Dai Rui, Wang Yibo, Zhang Da, Ji Hu
BGRIMM Technology Group Co., Ltd., Beijing 102628, China.
Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 518055, China.
Entropy (Basel). 2023 Oct 16;25(10):1451. doi: 10.3390/e25101451.
The underground pressure disaster caused by the exploitation of deep mineral resources has become a major hidden danger restricting the safe production of mines. Microseismic monitoring technology is a universally recognized means of underground pressure monitoring and early warning. In this paper, the wavelet coefficient threshold denoising method in the time-frequency domain, STA/LTA method, AIC method, and skew and kurtosis method are studied, and the automatic P-phase-onset-time-picking model based on noise reduction and multiple detection indexes is established. Through the effect analysis of microseismic signals collected by microseismic monitoring system of coral Tungsten Mine in Guangxi, automatic P-phase onset time picking is realized, the reliability of the P-phase-onset-time-picking method proposed in this paper based on noise reduction and multiple detection indexes is verified. The picking accuracy can still be guaranteed under the severe signal interference of background noise, power frequency interference and manual activity in the underground mine, which is of great significance to the data processing and analysis of microseismic monitoring.
深部矿产资源开采引发的地下压力灾害已成为制约矿山安全生产的重大隐患。微震监测技术是一种被普遍认可的地下压力监测与预警手段。本文研究了时频域小波系数阈值去噪方法、STA/LTA方法、AIC方法以及偏度和峰度方法,并建立了基于降噪和多检测指标的自动P波初至时间拾取模型。通过对广西珊瑚钨矿微震监测系统采集的微震信号进行效果分析,实现了自动P波初至时间拾取,验证了本文提出的基于降噪和多检测指标的P波初至时间拾取方法的可靠性。在井下矿山背景噪声、工频干扰和人工活动等强信号干扰下仍能保证拾取精度,对微震监测的数据处理与分析具有重要意义。