Skip to main content
Log in

A Model-Based Diagnosis System for Identifying Faulty Components in Digital Circuits

  • Published:
Applied Intelligence Aims and scope Submit manuscript

Abstract

We describe the ideas and implementation of a model-based diagnosis system for digital circuits. Our work is based on Reiter's theory of diagnosis from first principles [14], incorporated with Hou's theory of measurements [17], to derive possible diagnoses in a fault diagnosis task. To determine the best order in which measurements are to be taken, a measurement selection strategy using the genetic algorithm (MSSGA) is proposed. A circuit description language for describing circuits hierarchically is given. An efficient propositional logic prover used for consistency checking based on the trie structure is developed [22]. An example run is given to illustrate the working of the system. Finally, a comparison with other systems is discussed, and possible extensions to our system are described.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. H.C.A. Dale, “Fault-finding in electronic equipment,” Ergonomics, vol. 1, pp. 356–385, 1957.

    Google Scholar 

  2. R.M. Hunt and W.B. Rouse, “A fuzzy rule-based model of human problem solving,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 14,no. 1, pp. 112–120, 1984.

    Google Scholar 

  3. J. Rasmussen and A. Jensen, “Mental procedures in real-life tasks: A case study of electronic trouble shooting,” Ergonomics, vol. 17,no. 3, pp. 293–307, 1974.

    Google Scholar 

  4. W.B. Rouse, “Model of human decision making in a fault diagnosis task,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 8,no. 5, pp. 357–361, 1978.

    Google Scholar 

  5. W.B. Rouse, S.H. Rouse, and S.J. Pellegrino, “A rule-based model of human problem solving performance in fault diagnosis tasks,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 10,no. 7, pp. 366–376, 1980.

    Google Scholar 

  6. B.G. Buchanan and E.H. Shortliffe, Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project, Addison-Wesley: Reading, MA, 1984.

    Google Scholar 

  7. E.H. Shortliffe, Computer-Based Medical Consultation: MYCIN, North-Holland: New York, 1976.

    Google Scholar 

  8. R.T. Hartley, “CRIB: Computer fault-finding through knowledge engineering,” Computer, pp. 76–83, 1984.

  9. T.J. Laffey, W.A. Perkins, and T.A. Nguyen, “Reasoning about fault diagnosis with LES,” IEEE Expert, pp. 13–20, 1986.

  10. W.R. Nelson, “REACTOR: An expert system for diagnosis and treatment of nuclear reactor accidents,” in Proceedings of the Second National Conference on Artificial Intelligence, Morgan Kaufmann, 1982, pp. 296–301.

  11. R. Davis, “Diagnostic reasoning based on structure and behavior,” Artificial Intelligence, vol. 24, pp. 347–410, 1984.

    Google Scholar 

  12. J. de Kleer and B.C. Williams, “Diagnosing multiple faults,” Artificial Intelligence, vol. 32, pp. 97–130, 1987.

    Google Scholar 

  13. W. Hamscher, “Model-based troubleshooting of digital systems,” Ph.D. Thesis, MIT Technical Report AI-TR-1074, 1988.

  14. R. Reiter, “A theory of diagnosis from first principles,” Artificial Intelligence, vol. 32, pp. 57–95, 1987.

    Google Scholar 

  15. M.R. Genesereth, “The use of design descriptions in automated diagnosis,” Artificial Intelligence, vol. 24, pp. 411–436, 1984.

    Google Scholar 

  16. R. Greiner, B.A. Smith, and R.W. Wilkerson, “A correction to the algorithm in Reiter's theory of diagnosis,” Artificial Intelligence, vol. 41, pp. 79–88, 1989/1990.

    Google Scholar 

  17. A. Hou, “A theory of measurement in diagnosis from first principles,” Artificial Intelligence, vol. 65, pp. 281–328, 1994.

    Google Scholar 

  18. W. Bibel, Automated Theorem Proving, Vieweg, 1982.

  19. C. Chang and R. Lee, Symbolic Logic and Mechanical Theorem Proving, Academic Press: New York, 1973.

    Google Scholar 

  20. C.-W. Chang and S.-J. Lee, “An improved path sensitization method in test pattern generation for combinational circuits,” in Proceedings of IEEE Conference on Industrial Automation and Control, Taipei, Taiwan, 1995, pp. 678–685.

  21. K.D. Forbus and J. de Kleer, Building Problem Solvers, The MIT Press, 1993.

  22. H. Zhang and M. Stickel, “Implementing the Davis-Putnam algorithm by tries,” Technical Report, Computer Science Department, The University of Iowa, Iowa City, Iowa, August 1994.

    Google Scholar 

  23. M. Abramovici, M.A. Breuer, and A.D. Friedman, Digital Systems Testing and Testable Design, The Institute of Electrical and Electronics Engineers, Inc.: New York, 1990.

    Google Scholar 

  24. D.B. Armstrong, “On finding a nearly minimal set of fault detection tests for combinational logic nets,” IEEE Transactions on Electronic Computers, vol. 15, pp. 66–73, 1966.

    Google Scholar 

  25. H. Fujiwara and T. Shimono, “On the acceleration of test generation algorithms,” IEEE Transactions on Computers, vol. C-32,no. 12, pp. 1137–1144, 1983.

    Google Scholar 

  26. P. Goel, “An implicit enumeration algorithm to generate tests for combinational logic circuits,” IEEE Transactions on Computers, vol. C-30,no. 3, pp. 215–222, 1981.

    Google Scholar 

  27. J.P. Hayes, Introduction to Digital Logic Design, Addison-Wesley, 1993.

  28. B. Han, “Diagnosis of combinational digital circuits from first principles,” Master Thesis, Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan, 1996.

    Google Scholar 

  29. B. Han and S.-J. Lee, “Deriving Minimal Conflict Sets by CS-Trees with Mark Set in Diagnosis from First Principles,” IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics, to appear.

  30. M. Buro and H.K. Büning, Report on a SAT Competition, Mathematik/Informatik, Universität Paderborn, 1992.

  31. M.R. Garey and D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, Bell Laboratories: NJ, 1979.

    Google Scholar 

  32. L. Davis et al., Handbook of Genetic Algorithms, Van Nostrand Reinhold, 1991.

  33. D.E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, 1989.

  34. J.J. Grefenstette, “Optimization of control parameters for genetic algorithms,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 16,no. 1, pp. 122–128, 1986.

    Google Scholar 

  35. J.H. Holland, Adaptation in Natural and Artificial Systems, University of Michigan Press, 1975.

  36. S.A. Cook, “The complexity of theorem-proving procedures,” in Proceedings of the 3rd Annual ACM Symposium on Theory of Computing, 1971, pp. 151–158.

  37. S.-J. Lee and D. Plaisted, “Eliminating duplication with the hyper-linking strategy,” Journal of Automated Reasoning, vol. 9,no. 1, pp. 25–42, 1992.

    Google Scholar 

  38. J. de Kleer et al., “One step lookahead is pretty good,” in Readings in Model-Based Diagnosis, edited by W. Hamsher, L. Console, and J. de Kleer, Morgan Kaufmann, pp. 138–142, 1992.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Han, B., Lee, SJ. & Yang, HT. A Model-Based Diagnosis System for Identifying Faulty Components in Digital Circuits. Applied Intelligence 10, 37–52 (1999). https://doi.org/10.1023/A:1008333430997

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1008333430997

Navigation