Research on a nonlinear hybrid optimal PSO microseismic positioning method
Xiao Yang*, Liu Wei-jian, Wang Hao-nan, Hou Meng-jie, Dong Sen-sen Zhang Zhi-zeng
1. School of Civil Engineering and Architecture, Zhongyuan University of Technology, Zhengzhou 451191, China;
2. General aff airs department, ANY SCIENCE & TECHNOLOGIES(CHANGZHOU) INC., Changzhou 213000, China
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 eff ect, 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.
作者简介: Author Biography: Xiao Yang (1999-), Male, Shangqiu city, Henan Province, Master Degree,
His research interests include Rock mechanics, Prevention and control of rockburst, Microseismic monitoring. E-mail:yangxiao157999@163.com;
2025, Vol. 22 
