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

Yu Huang,Lei Li,Renxing Ji,He Chen

doi:10.1155/2021/8828148

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.

Highlights

In recent years, many hazardous gas leakages have occurred, causing serious economic losses
Under the action of wind with random factors, the puff drifts at a certain direction and speed in the two-dimensional rectangular flat land of 100 m × 200 m, forming a gas diffusion model with variable wind direction and speed. e concentration of the gas source reaches the order of 10−4 kg/m3. e experiment simulates the diffusion process of the puff in 0 to 250 minutes. e unmanned vehicles start searching for the gas leakage source after the source continued to leak for 150 minutes, as shown in Figure 3. e puff continued to diffuse during the vehicles search, ignoring the concentration change caused by the vehicles
The gas leakage source location by unmanned vehicles in a dynamic gas field based on particle swarm optimization (PSO) is studied, and PSO combined with Nelder–Mead simplex method is presented. e hybrid algorithm is more suitable for the problem of gas source location and provides a new way to solve this problem

Summary

Introduction

Many hazardous gas leakages have occurred, causing serious economic losses. The active olfactory method based on mobile robot system and sensor system is a popular research in this field. The gas source location by unmanned vehicles based on PSO is studied, and a gas source location algorithm combining PSO and Nelder–Mead simplex method (NMSM) is presented. Based on the gas concentration sensors and unmanned vehicle system, the algorithm can use limited environmental information to locate the gas source in a dynamic gas field. E paper points out that the standard PSO algorithm is better than gradient-based algorithms (GRD) and biased random walks (BRW). E research of this paper is based on the hybrid algorithm combining PSO and NMSM; the unmanned vehicle system with gas concentration sensor is used to locate the gas leakage source quickly with limited information. Compared with the standard PSO for seeking gas source, using this algorithm has a better stability and less iterations. e study has some enlightening significance for gas leakage source location

Design of Gas Source Location Algorithm

Simulation Experiment and Conclusion

Findings

Conclusion