副井振动信号处理的提升小波变换方法
|
摘要
高层结构受气象、地基沉陷等外界因素影响,会产生一系列的振动变形;为研究其振动特性,保障结构安全,须对其进行变形监测。利用GPS对高层结构进行变形监测时,得到的变形信号往往包含大量的无用信息,为准确把握结构体的变形信息,可以用提升小波变换的方法对信号进行处理。以皖北矿区某副井提升台为研究对象,将监测点设于振动台上,利用天宝R10对监测点进行监测试验,对得到的振动变形信号进行提升小波变换以初步降噪,然后对降噪后的信号进行小波分解。结果表明,GPS监测获取的振动信号中包含大量噪声,通过提升小波变换处理及小波分解之后,将噪声与振动信息分离开来,提取出了有效的结构振动信息,这对于实践中的GPS数据处理及形变信息提取工作具有着重要的参考价值。
Influenced by outside factors such as meteorology and subsidence,high-level structure always produce a series of vibration deformation,so deformation monitoring should be performed to study its vibration characters and ensure its safety.In the process of deformation monitoring,the deformation signal often contains a lot of useless information with the technology of GPS. In order to get useful vibration deformation information,lifting wavelet analysis in signal processing has been considered.Taking a auxiliary shaft elevator platform of Wanbei mining area as an example,monitoring stations positioning on the vibration table,monitoring tests with Trimble R10 for plane point had been made,and lifting wavelet analysis had been operated on the vibration deformation signal,and then wavelet decomposition had been made to achieve useful information. Results showed that the vibration signal obtained by GPS monitoring contained a lot of noise. With the technology of lifting wavelet analysis and decomposition,noise was separated from the effective structural vibration information. It has important reference value for the practice of GPS data processing and the work of deformation information extraction.
Influenced by outside factors such as meteorology and subsidence,high-level structure always produce a series of vibration deformation,so deformation monitoring should be performed to study its vibration characters and ensure its safety.In the process of deformation monitoring,the deformation signal often contains a lot of useless information with the technology of GPS. In order to get useful vibration deformation information,lifting wavelet analysis in signal processing has been considered.Taking a auxiliary shaft elevator platform of Wanbei mining area as an example,monitoring stations positioning on the vibration table,monitoring tests with Trimble R10 for plane point had been made,and lifting wavelet analysis had been operated on the vibration deformation signal,and then wavelet decomposition had been made to achieve useful information. Results showed that the vibration signal obtained by GPS monitoring contained a lot of noise. With the technology of lifting wavelet analysis and decomposition,noise was separated from the effective structural vibration information. It has important reference value for the practice of GPS data processing and the work of deformation information extraction.
引文
[1]毛亚纯,贾葳葳,沙成满,等.边坡变形监测数据小波去噪研究[J].金属矿山,2010(9):137-142.Mao Yachun,Jia Weiwei,Sha Chengman,et al.Investigation on wavelet denoising with deformation monitoring data of slopes[J].Metal Mine,2010(9):137-142.
[2]崔红超.小波分析在GPS数据处理中的应用研究[D].抚州:东华理工大学,2013.Cui Hongchao.Research on GPS Data Denoising Based on Wavelet Analysis[D].Fuzhou:East China Institute of Technology,2013.
[3]黄维婷.多尺度小波分析及其在测井曲线自动分层中的应用研究[D].成都:成都理工大学,2012.Huang Weiting.Research on Multi-scale Wavelet Analysis on the Application of Well Logging Curves Automatic Stratification[D].Chengdu:Chengdu University of Technology,2012.
[4]桑燕芳,王中根,刘昌明.小波分析方法在水文学研究中的应用现状及展望[J].地理科学进展,2013,32(9):1413-1414.Sang Yanfang,Wang Zhonggen,Liu Changming.Applications of wavelet analysis to hydrology status and prospects[J].Progress in Geography,2013,32(9):1413-1414.
[5]梁跃.基于小波包变换的地电场信号去噪研究[D].哈尔滨:东北农业大学,2014.Liang Yue.Denoising Research of Geoelectric Field Signal Based on Wavelet Packet Transform[D].Harbin:The Northeast Forestry University,2014.
[6]王涛,夏岸雄,廖新旭.基于小波变换的爆破振动信号不同频带能量分析[J].金属矿山,2014(3):52-55.Wang Tao,Xia Anxiong,Liao Xinxu.Analysis on different frequencyband energy of blasting vibration signal based on wavelet transform[J].Metal Mine,2014(3):52-55.
[7]李寅寅,徐晓苏,刘锡祥.基于小波包阈值处理的GPS软件接收机跟踪结果降噪算法[J].中国惯性技术学报,2011,19(4):431-435.Li Yinyin,Xu Xiaosu,Liu Xixiang.Denoising method for tracking results of GPS software receiver based on wavelet packet soft-threshold algorithm[J].Journal of Chinese Inertial Technology,2011,19(4):431-435.
[8]武东辉,田林亚,张金华.小波时间序列在地铁沉降监测中的应用[J].测绘科学,2013,38(2):150-151.Wu Donghui,Tian Linya,Zhang Jinhua.Application of wavelet timeseries in settlement monitoring for urban subway[J].Science of Surveying and Mapping,2013,38(2):150-151.
[9]章浙涛,朱建军,匡翠林,等.小波包多阈值去噪法及其在形变分析中的应用[J].测绘学报,2014,43(1):13-20.Zhang Zhetao,Zhu Jianjun,Kuang Cuilin,et al.Multi-threshold wavelet packet denoising method and its application in deformation analysis[J].Acta Geodaetica et Cartographica Sinica,2014,43(1):13-20.
[10]徐秀杰,黄张裕,凌晨阳,等.基于小波分析的灰色组合模型在变形监测数据处理中的应用[J].工程勘察,2014(4):80-83.Xu Xiujie,Huang Zhangyu,Ling Chenyang,et al.Application of grey theory and wavelet in deformation monitoring data processing[J].Geotechnical Investigation&Surveying,2014(4):80-83.
[11]李红连,方红,唐炬,等.基于提升小波变换的GPS动态滤波新算法[J].交通运输系统工程与信息,2013,13(1):43-48.Li Honglian,Fang Hong,Tang Ju,et al.GPS dynamic filter algorithm based on lifting wavelet transformation[J].Journal of Transportation System Engineering and Information Technology,2013,13(1):43-48.
[12]梁高翔,马铁华,张艳兵.基于提升小波变换的容栅传感器输出信号降噪[J].传感技术学报,2011,24(8):1178-1181.Liang Gaoxiang,Ma Tiehua,Zhang Yanbing.Denoising of capacitive bars sensor signal based on lifting wavelet transform[J].Chinese Journal of Sensors and Actuators,2011,24(8):1178-1181.
[13]高永梅,欧吉坤.基于提升小波的GPS周跳探测仿真分析[J].煤炭学报,2009,34(11):1494-1498.Gao Yongmei,Ou Jikun.Simulation analysis of GPS cycle-slip detection based on lifting wavelet[J].Journal of China Coal Society,2009,34(11):1494-1498.
[14]廖重贵.小波分析在变形监测中的应用研究[D].赣州:江西理工大学,2010.Liao Zhonggui.The Application of Wavelet Analysis in Deformation Monitoring[D].Ganzhou:Jiangxi University of Science and Technology,2010.
[15]张永学,陈丽霞,钟正斌.提升小波变换在信号去噪中的应用[J].石油仪器,2007,21(1):80-82.Zhang Yongxue,Chen Lixia,Zhong Zhengbin.The application of lifting wavelet transformation in signal denoising[J].Petroleum Instruments,2007,21(1):80-82.
[16]吴继忠,花向红,高俊强.基于小波包分解的结构自振特征提取及多路径误差分离[J].武汉大学学报:信息科学版,2010,35(4):486-490.Wu Jizhong,Hua Xianghong,Gao Junqiang.Feature extraction of structure natural vibration and multipath separation based on wavelet packet decomposition[J].Journal of Wuhan University:Information Science,2010,35(4):486-490.
[17]徐克科,伍吉仓.高频GNSS高楼结构振动动态监测试验[J].测绘科学,2014,39(7):43-47.Xu Keke,Wu Jicang.Experiment on structural vibration monitoring of tall building by high-rate GNSS[J].Science of Surveying and Mapping,2014,39(7):43-47.
[2]崔红超.小波分析在GPS数据处理中的应用研究[D].抚州:东华理工大学,2013.Cui Hongchao.Research on GPS Data Denoising Based on Wavelet Analysis[D].Fuzhou:East China Institute of Technology,2013.
[3]黄维婷.多尺度小波分析及其在测井曲线自动分层中的应用研究[D].成都:成都理工大学,2012.Huang Weiting.Research on Multi-scale Wavelet Analysis on the Application of Well Logging Curves Automatic Stratification[D].Chengdu:Chengdu University of Technology,2012.
[4]桑燕芳,王中根,刘昌明.小波分析方法在水文学研究中的应用现状及展望[J].地理科学进展,2013,32(9):1413-1414.Sang Yanfang,Wang Zhonggen,Liu Changming.Applications of wavelet analysis to hydrology status and prospects[J].Progress in Geography,2013,32(9):1413-1414.
[5]梁跃.基于小波包变换的地电场信号去噪研究[D].哈尔滨:东北农业大学,2014.Liang Yue.Denoising Research of Geoelectric Field Signal Based on Wavelet Packet Transform[D].Harbin:The Northeast Forestry University,2014.
[6]王涛,夏岸雄,廖新旭.基于小波变换的爆破振动信号不同频带能量分析[J].金属矿山,2014(3):52-55.Wang Tao,Xia Anxiong,Liao Xinxu.Analysis on different frequencyband energy of blasting vibration signal based on wavelet transform[J].Metal Mine,2014(3):52-55.
[7]李寅寅,徐晓苏,刘锡祥.基于小波包阈值处理的GPS软件接收机跟踪结果降噪算法[J].中国惯性技术学报,2011,19(4):431-435.Li Yinyin,Xu Xiaosu,Liu Xixiang.Denoising method for tracking results of GPS software receiver based on wavelet packet soft-threshold algorithm[J].Journal of Chinese Inertial Technology,2011,19(4):431-435.
[8]武东辉,田林亚,张金华.小波时间序列在地铁沉降监测中的应用[J].测绘科学,2013,38(2):150-151.Wu Donghui,Tian Linya,Zhang Jinhua.Application of wavelet timeseries in settlement monitoring for urban subway[J].Science of Surveying and Mapping,2013,38(2):150-151.
[9]章浙涛,朱建军,匡翠林,等.小波包多阈值去噪法及其在形变分析中的应用[J].测绘学报,2014,43(1):13-20.Zhang Zhetao,Zhu Jianjun,Kuang Cuilin,et al.Multi-threshold wavelet packet denoising method and its application in deformation analysis[J].Acta Geodaetica et Cartographica Sinica,2014,43(1):13-20.
[10]徐秀杰,黄张裕,凌晨阳,等.基于小波分析的灰色组合模型在变形监测数据处理中的应用[J].工程勘察,2014(4):80-83.Xu Xiujie,Huang Zhangyu,Ling Chenyang,et al.Application of grey theory and wavelet in deformation monitoring data processing[J].Geotechnical Investigation&Surveying,2014(4):80-83.
[11]李红连,方红,唐炬,等.基于提升小波变换的GPS动态滤波新算法[J].交通运输系统工程与信息,2013,13(1):43-48.Li Honglian,Fang Hong,Tang Ju,et al.GPS dynamic filter algorithm based on lifting wavelet transformation[J].Journal of Transportation System Engineering and Information Technology,2013,13(1):43-48.
[12]梁高翔,马铁华,张艳兵.基于提升小波变换的容栅传感器输出信号降噪[J].传感技术学报,2011,24(8):1178-1181.Liang Gaoxiang,Ma Tiehua,Zhang Yanbing.Denoising of capacitive bars sensor signal based on lifting wavelet transform[J].Chinese Journal of Sensors and Actuators,2011,24(8):1178-1181.
[13]高永梅,欧吉坤.基于提升小波的GPS周跳探测仿真分析[J].煤炭学报,2009,34(11):1494-1498.Gao Yongmei,Ou Jikun.Simulation analysis of GPS cycle-slip detection based on lifting wavelet[J].Journal of China Coal Society,2009,34(11):1494-1498.
[14]廖重贵.小波分析在变形监测中的应用研究[D].赣州:江西理工大学,2010.Liao Zhonggui.The Application of Wavelet Analysis in Deformation Monitoring[D].Ganzhou:Jiangxi University of Science and Technology,2010.
[15]张永学,陈丽霞,钟正斌.提升小波变换在信号去噪中的应用[J].石油仪器,2007,21(1):80-82.Zhang Yongxue,Chen Lixia,Zhong Zhengbin.The application of lifting wavelet transformation in signal denoising[J].Petroleum Instruments,2007,21(1):80-82.
[16]吴继忠,花向红,高俊强.基于小波包分解的结构自振特征提取及多路径误差分离[J].武汉大学学报:信息科学版,2010,35(4):486-490.Wu Jizhong,Hua Xianghong,Gao Junqiang.Feature extraction of structure natural vibration and multipath separation based on wavelet packet decomposition[J].Journal of Wuhan University:Information Science,2010,35(4):486-490.
[17]徐克科,伍吉仓.高频GNSS高楼结构振动动态监测试验[J].测绘科学,2014,39(7):43-47.Xu Keke,Wu Jicang.Experiment on structural vibration monitoring of tall building by high-rate GNSS[J].Science of Surveying and Mapping,2014,39(7):43-47.