Machine fault diagnosis using a cluster-based wavelet feature extraction and probabilistic neural networks

International Journal of Advanced Manufacturing Technology

Volumn 42, Issue 1-2, 2009, Pages 145-151

  Yu, Gang ^a   Li, Changning ^a   Kamarthi, Sagar ^b  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b Northeastern University   (United States)

Author keywords

Fault diagnosis; Feature extraction; Probabilistic neural networks; Wavelet

Indexed keywords

BEARING FAULT DIAGNOSIS; CLUSTER-BASED; CONVENTIONAL METHODS; ENERGY CONTENTS; ENTROPY VALUES; FAULT DIAGNOSIS; FAULT DIAGNOSTICS; FEATURE VECTORS; INFORMATION CONTENTS; INFORMATIVE ATTRIBUTES; MACHINE FAULT DIAGNOSIS; MACHINE FAULTS; MATRIXES; PROBABILISTIC NEURAL NETWORKS; TEST SIGNALS; WAVELET; WAVELET COEFFICIENTS;

DISCRETE WAVELET TRANSFORMS; FAILURE ANALYSIS; FEATURE EXTRACTION; QUALITY ASSURANCE;

NEURAL NETWORKS;

EID: 67349229772     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-008-1563-9     Document Type: Article

References (24)

1. Julius SB, Allan GP (1986) Random data analysis and measurement procedures, 2nd edn. Wiley, New York
2. S Gu J Ni J Yuan 2002 Non-stationary signal analysis and transient machining process condition monitoring Int J Mach Tools Manuf 42 41 51
3. LR Padovese 2004 Hybrid time-frequency methods for non-stationary mechanical signal analysis Mech Syst Signal Process 18 1047 1064
4. Daubechies I (1992) Ten lectures on wavelets. SIAM Press, Philadelphia, PA
5. LM Bruce CH Koger J Li 2002 Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction IEEE Trans Geosci Remote Sens 40 2331 2338
6. SG Mallat 1989 Multifrequency Channel decompositions of images and wavelet models IEEE Trans Acoust Speech Signal Process 37 2091 2110
7. ZK Peng FL Chu 2004 Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography Mech Syst Signal Process 18 199 221
8. AG Rehorn J Jiang PE Orban 2005 State-of-the-art methods and results in tool condition monitoring: a review Int J Adv Manuf Technol 26 693 710
9. S Pittner SV Kamarthi 1999 Feature extraction from wavelet coefficients for pattern recognition tasks IEEE Trans Pattern Anal Mach Intell 21 83 88
10. A Saxena BQ Wu G Vachtsevanos 2005 A methodology for analyzing vibration data from planetary gear systems using complex Morlet wavelets Proceedings of 2005 American Control Conference 7 4730 4735
11. I Daubechies 1990 Wavelet transform, time-frequency localization and signal analysis IEEE Trans Inf Theory 36 961 1005
12. S Mallat 1989 A theory for multiresolution signal decomposition: the wavelet representation IEEE Trans Pattern Anal Mach Intell 2 674 693
13. Mallat S (1999) A wavelet tour of signal processing. Academic, San Diego, CA
14. Shannon CE, Weaver W (1963) The mathematical theory of communication. University of Illinois Press, Illinois
15. Sen PK, Singer JM (1993) Large sample methods in statistics-an introduction with applications. Chapman & Hall, New York
16. DC Baillie JA Mathew 1996 Comparison of autoregressive modeling techniques for fault diagnosis of rolling element bearings Mech Syst Signal Process 10 1 17
17. AC McCormick AK Nandi 1997 Real time classification of rotating shaft loading conditions using artificial neural networks IEEE Trans Neural Netw 8 748 757
18. NH Abu-Zahra S Karimi 2002 On-line monitoring of PVC foam density using ultrasound waves and artificial neural networks Int J Adv Manuf Technol 19 618 622
19. J-S Kwak M-K Ha 2004 Intelligent diagnostic technique of machining state for grinding Int J Adv Manuf Technol 23 436 443
20. R Quiza L Figueira J Paulo Davim 2008 Comparing statistical models and artificial neural networks on predicting the tool wear in hard machining D2 AISI steel Int J Adv Manuf Technol 37 7-8 641 648
21. DF Specht 1990 Probabilistic neural networks Neural Netw 3 109 118
22. E Parzen 1962 On Estimation of a probability density function and mode Ann Math Stat 33 1065 1076
23. Specht DF, Shapiro PD (1991) Generalization accuracy of probabilistic neural networks compared with backpropagation networks. Neural Networks, 1991, IJCNN-91-Seattle International Joint Conference on, 1991, pp 887-892
24. Case Western Reserve University Bearing Test Data Center. http://www.eecs.case.edu/laboratory/bearing/