Research on the Design of Coal Mine Microseismic Monitoring Network Based on Improved Particle Swarm Optimization
Source abstract
Abstract
The quality of a mine’s microseismic network layout directly affects the location accuracy of the microseismic network. Introducing the microseismic probability factor Fe, the microseismic importance factor FQ, and the effective range factor FV, an improved particle swarm algorithm with bacterial foraging algorithm is proposed to optimize the mine’s microseismic network layout and evaluation system based on the D-value optimization design theory. Through numerical simulation experiments, it is found that the system has the advantages of fast optimization speed and good network layout effect. Combined with the system application at Xiashijie Coal Mine in Tongchuan City, Shaanxi Province, the method in this paper successfully optimizes the layout of the 20-channel network, ensuring that the positioning error of key monitoring areas is controlled within 20 m, and the minimum measurable magnitude can reach −3.26. Finally, it is verified by blasting tests that the maximum spatial positioning accuracy of the site is within 12.2 m, and the positioning capability of the site network is more accurately evaluated. The relevant research can provide a reference for the layout of the microseismic monitoring network for similar projects.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Landslides and related hazards · Rock Mechanics and Modeling · Dam Engineering and Safety
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
Institute of Rock Instability and Seismicity Research, Dalian University of Technology, Dalian 116024, China
Funding
National Natural Science Foundation of China
References (32)
Show source-provided references
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