刀具磨损声发射信号小波分析中小波基的选取
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摘要
针对在用小波理论分析刀具磨损声发射(AE)信号时选取不同的小波基对分析结果有重要影响的问题,通过对小波基性质和刀具磨损AE信号特点的研究,从理论上分析了小波分析中刀具磨损AE信号处理中小波基选取的方法。在试验验证过程中,根据信号在小波包分解前后遵循能量守恒的原理,用四种小波基对刀具磨损AE信号进行三层小波包分解。以经小波包分解后AE信号各频带上的频带能量为特征参数,比较四种情况下特征参数的变化,验证了理论分析的正确性。
In order to solve the problem that different wavelet bases have an important impact on the results when the wavelet theory is used to analyze the tool wear acoustic emission(AE) signal,the suitable wavelet basis selection in wavelet analysis from the cutting tool wear acoustic emission(AE) signals was theoretically analyzed through researching the properties of wavelet basis and the features of cutting tool wear AE signal.In the process of experimental verification,the cutting tool wear AE signal was decomposed into 3 level wavelet packets with four different wavelet bases according to the theory of signal energy conservation.When the signal energy in frequency band was taken as characteristic parameter,the theoretical analysis accuracy was confirmed after comparing the contrast of characteristic parameter in these four situations.
In order to solve the problem that different wavelet bases have an important impact on the results when the wavelet theory is used to analyze the tool wear acoustic emission(AE) signal,the suitable wavelet basis selection in wavelet analysis from the cutting tool wear acoustic emission(AE) signals was theoretically analyzed through researching the properties of wavelet basis and the features of cutting tool wear AE signal.In the process of experimental verification,the cutting tool wear AE signal was decomposed into 3 level wavelet packets with four different wavelet bases according to the theory of signal energy conservation.When the signal energy in frequency band was taken as characteristic parameter,the theoretical analysis accuracy was confirmed after comparing the contrast of characteristic parameter in these four situations.
引文
[1]王信义,徐春广,等.自动化加工中刀具破损实时监测方法研究[J].北京理工大学学报,1995,15(3):294-298.
[2]刘泽华,谷立臣.基于频域能量特征的故障分类方法研究[J].液压与气动,2007(3):67-70.
[3]Qing N,Misada Y.Analysis of AE signals by wavelettrans form[J].Journal of Society Material Science,1998,47(3):305-311.
[4]赵冬梅,朱目成,江涌,等.小波理论及其在AE信号处理中应用现状[J].传感器世界,2006(3):11-15.
[5]《国防科技工业无损检测人员资格鉴定与认证培训教材》编审委员会.声发射检测[M].北京:机械工业出版社,2005.
[6]陈新全,李西南,邓敏.金属切削过程中的声发射现象及其研究的意义[J].长沙电力学院学报,2001,16(1):75-76.
[7]陈志奎.工程信号处理中的小波基和小波变换分析仪系统的研究[D].重庆大学测试中心,1998:24-27.
[8]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(6):347-348.
[9]李宏男,孙鸿敏.基于小波分析和神经网络的框架结构损伤诊断方法[J].地震工程与工程振动,2003,23(5):141-148.
[10]飞思科技产品研发中心.MATLAB6.5辅助小波分析与应用[M].北京:电子工业出版社,2003.
[11]孟永鹏,贾申利,荣命哲.小波包频带能量分解在断路器机械状态监测中的应用[J].西安交通大学学报,2004,38(10):1014-1017.
[2]刘泽华,谷立臣.基于频域能量特征的故障分类方法研究[J].液压与气动,2007(3):67-70.
[3]Qing N,Misada Y.Analysis of AE signals by wavelettrans form[J].Journal of Society Material Science,1998,47(3):305-311.
[4]赵冬梅,朱目成,江涌,等.小波理论及其在AE信号处理中应用现状[J].传感器世界,2006(3):11-15.
[5]《国防科技工业无损检测人员资格鉴定与认证培训教材》编审委员会.声发射检测[M].北京:机械工业出版社,2005.
[6]陈新全,李西南,邓敏.金属切削过程中的声发射现象及其研究的意义[J].长沙电力学院学报,2001,16(1):75-76.
[7]陈志奎.工程信号处理中的小波基和小波变换分析仪系统的研究[D].重庆大学测试中心,1998:24-27.
[8]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(6):347-348.
[9]李宏男,孙鸿敏.基于小波分析和神经网络的框架结构损伤诊断方法[J].地震工程与工程振动,2003,23(5):141-148.
[10]飞思科技产品研发中心.MATLAB6.5辅助小波分析与应用[M].北京:电子工业出版社,2003.
[11]孟永鹏,贾申利,荣命哲.小波包频带能量分解在断路器机械状态监测中的应用[J].西安交通大学学报,2004,38(10):1014-1017.
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