To address the problem that traditional sample entropy cannot distinguish the planetary gearbox’s working condition as its weak fault feature and complex signal transmission path, a feature extraction method combining variational mode decomposition (VMD) and sample entropy was proposed.We have studied optimization strategies of VMD decomposition scale and secondary penalty factors, determined the threshold of correlation coefficient between IMF and the original signal on maximum sensitivity principle, collected vibration signals under various operating conditions in a planetary gearbox fault simulation experiment table, and considered the planetary gear cycle problem to obtain available data.The results show that, compared to sample entropy and EEMD sample entropy, VMD sample entropy has characteristics of high computational efficiency and a strong ability to distinguish between various conditions, and sampling frequency has little effect on results.This information can be used in planetary gearbox fault diagnosis.
[1] 雷亚国,何正嘉,林京,等. 行星齿轮箱故障诊断技术的研究进展[J]. 机械工程学报,2011,47(19):59-67.
LEI Yaguo,HE Zhengjia,LIN Jing,et al. Research Advances of Fault Diagnosis Technique for Planetary Gearboxes [J]. Journal of Mechanical Engineering,2011,47(19):59-67.
[2] Konstantin Dragomiretskiy,Dominique Zosso.Variational Mode Decomposition[J].IEEE Transactionson Signal Processing, 2014,62(3):531-544.
[3] 钱林,康敏,傅秀清,等. 基于VMD的自适应形态学在轴承故障诊断中的应用[J]. 振动与冲击,2017,36(03):227-233.
QIAN Lin,KANG Min,FU Xiuqing,et al.Application of adaptivemorphology in bearing fault diagnosis based on VMD
[J].Journal of vibration and shock,2017,36(03):227-233.
[4] 吕勇,李友荣,肖涵,等. 基于加权相空间重构降噪及样本熵的齿轮故障分类[J]. 振动工程学报,2009,22(05):462-466.
Lu Yong,Li You-rong,Xiao Han,et al.Gear fault classification based on weighted phase space reconstruction and sample entropy[J].Journal of Vibration Engineering,2009,22(05): 462-466.
[5] Cheng G, Chen X, Li H, et al. Study on Planetary Gear Fault Diagnosis Based on Entropy Feature Fusion of Ensemble Empirical Mode Decomposition[J].Measurement,2016, 91(15):140-154.
[6] 赵磊,夏均忠,李泽华,等. 基于VMD样本熵和LS-SVM的滚动轴承故障诊断[J]. 军事交通学院学报,2017,19(04):43-47.
ZHAO Lei,XIA Junzhong,LI Zehua,et al.Fault Diagnosis of rolling Bearing Based on VMD Sample Entropy and LS-SVM[J]. Journal of Military Transportation University,2017,19(04):43-47. [7] Richman J S，Moorman J R． Physiological time series analysis using approximate entropy and sample entropy[J].Am J Physio Heart Physio,2000,278(3): 2039－2049．
[8] 赵志宏,杨绍普. 一种基于样本熵的轴承故障诊断方法[J]. 振动与冲击,2012,31(06):136-140+154.
ZHAO Zhi-hong,YANG Shao-pu. Sample entropy-based roller bearing fault diagnosis method[J]. Journal of vibration and shock,2012,31(06): 136-140+154.
[9] 雷亚国,汤伟,孔德同,等. 基于传动机理分析的行星齿轮箱振动信号仿真及其故障诊断[J]. 机械工程学报，2014,50 (17):61-68.
LEI Yaguo,TANG Wei,KONG Detong,et al. Vibration Signal Simulation and Fault Diagnosis of Planetary Gearboxes Based on Transmission Mechanism Analysis [J]. Journal of Mechanical Engineering,2014,50(17):61-68.
[10] WU Chunyan，LIU Jian，PENG Fuqiang，et al. Gearbox fault diagnosis using adaptive zero phase time-varying filter based on multi-scale chirplet sparse signal decomposition[J]. Chinese Journal of Mechanical Engineering，2013，26(4)：831-838.
[11] 唐贵基,王晓龙. 参数优化变分模态分解方法在滚动轴承早期故障诊断中的应用[J]. 西安交通大学学报,2015,49(05): 73-81.
TANG Guiji,WANG Xiaolong.Parameter optimized variational mode decomposition method with application to incipient fault diagnosis of rolling bearing[J]. Journal of xi’an jiaotong University,2015,49(05):73-81.
[12] 王振威. 基于变分模态分解的故障诊断方法研究[D].燕山大学,2015.
Zhenwei Wang.Research on fault diagnosis method based on variational mode decomposition[D].Yanshan University,2015.
[13] Wang X,Zi Y,He Z.Multiwavelet denoising with improved neighboring coefficients for application on rolling bearing fault diagnosis[J]. Mechanical Systems and Signal Processing, 2011, 25(1): 285-304.
[14] 唐贵基,王晓龙.基于EEMD降噪和1.5维能量谱的滚动轴承故障诊断研究[J].振动与冲击，2014，33( 1) : 6 －10．
TANG Guiji，WANG Xiaolong．Fault diagnosis for roller bearings based on EEMD denoising and 15-dimensional energy spectrum［J］.Journal of Vibration and Shock，2014，
33( 1) : 6－10．
[15] FLANDRIN P，GABRIEL R，PAULO G. Empirical mode decomposition as a filter bank[J]. IEEE Signal Processing Letter，2004，11：112-114.
[16] WU Z H，HUANG N E. Ensemble empirical mode decomposition：A noise assisted data analysis method[J].Advances in Adaptive Data Analysis，2009，1：1-41.
[17] 周智,朱永生,张优云,等. 基于EEMD 和共振解调的滚动轴承自适应故障诊断[J]. 振动与冲击，2013，32(2)：76-80.
ZHOU Zhi，ZHU Yongsheng，ZHANG Youyun，et al.Adaptive fault diagnosis of rolling bearings based on EEMD and demodulated resonance[J]. Journal of Vibration and Shock，2013，32(2)：76-80.
