摘要：Hazardous gas leaks in the atmosphere can cause significant economic losses in addition to environmental hazards, such as fires and explosions. A three-stage hazardous gas leak source localization method was developed that uses movable and stationary gas concentration sensors. The method calculates a preliminary source inversion with a modified genetic algorithm (MGA) and has the potential to crossover with eliminated individuals from the population, following the selection of the best candidate. The method then determines a search zone using Markov Chain Monte Carlo (MCMC) sampling, utilizing a partial evaluation strategy. The leak source is then accurately localized using a modified guaranteed convergence particle swarm optimization algorithm with several bad-performing individuals, following selection of the most successful individual with dynamic updates. The first two stages are based on data collected by motionless sensors, and the last stage is based on data from movable robots with sensors. The measurement error adaptability and the effect of the leak source location were analyzed. The test results showed that this three-stage localization process can localize a leak source within 1.0 m of the source for different leak source locations, with measurement error standard deviation smaller than 2.0. (C) 2017 Elsevier Ltd. All rights reserved.

关键字：Source inversion Hazardous gas leak Genetic algorithm Markov Chain Monte Carlo Particle swarm optimization

ISSN号：1352-2310

卷、期、页：卷: 157 页: 27-37

发表日期：2017-05-01

影响因子：3.629000

期刊分区（SCI为中科院分区）：二区

收录情况：SCIE（科学引文索引网络版）

发表期刊名称：ATMOSPHERIC ENVIRONMENT

参与作者：张儒,Yan, Yuting,Dong, Xiaoqiang,Li, Jun Ming

第一作者：王吉

论文类型：期刊论文

论文概要：王吉,张儒,Yan, Yuting,Dong, Xiaoqiang,Li, Jun Ming，Locating hazardous gas leaks in the atmosphere via modified genetic, MCMC and particle swarm optimization algorithms，ATMOSPHERIC ENVIRONMENT，2017，卷: 157 页: 27-37

论文题目：Locating hazardous gas leaks in the atmosphere via modified genetic, MCMC and particle swarm optimization algorithms