摘要
随着煤矿开采活动的不断深入,煤矿微震事件的监测与分析变得日益重要。为实现对煤矿微震的监测、防止事故的发生,提出了一种基于背景噪声探测的矿山微震监测方法。该方法使用短时平均与长时平均比值法与贝叶斯信息准则(BIC)实现对煤矿微震噪声的数据选择和定位,同时使用改进经验模态分解(EMD)算法对背景噪声数据进行降噪。研究结果表明,该方法能够显著提升矿山微震监测准确率,其信噪比最高能够达到22.345 dB,均方根误差为0.012 mV,指标性能显著高于其他的噪声滤波方法;并且数据冗杂量显著降低。该方法对提升煤矿微震信号的定位监测准确率具有重要的意义。
With the continuous deepening of coal mining activities,monitoring and analysis of microseismic events in coal mines have become increasingly important.To achieve monitoring of microseismicity in coal mines and prevent accidents,a mine microseismic monitoring method based on background noise detection was proposed.This method uses the short-term average to long-term average ratio method and Bayesian Information Criterion(BIC)to select and locate microseismic noise in coal mines,while using an improved Empirical Mode Decomposition(EMD)algorithm to denoise the background noise data.The research results show that this method can significantly improve the accuracy of microseismic monitoring in coal mines,can achieve a maximum signal-to-noise ratio of 22.345 dB and root mean square error of 0.012 mV,with significantly higher performance indicators than other noise filtering methods,and significantly reduces the amount of data redundancy.This method has important significance for improving the positioning and monitoring accuracy of microseismic signals in coal mines.
作者
杨志立
刘攀飞
冯海军
王奎辉
吕占魁
郭文浩
Yang Zhili;Liu Panfei;Feng Haijun;Wang Kuihui;Lyu Zhankui;Guo Wenhao(Shanxi Huaning Coking Coal Co.,Ltd.,Linfen 041000,China;The Fifth Geological Brigade,Jiangxi Geological Bureau,Xinyu 338000,China)
出处
《煤矿机械》
2026年第2期212-216,共5页
Coal Mine Machinery
基金
江西省地质局2023年度地质灾害防治公益性项目(202211924)。
关键词
矿山微震
背景噪声
监测
准确率
mine microseismic
background noise
monitoring
accuracy
