1.河南科技大学 机电工程学院, 河南 洛阳 471003
2.河南科技大学 机械装备先进制造河南省协同创新中心, 河南 洛阳 471003
3.郑州轻工业大学 机电工程学院 河南省机械装备智能制造重点实验室, 河南 郑州 450002
程立(1990— ),男,河南固始人,博士研究生;研究方向为滚动轴承可靠性分析。
马文锁(1969— ),男,山西阳城人,博士,教授,博士生导师;研究方向为轴承性能与复合材料。
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程立,马文锁,夏新涛等.基于改进模糊熵和灰关系的滚动轴承性能退化评估[J].机械传动,2022,46(01):56-64.
Cheng Li,Ma Wensuo,Xia Xintao,et al.Performance Degradation Evaluation of Rolling Bearing based on Improved Fuzzy Entropy and Grey Relation[J].Journal of Mechanical Transmission,2022,46(01):56-64.
程立,马文锁,夏新涛等.基于改进模糊熵和灰关系的滚动轴承性能退化评估[J].机械传动,2022,46(01):56-64. DOI: 10.16578/j.issn.1004.2539.2022.01.007.
Cheng Li,Ma Wensuo,Xia Xintao,et al.Performance Degradation Evaluation of Rolling Bearing based on Improved Fuzzy Entropy and Grey Relation[J].Journal of Mechanical Transmission,2022,46(01):56-64. DOI: 10.16578/j.issn.1004.2539.2022.01.007.
针对模糊熵在提取滚动轴承性能退化特征时敏感度较低的问题,提出了一种基于类Sigmoid函数的改进模糊熵,并将其用于滚动轴承退化特征提取。针对传统的滚动轴承性能退化评估方法局部化的问题,提出了一种基于灰关系的滚动轴承性能退化评估方法,该方法使用灰关系理论评估提取的滚动轴承退化特征与可靠性之间的关系,从而达到从滚动轴承可靠性演变规律的整体角度评估滚动轴承退化特征的目的。实验结果表明,改进模糊熵可以精准地提取出滚动轴承的性能退化特征,并且基于改进模糊熵提取的滚动轴承退化特征与滚动轴承的保持可靠度具有一致的演变规律,可信水平均达到95%以上。
In light of low sensitivity of fuzzy entropy in extracting degraded features of rolling bearing,an improved fuzzy entropy based on the sigmoid-like function is proposed. Aiming at the localization issues of assessment methods for traditional rolling bearing performance degradation,a novel performance degradation evaluation method based on grey relation is proposed. This method uses grey relation theory to evaluate the relationship between extracted rolling bearing degradation characteristics and reliability,so as to achieve the purpose of evaluating the degradation features of rolling bearing from the overall perspective of rolling bearing reliability evolution. The experimental results show that the improved fuzzy entropy can accurately extract the performance degradation features of rolling bearing,and the rolling bearing degradation features extracted based on the improved fuzzy entropy have a consistent evolution law with the rolling bearing maintaining reliability,with a credibility level above 95%.
滚动轴承退化特征模糊熵可靠性灰关系
Rolling bearingDegradation characteristicFuzzy entropyReliabilityGrey relation
DONG S,WU W,HE K,et al.Rolling bearing performance degradation assessment based on improved convolutional neural network with anti-interference[J].Measurement,2020,151:107219.
HU M,WANG G,MA K,et al.Bearing performance degradation assessment based on optimized EWT and CNN[J].Measurement,2020,172(1):108868.
童靳于,罗金,郑近德.基于增强深度自编码网络的滚动轴承故障诊断方法[J].中国机械工程,2021,32(21):2617-2624.
TONG Jinyu,LUO Jin,ZHENG Jinde.Fault diagnosis method for rolling bearing based on enhanced deep auto-encoder network[J].China Mechanical Engineering,2021,32(21):2617-2624.
戴邵武,陈强强,戴洪德,等.基于平滑先验分析和模糊熵的滚动轴承故障诊断[J].航空动力学报,2019,34(10):2218-2226.
DAI Shaowu,CHEN Qiangqiang,DAI Hongde,et al.Rolling bearing fault diagnosis base on smoothness priors approach and fuzzy entropy[J].Journal of Aerospace Power,2019,34(10):2218-2226.
郑近德,姜战伟,代俊习,等.基于VMD的自适应复合多尺度模糊熵及其在滚动轴承故障诊断中的应用[J].航空动力学报,2017,32(7):1683-1689.
ZHENG Jinde,JIANG Zhanwei,DAI Junxi,et al.VMD based adaptive composite multiscale fuzzy entropy and its application to fault diagnosis of rolling bearing[J].Journal of Aerospace Power,2017,32(7):1683-1689.
PINCUS S M.Approximate entropy as a measure of system complexity[J].Proceedings of the National Academy of Sciences of the United States of America,1991,88(6):2297-2301.
RICHMAN J S,RANDALL M J.Physiological time-series analysis using approximate entropy and sample entropy[J].American Journal of Physiology Heart & Circulatory Physiology,2000,278(6):2039.
CHWN W,WAND Z,XIE H,et al.Characterization of surface EMG signal based on fuzzy entropy[J].IEEE Transactions on Neural Systems and Rehabilitation Engineering,2007,15(2):266-272.
BANDT C,POMPE B.Permutation Entropy:A natural complexity measure for time series[J].Physical Review Letters,2002,88(17):174102.
