Microseism Positioning Based on an SA-PSO Hybrid Algorithm
(1 School of Civil & Environmental Engineering, University of Science and Technology Beijing, Beijing 100083; 2 Key Laboratory of High-Efficient Mining and Safety of Metal Mines, Ministry of Education, University of Science and Technology Beijing, Beijing 100083; 3 Dalian Academy of Reconnaissance and Mapping Co. Ltd., Dalian 116021)
Abstract：
Based on the search capabilities and features of Simulated Annealing (SA) and Particle Swarm Optimization (PSO), and combining the ability to escape from the local optimization solution of the SA method and the global optimization ability of the PSO method, an SA-PSO hybrid algorithm with a stronger search capability is put forward in this paper and applied to microseism positioning. The research results show that: 1) the positioning error of the SA-PSO hybrid algorithm is smaller than that of the SA/PSO algorithm; 2) whether the wave velocity is given or not, the spatial positioning errors of the seismic source are all within 1m on the non-symmetric plane of the detector arrays under this algorithm; 3) apart from the point M6, which is far away from the seimic source, the positioning errors of the points are all within 50 m when the wave velocity fluctuates randomly within ±1%, ±3% and ± 5%. Using the Dongguashan copper mine with a micro-seismic monitoring system as an example, this algorithm was verified by giving a positioning accuracy of about 30 m.
2016, Vol. 53 