基于迭代滤波和快速峭度图的滚动轴承微弱故障特征提取
|
摘要
在强背景噪声干扰下,快速峭度图提取滚动轴承微弱信号故障的特征效果并不明显。将迭代滤波(Iterative Filtering,IF)和快速峭度图相结合用于滚动轴承的微弱故障特征提取。滚动轴承故障振动信号通过迭代滤波进行自适应分解得到一组内禀模态分量,用迭代滤波对强噪声滚动轴承信号进行降噪处理,用快速峭度图构造最优带通滤波器,将滤波后信号的包络谱与轴承故障特征频率进行比较,从而诊断出具体故障。通过仿真和试验验证了所述方法的有效性及优点。
The effect of fast kurtogram to extract rolling bearings ' weak fault signals is not obvious under interference of strong background noise. Here,rolling bearings' weak fault feature extraction was conducted with the combination of iterative filtering and fast kurtogram. The faulty bearing's vibration signals were adaptively decomposed into a group of intrinsic mode components with iterative filtering. The iterative filtering method was used to denoise rolling bearing's vibration signals with strong noise. An optimal band-pass filter was constructed using the fast kurtogram.Finally,the envelope spectra of the filtered signals were compared with fault feature frequencies of rolling bearings to judge the diagnosed bearing's fault types. The effectiveness and advantages of the proposed method were verified with numerical simulation and tests.
The effect of fast kurtogram to extract rolling bearings ' weak fault signals is not obvious under interference of strong background noise. Here,rolling bearings' weak fault feature extraction was conducted with the combination of iterative filtering and fast kurtogram. The faulty bearing's vibration signals were adaptively decomposed into a group of intrinsic mode components with iterative filtering. The iterative filtering method was used to denoise rolling bearing's vibration signals with strong noise. An optimal band-pass filter was constructed using the fast kurtogram.Finally,the envelope spectra of the filtered signals were compared with fault feature frequencies of rolling bearings to judge the diagnosed bearing's fault types. The effectiveness and advantages of the proposed method were verified with numerical simulation and tests.
引文
[1]HUANG N E,SHEN Z,LONG S R.The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis[J].Proceedings of the Royal Society of London Series,1998,454(1971):903-995.
[2]CHENG Junsheng,YU Dejie,YANG Yu.Application of SVM and SVD technique based on EMD to the fault diagnosis of the rotating machinery[J].Shock and Vibration,2009,16(1):89-98.
[3]汤宝平,蒋永华,张详春.基于形态奇异值分解和经验模态分解的滚动轴承故障特征提取方法[J].机械工程学报,2010,46(5):37-42.TANG Baoping,JIANG Yonghua,ZHANG Xiangchun.Feature extraction method of rolling bearing fault based on singular value decomposition-morphology filter and empirical mode decomposition transform[J].Journal of Mechanical Engineering,2010,46(5):37-42.
[4]唐海英,栾军英,郑海起,等.基于阶次跟踪和经验模态分解的滚动轴承包络解调分析[J].机械工程学报,2007,43(8):119-122.TANG Haiying,LUAN Junying,ZHENG Haiqi,et al.Envelope demodulation analysis of bearing based on order tracking and empirical mode decomposition[J].Journal of Mechanical Engineering,2007,43(8):119-122.
[5]CHENG Junsheng,YU Dejie,YANG Yu.Energy operator demodulating approach based on EMD and its application in mechanical fault diagnosis[J].Chinese Journal of Mechanical Engineering,2004,40(8):115-118.
[6]LI Hui,ZHANG Yuping,ZHENG Haiqi.Hilbert-Huang transform and marginal spectrum for detection and diagnosis of localized defects in roller bearings[J].Journal of Mechanical Science and Technology,2009,23(2):291-30.
[7]唐先广,郭瑜,丁彦春.基于独立分量分析与希尔伯特-黄变换的轴承故障特征提取[J].振动与冲击,2011,30(10):45-49.TANG Xianguang,GUO Yu,DING Yanchun.Application of hilbert huang transition and independent components analysis on rolling element bearing faults features extraction[J].Journal of Vibration and Shock,2011,30(10):45-49.
