Teager能量算子结合MCKD的滚动轴承早期故障识别

PDF(1900 KB)

振动与冲击 ›› 2016, Vol. 35 ›› Issue (15) : 98-102.

论文

刘尚坤，唐贵基，何玉灵

作者信息 +

Incipient fault diagnosis of rolling bearing based on Teager energy operator and maximum correlated kurtosis deconvolution

LIU Shang-kun，TANG Gui-ji，HE Yu-ling

Author information +

文章历史 +

摘要

针对Teager能量算子在解调滚动轴承早期微弱故障特征中的不足，提出一种最大相关峭度解卷积降噪与Teager能量算子解调相结合的滚动轴承早期故障识别方法。首先采用最大相关峭度解卷积算法以包络谱的峭度最大化为目标对原信号进行降噪处理、检测信号中的周期性冲击成分，然后利用Teager能量算子增强降噪信号中的周期性冲击特征、抑制非冲击成分，最后通过分析Teager能量谱中明显的频率成分来诊断故障类型。滚动轴承外圈、内圈故障诊断实例表明，该方法能有效实现滚动轴承早期微弱故障的识别。

Abstract

Because of Teager energy operator’s insufficient in demodulating rolling bearing’s incipient weak fault feature. A diagnosis method combined maximum correlated kurtosis deconvolution(MCKD) and Teager energy operator was proposed. First, the original signal was de-nosed by MCKD arithmetic with the goal of the max kurtosis of its envelope spectrum to detect the periodic impact component. Then the periodic impact component was enhanced and the non impact component was inhibited by using Teager energy operator. At last, the fault type was diagnosed by analyzing the obvious frequency component in the Teager energy spectrum. Analysis results of the rolling bearing’s outer fault and inner fault test signals proved this method could identify the incipient weak fault of rolling bearing effectively.

导出引用

刘尚坤，唐贵基，何玉灵. Teager能量算子结合MCKD的滚动轴承早期故障识别[J]. 振动与冲击, 2016, 35(15): 98-102

LIU Shang-kun, TANG Gui-ji，HE Yu-ling. Incipient fault diagnosis of rolling bearing based on Teager energy operator and maximum correlated kurtosis deconvolution[J]. Journal of Vibration and Shock, 2016, 35(15): 98-102

参考文献

[1] 雷亚国，韩冬，林京，等．自适应随机共振新方法及其在故障诊断过中的应用[J]．机械工程学报，2012，48(7)：62-67．
Lei Yaguo，Han Dong，Lin Jing，et al．New adaptive stochastic resonance method and its application to fault diagnosis[J]．Journal of Mechanical Engineering，2012，48(7)：62-67．
[2] Cheng J，Yu D，Yang Y．The application of energy operator demodulation approach based on EMD in machinery fault diagnosis[J]．Mechanical Systems and Signal Processing，2007，21( 2)：668-677．
[3] 王天金，冯志鹏，郝如江，褚福磊．基于Teager能量算子的滚动轴承故障诊断研究[J]．振动与冲击，2012，31(2)：1-5，85．
Wang Tianjin，Feng Zhipeng，Hao Rujiang，Chu Fulei．Fault diagnosis of rolling element bearings based on teager energy operator[J]．Journal of Vibration and Shock，2012，31(2)：1-5，85．
[4] 张文义，于德介，陈向民．基于信号共振稀疏分解与能量算子解调的轴承故障诊断方法[J]．中国电机工程学报，2013，33(20)：111-118．
Zhang Wenyi，YU Dejie，Chen Xiangmin．Fault diagnosis of rollingbearings based on resonance-based sparse signal decomposition and energy operator demodulating [J]．Proceedings of the CSEE，2013，33(20)：111-118．
[5] 杨青乐，梅检民，肖静，等．Teager能量算子增强倒阶次谱提取轴承微弱故障特征[J]．振动与冲击，2015，34(6)：1-5．
Yang Qingle，Mei Jianmin，Xiao Jing，et al．Weak fault feature extraction for bearing based on order cepstrum enhanced by teager energy operator[J]．Journal of Vibration and Shock，2015，34(6)：1-5．
[6] Marago s P，Kaiser J F，Quatieri T F．Energy separation in signal modulations with applications to speech analysis [J] ．IEEE Transactions on Signal Processing，1993，41(10)：3024-3051．
[7] 程军圣，杨怡，杨宇．基于LMD的能量算子解调机械故障诊断方法[J]．振动、测试与诊断，2012，32(6)：915-919，1033．
Cheng Junsheng，Yang Yi，Yang Yu．Mechanical fault diagnosis of energy operator demodulating approach based on LMD[J]．Journal of Vibration，Measurement & Diagnosis，2012，32(6)：915-919，1033．
[8] 鞠萍华，秦树人，赵玲．基于LMD的能量算子解调方法及其在故障特征信号提取中的应用[J]．振动与冲击，2011，30(2)：1-4．
Ju Pinghua，Qin Shuren，Zhao lin．Energy operator demodulating approach based on LMD and its application in extracting the fault characteristics of signal[J]．Journal of Vibration and Shock，2011，30(2)： 1-4．
[9] Mcdonald G L，Zhao Q，Zuo M J．Maximum correlated kurtosis deconvolution and application on gear tooth chip fault detection[J]．Mechanical Systems and Signal Processing，2012，33：237-255．
[10] 武兵，贾峰，熊晓燕．基于最大相关峭度反褶积的轴承故障诊断方法[J]．振动、测试与诊断，2014，34(3)：570-575，579．
Wu Bing，Jia Feng，Xiong Xiaoyan．Bearing fault diagnosis based on maximum correlated kurtosis deconvolution [J]．Journal of Vibration，Measurement & Diagnosis，2014，34(3)：570-575，579．
[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] Qiu H，Lee J，Lin J，et al．Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics[J]．Journal of Sound and Vibration，2006，289(4-5)：1066-1090．