------------------------------------------------------------------------------------------
Vielkanalmesssysteme werden zur Messung von Dehnungen und Beschleunigungen bei Fallversuchen von Gefahrstoffbehältern eingesetzt. Konventionelle Systeme erfordern die Verkabelung jeder einzelnen Messstelle und somit das Mitfallen eines Kabelbaums, wodurch Probleme bei der Versuchsvorbereitung und Durchführung entstehen. In einer vorangegangenen Studie wurden vielversprechende Ergebnisse durch Verwendung eines 1-Kabelmesssystems mit Datenbus und dezentraler Datenspeicherung erzielt. Dieser Artikel beinhaltet weiterführende Ergebnisse aus Labor- und Realversuchen mit einem weiterentwickelten System zur Anwendung bei Fallversuchen.
This article presents the development and validation of an autonomous, gas sensitive microdrone that is capable of estimating the wind vector in real time using only the onboard control unit of the microdrone and performing gas distribution mapping (DM). Two different sampling approaches are suggested to address this problem. On the one hand, a predefined trajectory is used to explore the target area with the microdrone in a real-world gas DM experiment. As an alternative sampling approach, we introduce an adaptive strategy that suggests next sampling points based on an artificial potential field (APF). Initial results in real-world experiments demonstrate the capability of the proposed adaptive sampling strategy for gas DM and its use for gas source localization.
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.
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.
Poor air quality, particularly in urban areas, causes various diseases and degrades living standards. Air Quality could be affected by emissions of odor, Volatile Organic Compounds (VOCs), and other gases. Therefore, assessment and monitoring of odorous air quality using sensitive, simple, rapid, accurate and portable tools is very important for public health. This study aimed to characterize odor emissions to detect malfunctions in facilities and to prevent air pollution and olfactory nuisance in the environment. A gas chromatographic method, in conjunction with sensorial analysis were performed for odorous air samples analysis collected from neighborhood of Meknes city (Morocco). Advanced multivariate statistical approaches, such as Principal Components Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to describe samples similarities. The electronic nose (e-nose) data processing exhibits a satisfactory discrimination between the odorous air samples. Twenty-four VOCs with known molecular formulas were identified with Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS). A validated Partial Least Square (PLS) model foresees good calibration between e-nose measurement and TD-GCMS analysis. The finding indicates that TD-GC–MS approach in conjunction with e-nose unit could be suitable tool for environmental measurement-based odor emissions.
Wastewater contains harmful chemicals and heavy metals that are known to cause various environmental and health problems. Therefore, the water quality control using sensitive, simple, fast, accurate, and portable tools is of great importance. This study aimed to evaluate the pollution parameters of wastewaters collected at different treatment stages from a wastewater treatment plant (WWTP) that treats domestic and industrial wastewaters by using an electronic nose (E-nose) and a voltammetric electronic tongue (E-tongue) combined with chemometric techniques. Water and wastewater pollution parameters determination were performed using inductively coupled plasma optical emission spectrometry for the determination of cations, and anions by using ion chromatography. Chemometric techniques, such as Principal Component Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to process the E-nose and E-tongue datasets to describe the similarities between the samples. In addition, Partial Least Squares Regression (PLSR) model was constructed using electronic sensing data to simultaneously predict the concentration values of physicochemical parameters. The obtained correlation coefficient, for training and testing sets, is higher than 0.91 for the prediction of the concentration of all physicochemical parameters, except for iron (Fe) which remains 0.84. These results suggest that simple, portable, and inexpensive tools such as electronic nose and tongue are suitable for wastewater analysis.
Fiber optic sensors have gained increasing importance in recent years and are well established in many areas of industrial applications. In this paper, we introduce a concept of a self-diagnostic fiber optic sensor. The presented sensor is to resolve the problems of embedded fiber optic sensors in complex structures and to enable the validation under operational conditions. For this purpose, different magnetostrictive coated fiber optic sensors were developed and various experiments were performed to verify their mode of Operation and to determine the respective reproducibility. The measuring principle is illustrated by obtained experimental results, which showed a change in wavelength from 1 pm at a magnetic field strength change of 0.25 mT.
In addition, the temperature characteristics of the implemented magnetostrictive sensor were analyzed and an experimental factor of 1.5 compared to a reference fiber optic sensor was determined.
A monitoring method is introduced that creates twodimensional (2D) maps of the soil gas distribution. The method combines linear gas sensing technology for in-situ monitoring of gases in soil with the mapping capabilities of Computed Tomography (CT) to reconstruct spatial and temporal resolved gas distribution maps. A weighted iterative algebraic reconstruction method based on Maximum Likelihood with Expectation Maximization (MLEM) in combination with a source-by-source reconstruction approach is introduced that works with a sparse setup of orthogonally-aligned linear gas sensors. The reconstruction method successfully reduces artifact production, especially when multiple gas sources are present, allowing the discrimination between true and non-existing so-called ghost source locations. Experimental validation by controlled field experiments indicates the high potential of the proposed method for rapid gas leak localization and quantification with respect to Pipeline or underground gas storage issues.