Temporal Neuro-Fuzzy systems in fault diagnosis and prognosis

International Review on Modelling and Simulations

Volumn 4, Issue 1, 2011, Pages 436-440

  Rafik, Mahdaoui ^a,b   Hayet, Mouss Leila ^a   Djamel, Mouss Med ^a   Ouahiba, Chouhal ^a,b  

^a UNIVERSITY OF BATNA   (Algeria)

^b ABBES LAGHROUR UNIVERSITY   (Algeria)

Author keywords

Artificial neuronal networks; Diagnosis; FMEAC; Fuzzy logic; Neuro Fuzzy systems; Pattern recognition

Indexed keywords

EID: 79956132757     PISSN: 19749821     EISSN: 25331701     Source Type: Journal    
DOI: None     Document Type: Article

References (16)

1. H.K. Kwan and Y. Cai, A fuzzy neural network and its application to pattern recognition" IEEE Transactions on Fuzzy Systems, 3 pp. 185-193. 1994
2. J.-S. Roger Jang "ANFIS: Adaptive-network-based fuzzy inference system", IEEE Trans. Syst., Man, and Cybernetics, 23(1993) 665-685.
3. J.M. Keller and H. Tahani "Implementation of conjunctive and disjunctive fuzzy logic rules with neural networks" International Journal of Approximate Reasoning, 6 (1992) 221-240.
4. G. Zweingelstein "Diagnostic des défaillances, théories et pratique pour les systèmes industriels" Col. Traité des nouvelles technologies, séries diagnostic et maintenance, Hermès, 1995.
5. L.-X wang and J.M Mendel Generation fuzzy rules by learning from examples IEEE trans. Syst., Man, and Cybernetics, (1992) 22(6):1414-1427.
6. D. Mouss Diagnostic et conduite des systèmes de production par approche a base de connaissances Thèse de doctorat Université de Batna, 2006.
7. D. Nauck "Neuro-fuzzy systems: review and prospects"European congress on intelligent technique and sift computing (EUFIT'97), Aachen, sep.8.11, (1997)
8. D. Racoceanu "contribution à la surveillance des systèmes de production en utilisant les techniques de l'intelligence artificielle"
9. M. Orchard and G. Vachtsevanos, "A particle filtering-based frame-work for real-time falut diagnosis and faillure prognosis in a tur-bine engine," Mediterranean Conference on Control and AutomationMED'07, Athens, Greece, July 2007.
10. A. Al-Ghamd and D. Mba, "A comparative experimental study onthe use of acoustic emission and vibration analysis for bearing defectidentification and estimation of defect size," Mechanical Systems andSignal Processing, vol. 20, pp. 1537-1571, 2006.
11. B. Li, M.-Y. Chow, Y. Tipsuwan and J. Hung, "Neural-networkbased motor rolling bearing fault diagnosis," IEEE Trans. IndustrialElectronics, vol. 47, no. 5, pp. 1060-1069, Oct. 2000.
12. Orchard, M., "A Particle Filtering-Based Framework for On-Line Fault Diagnosis and Failure Prognosis," Ph.D. Thesis. Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, 2007.
13. Orchard, M., Wu, B. and Vachtsevanos, G., "A Particle Filter Framework for Failure Prognosis," Proceedings of WTC2005, World Tribology Congress III, Washington D.C., USA, 2005.
14. Rafik Mahdaoui, Mouss Hayet Laila, "Industrial dynamics monitoring by Temporals Neuro-Fuzzy systems: Application to manufacturing system" GVIP 2009. pp
15. Doaa Khalil Ibrahim, Ahmed F. Zobaa, Essam Abo El-Zahab, Ghada M. Abo-Hamad, "Improving Mho and Quadrilateral Relays Performance during Power Swings" IREE 2010
16. S. I. Sulaiman, T. K. A. Rahman, I. Musirin, "Multi-Objective Evolutionary Programming for Optimal Grid-connected Photovoltaic System Design" IREE 2010.