Adaptive UPEMD-MCKD rolling bearing fault feature extraction method
SONG Yubo1, LIU Yunhang1, ZHU Dapeng2
1.Institute of Mechanical and Electrical Technology, Lanzhou Jiaotong University, Lanzhou 730070, China;
2.School of Communications and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China
Abstract:at the difficulty of extracting weak fault signals of bearings under strong noise background, combined with the advantages of Uniform Phase Empirical Mode Decomposition and Maximum Correlated Kurtosis Deconvolution method, an adaptive UPEMD-MCKD bearing fault feature extraction method was proposed.The minimum entropy kurtosis ratio was constructed by combining sample entropy and kurtosis index, and the minimum entropy kurtosis ratio was searched by genetic algorithm to obtain the optimal parameter combination of shift number, filter length and period.The noise signals preprocessed by Uniform Phase Empirical Mode Decomposition method were screened out by correlation calculation for signal reconstruction, and fault features were extracted from reconstructed signals by MCKD algorithm under optimal parameter combination.The analysis of inner and outer ring faults shows that the proposed method can effectively extract weak fault features from fault signals by virtue of UPEMD's noise suppression ability and minimum entropy ratio parameter combination optimization evaluation ability.
[1] 刘湘楠,赵学智,上官文斌. 强背景噪声振动信号中滚动轴承故障冲击特征提取[J]. 振动工程学报, 2021, 34(01): 202-210.
LIU Xiang-nan, ZHAO Xue-zhi, SHANGGUAN Wen-bin. The impact features extraction of rolling bearing under strong background noise [J]. Journal of Vibration Engineering, 2021, 34(01): 202-210.
[2] 唐贵基,蔡 伟. 应用小波包和包络分析的滚动轴承故障诊断[J]. 振动、测试与诊断, 2009, 29(02): 201-204+244.
TANG Gui-ji, CAI Wei. Rolling bearings fault diagnosis by using wavelet packet and envelope analysis [J]. Journal of Vibration, Measurement and Diagnosis, 2009, 29(02): 201-204+244.
[3] 陈志新,徐金梧,杨德斌. 基于复小波块阈值的降噪方法及其在机械故障诊断中的应用[J]. 机械工程学报, 2007(06): 200-204.
CHEN Zhi-xin, XU Jin-wu, YANG De-bin, Denoising method of block thresholding based on DT-CWT and its application in mechanical fault diagnosis [J]. Journal of Mechanical Engineering, 2007(06): 200-204.
[4] Wu Z H, Huang N E. Ensemble empirical mode decomposition: a noise assisted data analysis method [J]. Advances in Adaptive Data Analysis, 2009, 1(1): 1-41.
[5] Ryan D, Kaiser J F. The use of a masking signal toimprove empirical mode decomposition [C]// Interna-tional Conference on Acoustic, Speech and Signal Pro-cessing 2005 IEEE. MA, USA: MIT Press, 2005: 485-488.
[6] 李 华,刘 韬,伍 星,等. EEMD和优化的频带熵应用于轴承故障特征提取[J]. 振动工程学报, 2020, 33(02): 414-423.
LI Hua, LIU Tao, WU Xing,et al. EEMD and optimized frequency band entropy for fault feature extraction of bearings [J]. Journal of Vibration Engineering, 2020, 33(02): 414-423.
[7] 王 威,陈熙源. 基于改进掩膜EMD的光纤陀螺振动信号处理方法[J]. 东南大学学报(自然科学版), 2018, 48(06): 1123-1129.
WANG Wei, CHEN Xi-yuan. Vibration signal processing method of FOG based on improved EMD with masking signal [J]. Journal of Southeast University (Natural Science Edition), 2018, 48(06): 1123-1129.
[8] Wang Y H, Hu K, Lo M. Uniform phase empirical mode decomposition: An optimal hybridization of masking signal and ensemble approaches [J]. IEEE Access, 2018, 06: 34819-34833.
[9] WIGGINS R A. Minimum entropy deconvolution [J]. Geophysical Prospecting for Petrole, 1980, 16(1): 21-35.
[10] 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.
[11] 王新刚,王 超,韩凯忠. 基于优化VMD和MCKD的滚动轴承早期故障诊断方法[J]. 东北大学学报(自然科学版), 2021, 42(03): 373-380+388.
WANG Xin-gang, WANG Chao, HAN Kai-zhong. Early fault diagnosis method of rolling bearings based on optimization of VMD and MCKD [J]. Journal of Northeastern University (Natural Science), 2021, 42(03): 373-380+388.
[12] 祝小彦,王永杰. 基于自相关分析与MCKD的滚动轴承早期故障诊断[J]. 振动与冲击, 2019, 38(24): 183-188.
ZHU Xiao-yan, WANG Yong-jie. A method of incipient fault diagnosis of bearings based on autocorrelation analysis and MCKD [J]. Journal of Vibration and Shock, 2019, 38(24): 183-188.
[13] 张 俊,张建群,钟 敏,等. 基于PSO-VMD-MCKD方法的风机轴承微弱故障诊断[J]. 振动、测试与诊断, 2020, 40(02): 287-296+418.
ZHANG Jun, ZHANG Jian-qun, ZHONG Min,et al. PSO-VMD-MCKD based fault diagnosis for incipient damage in wind turbine rolling bearing [J]. Journal of Vibration, Measurement and Diagnosis, 2020, 40(02): 287-296+418.
[14] 杨 斌,张家玮,樊改荣,等. 最优参数MCKD与ELMD在轴承复合故障诊断中的应用研究[J]. 振动与冲击, 2019, 38(11): 59-67.
YANG Bin, ZHANG Jia-wei, FAN Gai-rong,et al. Application of MCKD and ELMD in bearing compound fault diagnosis [J]. Journal of Vibration and Shock, 2019, 38(11): 59-67.
[15] Richman J S, Moorman J R. Physiological time-series analysis using approximate entropy and sample entropy [J]. American journal of physiology. Heart and circulatory physiology, 2000, 278(6): 2039-2049.
[16] 胡爱军,赵 军,孙尚飞,等. 基于相关峭度共振解调的滚动轴承复合故障特征分离方法[J]. 振动与冲击, 2019, 38(08): 110-116.
HU Ai-jun, ZHAO Jun, SUN Shang-fei,et al. A composite fault feature separation method of rolling bearing based on correlation kurtosis resonance demodulation [J]. Journal of Vibration and Shock, 2019, 38(08): 110-116.
[17] 何大阔,王福利,贾明兴. 遗传算法初始种群与操作参数的均匀设计[J]. 东北大学学报, 2005(09): 828-831.
He Da-kuo, WANG Fu-li, JIA Ming-xing. Uniform design of initial population and operational parameters for genetic algorithm [J]. Journal of Northeastern University (Natural Science), 2005(09): 828-831.
[18] 吕中亮,汤宝平,周 忆,等. 基于网格搜索法优化最大相关峭度反卷积的滚动轴承早期故障诊断方法[J]. 振动与冲击, 2016, 35(15): 29-34.
LU Zhong-liang, TANG Bao-ping, ZHOU Yi.et al. Rolling bearing early fault diagnosis based on maximum correlated kurtosis deconvolution optimized with grid search algorithm [J]. Journal of Vibration and Shock, 2016, 35(15): 29-34.