[8]苏文胜,王奉涛,张志新.EMD降噪和谱峭度方法在滚动轴承早期故障诊断中的应用[J].振动与冲击,2010,29(3):18-21.SU Wensheng,WANG Fengtao,ZHANG Zhixin,et al.Application of EMD denoising and spectral kurtosis in early fault diagnosis of rolling element bearings[J].Journal of Vibration and Shock,2010,29(3):18-21.
[9]高强,杜小山,范虹,等.滚动轴承故障的EMD诊断方法研究[J].振动工程学报,2007,20(1):15-18.GAO Qiang,DU Xiaoshan,FAN Hong,et al.An empirical mode decomposition based method for rolling bearing fault diagnosis[J].Journal of Vibration Engineering,2007,20(1):15-18.
[10]陈略,訾艳阳,何正嘉,等.总体平均经验模式分解与1.5维谱方法的研究[J].西安交通大学学报,2009,43(5):94-98.CHEN Lue,ZI Yanyang,HE Zhengjia,et al.Research and application of ensemble empirical mode decomposition principle and 1.5 dimension spectrum method[J].Journal of Xi’an Jiaotong University,2009,43(5):94-98.
[11]胡爱军,马万里,唐贵基.基于集成经验模态分解和峭度准则的滚动轴承故障特征提取方法[J].中国电机工程学报,2012,32(11):106-111.HU Aijun,MA Wanli,TANG Guiji.Rolling bearing fault feature extraction method based on ensemble empirical mode decomposition and kurtosis criterion[J].Proceedings of the CSEE,2012,32(11):106-111.
[12]蔡艳平,李艾华,石林锁,等.EMD端点效应的改进型混沌延拓方法及其在机械故障诊断中的应用[J].振动与冲击,2011,30(11):46-52.CAI Yanping,LI Aihua,SHI Linsuo,et al.Processing method for end effects of EMD based on improved chaos forecasting model and its application in machinery fault diagnosis[J].Journal of Vibration and Shock,2011,30(11):46-52.
[13]曹冲锋,杨世锡,杨将新.一种抑制EMD端点效应新方法及其在信号特征提取中的应用[J].振动工程学报,2008,21(6):589-593.CAO Chongfeng,YANG Shixi,YANG Jiangxin.A new method for restraining the end effect of empirical mode decomposition and its applications to signal feature extraction[J].Journal of Vibration Engineering,2008,21(6):589-593.
[14]ANTONI J,RANDALL R B.The spectral kurtosis:application to the vibratory surveillance and diagnostics of rotating machines[J].Mechanical Systems and Signal Processing,2006,20(2):308-331.
[15]LIN L,WANG Y,ZHOU H.Iterative filtering as an alternative algorithm for empirical mode decomposition[J].Advances in Adaptive Data Analysis,2011,1(4):543-560.
[16]MC FADDEN P D,SMITH J D.Model for the vibration produced by a single point defect in a rolling element bearing[J].Journal of Sound and Vibration,1984,96(1):69-82.
[2]CHENG Junsheng,YU Dejie,YANG Yu.Application of SVM and SVD technique based on EMD to the fault diagnosis of the rotating machinery[J].Shock and Vibration,2009,16(1):89-98.
[3]汤宝平,蒋永华,张详春.基于形态奇异值分解和经验模态分解的滚动轴承故障特征提取方法[J].机械工程学报,2010,46(5):37-42.TANG Baoping,JIANG Yonghua,ZHANG Xiangchun.Feature extraction method of rolling bearing fault based on singular value decomposition-morphology filter and empirical mode decomposition transform[J].Journal of Mechanical Engineering,2010,46(5):37-42.
[4]唐海英,栾军英,郑海起,等.基于阶次跟踪和经验模态分解的滚动轴承包络解调分析[J].机械工程学报,2007,43(8):119-122.TANG Haiying,LUAN Junying,ZHENG Haiqi,et al.Envelope demodulation analysis of bearing based on order tracking and empirical mode decomposition[J].Journal of Mechanical Engineering,2007,43(8):119-122.
