A Hybrid Algorithm for Gas Source Locating Based on Unmanned Vehicles in Dynamic Gas Environment

A Hybrid Algorithm for Gas Source Locating Based on Unmanned Vehicles in Dynamic Gas Environment

A new method for locating hazardous gas source based on unmanned vehicles is presented in this paper. Based on the gas sensors and unmanned vehicles, the research on the gas source location algorithm, using the gas concentration of several detection sites as heuristic information, is carried out. Wh...

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Main Authors: Yu Huang, Lei Li, Renxing Ji
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2021/8828148
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spelling doaj-f9e72d6b4fc74f84ad6316e7e609f6be2021-04-19T00:05:09ZengHindawi LimitedMathematical Problems in Engineering1563-51472021-01-01202110.1155/2021/8828148A Hybrid Algorithm for Gas Source Locating Based on Unmanned Vehicles in Dynamic Gas EnvironmentYu Huang0Lei Li1Renxing Ji2China Fire and Rescue InstituteSchool of AutomationChina Fire and Rescue InstituteA new method for locating hazardous gas source based on unmanned vehicles is presented in this paper. Based on the gas sensors and unmanned vehicles, the research on the gas source location algorithm, using the gas concentration of several detection sites as heuristic information, is carried out. When the available information is less, such that the gas diffusion model is unknown, the algorithm can locate the gas leakage source quickly. The proposed algorithm combines particle swarm optimization (PSO) and Nelder–Mead simplex method. Compared with the standard PSO, the proposed algorithm has fewer iterations and faster convergence speed. Finally, the feasibility of the algorithm is verified by digital simulation experiments.http://dx.doi.org/10.1155/2021/8828148
collection DOAJ
language English
format Article
sources DOAJ
author Yu Huang
Lei Li
Renxing Ji
spellingShingle Yu Huang
Lei Li
Renxing Ji
A Hybrid Algorithm for Gas Source Locating Based on Unmanned Vehicles in Dynamic Gas Environment
Mathematical Problems in Engineering
author_facet Yu Huang
Lei Li
Renxing Ji
author_sort Yu Huang
title A Hybrid Algorithm for Gas Source Locating Based on Unmanned Vehicles in Dynamic Gas Environment
title_short A Hybrid Algorithm for Gas Source Locating Based on Unmanned Vehicles in Dynamic Gas Environment
title_full A Hybrid Algorithm for Gas Source Locating Based on Unmanned Vehicles in Dynamic Gas Environment
title_fullStr A Hybrid Algorithm for Gas Source Locating Based on Unmanned Vehicles in Dynamic Gas Environment
title_full_unstemmed A Hybrid Algorithm for Gas Source Locating Based on Unmanned Vehicles in Dynamic Gas Environment
title_sort hybrid algorithm for gas source locating based on unmanned vehicles in dynamic gas environment
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1563-5147
publishDate 2021-01-01
description A new method for locating hazardous gas source based on unmanned vehicles is presented in this paper. Based on the gas sensors and unmanned vehicles, the research on the gas source location algorithm, using the gas concentration of several detection sites as heuristic information, is carried out. When the available information is less, such that the gas diffusion model is unknown, the algorithm can locate the gas leakage source quickly. The proposed algorithm combines particle swarm optimization (PSO) and Nelder–Mead simplex method. Compared with the standard PSO, the proposed algorithm has fewer iterations and faster convergence speed. Finally, the feasibility of the algorithm is verified by digital simulation experiments.
url http://dx.doi.org/10.1155/2021/8828148
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AT renxingji ahybridalgorithmforgassourcelocatingbasedonunmannedvehiclesindynamicgasenvironment
AT yuhuang hybridalgorithmforgassourcelocatingbasedonunmannedvehiclesindynamicgasenvironment
AT leili hybridalgorithmforgassourcelocatingbasedonunmannedvehiclesindynamicgasenvironment
AT renxingji hybridalgorithmforgassourcelocatingbasedonunmannedvehiclesindynamicgasenvironment
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