爆破震动与岩石破裂微震信号能量分布特征研究
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摘要
以矿山现场微震数据为基础,选取矿山爆破震动信号与岩石破裂微震信号对比研究。首先,运用Matlab的小波包分析模块对微震信号进行5层多尺度分解,分别求取各节点处重构信号的小波包频带能量,对爆破震动信号与岩石破裂信号的频带能量分布特征进行研究;其次,通过建立新的频带空间,对比二者的能量分布特征。结果表明,矿山现场微震信号的频带能量分布特征为:岩体破裂信号的能量多集中于S5,0～S5,7低频频带(0～125 Hz),爆破震动信号的能量则在S5,24～S5,31频带(375～500 Hz)表现得较为集中。该分析方法为矿山识别爆破震动事件与岩石破裂事件提供了一种思路,利用二者能量分布差异大、特征对比明显的特点,通过对比新频带空间内的能量分布特征,可以实现对两类微震波形的初步辨识。
Based on in-situ microseismic data,the features of blasting vibration and rock fracture microseismic signals were studied.Firstly,using the wavelet packet analysis method,the microseismic signals were decomposed into 5 multi-scale,32 frequency bands to calculate the signals energy under different bands.Secondly,via building 4 new frequency bands to compare the rock fracture signals and blasting vibration signals,the energy distribution was different,and the contrasting characteristics was more obvious.The results indicate that the frequency band energy distribution character of microseismic signals in mine field are as follows:the energy of rock fracture signals was concentrated in S5,0-S5,7 bands(0-125 Hz);blasting vibration signal was more obviously concentrated in S5,24-S5,31 bands(375-500 Hz).This analysis procedure provides a new method for recognizing blasting vibration and rock fracture signals,and the calculated distribution feature of signals energy can be used to recognize microseismic waveforms as feature index.
Based on in-situ microseismic data,the features of blasting vibration and rock fracture microseismic signals were studied.Firstly,using the wavelet packet analysis method,the microseismic signals were decomposed into 5 multi-scale,32 frequency bands to calculate the signals energy under different bands.Secondly,via building 4 new frequency bands to compare the rock fracture signals and blasting vibration signals,the energy distribution was different,and the contrasting characteristics was more obvious.The results indicate that the frequency band energy distribution character of microseismic signals in mine field are as follows:the energy of rock fracture signals was concentrated in S5,0-S5,7 bands(0-125 Hz);blasting vibration signal was more obviously concentrated in S5,24-S5,31 bands(375-500 Hz).This analysis procedure provides a new method for recognizing blasting vibration and rock fracture signals,and the calculated distribution feature of signals energy can be used to recognize microseismic waveforms as feature index.
引文
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[10]谭云亮,赵同彬,颜伟.顶板活动地震波突变特征的小波识别[J].岩石力学与工程学报,2003,22(11):1874–1877.(TAN Yunliang,ZHAO Tongbin,YAN Wei.Wavelet identification for roof-failure-induced seismic wave feature[J].Chinese Journal of Rock Mechanicsand Engineering,2003,22(11):1 874–1 877.(in Chinese))
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[12]孙延奎.小波分析及其应用[M].北京:机械工业出版社,2005:245–260.(SUN Yankui.Wavelet analysis and its application[M].Beijing:China Machine Press,2005:245–260.(in Chinese))
[13]凌同华,李夕兵.多段微差爆破振动信号频带能量分布特征的小波包分析[J].岩石力学与工程学报,2005,24(7):1117–1122.(LINGTonghua,LI Xibing.Analysis of frequency-band energy distributionsof millisecond blast vibration signals using the wavelet packetmethod[J].Chinese Journal of Rock Mechanics and Engineering,2005,24(7):1 117–1 122.(in Chinese))
[14]李洪涛,卢文波,舒大强,等.爆破地震波的能量衰减规律研究[J].岩石力学与工程学报,2010,29(增1):3364–3369.(LIHongtao,LU Wenbo,SHU Daqiang,et al.Study of energy attenuationlaw of blast-induced seismic wave[J].Chinese Journal of RockMechanics and Engineering,2010,29(Supp.1):3 364–3 369.(inChinese))
[15]宋光明,曾新吾,陈寿如,等.位置条件对爆破震动信号分析中小波包时频特征的影响[J].工程爆破,2002,8(4):1–6.(SONGGuangming,ZENG Xinwu,CHEN Shouru,et al.Effect of situationcondition on time-frequency characteristics of blasting vibration withwavelet packets analysis[J].Engineering Blasting,2002,8(4):1–6.(in Chinese))
[16]李舜酩,李香莲.振动信号的现代分析技术与应用[M].北京:国防工业出版社,2008:4–6.(LI Shunming,LI Xianglian.Modernanalysis techniques of vibration signals and its application[M].Beijing:National Defense Industry Press,2008:4–6.(in Chinese))
[2]凌同华,李夕兵.多段微差爆破振动信号频带能量分布特征的小波包分析[J].岩石力学与工程学报,2005,24(7):1117–1122.(LINGTonghua,LI Xibing.Analysis of energy distributions of millisecondblast vibration signals using the wavelet packet method[J].ChineseJournal of Rock Mechanics and Engineering,2005,24(7):1 117–1 122.(in Chinese))
[3]邱宏茂,范万春,孙煜.基于能量分布特征的地震事件自动识别[J].核电子学与探测技术,2004,24(6):698–701.(QIUHongmao,FAN Wanchun,SUN Yu.Discriminating seismic events based onenergy-distributing feature[J].Nuclear Electronics and DetectionTechnology,2004,24(6):698–701.(in Chinese))
[4]陆菜平,窦林名,郭晓强,等.顶板岩层破断诱发矿震的频谱特征[J].岩石力学与工程学报,2010,29(5):1017–1022.(LUCaiping,DOU Linming,GUO Xiaoqiang,et al.Frequency-spectrumcharacters of microseismic signals induced by roof stratum fracture[J].Chinese Journal of Rock Mechanics and Engineering,2010,29(5):1 017–1 022.(in Chinese))
[5]RACHEL E L,WILLSKY A S.A wavelet packet approach to transientsignal classification[J].Applied and Computational Harmonic Analysis,1995,2(3):265–278.
