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

机译:一种基于无人驾驶动态气体环境中无人车辆的气体源定位混合算法

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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.
机译:本文提出了一种基于无人车辆定位危险气体源的新方法。 基于气体传感器和无人驾驶车辆,进行了对气体源定位算法的研究,使用几个检测部位的气体浓度作为启发式信息。 当可用信息较少时,使得气体扩散模型未知,该算法可以快速定位气体泄漏源。 该算法结合了粒子群优化(PSO)和Nelder-Mead Simplex方法。 与标准PSO相比,该算法的迭代率较少,收敛速度更快。 最后,通过数字仿真实验验证了算法的可行性。

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