[5]CHENG Junsheng,YU Dejie,YANG Yu.Energy operator demodulating approach based on EMD and its application in mechanical fault diagnosis[J].Chinese Journal of Mechanical Engineering,2004,40(8):115-118.
[6]LI Hui,ZHANG Yuping,ZHENG Haiqi.Hilbert-Huang transform and marginal spectrum for detection and diagnosis of localized defects in roller bearings[J].Journal of Mechanical Science and Technology,2009,23(2):291-30.
[7]唐先广,郭瑜,丁彦春.基于独立分量分析与希尔伯特-黄变换的轴承故障特征提取[J].振动与冲击,2011,30(10):45-49.TANG Xianguang,GUO Yu,DING Yanchun.Application of hilbert huang transition and independent components analysis on rolling element bearing faults features extraction[J].Journal of Vibration and Shock,2011,30(10):45-49.
[8]苏文胜,王奉涛,张志新.EMD降噪和谱峭度方法在滚动轴承早期故障诊断中的应用[J].振动与冲击,2010,29(3):18-21.SU Wensheng,WANG Fengtao,ZHANG Zhixin,et al.Application of EMD denoising and spectral kurtosis in early fault diagnosis of rolling element bearings[J].Journal of Vibration and Shock,2010,29(3):18-21.
[9]高强,杜小山,范虹,等.滚动轴承故障的EMD诊断方法研究[J].振动工程学报,2007,20(1):15-18.GAO Qiang,DU Xiaoshan,FAN Hong,et al.An empirical mode decomposition based method for rolling bearing fault diagnosis[J].Journal of Vibration Engineering,2007,20(1):15-18.
[10]陈略,訾艳阳,何正嘉,等.总体平均经验模式分解与1.5维谱方法的研究[J].西安交通大学学报,2009,43(5):94-98.CHEN Lue,ZI Yanyang,HE Zhengjia,et al.Research and application of ensemble empirical mode decomposition principle and 1.5 dimension spectrum method[J].Journal of Xi’an Jiaotong University,2009,43(5):94-98.
[11]胡爱军,马万里,唐贵基.基于集成经验模态分解和峭度准则的滚动轴承故障特征提取方法[J].中国电机工程学报,2012,32(11):106-111.HU Aijun,MA Wanli,TANG Guiji.Rolling bearing fault feature extraction method based on ensemble empirical mode decomposition and kurtosis criterion[J].Proceedings of the CSEE,2012,32(11):106-111.
[12]蔡艳平,李艾华,石林锁,等.EMD端点效应的改进型混沌延拓方法及其在机械故障诊断中的应用[J].振动与冲击,2011,30(11):46-52.CAI Yanping,LI Aihua,SHI Linsuo,et al.Processing method for end effects of EMD based on improved chaos forecasting model and its application in machinery fault diagnosis[J].Journal of Vibration and Shock,2011,30(11):46-52.
[13]曹冲锋,杨世锡,杨将新.一种抑制EMD端点效应新方法及其在信号特征提取中的应用[J].振动工程学报,2008,21(6):589-593.CAO Chongfeng,YANG Shixi,YANG Jiangxin.A new method for restraining the end effect of empirical mode decomposition and its applications to signal feature extraction[J].Journal of Vibration Engineering,2008,21(6):589-593.
[14]ANTONI J,RANDALL R B.The spectral kurtosis:application to the vibratory surveillance and diagnostics of rotating machines[J].Mechanical Systems and Signal Processing,2006,20(2):308-331.
[15]LIN L,WANG Y,ZHOU H.Iterative filtering as an alternative algorithm for empirical mode decomposition[J].Advances in Adaptive Data Analysis,2011,1(4):543-560.
[16]MC FADDEN P D,SMITH J D.Model for the vibration produced by a single point defect in a rolling element bearing[J].Journal of Sound and Vibration,1984,96(1):69-82.