[6]和雪松,李世愚,沈萍,等.用小波包识别地震和矿震[J].中国地震,2006,22(4):425–434.(HE Xuesong,LI Shiyu,SHEN Ping,et al.A wavelet packet approach to wave classification of earthquakesand mining shocks[J].Earthquake Research in China,2006,22(4):425–434.(in Chinese))
[7]刘希强,周蕙兰,李红.基于小波包变换的地震数据时频分析方法[J].西北地震学报,2000,22(2):40–43.(LIU Xiqiang,ZHOUHuilan,LI Hong.The time-frequency analysis method about seismicdata based on wavelet packet transform[J].Northwestern SeismologicalJournal,2000,22(2):40–43.(in Chinese))
[8]边银菊.遗传BP网络在地震和爆破识别中的应用[J].地震学报,2002,24(5):516–524.(BIAN Yinju.Application of genetic BPnetwork to discriminate earthquakes and explosions[J].Acta SeismoloicaSinica,2002,24(5):516–524.(in Chinese))
[9]中国生,徐国元,熊正明.基于小波变换的爆破地震信号能量分析法的应用研究[J].爆破与冲击,2006,26(3):222–227.(ZHONGGuosheng,XU Guoyuan,XIONG Zhengming.Application research ofthe energy analysis method for blasting seismic signal based onwavelet transform[J].Explosion and Shock Wave,2006,26(3):222–227.(in Chinese))
[10]谭云亮,赵同彬,颜伟.顶板活动地震波突变特征的小波识别[J].岩石力学与工程学报,2003,22(11):1874–1877.(TAN Yunliang,ZHAO Tongbin,YAN Wei.Wavelet identification for roof-failure-induced seismic wave feature[J].Chinese Journal of Rock Mechanicsand Engineering,2003,22(11):1 874–1 877.(in Chinese))
[11]王宏禹.非平稳随机信号分析与处理[M].北京:国防工业出版社,1999:122–140.(WANG Hongyu.Non-stationary random signalanalysis and processing[M].Beijing:National Defense Industry Press,1999:122–140.(in Chinese))
[12]孙延奎.小波分析及其应用[M].北京:机械工业出版社,2005:245–260.(SUN Yankui.Wavelet analysis and its application[M].Beijing:China Machine Press,2005:245–260.(in Chinese))
[13]凌同华,李夕兵.多段微差爆破振动信号频带能量分布特征的小波包分析[J].岩石力学与工程学报,2005,24(7):1117–1122.(LINGTonghua,LI Xibing.Analysis of frequency-band energy distributionsof millisecond blast vibration signals using the wavelet packetmethod[J].Chinese Journal of Rock Mechanics and Engineering,2005,24(7):1 117–1 122.(in Chinese))
[14]李洪涛,卢文波,舒大强,等.爆破地震波的能量衰减规律研究[J].岩石力学与工程学报,2010,29(增1):3364–3369.(LIHongtao,LU Wenbo,SHU Daqiang,et al.Study of energy attenuationlaw of blast-induced seismic wave[J].Chinese Journal of RockMechanics and Engineering,2010,29(Supp.1):3 364–3 369.(inChinese))
[15]宋光明,曾新吾,陈寿如,等.位置条件对爆破震动信号分析中小波包时频特征的影响[J].工程爆破,2002,8(4):1–6.(SONGGuangming,ZENG Xinwu,CHEN Shouru,et al.Effect of situationcondition on time-frequency characteristics of blasting vibration withwavelet packets analysis[J].Engineering Blasting,2002,8(4):1–6.(in Chinese))
[16]李舜酩,李香莲.振动信号的现代分析技术与应用[M].北京:国防工业出版社,2008:4–6.(LI Shunming,LI Xianglian.Modernanalysis techniques of vibration signals and its application[M].Beijing:National Defense Industry Press,2008:4–6.(in Chinese))
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