A novel fault diagnosis method of bearing based on improved fuzzy ARTMAP and modified distance discriminant technique

被引:50
作者
Xu, Zengbing
Xuan, Jianping [1 ]
Shi, Tielin
Wu, Bo
Hu, Youmin
机构
[1] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Feature selection; Modified distance discriminant technique; Improved fuzzy ARTMAP; Yu's norm; Bootstrap method; Fault diagnosis; ARTIFICIAL NEURAL-NETWORKS; ROTATING MACHINERY; VIBRATION; SIGNALS;
D O I
10.1016/j.eswa.2009.04.021
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a novel intelligent diagnosis method based on multiple domain features, modified distance discrimination technique and improved fuzzy ARTMAP (IFAM). The method consists of three steps. To begin with, time-domain, frequency-domain and wavelet grey moments are extracted from the raw vibration signals to demonstrate the fault-related information. Then through the modified distance discrimination technique some salient features are selected from the original feature set. Finally, the optimal feature set is input into the IFAM incorporated with similarity based on the Yu's norm in the classification phase to identify the different fault categories. The proposed method is applied to the fault diagnosis of rolling element bearing. and the test results show that the IFAM identify the fault categories of rolling element bearing more accurately and has a better diagnosis performance compared to the FAM. Furthermore, by the application of the bootstrap method to the diagnosis results it can testify that the IFAM has more capacity of reliability and robustness. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:11801 / 11807
页数:7
相关论文
共 18 条
[1]  
[Anonymous], 1994, An introduction to the bootstrap: CRC press
[2]   1977 RIETZ LECTURE - BOOTSTRAP METHODS - ANOTHER LOOK AT THE JACKKNIFE [J].
EFRON, B .
ANNALS OF STATISTICS, 1979, 7 (01) :1-26
[3]  
Garperter G.A., 1992, IEEE T NEURAL NETWOR, V3, P698
[4]   A fuzzy neural network approach to machine condition monitoring [J].
Javadpour, R ;
Knapp, GM .
COMPUTERS & INDUSTRIAL ENGINEERING, 2003, 45 (02) :323-330
[5]   Symbolic analysis of chaotic signals and turbulent fluctuations [J].
Lehrman, M ;
Rechester, AB ;
White, RB .
PHYSICAL REVIEW LETTERS, 1997, 78 (01) :54-57
[6]   A new approach to intelligent fault diagnosis of rotating machinery [J].
Lei, Yaguo ;
He, Zhengjia ;
Zi, Yanyang .
EXPERT SYSTEMS WITH APPLICATIONS, 2008, 35 (04) :1593-1600
[7]   Methods of fault diagnosis [J].
Leonhardt, S ;
Ayoubi, M .
CONTROL ENGINEERING PRACTICE, 1997, 5 (05) :683-692
[8]   Invariant optimal feature selection: A distance discriminant and feature ranking based solution [J].
Liang, Jianning ;
Yang, Su ;
Winstanley, Adam .
PATTERN RECOGNITION, 2008, 41 (05) :1429-1439
[9]  
Loparo K. A., 2003, BEARINGS VIBRATION D
[10]   Similarity classifier using similarity measure derived from Yu's norms in classification of medical data sets [J].
Luukka, Pasi .
COMPUTERS IN BIOLOGY AND MEDICINE, 2007, 37 (08) :1133-1140