独山子台跨断层垂直形变观测资料干扰消除研究
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摘要
结合多参考自适应噪声对消和小波模极大值去噪理论,研究了新疆独山子台跨断层垂直形变观测数据的干扰因素及消除方法,结果表明:利用气象温度数据和断层两盘温差数据作为两个噪声参考输入进行自适应噪声对消,可有效消除信号中的年周期变化;利用小波模极大值去噪方法,可以抑制信号中的高频白噪声成分,使信号畸变更加明显。仿真结果及实际应用均验证了此方法的有效性与实用性,消除干扰后的垂直形变数据与台站100 km范围内4级以上地震有较好的对应性,反映了独山子台对周边地区4级以上地震的映震能力。
Based on the theory of multiple-reference adaptive noise cancellation and wavelet transform modulus maxima,this paper studied the method of interference cancellation for vertical deformation data from Dushanzi.The results indicate that: The annual variation in vertical deformation data is produced by seasonal variety of near-surface temperature and the temperature difference between fault′s hanging wall and foot wall,and the data is also influenced by white noise and other random noise.By using the data of meteorological temperature and auxiliary temperature to carry out adaptive noise cancellation,we can eliminate the effect of annual variation.Furthermore,by means of wavelet transform modulus maxima denoising on the data which has been ruled out the effect of annual variation,the white noise is inhibited,and the signal′s distortion is clearer and more accurate.Simulation testing and practical application demonstrate the denoise effect of the said method is effective and practical.The vertical deformation data that eliminated the effect of interference is found in good correspondence to the earthquakes of Ms≥4 within the radius of 100km from the station,and that reflects the station′s ability to response earthquake of Ms≥4 for surrounding area.
Based on the theory of multiple-reference adaptive noise cancellation and wavelet transform modulus maxima,this paper studied the method of interference cancellation for vertical deformation data from Dushanzi.The results indicate that: The annual variation in vertical deformation data is produced by seasonal variety of near-surface temperature and the temperature difference between fault′s hanging wall and foot wall,and the data is also influenced by white noise and other random noise.By using the data of meteorological temperature and auxiliary temperature to carry out adaptive noise cancellation,we can eliminate the effect of annual variation.Furthermore,by means of wavelet transform modulus maxima denoising on the data which has been ruled out the effect of annual variation,the white noise is inhibited,and the signal′s distortion is clearer and more accurate.Simulation testing and practical application demonstrate the denoise effect of the said method is effective and practical.The vertical deformation data that eliminated the effect of interference is found in good correspondence to the earthquakes of Ms≥4 within the radius of 100km from the station,and that reflects the station′s ability to response earthquake of Ms≥4 for surrounding area.
引文
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[17]Mallat S,Hwang W L.Singularity detection and processing withwavelets[J].IEEE Transactions on Information Theory,1992,38(2):617-643.]
[18]Meng Qinghua,Zhao Wenli.Study on signal denoising of modulusmaximum based on optimal wavelet package decomposition[J].Chinese Journal ofSensors and Actuators,2006,19(6):2 582-2 584.[孟庆华,赵文礼.基于最优小波包基的模极大值法信号消噪研究[J].传感技术学报,2006,19(6):2 582-2 584.]
[19]Fan Jichang,Liu Mingjun,Wang Fuyun,et al.Analysis on maxi-mum wavelet decomposition level from theory and application[J].ReviewScience&Technology,2008,26(10):40-42.[樊计昌,刘明军,王夫运,等.浅析小波最大分解层[J].科技导报,2008,26(10):40-42.]
[20]Dimitris G Manolakis,Vinay K Ingle,Stephen M Kogon.Statisti-cal and Adaptive Signal Processing[M].Zhou Zheng,et al.translated.Beijing:Publishing House of Electronics Industry,2003:499-521.[Dimitris G Manolakis,Vinay k Ingle,StephenMKogon.统计与自适应信号处理[M].周正等译.北京:电子工业出版社,2003:499-521.]
[2]Gao Fuwang,Li li,Niu Anfu,et al.Study on the identification andelimination of the disturbance in crustal strain record[J].Earth-quake,2004,24:91-97.[高福旺,李丽,牛安福,等.对体应变干扰因素的识别及排除[J].地震,2004,24:91-97.]
[3]Zhang Wenlai,Luo Hongjiang,Su Ping.The interferential analysison air pressure change toward observational daily change curve ofSS-Y tensometer[J].Inland Earthquake,2006,20(3):266-270.[张文来,罗宏江,苏萍.气压变化对SS-Y伸缩仪观测日变曲线的干扰分析[J].内陆地震,2006,20(3):266-270.]
[4]Liu Shijin,Yang Guang,Li Xuechuan.Interfering recognization inthe digitize data of deformation observation in Guza seismic station[J].Earthquake Research in Sichuan,2007,123:31-35.[刘仕锦,阳光,李学川.姑咱地震台数字化形变观测资料干扰识别[J].四川地震,2007,123:31-35.]
[5]Li Jie.Analysis of main interference of leveling survey in Gaoya,Shandong[J].Earthquake Research in Shanxi,1998,92:47-50.[李杰.山东高崖水准主要干扰的分析[J].山西地震,1998,92:47-50.]
