| 基于微震监测试验的微震信号类别识别降噪方法研究 |
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| 引用本文： | 刘跃成,康跃明,赵智辉,周 创,周 水.基于微震监测试验的微震信号类别识别降噪方法研究[J].中州煤炭,2022,0(2):186-192. |
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| 作者姓名： | 刘跃成 康跃明 赵智辉 周 创 周 水 |
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| 作者单位： | （1.云南交投集团投资有限公司，云南 昆明 675800； 2.中煤科工集团重庆研究院有限公司，重庆 400039） |
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| 摘 要： | 微震监测技术是目前预测岩体损伤最有前景的探测技术之一。为提升微震监测技术的准确性，以云县至凤庆高速公路隧道开挖工程为背景，现场进行了微震监测，并对爆破、打炮眼、电气干扰及岩石破裂信号进行了分析。结果表明，可以根据体变势、频谱最大频率、视体积及视应力大小等特征来区分不同信号。其中爆破信号的体变势、视体积和视应力的数值最大，频谱最大频率多数分布在0~10 Hz。岩石破裂产生的微震信号的体变势大多集中在0~10 m3，数值较大，频谱最大频率多数分布在50~60 Hz和180~200 Hz。研究结果对剔除干扰信号和指导现场微震监测具有重要意义。
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| 关 键 词： | 深埋隧道 微震监测 岩爆 动力扰动 信号识别 |
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| Research on noise reduction method of microseismic signal category identification based on microseismic monitoring test.-[J].Zhongzhou Coal,2022,0(2):186-192. |
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| Authors: | Research on noise reduction method of microseismic signal category identification based on microseismic monitoring test |
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| Affiliation: | Liu Yuecheng1，Kang Yueming2，Zhao Zhihui2，Zhou Chuang1，Zhou Shui1 |
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| Abstract: | Microseismic monitoring technology is one of the most promising detection technologies for predicting rock mass damage.In order to improve the accuracy of microseismic monitoring technology,on the background of the tunnel excavation project of Yunxian-Fengqing Expressway,microseismic monitoring was carried out on site,and blasting,blasting,electrical interference and rock rupture signals were analyzed.The results showed that different signals could be distinguished according to the characteristics of volume potential,maximum frequency of spectrum,apparent volume and apparent stress.Among them,the volume change potential,apparent volume and apparent stress of the blasting signal were the largest,and the maximum frequency of the spectrum was mostly distributed in the range of 0~10 Hz.The volume potentials of the microseismic signals generated by rock rupture were mostly concentrated in 0~10 m3,and the value was relatively large,and the maximum frequency of the spectrum was mostly distributed in the range of 50~60 Hz and 180~200 Hz.The research results were of great significance for eliminating interference signals and guiding on-site microseismic monitoring. |
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| Keywords: | ,deep buried tunnel, microseismic monitoring, rock burst, dynamic disturbance, signal identification |
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