An Improvement of Faults Diagnosis and Prognosis of Discrete Event Systems Based on Reliability Laws

Abstract:

In this work, we are interested in the faults diagnosis and the faults prognosis in discrete event systems described by sequences of generated events. Through this work, we aim the maximization of the efficiency of diagnosis/prognosis operations by combining two concepts. The first one is the approach already developed in one of our works which consider the k-last generated events to perform the diagnosis/prognosis. The second concept is the reliability that takes into consideration the life cycle of each component of the discrete event systems to give the failure probability. This combination will be made using some notions of fuzzy logic.

• Periodical: International Journal of Engineering Research in Africa (Volume 45)
• Pages: 148-155
• DOI: https://doi.org/10.4028/www.scientific.net/JERA.45.148
• Online since: November 2019
• Authors: Mohammed Msaaf*, Fouad Belmajdoub
• Keywords: Discrete Event Systems, Fault Diagnosis, Fault Prognosis, Fuzzy Logic, Reliability, Statistical Model

References

[1] F. Cassez and A. Grastien, Predictability of event occurrences in timed systems,, in International Conference on Formal Modeling and Analysis of Timed Systems, 2013, pp.62-76.

DOI: 10.1007/978-3-642-40229-6_5

[2] S. Genc and S. Lafortune, PREDICTABILITY IN DISCRETE-EVENT SYSTEMS UNDER PARTIAL OBSERVATION 1,, IFAC Proceedings Volumes, vol. 39, pp.1461-1466, (2006).

DOI: 10.3182/20060829-4-cn-2909.00243

[3] M. Sampath, R. Sengupta, S. Lafortune, K. Sinnamohideen, and D. Teneketzis, Diagnosability of discrete-event systems,, IEEE Transactions on automatic control, vol. 40, pp.1555-1575, (1995).

DOI: 10.1109/9.412626

[4] J. Saives, G. Faraut, and J.-J. Lesage, Identification of discrete event systems unobservable behaviour by petri nets using language projections,, in Control Conference (ECC), 2015 European, 2015, pp.464-471.

DOI: 10.1109/ecc.2015.7330587

[5] D. Lefebvre and C. Delherm, Diagnosis of DES with Petri net models,, Automation Science and Engineering, IEEE Transactions on, vol. 4, pp.114-118, (2007).

DOI: 10.1109/tase.2006.872122

[6] S. S. Tayarani-Bathaie, Z. S. Vanini, and K. Khorasani, Dynamic neural network-based fault diagnosis of gas turbine engines,, Neurocomputing, vol. 125, pp.153-165, (2014).

DOI: 10.1016/j.neucom.2012.06.050

[7] Y. Xu, Y. J. Chen, and Q. X. Zhu, An Extension Sample Classification‐Based Extreme Learning Machine Ensemble Method for Process Fault Diagnosis,, Chemical Engineering & Technology, vol. 37, pp.911-918, (2014).

DOI: 10.1002/ceat.201300622

[8] M. MSAAF and F. BELMAJDOUB, Fault diagnosis and prognosis in discrete event systems using statistical model and neural networks,, International Journal of Mechatronics and Automation, vol. 6, pp.173-182, (2018).

DOI: 10.1504/ijma.2018.10016612

[9] Z. Gao, C. Cecati, and S. X. Ding, A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches,, IEEE Transactions on Industrial Electronics, vol. 62, pp.3757-3767, (2015).

DOI: 10.1109/tie.2015.2417501

[10] P. Crow-AMSAA, The New Weibull Handbook,, (1993).

[11] K. Kołowrocki, Reliability of large systems,, Encyclopedia of quantitative risk analysis and assessment, vol. 4, (2008).

[12] L. Zadeh, Fuzzy Sets,, Inform Control, vol. 8, pp.338-353, (1965).

[13] S. K. De, R. Biswas, and A. R. Roy, Some operations on intuitionistic fuzzy sets,, Fuzzy Sets and Systems, vol. 114, pp.477-484, 2000/09/16/ (2000).

DOI: 10.1016/s0165-0114(98)00191-2

[14] L. A. Zadeh, A Fuzzy-Set-Theoretic Interpretation of Linguistic Hedges,, Journal of Cybernetics, vol. 2, pp.4-34, 1972/01/01 (1972).

DOI: 10.1080/01969727208542910

[15] F. Lin, Diagnosability of discrete event systems and its applications,, Discrete Event Dynamic Systems, vol. 4, pp.197-212, 1994/05/01 (1994).

DOI: 10.1007/bf01441211

[16] Z. Gao, C. Cecati, and S. X. Ding, A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part II: Fault Diagnosis With Knowledge-Based and Hybrid/Active Approaches,, IEEE Transactions on Industrial Electronics, vol. 62, pp.3768-3774, (2015).

DOI: 10.1109/tie.2015.2419013