基于小波包能量谱的声发射信号处理技术
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摘要
为实现材料早期结构疲劳损伤程度的监测与评价,提出采用小波包能量谱的声发射信号处理方法.首先,搭建金属疲劳损伤在线声发射监测系统,采集金属材料早期结构疲劳损伤产生的裂纹扩展与闭合的声发射信号;其次,选取适用于该声发射信号的小波函数和小波包分解层数,从而得到小波包分解后的各个频带的能量随疲劳周期数增加的变化情况的小波包能量谱图.实验表明:上述信号处理方法可获得能表征金属材料随着疲劳周期数增加的早期结构疲劳损伤程度变化的频带特征,为桥梁结构、建筑工程结构构件中常用钢材疲劳过程的声发射监测及早期疲劳损伤程度的加剧提供参考依据.
In order to realize the monitoring and evaluation of fatigue damage degree of early material structures,an acoustic emission signal processing method based on wavelet packet energy spectrum is proposed.Firstly,an on-line acoustic emission monitoring system for metal fatigue damage is established to collect acoustic emission signals of crack propagation and closure caused by early structural fatigue damage of metal materials.Secondly,the wavelet function and wavelet packet decomposition layers suitable for the AE signal are selected.Finally,the wavelet packets energy spectrum of each frequency band after wavelet packet decomposition with the increase of fatigue cycle number are obtained.Experimental results show that the above signal processing method can obtain the frequency band characteristics that can characterize the early structural fatigue damage degree of metallic materials with the increase of fatigue cycle number.It provides reference basis for acoustic emission monitoring of steel fatigue process commonly used in bridge structure and construction engineering structural components and aggravation of early fatigue damage degree.
In order to realize the monitoring and evaluation of fatigue damage degree of early material structures,an acoustic emission signal processing method based on wavelet packet energy spectrum is proposed.Firstly,an on-line acoustic emission monitoring system for metal fatigue damage is established to collect acoustic emission signals of crack propagation and closure caused by early structural fatigue damage of metal materials.Secondly,the wavelet function and wavelet packet decomposition layers suitable for the AE signal are selected.Finally,the wavelet packets energy spectrum of each frequency band after wavelet packet decomposition with the increase of fatigue cycle number are obtained.Experimental results show that the above signal processing method can obtain the frequency band characteristics that can characterize the early structural fatigue damage degree of metallic materials with the increase of fatigue cycle number.It provides reference basis for acoustic emission monitoring of steel fatigue process commonly used in bridge structure and construction engineering structural components and aggravation of early fatigue damage degree.
引文
[1]王丙阳,耿荣生,周炳如,等.飞机主起落架疲劳试验中的声发射信号处理[J].无损检测,2012,34(9):2-6.Wang Bingyang,Geng Rongsheng,Zhou Bingru,et al.Processing of acoustic emission signals in the aircraft main landing gear fatigue test[J].Nondestructive Testing,2012,34(9):2-6.(in Chinese)
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[13]操礼林,李爱群,邓扬,等.声发射和小波包分析在损伤状态监测中的应用[J].振动、测试与诊断,2012,32(4):591-595.Cao Lilin,Li Aiqun,Deng Yang,et al.Application of acoustic emission and wavelet packet analysis in damage state monitoring[J].Journal of Vibration Measurement&Diagnosis,2012,32(4):591-595.(in Chinese)
[14]朱宏平,余璟,张俊兵.结构损伤动力检测与健康监测研究现状与展望[C].全国结构工程学术会议.2010:1-11.
[15]沈再阳.精通MATLAB信号处理[M].北京:清华大学出版社,2015.
[16]吴延军.小波包分解及其参数模型[J].应用声学,1998(3):25-29.Wu Yanjun.Wavelet packet decomposition and its parametric model[J].Journal of Applied Acoustics,1998(3):25-29.(in Chinese)
[17]曾祥君,张小丽,马洪江,等.基于小波包能量谱的电网故障行波定位方法[J].高电压技术,2008,34(11):2311-2316.Zeng Xiangjun,Zhang Xiaoli,Ma Hongjiang,et al.Traveling wave fault location method for power grids based on wavelet packet energy spectra[J].High Voltage Engineering,2008,34(11):2311-2316.(in Chinese)
[18]杨明纬.声发射检测[M].北京:机械工业出版社,2005.
