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作 者:石雅倩 张达 冀虎 陶志达 SHI Yaqian;ZHANG Da;JI Hu;TAO Zhida(BGRIMM Technology Group,Beijing 102628,China;National Center for International Joint Research on Green Metal Mining,Beijing 102628,China;China-South Africa Joint Research Center for Mineral Resources Development,Beijing 102628,China;China-South Africa BRI Joint Laboratory for Sustainable Development and Utilization of Mineral Resources,Beijing 102628,China;Beijing Key Laboratory of Nonferrous Intelligent Mining Technology,Beijing 102628,China;China Coal Processing and Utilization Association,Beijing 100013,China)
机构地区:[1]矿冶科技集团有限公司,北京102628 [2]国家金属矿绿色开采国际联合研究中心,北京102628 [3]中国-南非矿产资源开发利用联合研究中心,北京102628 [4]中国-南非矿产资源可持续开发利用“一带一路”联合实验室,北京102628 [5]金属矿山智能开采技术北京市重点实验室,北京102628 [6]中国煤炭加工利用协会,北京100013
出 处:《有色金属(矿山部分)》2024年第3期95-100,共6页NONFERROUS METALS(Mining Section)
基 金:国家重点研发计划青年科学家项目(2021YFC2900600)。
摘 要:微震监测技术是一种保证矿山安全、高效、可持续发展的重要地压监测手段。矿山传感器获取的微震数据容易受到宽频带非平稳噪声的影响,导致微震监测缺乏可用的高质量数据。本文介绍了一种新的频谱分析方法——同步挤压小波变换,它提供了一种将数据同时分解到时域和频域的方法,且比小波变换等方法的时频分辨率更高,可以在时频谱上更为清晰地展示微震信号。同时,本文还比较了Morlet小波基和Bump小波基对微震波形的影响程度,并通过现场微震监测波形验证了Morlet小波基的相对可靠性。采用基于噪声水平的硬阈值滤波方法对其进行分别处理,结果表明,基于Morlet小波基的同步挤压小波变换在从原始数据中提取微震信号方面具有更大的实用价值,能够有效地提高信号的信噪比。Microseismic monitoring technology is an important ground pressure monitoring method to ensure the safety,efficiency,and sustainable development of mines.The data obtained by microseismic sensors are easily affected by broadband non-stationary noises,resulting in a lack of available high-SNR data for microseismic analysis.This paper introduces a new spectral analysis method-synchrosqueezed wavelet transform,which provides a method for decomposing data into both time and frequency domains and has higher time-frequency resolution than wavelet transform.It can more clearly display the microseismic waveform in the time-frequency spectrum.Meanwhile,this paper compares the impact of the Morlet wavelet basis and Bump wavelet basis on microseismic waveforms and verified the relative reliability of the Morlet wavelet basis through on-site microseismic monitoring waveforms.The hard threshold filtering method based on noise level is used here to verify that the synchrosqueezed wavelet transform based on the Morlet wavelet basis has great practical value in extracting microseismic signals from raw data,and can effectively improve the SNR of the signal.
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