Skip to main content

BRIDGE: Matching Model-Based Diagnosis from FDI and DX Perspectives

  • Chapter
  • First Online:
Fault Diagnosis of Dynamic Systems

Abstract

As introduced in Chap. 1, the goal diagnosis is to identify the possible causes of explaining a set of observed symptoms. Several communities have addressed the diagnosis problem. This chapter establishes the correspondence of concepts and compares the techniques used by the FDI and DX model-based diagnosis communities.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    This framework has been extended to fault models in [12].

  2. 2.

    The hitting sets of a collection of sets are given by the sets that intersect every set of the collection.

References

  1. Adrot, O., Maquin, D., Ragot, J.: Fault detection with model parameter structured uncertainties. In: Proceedings of the European Control Conference, ECC’99. Karlsruhe (1999)

    Google Scholar 

  2. Armengol, J., Bregon, A., Escobet, T., Gelso, E., Krysander, M., Nyberg, M., Olive, X., Pulido, B., Travé-Massuyès, L.: Minimal Structurally Overdetermined sets for residual generation: a comparison of alternative approaches. In: Proceedings of the 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, Safeprocess’09 (2009)

    Google Scholar 

  3. Basseville, M., Nikiforov, I.: Detection of Abrupt Changes: Theory and Application. Citeseer (1993)

    Google Scholar 

  4. Blanke, M., Kinnaert, M., Lunze, J., Staroswiecki, M.: Diagnosis and Fault-Tolerant Control. Springer, Berlin (2003)

    Book  Google Scholar 

  5. Chow, E., Willsky, A.: Analytical redundancy and the design of robust failure detection systems. IEEE Trans. Autom. Control 29(7), 603–614 (1984)

    Article  MathSciNet  Google Scholar 

  6. Cordier, M., Dague, P., Lévy, F., Montmain, J., Staroswiecki, M., Travé-Massuyès, L.: Conflicts versus analytical redundancy relations: a comparative analysis of the model based diagnosis approach from the artificial intelligence and automatic control perspectives. IEEE Trans. Syst. Man Cybern. Part B 34(5), 2163–2177 (2004)

    Article  Google Scholar 

  7. Denis-Vidal, L., Joly-Blanchard, G., Noiret, C.: Some effective approaches to check the identifiability of uncontrolled nonlinear systems. Math. Comput. Simul. 57(1–2), 35–44 (2001)

    Article  MathSciNet  Google Scholar 

  8. Dubuisson, B.: Automatique et statistiques pour le diagnostic. Hermes Science Europe Ltd (2001)

    Google Scholar 

  9. Gertler, J.: Analytical redundancy methods in failure detection and isolation. In: Preprints of the IFAC SAFEPROCESS Symposium, pp. 9–21 (1991)

    Google Scholar 

  10. Gertler, J.: Fault Detection and Diagnosis in Engineering Systems. Marcel Deker, New York City (1998)

    Google Scholar 

  11. Katsillis, G., Chantler, M.: Can dependency-based diagnosis cope with simultaneous equations. In: Proceedings of the 8th International Workshop on Principles of Diagnosis DX-97, pp. 51–59 (1997)

    Google Scholar 

  12. Kleer, J., Mackworth, A., Reiter, R.: Characterizing diagnoses and systems. Artif. Intell. 56(2–3), 197–222 (1992)

    Article  MathSciNet  Google Scholar 

  13. Krysander, M., Aslund, J., Nyberg, M.: An efficient algorithm for finding minimal overconstrained subsystems for model-based diagnosis. IEEE Trans. Syst. Man Cybern. Part A: Syst. Hum. 38(1), 197–206 (2008)

    Article  Google Scholar 

  14. Loiez, E., Taillibert, P.: Polynomial temporal band sequences for analog diagnosis. In: Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence IJCAI-97, Nagoya, Japan, 23–29 Aug 1997, p. 474 (1997)