[19]李光海,刘正义.基于声发射技术的金属高频疲劳监测[J].中国机械工程,2004,15(13):1205-1209.LI Guanghai,LIU Zhengyi.Inspection of metal high frequency cyclic fatigue behavior utilizing acoustic emission technique[J].China Mechanical Engineering,2004,15(13):1205-1209.(in Chinese)
[20]孙立瑛,李一博,靳世久,等.基于小波包和HHT变换的声发射信号分析方法[J].仪器仪表学报,2008,29(8):1577-1582.Sun Liying,Li Yibo,Jin Shijiu,et al.Acoustic emission signal processing method based on wavelet package and HHT transform[J].Chinese Journal of Scientific Instrument,2008,29(8):1577-1582.(in Chinese)
[2]彭国平,张在东,卢超,等.Q345R钢拉伸损伤过程声发射特征参数表征及定量评价[J].无损检测,2018,40(1):50-54.Peng Guoping,Zhang Zaidong,Lu Chao,et al.Characterization and quantitative evaluation of tensile damage process of Q345R steel with acoustic emission characteristic parameter[J].Nondestructive Testing,2018,40(1):50-54.(in Chinese)
[3]Aggelis D G,Kordatos E Z,Matikas T E.Acoustic emission for fatigue damage characterization in metal plate[J].Mechanics Research Communications,2011,38(2):106-110.
[4]柴孟瑜,段权,张早校.Q345R疲劳裂纹扩展过程的声发射研究[J].工程科学学报,2015,37(12):1588-1593.Chai Mengyu,Duan Quan,Zhang Zaoxiao.Acoustic emission study of fatigue crack propagation in Q345R[J].Chinese Journal of Engineering,2015,37(12):1588-1593.(in Chinese)
[5]Aguiar P R,Serni P J A,Bianchi E C,et al.Inprocess grinding monitoring by acoustic emission[J].2004,5:405-408.
[6]Klyosumphan T,Prateepasen A.Monitoring nugget formation of nickel-alloys in micro spot welding using acoustic emission[J].Key Engineering Materials,2004,270-273:510-517.
[7]Talebzadeh M,Roberts T M.Correlation of crack propagation and acoustic emission rates[J].Key Engineering Materials,2001,204-205(204):341-350.
[8]Beck P,Bradshaw T P,Lark R J,et al.A quantitative study of the relationship between concrete crack parameters and acoustic emission energy released during failure[J].Key Engineering Materials,2003,245:461-466.
[9]Ni Q Q,Iwamoto M.Wavelet transform of acoustic emission signals in failure of model composites[J].Engineering Fracture Mechanics,2002,69(6):717-728.
[10]Liao T W,Ting C F,Qu J,et al.A wavelet-based methodology for grinding wheel condition monitoring[J].International Journal of Machine Tools&Manufacture,2007,47(3-4):580-592.
[11]金鑫,施展.基于小波的声发射信号参数提取方法[J].仪器仪表学报,2006,27(z1):347-348.Jin Xing,Shi Zhan.Research on the selection method of acoustic emission signal based on wavelet[J].Chinese Journal of Scientific Instrument.2006,27(z1):347-348.(in Chinese)
[12]Antonaci P,Bocca P,Masera D.Fatigue crack propagation monitoring by acoustic emission signal analysis[J].Engineering Fracture Mechanics,2012,465:370-373.
[13]操礼林,李爱群,邓扬,等.声发射和小波包分析在损伤状态监测中的应用[J].振动、测试与诊断,2012,32(4):591-595.Cao Lilin,Li Aiqun,Deng Yang,et al.Application of acoustic emission and wavelet packet analysis in damage state monitoring[J].Journal of Vibration Measurement&Diagnosis,2012,32(4):591-595.(in Chinese)
[14]朱宏平,余璟,张俊兵.结构损伤动力检测与健康监测研究现状与展望[C].全国结构工程学术会议.2010:1-11.
[15]沈再阳.精通MATLAB信号处理[M].北京:清华大学出版社,2015.
[16]吴延军.小波包分解及其参数模型[J].应用声学,1998(3):25-29.Wu Yanjun.Wavelet packet decomposition and its parametric model[J].Journal of Applied Acoustics,1998(3):25-29.(in Chinese)
[17]曾祥君,张小丽,马洪江,等.基于小波包能量谱的电网故障行波定位方法[J].高电压技术,2008,34(11):2311-2316.Zeng Xiangjun,Zhang Xiaoli,Ma Hongjiang,et al.Traveling wave fault location method for power grids based on wavelet packet energy spectra[J].High Voltage Engineering,2008,34(11):2311-2316.(in Chinese)
[18]杨明纬.声发射检测[M].北京:机械工业出版社,2005.
[19]李光海,刘正义.基于声发射技术的金属高频疲劳监测[J].中国机械工程,2004,15(13):1205-1209.LI Guanghai,LIU Zhengyi.Inspection of metal high frequency cyclic fatigue behavior utilizing acoustic emission technique[J].China Mechanical Engineering,2004,15(13):1205-1209.(in Chinese)
[20]孙立瑛,李一博,靳世久,等.基于小波包和HHT变换的声发射信号分析方法[J].仪器仪表学报,2008,29(8):1577-1582.Sun Liying,Li Yibo,Jin Shijiu,et al.Acoustic emission signal processing method based on wavelet package and HHT transform[J].Chinese Journal of Scientific Instrument,2008,29(8):1577-1582.(in Chinese)
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