| Citation: | Rolling bearing collaborative fault diagnosis technology for casing vibration signal[J]. Journal of Aerospace Power, 2018, 33(10): 2376-2384. doi: 10.13224/j.cnki.jasp.2018.10.009
|
| [1] |
梅宏斌.滚动轴承振动监测与诊断［M］.机械工业出版社,1995.
|
| [2] |
RANDALL R B,ANTONI J.Rolling element bearing diagnostics:a tutorial［J］.Mechanical Systems and Signal Processing,2011,25(2):485-520.
|
| [3] |
尉询楷,冯悦,杨立,等.航空发动机中介主轴承故障预测研究［R］.北京:航空安全与装备维修技术学术研讨会,2014.
|
| [4] |
CHEN G,HAO T F,WANG H F,et al.Sensitivity analysis and experimental research on ball bearing early fault diagnosis based on testing signal from casing［J］.Journal of Dynamic Systems,Measurement and Control,2014,136(6):061009-061019.
|
| [5] |
陈果,郝腾飞,程小勇,等.基于机匣测点信号的航空发动机滚动轴承故障诊断灵敏性分析［J］.航空动力学报,2014,29(12):2874-2884.CHEN Guo,HAO Tengfei,CHENG Xiaoyong,et al.Sensitivity analysis of fault diagnosis of aero-engine rolling bearing based on vibration signal measured on casing［J］.Journal of Aerospae Power,2014,29(12):2874-2884.(in Chinese)
|
| [6] |
WIGGINS R A.Minimum entropy deconvolution［J］.Geophysical Prospecting for Petrole,1978,16(1/2):21-35.
|
| [7] |
ENDO H,RANDALL R B.Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter［J］.Mechanical Systems and Signal Processing,2007,21(2):906-919.
|
| [8] |
江瑞龙.基于最小熵解卷积的滚动轴承故障诊断研究［D］.上海:上海交通大学,2013.JIANG Ruilong.Research on minimum entropy deconvolution for rolling element bearing fault diagnosis［D］.Shanghai:Shanghai Jiao Tong University,2013.(in Chinese)
|
| [9] |
王宏超,陈进,董广明.基于最小熵解卷积与稀疏分解的滚动轴承微弱故障特征提取［J］.机械工程学报,2013,49(1):88-94.WANG Hongchao,CHEN Jin,DONG Guangming.Feature extraction of weak faults of rolling bearings based on minimum entropy deconvolution and sparse decomposition［J］.Journal of Mechanical Engineering,2013,49(1):88-94.(in Chinese)
|
| [10] |
WANG H C,CHEN J,DONG G M.Fault diagnosis of rolling bearings early weak fault based on minimum entropy de-convolution and fast Kurtogram algorithm［J］.Proceedings of the Institution of Mechanical Engineers:Part C:Journal of Mechanical Engineering Science,2015,229(16):2890-2907.
|
| [11] |
张龙,胡俊锋,熊国良.基于MED和ICA的滚动轴承循环冲击故障特征增强［J］.计算机集成制造系统,2017,23(2):333-339.ZHANG Long,HU Junfeng,XIONG Guoliang.Cyclic impact feature enhancement for rolling bearing fault detection based on MED and ICA［J］.Computer Integrated Manufacturing Systems,2017,23(2):333-339.(in Chinese)
|
| [12] |
何正嘉,李富才,杜远,等.小波技术在机械监测诊断领域的应用现状与进展［J］.西安交通大学学报,2001,35(5):540-545.HE Zhengjia,LI Fucai,DU Yuan,et al.Development and status quo of applications on wavelet technology for mechanical surveillance and diagnosis［J］.Journal of Xian Jiaotong University,2001,35(5):540-545.(in Chinese)
|
| [13] |
PENG Z K,CHU F L.Application of the wavelet transform in machine condition monitoring and fault diagnostics:a review with bibliography［J］.Mechanical Systems and Signal Processing,2004,18(2):199-221.
|
| [14] |
LI C J,MA J.Wavelet decomposition of vibrations for detection of bearing-localized defects［J］.Ndt & E International,1997,30(3):143-149.
|
| [15] |
陈果.滚动轴承早期故障的特征提取与智能诊断［J］.航空学报,2009,30(2):362-367.CHEN Guo.Feature extraction and intelligent diagnosis for ball bearing early faults［J］.Acta Aeronautica et Astronautica Sinica,2009,30(2):362-367.(in Chinese)
|
| [16] |
胥永刚,孟志鹏,陆明.基于双树复小波包变换和SVM的滚动轴承故障诊断方法［J］.航空动力学报,2014,29(1):67-73.XU Yonggang,MENG Zhipeng,LU Ming.Fault diagnosis method of rolling bearing based on dual-tree complex wavelet packet transform and SVM［J］.Journal of Aerospace Power,2014,29(1):67-73.(in Chinese)
|
| [17] |
郑红,周雷,杨浩.基于小波包分析与多核学习的滚动轴承故障诊断［J］.航空动力学报,2015,30(12):3035-3042.ZHENG Hong,ZHOU Lei,YANG Hao.Rolling bearing fault diagnosis based on wavelet packet analysis and multi-core learning［J］.Journal of Aerospace Power,2015,30(12):3035-3042.(in Chinese)
|
| [18] |
孟涛,廖明夫.利用时延相关解调法诊断滚动轴承的故障［J］.航空学报,2004,25(1):41-44.MENG Tao,LIAO Mingfu.Detection and diagnosis of the rolling element bearing fault by the delayed correlation-envelope technique［J］.Acta Aeronautica et Astronautica Sinica,2004,25(1):41-44.(in Chinese)
|
| [19] |
程军圣,于德介,邓乾旺,等.时间-小波能量谱在滚动轴承故障诊断中的应用［J］.振动与冲击,2004,23(2):33-36.CHENG Jusheng,YU Dejie,DENG Qianwang,et al.Application of time-wavelet energy spectrum in fault diagnosis of rolling bearings［J］.Journal of Vibration and Shock,2004,23(2):33-36.(in Chinese)
|
| [20] |
SU W,WANG F,ZHU H,et al.Rolling element bearing faults diagnosis based on optimal Morlet wavelet filter and autocorrelation enhancement［J］.Mechanical Systems and Signal Processing,2010,24(5):1458-1472.
|
| [21] |
明安波,褚福磊,张炜.滚动轴承故障特征提取的频谱自相关方法［J］.机械工程学报,2012,48(19):65-71.MING Anbo,CHU Fulei,ZHANG Wei.Feature extracting method in the rolling element bearing fault diagnosis：spectrum auto-correlation［J］.Journal of Mechanical Engineering,2012,48(19):65-71.(in Chinese)
|
| [22] |
LEE J Y,NANDI A K.Blind deconvolution of impacting signals using higher-order statistics［J］.Mechanical Systems and Signal Processing,1998,12(2):357-371.
|
| [23] |
MALLAT S G.A theory for multi-resolution signal decomposition:the wavelet representation［J］.IEEE Computer Society,1989,11(7):674-693.
|
DownLoad: