基于第二代小波变换的结构损伤检测研究进展
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摘要
小波变换可以对非稳态信号进行详细的时频分析,已广泛应用于机械?航空航天?土木等工程领域中,特别是在结构损伤识别和健康监测中的应用尤为突出.在第一代小波变换基础上提出的第二代小波变换,具有算法简单?运算速度快?能够准确匹配信号的局部特征等优点.笔者综合论述了第二代小波变换理论及其在结构损伤检测中的应用,并对其未来发展进行展望.
Wavelet transform can conduct a detailed time-frequency analysis to non-steady-state signal and has been widely used in mechanical,aeronautical,civil engineering and so on.It is particularly conspicuous that wavelet analysis is applied in structural health monitoring and damage identification.The second generation wavelet transform had been raised on the basis of the first generation wavelet transform.It has much more advantages.Its algorithm is simple and the calculation is fast.It is able to suit fairly the partial feature of the signal and so on.This paper reviewed and summed up the second generation wavelet transform theory and its application in structural damage identification.And its future development has been pointed out.
Wavelet transform can conduct a detailed time-frequency analysis to non-steady-state signal and has been widely used in mechanical,aeronautical,civil engineering and so on.It is particularly conspicuous that wavelet analysis is applied in structural health monitoring and damage identification.The second generation wavelet transform had been raised on the basis of the first generation wavelet transform.It has much more advantages.Its algorithm is simple and the calculation is fast.It is able to suit fairly the partial feature of the signal and so on.This paper reviewed and summed up the second generation wavelet transform theory and its application in structural damage identification.And its future development has been pointed out.
引文
[1]SURACE C,RUOTOLO R.Crack detection of a beamusing the wavelet transform.In:Proceedings the 12thInternational Modal Analysis Conf[C].Honolulu:Ha-waii,1994.1141-1147.
[2]SUN Z,CHANG C C.Structural damage assessmentbased on wavelet packet transform[J].J Structure En-gineering,2002,128(10):1354-1361.
[3]段晨东,李凌均,何正嘉.第二代小波变换在旋转机械故障诊断中的应用[J].机械科学与技术,2004,23(2):224-225.
[4]DAUBECHIES W S.Factoring wavelet transform intolifting steps[J].Math Anal Appl.1998,4(3):247-269.
[5]飞思科技产品研发中心.小波分析理论与MATLA-BR2007实现[M].北京:电子工业出社,2007:375-381.
[6]孙增寿,韩建刚,任伟新.基于小波分析的结构损伤检测研究进展[J].地震工程与工程振动,2005,25(2):93-99.
[7]何正嘉,陈雪峰,段晨东,等.早期故障预示的若干方法及应用[J].振动工程学报,2004,17(5):309-312.
[8]姜洪开,何正嘉,段晨东,等.自适应冗余第二代小波设计及齿轮箱故障特征提取[J].西安交通大学学报,2005,39(7):715-718.
[9]王忠民,乐全明,杨光亮,等.基于提升小波和神经网络的超高压电网故障类型识别[J].华东电力,2006,34(2):29-33.
[10]郑华珍,乐全明,郁惟镛,等.基于小波理论的超高压电网故障时刻提取[J].电网技术,2005,29(19):33-38.
[11]冯彩红,韩捷,李凌均.全信息小波包分析及其在旋转机械故障中的应用[J].机械强度,2006,28(5):639-642.
[12]马波,高金吉,江志农.自适应提升小波在往复机械故障检测中的应用[J].流体机械,2007,35(4):23-27.
[13]段晨东,何正嘉,姜洪开.非线性小波变换在故障特征提取中的应用[J].振动工程学报,2005,18(1):129-132.
[14]唐贵基,王誉蓉,胡爱军,等.基于第二代小波变换的旋转机械振动信号去噪[J].噪声与振动控制,2007,(1):51-53.
[15]周瑞,鲍文,左国华,等.基于改进冗余提升方案的汽轮机组振动故障特征提取[J].中国电机工程学报,2008,28(18):88-93.
[16]LI Z,HE Z J,ZI Y Y,et al.Bearing condition monito-ring based on shock pulse method and improved redun-dant lifting scheme[J].Mathematics and computers insimulation,2008,79:319-338.
[17]CAO HR,CHEN X F,ZI Y Y,et al.End milling toolbreakage detection using lifting scheme and Mahalano-bis distance[J].Machine Tools&Manufacture,2008,48(2):141-80.
[18]陈香朋,曹思远.第二代小波变换及其在地震信号去噪中的应用[J].石油物探,2004,43(6):547-550.
[19]ERGUN E.Electrocardiogram signals de-noising u-sing lifting-based discrete wavelet transform[J].Computers in Biology and Medicine,2004,34:479-493.
[2]SUN Z,CHANG C C.Structural damage assessmentbased on wavelet packet transform[J].J Structure En-gineering,2002,128(10):1354-1361.
[3]段晨东,李凌均,何正嘉.第二代小波变换在旋转机械故障诊断中的应用[J].机械科学与技术,2004,23(2):224-225.
[4]DAUBECHIES W S.Factoring wavelet transform intolifting steps[J].Math Anal Appl.1998,4(3):247-269.
[5]飞思科技产品研发中心.小波分析理论与MATLA-BR2007实现[M].北京:电子工业出社,2007:375-381.
[6]孙增寿,韩建刚,任伟新.基于小波分析的结构损伤检测研究进展[J].地震工程与工程振动,2005,25(2):93-99.
[7]何正嘉,陈雪峰,段晨东,等.早期故障预示的若干方法及应用[J].振动工程学报,2004,17(5):309-312.
[8]姜洪开,何正嘉,段晨东,等.自适应冗余第二代小波设计及齿轮箱故障特征提取[J].西安交通大学学报,2005,39(7):715-718.
[9]王忠民,乐全明,杨光亮,等.基于提升小波和神经网络的超高压电网故障类型识别[J].华东电力,2006,34(2):29-33.
[10]郑华珍,乐全明,郁惟镛,等.基于小波理论的超高压电网故障时刻提取[J].电网技术,2005,29(19):33-38.
[11]冯彩红,韩捷,李凌均.全信息小波包分析及其在旋转机械故障中的应用[J].机械强度,2006,28(5):639-642.
[12]马波,高金吉,江志农.自适应提升小波在往复机械故障检测中的应用[J].流体机械,2007,35(4):23-27.
[13]段晨东,何正嘉,姜洪开.非线性小波变换在故障特征提取中的应用[J].振动工程学报,2005,18(1):129-132.
[14]唐贵基,王誉蓉,胡爱军,等.基于第二代小波变换的旋转机械振动信号去噪[J].噪声与振动控制,2007,(1):51-53.
[15]周瑞,鲍文,左国华,等.基于改进冗余提升方案的汽轮机组振动故障特征提取[J].中国电机工程学报,2008,28(18):88-93.
[16]LI Z,HE Z J,ZI Y Y,et al.Bearing condition monito-ring based on shock pulse method and improved redun-dant lifting scheme[J].Mathematics and computers insimulation,2008,79:319-338.
[17]CAO HR,CHEN X F,ZI Y Y,et al.End milling toolbreakage detection using lifting scheme and Mahalano-bis distance[J].Machine Tools&Manufacture,2008,48(2):141-80.
[18]陈香朋,曹思远.第二代小波变换及其在地震信号去噪中的应用[J].石油物探,2004,43(6):547-550.
[19]ERGUN E.Electrocardiogram signals de-noising u-sing lifting-based discrete wavelet transform[J].Computers in Biology and Medicine,2004,34:479-493.
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