岩石微破裂信号的小波降噪处理方法研究

Study on Wavelet Denoising Method of Rock Microcrack Signal

【目的】隧道在开挖过程中,施工环境比较复杂,微震监测设备接收到的微破裂信号中含有一定的噪声,噪声的存在会对事件定位和岩体失稳信息的判断造成一定的影响。为了使岩石内部微破裂的位置定位更加准确,以及其他参数的计算更加精确,需要对监测到的信号进行降噪处理。【方法】选取4个现场典型波形,用小波分析方法的db小波基函数和sym小波基函数对其进行降噪处理,得出信噪比值。【结果】通过对信噪比值和波形分析比较发现,db10小波函数具有较好的降噪效果,信噪比可以达到73.8491,且信号降噪后,不会丢失原始信号的有效信息。【结论】db10小波函数降噪法是深埋隧洞岩石微破裂信号的最佳小波降噪方法,该研究成果对震源其他参数的精准确定具有重要意义,对提高岩体失稳预测的精度具有重要作用,也是建立智能化预警系统的重要基础。

[Purposes]During the excavation process of tunnels,the construction environment is relatively complex,and the microcrack signals received by microseismic monitoring equipment contain a certain amount of noise.The presence of noise has a certain impact on the localization of events and the judg⁃ment of rock mass instability information.In order to accurately locate the location of the microcrack in⁃side rocks and calculate other parameters more accurately,it is necessary to first perform noise reduction processing on the monitored signals.[Methods]This article selects four typical waveforms on site,and uses the wavelet analysis method's db wavelet basis function and sym wavelet basis function to denoise them,obtaining the signal-to-noise ratio.[Findings]By comparing the signal-to-noise ratio and wave⁃form analysis,it was found that the db10 wavelet function has a good denoising effect,with a signal-to-noise ratio of 73.8491.Moreover,after signal denoising,the effective information of the original signal will not be lost.[Conclusions]The db10 wavelet function denoising method is the best wavelet denoising method for rock microcrack signals in deep buried tunnels.This research work is of great significance for accurately determining other parameters of the seismic source,improving the accuracy of rock mass instability prediction,and is also an important foundation for establishing an intelligent warning system.