    Google Scholar 

  15. Patton, R., Chen, J.: A re-examination of the relationship between parity space and observer-based approaches in fault diagnosis. Eur. J. Diagn. Saf. Autom. 1(2), 183–200 (1991)

    Google Scholar 

  16. Patton, R., Frank, P., Clark, R.: Fault diagnosis in dynamic systems. Theory and Applications (1989)

    Google Scholar 

  17. Pulido, B., Gonzalez, C.: Possible conflicts: a compilation technique for consistency-based diagnosis. IEEE Trans. Syst. Man Cybern. - Part B: Cybern. 34(5), 2192–2206 (2004)

    Article  Google Scholar 

  18. Qiu, Z., Gertler, J.: Robust FDI and \(H_{\inf }\) optimization. In: Proceedings of the 32nd IEEE Conference on Control and Decision CDC’93. San Antonio, Texas (1993)

    Google Scholar 

  19. Reiter, R.: A theory of diagnosis from first principles. Artif. Intell. 32(1), 57–95 (1987)

    Article  MathSciNet  Google Scholar 

  20. Sachenbacher, M., Williams, B.: Diagnosis as semiring-based constraint optimization. In: Proceedings of the European Conference on Artificial Intelligence ECAI’04, vol. 16, p. 873 (2004)

    Google Scholar 

  21. Staroswiecki, M., Comtet-Varga, G.: Analytical redundancy relations for fault detection and isolation in algebraic dynamic systems. Automatica 37(5), 687–699 (2001)

    Article  MathSciNet  Google Scholar 

  22. Staroswiecki, M., Declerck, P.: Analytical redundancy in non linear interconnected systems by means of structural analysis. In: Proceedings of the IFAC Symposium on Advanced Information Processing in Automatic Control, pp. 51–55 (1989)

    Google Scholar 

  23. Travé-Massuyès, L.: Bridging control and artificial intelligence theories for diagnosis: a survey. Eng. Appl. Artif. Intell. 27, 1–16 (2014)

    Article  Google Scholar 

  24. Venkatasubramanian, V., Rengaswamy, R., Kavuri, S.N.: A review of process fault detection and diagnosis part ii: qualitative models and search strategies. Comput. Chem. Eng. 27(3), 313–326 (2003)

    Article  Google Scholar 

  25. Venkatasubramanian, V., Rengaswamy, R., Kavuri, S.N., Yin, K.: A review of process fault detection and diagnosis part iii: process history based methods. Comput. Chem. Eng. 27(3), 327–346 (2003). https://doi.org/10.1016/S0098-1354(02)00162-X-a3

  26. Venkatasubramanian, V., Rengaswamy, R., Yin, K., Kavuri, S.N.: A review of process fault detection and diagnosis part i: quantitative model-based methods. Comput. Chem. Eng. 27(3), 293–311 (2003)

    Article  Google Scholar 

  27. Vento, J., Puig, V., Sarrate, R., Travé-Massuyès, L.: Fault detection and isolation of hybrid systems using diagnosers that reason on components. IFAC Proc. Vol. 45(20), 1250–1255 (2012)

    Article  Google Scholar 

  28. Washio, T., Motoda, H., Niwa, Y., INSS, I.: Discovering admissible model equations from observed data. In: Proceedings of the 16th International Joint Conference on Artificial Intelligence IJCAI’99, vol. 2, pp. 772–779. Citeseer (1999)

    Google Scholar 

  29. Williams, B., Ragno, R.: Conflict-directed A* and its role in model-based embedded systems. J. Discret. Appl. Math. Citeseer (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Louise Travé-Massuyès .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Travé-Massuyès, L., Escobet, T. (2019). BRIDGE: Matching Model-Based Diagnosis from FDI and DX Perspectives. In: Escobet, T., Bregon, A., Pulido, B., Puig, V. (eds) Fault Diagnosis of Dynamic Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-17728-7_7

Download citation

Publish with us

Policies and ethics