同步挤压小波变换在矿山微震监测系统中的应用

Synchrosqueezed wavelet transform application in mine microseismic monitoring system

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.