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.

煤矿开采过程中冲击地压事件频繁发生，严重影响施工人员的人身安全。实时微震监测煤岩体破裂信息可以提供早期预警，而震源定位方法是评价微震监测系统的重要指标。本文提出一种基于该技术的非线性混合最优粒子群优化（PSO）微震定位方法。该方法首先对PSO算法进行改进，利用该方法的全局搜索性能，快速找到可行解，为非线性最优微震定位方法的后续求解提供更好的初始解。该方法有效防止了微震定位方法因过度依赖初始值而陷入局部最优的问题。此外，基于PSO算法的非线性最优微震定位方法进一步缩小了定位误差。仿真测试表明，该方法具有良好的定位效果，工程应用实例也表明该方法具有较高的精度和较强的定位稳定性。新方法无论是整体还是三个方向均优于单独定位方法，更适合解决微震定位问题。