Fault Detection in Engineering Application using Fuzzy Petri net and Abduction Technique

Authors:

Sudipta Ghosh,Nabanita Das,Debasish Kunduand,Gopal Paul,

DOI NO:

https://doi.org/10.26782/jmcms.2015.01.00001

Keywords:

Fuzzy abduction ,Petri net,Relational matrix,Abductive Reasoning,

Abstract

This paper addresses onengineering application using fuzzy abductionandPetrinettechnique. The problems are introduced informallyabout the fault finding technique ofelectronic networks with different illustrations,so that anyone without any background inthe specific domain easily understands them.and easily find out the fault of thecomplicatedelectronic circuit.The problems require either a mathematical formulation ora computer simulation for their solutions. The detail outlineofthe solution of theengineering problem is illustrated here.

Refference:

I.Bugarin, A. J. and Barro, S., “Fuzzy reasoning supported by Petri nets”,IEEE Trans. on Fuzzy Systems,vol. 2, no.2, pp 135-150,1994.

II.Buchanan, B. G., and Shortliffe E. H.,Rule Based Expert Systems: TheMYCIN Experiment of the Stanford University, Addison-Wesley, Reading,MA, 1984.

III.Cao, T. and Sanderson, A. C., “A fuzzy Petri net approach to reasoningabout uncertainty in robotic systems,”in Proc. IEEE Int. Conf. Robotics andAutomation, Atlanta, GA, pp. 317-322, May 1993.

IV.Cao, T., “Variable reasoning and analysis about uncertainty with fuzzyPetrinets,”Lecture Notes in Computer Science, vol. 691, Marson, M. A., Ed.,Springer-Verlag, New York, pp. 126-145, 1993.

V.Cao, T. and Sanderson, A. C., “Task sequence planing using fuzzy Petrinets,”IEEE Trans. on Systems, Man and Cybernetics, vol. 25, no.5, pp. 755-769, May 1995.

VI.Cardoso, J., Valette, R., and Dubois, D., “Petri nets with uncertainmarkings”, in Advances in Petri nets, Lecture Notes in Computer Science,Rozenberg, G., Ed., vol.483, Springer-Verlag, New York, pp. 65-78, 1990.

VII.Chen, S. M., Ke, J. S. and Chang, J. F., “Knowledge representation usingfuzzy Petri nets,”IEEE Trans. on Knowledge and Data Engineering, vol. 2 ,no. 3, pp. 311-319, Sept. 1990.

VIII.Chen, S. M., “A new approach to inexact reasoning for rule-based systems,”Cybernetic Systems, vol. 23, pp. 561-582, 1992.

IX.Daltrini, A., “Modeling and knowledge processing based on the extendedfuzzy Petri nets,”M. Sc. degree thesis, UNICAMP-FEE0DCA, May 1993.

X.Doyle, J., “Truth maintenance systems,”Artificial Intelligence, vol. 12,1979

XI.Garg, M. L., Ashon, S. I., and Gupta, P. V., “A fuzzy Petri net forknowledge representation and reasoning”,Information Processing Letters,vol. 39, pp.165-171,1991.

XII.Graham, I. and Jones, P. L.,Expert Systems: Knowledge, Uncertainty andDecision, Chapman and Hall, London, 1988.

XIII.Hirota, K. and Pedrycz, W., ” OR-AND neuron in modeling fuzzy setconnectives,”IEEE Trans. on Fuzzy systems, vol. 2 , no. 2 , May 1994.

XIV.Hutchinson, S. A. and Kak, A. C., “Planning sensing strategies in a robotworkcell with multisensor capabilities,”IEEE Trans. Robotics andAutomation, vol. 5, no. 6, pp.765-783, 1989.

XV.Jackson, P.,Introduction to Expert Systems, Addison-Wesley, Reading, MA,1988.

XVI.Konar, A. and Mandal, A. K., “Uncertainty management in expert systemsusing fuzzy Petri nets ,”IEEE Trans. on Knowledge and Data Engineering,vol. 8, no. 1, pp. 96-105, February 1996.

XVII.Konar, A. and Mandal, A. K., “Stability analysis of a non-monotonic Petrinet for diagnostic systems using fuzzy logic,”Proc. of 33rd Midwest Symp.on Circuits, and Systems, Canada, 1991.

XVIII.Konar, A. and Mandal, A. K., “Non-monotonic reasoning inExpertsystems using fuzzy Petri nets,” Advances in Modeling &Analysis, B,AMSE Press, vol. 23, no. 1, pp. 51-63, 1992.

Author(s) : Sudipta Ghosh, Nabanita Das, Debasish Kundu and Gopal Paul View Download