[6]Zhao Shuping,Zhang Zhaodong.A study on the elimination of in-terference in the observed data of pressure solution differentialstress at Taianstation,Shandong province[J].North China Earth-quake Sciences,1996,14(1):47-50.[赵淑平,张昭栋.山东省泰安台压容差应变观测排除干扰研究[J].华北地震科学,1996,14(1):47-50.]
[7]Bo Wanju.Development and Application of the eliminating inter-ference method by Frequency-band division[J].Earthquake Re-search in Shanxi,1993,74:24-29.[薄万举.分频段排除干扰方法的建立与应用[J].山西地震,1993,74:24-29.]
[8]Zhu Xiaofang,Chen Yaguang.Application of noise cancellation insignal processing system[J].Modern Electronics Technique,2006,24:86-88.[朱小芳,陈亚光.噪声对消在信号处理系统中的应用[J].现代电子技术,2006,24:86-88.]
[9]Liu Guanzhong,Jiang Jingxiang,Wang Jianjun,et al.“Rate cumu-lative analysis”on across-fault fixed deformation data and prelimi-nary anomaly extraction method[J].Inland Earthquake,2007,21(3):230-237.[刘冠中,蒋靖祥,王建军,等.跨断层定点形变观测资料“速率累加分析”及其异常初步提取方法[J].内陆地震,2007,21(3):230-237.]
[10]Jiao Qing,Zhang Hongxu,Song Guangfu,et al.A preliminarystudy on the cross-fault displacement variation at Dushanzi stationin Xinjiang,China,before the M7.8 earthquake in Pakistan[J].Earthquake,2007,27(1):77-84.[焦青,张鸿旭,宋光甫,等.巴基斯坦7.8级地震前新疆独山子台跨断层位移变化初析[J].地震,2007,27(1):77-84.]
[11]Jing Yan,Zhang Shizhong,Li Hong,et al.Response of verticaldeformation on faults to remote strong earthquakes[J].Acta Seis-mologica Sinica,2007,29(2):165-172.[荆燕,张世中,李宏,等.断层垂直形变对强远震的响应[J].地震学报,2007,29(2):165-172.]
[12]Zhang Yiguang,Zhang Ruiyun.The annual variation rule of thedata observed by type DSJ fault-crossing levellers in Xinjiang[J].Inland Earthquake,1998,12(2):142-146.[张毅光,张瑞云.新疆DSJ型水平断层活动测量仪年变规律的研究[J].内陆地震,1998,12(2):142-146.]
[13]Wang Zaihua,Kong Defeng,Song Guangfu.Relative analysis be-tween fault deformation observational datum and auxiliary temper-ature observational datum[J].Inland Earthquake,2005,19(2):188-191.[王在华,孔德峰,宋光甫.断层形变测量资料与辅助温度观测资料相关分析[J].内陆地震,2005,19(2):188-191.]
[14]Li Jie,Liu Xiqiang,Li Hong,et al.Analyses on normal back-ground characteristics about deformation observation data on thebasis of wavelet transform method[J].Acta Seismologica Sinica,2005,27(1):33-41.[李杰,刘希强,李红,等.利用小波变换方法分析形变观测资料的正常背景变化特征[J].地震学报,2005,27(1):33-41.]
[15]He Zhenya.Adaptive Signal Processing[M].Beijing:SciencePress,2002:247-249.[何振亚.自适应信号处理[M].北京:科学出版社,2002:247-249.]
[16]Simon Haykin.Adaptive Filter Theory Fourth Edition[M].ZhengBaoyu,translated.Beijing:Publishing House of Electronics In-dustry,2003:185-202.[Simon Haykin.自适应滤波器原理[M].郑宝玉译.北京:电子工业出版社,2003:185-202.]
[17]Mallat S,Hwang W L.Singularity detection and processing withwavelets[J].IEEE Transactions on Information Theory,1992,38(2):617-643.]
[18]Meng Qinghua,Zhao Wenli.Study on signal denoising of modulusmaximum based on optimal wavelet package decomposition[J].Chinese Journal ofSensors and Actuators,2006,19(6):2 582-2 584.[孟庆华,赵文礼.基于最优小波包基的模极大值法信号消噪研究[J].传感技术学报,2006,19(6):2 582-2 584.]
[19]Fan Jichang,Liu Mingjun,Wang Fuyun,et al.Analysis on maxi-mum wavelet decomposition level from theory and application[J].ReviewScience&Technology,2008,26(10):40-42.[樊计昌,刘明军,王夫运,等.浅析小波最大分解层[J].科技导报,2008,26(10):40-42.]
[20]Dimitris G Manolakis,Vinay K Ingle,Stephen M Kogon.Statisti-cal and Adaptive Signal Processing[M].Zhou Zheng,et al.translated.Beijing:Publishing House of Electronics Industry,2003:499-521.[Dimitris G Manolakis,Vinay k Ingle,StephenMKogon.统计与自适应信号处理[M].周正等译.北京:电子工业出版社,2003:499-521.]
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