{"title":"Research on a nonlinear hybrid optimal PSO microseismic positioning method","authors":"Yang Xiao, Wei-jian Liu, Hao-nan Wang, Meng-jie Hou, Sen-sen Dong, Zhi-zeng Zhang","doi":"10.1007/s11770-024-1064-0","DOIUrl":null,"url":null,"abstract":"<p>Impact ground pressure events occur frequently in coal mining processes, significantly affecting the personal safety of construction workers. Real-time microseismic monitoring of coal rock body rupture information can provide early warnings, and the seismic source location method is an essential indicator for evaluating a microseismic monitoring system. This paper proposes a nonlinear hybrid optimal particle swarm optimisation (PSO) microseismic positioning method based on this technique. The method first improves the PSO algorithm by using the global search performance of this method to quickly find a feasible solution and provide a better initial solution for the subsequent solution of the nonlinear optimal microseismic positioning method. This approach effectively prevents the problem of the microseismic positioning method falling into a local optimum because of an over-reliance on the initial value. In addition, the nonlinear optimal microseismic positioning method further narrows the localisation error based on the PSO algorithm. A simulation test demonstrates that the new method has a good positioning effect, and engineering application examples also show that the proposed method has high accuracy and strong positioning stability. The new method is better than the separate positioning method, both overall and in three directions, making it more suitable for solving the microseismic positioning problem.</p>","PeriodicalId":55500,"journal":{"name":"Applied Geophysics","volume":"15 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geophysics","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s11770-024-1064-0","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Impact ground pressure events occur frequently in coal mining processes, significantly affecting the personal safety of construction workers. Real-time microseismic monitoring of coal rock body rupture information can provide early warnings, and the seismic source location method is an essential indicator for evaluating a microseismic monitoring system. This paper proposes a nonlinear hybrid optimal particle swarm optimisation (PSO) microseismic positioning method based on this technique. The method first improves the PSO algorithm by using the global search performance of this method to quickly find a feasible solution and provide a better initial solution for the subsequent solution of the nonlinear optimal microseismic positioning method. This approach effectively prevents the problem of the microseismic positioning method falling into a local optimum because of an over-reliance on the initial value. In addition, the nonlinear optimal microseismic positioning method further narrows the localisation error based on the PSO algorithm. A simulation test demonstrates that the new method has a good positioning effect, and engineering application examples also show that the proposed method has high accuracy and strong positioning stability. The new method is better than the separate positioning method, both overall and in three directions, making it more suitable for solving the microseismic positioning problem.
期刊介绍:
The journal is designed to provide an academic realm for a broad blend of academic and industry papers to promote rapid communication and exchange of ideas between Chinese and world-wide geophysicists.
The publication covers the applications of geoscience, geophysics, and related disciplines in the fields of energy, resources, environment, disaster, engineering, information, military, and surveying.