Multifault diagnosis of rolling element bearings using a wavelet kurtogram and vector median-based feature analysis

Shock and Vibration

Volumn 2015, Issue , 2015, Pages

  Nguyen, Phuong H ^a   Kim, Jong Myon ^a  

^a University of Ulsan   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC EMISSION TESTING; BEARINGS (MACHINE PARTS); COMPUTER AIDED DIAGNOSIS; DISCRIMINANT ANALYSIS; FAULT DETECTION; FREQUENCY DOMAIN ANALYSIS; PACKET NETWORKS; TIME DOMAIN ANALYSIS;

ACOUSTIC EMISSION SIGNAL; BEARING FAULT DIAGNOSIS; CLASSIFICATION ACCURACY; LINEAR DISCRIMINANT ANALYSIS; MULTI-FAULT DIAGNOSIS; ROLLING ELEMENT BEARING; STATE-OF-THE-ART APPROACH; WAVELET PACKET TRANSFORM(WPT);

ROLLER BEARINGS;

EID: 84946211882     PISSN: 10709622     EISSN: None     Source Type: Journal    
DOI: 10.1155/2015/320508     Document Type: Article

References (21)

1. J. Antoni, "Fast computation of the kurtogramfor the detection of transient faults, " Mechanical Systems and Signal Processing, vol. 21, no. 1, pp. 108-124, 2007.
2. N. Sawalhi, R. B. Randall, and H. Endo, "The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis, " Mechanical Systems and Signal Processing, vol. 21, no. 6, pp. 2616-2633, 2007.
3. T. Barszcz and R. B. Randall, "Application of spectral kurtosis for detection of a tooth crack in the planetary gear of a wind turbine, " Mechanical Systems and Signal Processing, vol. 23, no. 4, pp. 1352-1365, 2009.
4. P. Boskoski, J. Petrovicic, B. Musizza, and D. Juriicic, "Detection of lubrication starved bearings in electrical motors by means of vibration analysis, " Tribology International, vol. 43, no. 9, pp. 1683-1692, 2010.
5. R. F. Dwyer, "Detection of non-Gaussian signals by frequency domain kurtosis estimation, " in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 83), pp. 607-610, Boston, Mass, USA, 1984.
6. J. Antoni and R. B. Randall, "The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines, " Mechanical Systems and Signal Processing, vol. 20, no. 2, pp. 308-331, 2006.
7. B. Chen, Z. Zhang, Y. Zi, Z. He, and C. Sun, "Detecting of transient vibration signatures using an improved fast spatialspectral ensemble kurtosis kurtogram and its applications to mechanical signature analysis of short duration data from rotating machinery, " Mechanical Systems and Signal Processing, vol. 40, no. 1, pp. 1-37, 2013.
8. L. Shi, R. B. Randall, and J. Antoni, "Rolling element bearing fault detection using improved envelope analysis, " in Proceedings of the Eighth International Conference on Vibrations in Rotating Machinery, pp. 301-311, Swansea, Wales, September 2004.
9. M. Kang, J. Kim, J.-M. Kim, A. C. C. Tan, E. Y. Kim, and B.-K. Choi, "Reliable fault diagnosis for low-speed bearings using individually trained support vector machines with kernel discriminative feature analysis, " IEEE Transactions on Power Electronics, vol. 30, no. 5, pp. 2786-2797, 2015.
10. M. Kang, J. Kim, B.-K. Choi, and J.-M. Kim, "Envelop analysis with a genetic algorithm-based adaptive filter bank for bearing fault detection, "The Journal of theAcoustical Society of America, vol. 138, no. 1, article EL65, 6 pages, 2015.
11. A. Widodo and B.-S. Yang, "Machine health prognostics using survival probability and support vector machine, " Expert Systems with Applications, vol. 38, no. 7, pp. 8430-8437, 2011.
12. Y. Guo, J. Na, B. Li, and R.-F. Fung, "Envelope extraction based dimension reduction for independent component analysis in fault diagnosis of rolling element bearing, " Journal of Sound and Vibration, vol. 333, no. 13, pp. 2983-2994, 2014.
13. J. Harmouche, C. Delpha, and D. Diallo, "Improved fault diagnosis of ball bearings based on the global spectrum of vibration signals, " IEEE Transactions on Energy Conversion, vol. 30, no. 1, pp. 376-383, 2015.
14. K. Fukunaga, Introduction to Statistical Pattern Recognition, Computer Science and Scientific Computing, Academic Press, Boston, Mass, USA, 1990.
15. P. Comon, "Independent component analysis, a new concept?" Signal Processing, vol. 36, no. 3, pp. 287-314, 1994.
16. G. J. McLachlan, Discriminant Analysis and Statistical Pattern Recognition, Wiley, New York, NY, USA, 1992.
17. F. Cong, J. Chen, and G. Dong, "Spectral kurtosis based on AR model for fault diagnosis and condition monitoring of rolling bearing, " Journal of Mechanical Science and Technology, vol. 26, no. 2, pp. 301-306, 2012.
18. K. Mardia, J. Kent, and J. Bibby, Multivariate Analysis, Academic Press, London, UK, 1979.
19. J. Vaidya, M. Kantarcioglu, and C. Clifton, "Privacy-preserving Naive Bayes classification, " The VLDB Journal, vol. 17, no. 4, pp. 879-898, 2008.
20. Y.-L. He, R. Wang, S. Kwong, and X.-Z. Wang, "Bayesian classifiers based on probability density estimation and their applications to simultaneous fault diagnosis, " Information Sciences, vol. 259, pp. 252-268, 2014.
21. J. Rodriguez, A. J. Perez, and J. Lozano, "Sensitivity analysis of k-fold cross validation in prediction error estimation, " IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 3, pp. 569-575, 2010.