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

Author:

Huang Yu1ORCID,Li Lei2ORCID,Ji Renxing1ORCID

Affiliation:

1. China Fire and Rescue Institute, Beijing 102201, China

2. School of Automation, Beijing Information Science and Technology University, Beijing 100192, China

Abstract

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.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference12 articles.

1. Distributed odor source localization

2. Survey of application of swarm intelligence algorithm in gas source location;W. Wang;Computer Engineering and Applications,2019

3. Particle swarm-based olfactory guided search

4. A new optimizer using particle swarm theory;R. Eberhart

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