小波降噪在煤岩微震信号处理中的应用
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摘要
根据微震信号噪声强度ε,利用FFT滤波以及缺省的阈值确定模型、Birge-Massart策略的阈值确定模型和小波包变换中的penalty阈值确定模型对原煤单轴全程压缩加载破坏实验的微震信号进行降噪处理。理论分析及降噪结果表明,FFT滤波得到的降噪信号过于平滑,抑制了很多有用的信息成分,而小波三种阈值确定模型能够更加有效去除微震信号中的噪声成分,降噪后的信号与原信号有着很好的相似性,最大限度的反应了原始信号本身的性质。
According to noise intensity of micro-seismic(MS) signal,the denoising process of coal samples' MS signals obtained from uniaxial compression test with full loading to destruction was carried out with the use of FFT filtering,models determined on the basis of default threshold value,the threshold value obtained based on Birge-Massart strategy and the penalty threshold value of wavelet packet transform.The theoretical analysis and results of denoising process showed that the MS signals obtained after denoising with FFT filter was so smooth that the lots of the useful information was inhibited,however,comparing with FFT filter,the models determined based on the three of wavelet threshold values were able to remove the noise better,the MS signals obtained after denoising were similar to the original MS signals and reflected the properties of the original MS signals in the maximal degree.
According to noise intensity of micro-seismic(MS) signal,the denoising process of coal samples' MS signals obtained from uniaxial compression test with full loading to destruction was carried out with the use of FFT filtering,models determined on the basis of default threshold value,the threshold value obtained based on Birge-Massart strategy and the penalty threshold value of wavelet packet transform.The theoretical analysis and results of denoising process showed that the MS signals obtained after denoising with FFT filter was so smooth that the lots of the useful information was inhibited,however,comparing with FFT filter,the models determined based on the three of wavelet threshold values were able to remove the noise better,the MS signals obtained after denoising were similar to the original MS signals and reflected the properties of the original MS signals in the maximal degree.
引文
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[2]尹贤刚,李庶林,黄沛生,等.微震监测系统在矿山安全管理中的应用研究[J].矿业研究与开发,2006,26(1):65-68.
[3]唐礼忠,潘长良,杨承祥,等.冬瓜山铜矿微震监测系统及其应用研究[J].金属矿山,2006,(10):41-44,86.
[4]余克圣,唐绍辉,吴迪文.岩体工程灾害微震监测系统的新进展[J].矿业研究与开发,1999,19(2):40-42,50.
[5]刘国清.基于声发射的岩体工程灾害微震监测系统[J].采矿技术,2005,5(1):30-30,38.
[6]成云海,姜福兴,程久龙,等.关键层运动诱发矿震的微震探测初步研究[J].煤炭学报,2006,31(3):273-277.
[7]逢焕东,姜福兴,张兴民.微地震监测技术在矿井灾害防治中的应用[J].金属矿山,2004,(4):58-61.
[8]DOULinming,LIU Caiping,MU Zonglong.Prevention and fore-casting of rock burst hazards in coal mines[J].Mining scienceand technology,2009,19(5):585-591.
[9]Engi D.A spherical-stochastic methodology for microseismic e-vent location[J].Computers and Geosciences,1989,15(7):1037-1052.
[10]林卉,杜培军,张莲蓬.基于小波变换的影像融合算法与效果评价[J].矿业研究与开发,2005,25(2):48-52.
[11]何学秋,王恩元,聂百胜,等.煤岩流变电磁动力学[M].北京:科学出版社,2003.
[12]高成,董长虹,郭磊,等.Matlab小波分析与应用[M].北京:国防工业出版社,2006.
[13]飞思科技产品研发中心.小波分析理论与MATLAB7实现[M].北京:电子工业出版社,2005.
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