ROSTAGHI M,AZAMI H.Dispersion entropy:a measure for time-series analysis[J].IEEE Signal Processing Letters,2016:610-614.
COSTA M,GOLDBERGER A L,PENG C K.Multiscale entropy analysis of complex physiologic time series[J].Physical Review Letters,2007,89(6):705-708.
杨潇谊,吴建德,马军.基于散布熵和余弦欧氏距离的滚动轴承性能退化评估方法[J].电子测量与仪器学报,2020,34(7):15-24.
YANG Xiaoyi,WU Jiande,MA Jun.Rolling bearing performance degradation assessment method based on dispersion entropy and cosine Euclidean distance[J].Journal of Electronic Measurement and Instrumentation,2020,34(7):15-24.
张龙,宋成洋,邹友军,等.基于Renyi熵和K-medoids聚类的轴承性能退化评估[J].振动与冲击,2020,39(20):24-31.
ZHANG Long,SONG Chengyang,ZOU Youjun,et al.Bearing performance degradation assessment based on Renyi entropy and K-medoids clustering[J].Journal of Vibration and Shock,2020,39(20):24-31.
于重重,宁亚倩,秦勇,等.基于T-SNE样本熵和TCN的滚动轴承状态退化趋势预测[J].仪器仪表学报,2019,40(8):39-46.
YU Chongchong,NING Yaqian,QIN Yong,et al.Prediction of rolling bearing state degradation trend based on T-SNE sample entropy and TCN[J].Chinese Journal of Sci2entific Instrument,2019,40(8):39-46.
李耀龙,李洪儒,王冰,等.基于协整理论的滚动轴承退化特征提取[J].振动.测试与诊断,2021,41(2):385-391.
LI Yaolong,LI Hongru,WANG Bing,et al.Extraction of degradation feature for rolling bearings based on cointegration theory[J].Journal of Vibration,Measurement & Diagnosis,2021,41(2):385-391.
向丹,岑健.基于EMD熵特征融合的滚动轴承故障诊断方法[J].航空动力学报,2015,30(5):1149-1155.
XIANG Dan,CEN Jian.Method of roller bearing fault diagnosis based on feature fusion of EMD entropy[J].Journal of Aerospace Power,2015,30(5):1149-1155.
熊国良,毛志德,张龙,等.经验模态分解与核马氏距离的滚动轴承性能退化评估[J].机械设计与研究,2019,35(4):96-100.
XIONG Guoliang,MAO Zhide,ZHANG Long,et al.Performance degradation evaluation of rolling bearings based on empirical mode decomposition and nuclear Markov distance[J].Mechanical Design and Research,2019,35(4):96-100.
叶亮,夏新涛,常振.滚动轴承振动性能保持可靠性与不确定性关系的动态评估[J].航空动力学报,2020,35(11):2326-2338.
YE Liang,XIA Xintao,CHANG Zhen.Dynamic evaluation of relationship between vibration performance maintaining reliability and uncertainty of rolling bearings[J].Journal of Aerospace Power,2020,35(11):2326-2338.
邓聚龙.灰理论基础[M].武汉:华中科技大学出版社,2002:122-167.
DENG Julong.Grey system theory basis[M].Wuhan:Huazhong University of Science and Technology Press,2002:122-167.
马志远,王洪波,孙晴.基于EEMD样本熵与小波神经网络的汽车关门声品质预测[J].噪声与振动控制,2019,39(3):122-127.
MA Zhiyuan,WANG Hongbo,SUN Qing.Sound quality prediction for vehicle's door-slamming noise based on EEMD sample entropy and wavelet neural network[J].Noise and Vibration Control,2019,39(3):122-127.
郑近德,陈敏均,程军圣,等.多尺度模糊熵及其在滚动轴承故障诊断中的应用[J].振动工程学报,2014,27(1):145-151.
ZHENG Jinde,CHEN Minjun,CHENG Junsheng,et al.Multiscale fuzzy entropy and its application in rolling bearing fault diagnosis[J].Journal of Vibration Engineering,2014,27(1):145-151.
程立,夏新涛,叶亮.滚动轴承振动的非线性特征与性能保持可靠性分析[J].机械传动,2019,43(10):104-112.
CHENG Li,XIA Xintao,YE Liang.Analysis of nonlinear characteristic and performance continuity reliability of rolling bearing vibration[J].Journal of Mechanical Transmission,2019,43(10):104-112.
陈强强,戴邵武,戴洪德,等.基于SPA-FIG与优化ELM的滚动轴承性能退化趋势预测[J].振动与冲击,2020,39(19):187-194.
CHEN Qiangqiang,DAI Shaowu,DAI Hongde,et al.Performance degradation trend prediction of rolling bearings based on SPA-FIG and optimized ELM[J].Journal of Vibration and Shock,2020,39(19):187-194.
刘兴教,赵学智,李伟光,等.基于峭度原则的EEMD-MCKD的柔性薄壁轴承故障特征提取[J].振动与冲击,2021,40(1):157-164.
LIU Xingjiao,ZHAO Xuezhi,LI Weiguang,et al.EEMD-MCKD fault feature extraction method for flexible thin-wall bearing based on kurtosis principle.Journal of Vibration and Shock,2021,40(1):157-164.
WANG Biao,LEI Yaguo,LI Naipeng,et al.A hybrid prognostics approach for estimating remaining useful life of rolling element bearings[J].IEEE Transactions on Reliability,2018,69(1):401-412.
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