Fault diagnosis of rolling element bearings using an EMRAN RBF neural network-demonstrated using real experimental data

Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010

Volumn 1, Issue , 2010, Pages 287-291

  Samy, Ihab ^a   Fan, Ip Shing ^a   Perinpanayagam, Suresh ^a  

^a CRANFIELD UNIVERSITY   (United Kingdom)

Author keywords

Data mining; Neural networks; Pattern classifcation; Rotating machniery

Indexed keywords

EID: 78149291361     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNC.2010.5583833     Document Type: Conference Paper

References (11)

1. Y. Li, "Study on incipient fault diagnosis for rolling bearings based on wavelet and neural networks" IEEE Proceedings of 4th International Conference on Natural Computation, ICNC, Jinan, China, Vol. 4, pp. 262-265, 2008.
2. J. Pei, Q. Yang," The technologyt of machinery fault diagnosis", The University of Petroleum Press, Dongying, 1997.
3. L. Wang, C. Wang and Z. Cai, "The diagnosis method for the rolling bearings tiny fault based on wavelet", Chinese Journal of Applied Mechanics, Vol. 16, No. 2, pp. 95-99, 1999.
4. J. Pi, J. Lin and X. Li, "Self organising map based fault dictionary application research on rolling bearing faults", IEEE Proceedings of 4th International Conference on Natural Computation, ICNC, Jinan, China, Vold. 3, pp. 311-315, 2008.
5. B. Sreejith, A. K. Verma and A. Srividya A.," Fault diagnosis of rolling element bearing using time-domain features and neural networks", IEEE Proceedings of ICIIS, Kharagpur, India, pp. 1-6, 2008.
6. I. Samy, I. Postlethwaite and D.-W. Gu," Sensor fault detection and accommodation using neural netowkrs with application to a non-linear unmanned air vehicle model", Proceedings of IMechE Part G, Journal of Aerospace Engineering, Vol. 224, Number 4/2010, pp. 437-447, 2010.
7. H. Li and B. Wan," A product quality model for large scale hot rolling mill based on high-dimension input wavelet neural network", Systems Engineering, Vol. 20, No. 5, pp. 55-58, 2002.
8. A. C. McCormick and A. K. Nandi," Classification of the rotating machine condition using aritificial neural networks", Proceedings of Institution of Mechanical Engineers, Part C, Vol. 211, pp. 439-450, 1997.
9. I. Samy, I. Postlethwaite, D.-W. Gu and J. Green," EMRAN RBF NN based flugh air data sensing system demonstrated on a mini air vehicle, AIAA Journal of Aircraft, Vol. 47, No. 1, 2010.
10. Y. Li, N. Sundararajan and P. Saratchandran, "Analysis of minimal radial basis function network algorithm for real time identification of nonlinear dynamic systems, IEEE Control Theory and Application, Vol. 4, pp. 387-404, 1984.
11. N. Napolitano, Y. An, B. Seanor, S. Pispistos and D. Martinelli," Application of a neural sensor validation scheme to actual Boeing B737 flight data", Proc. Of the AIAA Guidance Navigation and Control Conference, 1999. K. Elissa, "Title of paper if known," unpublished.