A comparison of two learning mechanisms for the automatic design of fuzzy diagnosis systems for rotating machinery

Applied Soft Computing Journal

Volumn 4, Issue 4, 2004, Pages 413-422

  Salido, Jesús Manuel Fernández ^a,b   Murakami, Shuta ^a  

^a KYUSHU INSTITUTE OF TECHNOLOGY   (Japan)

^b Apt S ^*  (United States)

Author keywords

Fuzzy diagnosis; Genetic algorithms; Knowledge based networks

Indexed keywords

ARTICLE; AUTOANALYSIS; COMPUTER ANALYSIS; GENETIC ALGORITHM; INTERMETHOD COMPARISON; MACHINE; MATHEMATICAL COMPUTING; VIBRATION;

EID: 2942630598     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2004.02.004     Document Type: Article

References (21)

1. S. Bleuler, M. Brack, et al. Multiobjective genetic programming: reducing bloat using SPEA2, in: Proceedings of the 2001 Congress on Evolutionary Computation, vol. 1, 2001, pp. 535-543.
2. Dubois D., Prade H., Testemale C. Weighted fuzzy pattern matching. Fuzzy Sets Syst. 28:1988;313-331
3. Y.H. Chang, B. Zheng, Computer aided diagnosis of breast cancer using artificial networks: comparison of backpropagation and genetic algorithms, in: Proceedings of the IICNN'99 International Conference on Neural Networks, vol. 5, 1999, pp. 3674-3679.
4. Dyckhoff H., Pedrycz W. Generalized means as a model of compensative connectives. Fuzzy Sets Syst. 14:1984;143-154
5. Farag W.A., Quintana V.H. Genetic algorithms and back-propagation: a comparative study. IEEE Can. Conf. Electr. Comput. Eng. 1:1998;24-28
6. J.M. Fernández, S. Murakami, Construction of fuzzy diagnosis rules for rotating machinery using vibration analysis and knowledge-based networks, in: Proceedings of the 6th International Conference on Soft Computing (IIZUKA 2000), Iizuka, Japan, 2000.
7. J.M. Fernández, S. Murakami, A proposal for the automatic design of fuzzy diagnosis systems for rotating machinery, in: Proceedings of the 13th International Congress on Condition Monitoring and Diagnostic Engineering Management (COMADEM'2000), Houston, TX, USA, 2000, pp. 755-764.
8. J.M. Fernández, S. Murakami, Application of fuzzy pattern matching and genetic algorithms to rotating machinery diagnosis, in: S. Bae-Cho (Ed.), Practical Applications of Soft Computing in Industry, World Scientific, Singapore, 2001, pp. 255-285.
9. P.M. Frank, T. Marcu, Fuzzy techniques in fault detection, isolation and diagnosis, in: H.B. Verbruggen, R. Babuska (Eds.), Fuzzy Logic Control - Advances in Applications, World Scientific, Singapore, 1999, pp. 239-258.
10. J. Gertler, Survey of model-based failure detection and isolation in complex plants, IEEE Contr. Syst. Mag. (6) (1988) 3-11.
11. Hirota K., Pedrycz W. Knowledge-based networks in classification problems. Fuzzy Sets Syst. 59:1993;271-279
12. Owechko Y., Sham S. Comparison of neural networks and genetic algorithm for a resource allocation problem, IEEE International Conference on Neural Networks. IEEE World Congr. Comput. Intell. 7:1994;4655-4660
13. Paya B.A., Esat I.I., Badi M.N.M. Artificial neural network based fault diagnosis of rotating machinery using wavelet transforms as a preprocessor. Mech. Syst. Signal Process. 11(5):1997;751-765
14. Pedrycz W., Lam P.C.F., Rocha A. Distributed fuzzy system modeling. IEEE Trans. Syst. Man Cybernet. 25:1995;769-780
15. SKF Group, Paper mills gains from condition monitoring, in: Evolution: Business and Technology Magazine from SKF, March Issue, 2000.
16. Renwick J.T., Babson P.E. Vibration analysis - a proven technique as a predictive maintenance tool. IEEE Trans. Ind. Applic. 21(2):1985;324-330
17. Sanchez E. Importance in knowledge systems. Inform. Syst. 14(6):1989;455-464
18. Tsang E.C., Yeung D.S. Optimizing fuzzy knowledge base by genetic algorithms and neural networks. IEEE Int. Conf. Syst. Man Cybernet. 3:1999;367-371
19. E. Tunstel, M.-R. Akbarzadeh, Hybrid fuzzy control schemes for robotic systems, IEEE Int. Symp. Intell. Contr. August (1995) 171-176.
20. Tunstel E., Akbarzadeh M.-R., et al. Soft computing paradigm for hybrid fuzzy controller: experiment and applications. IEEE World Congress on Computational Intelligence. Fuzzy Syst. Proc. 2:1998;1200-1205
21. Ulieru U., Iserman I. Design of a fuzzy-logic based diagnostic model for technical processes. Fuzzy Sets Syst. 58:1993;249-259