Advertisement

Abstract

This chapter gives an overview of main traditional fault diagnosis techniques, including hardware redundancy based technique, signal processing based fault diagnosis and plausibility test, and their classification. The model-based fault diagnosis is then introduced in relationship with these traditional fault diagnosis techniques. It is followed by a review of the historical development of the model-based fault diagnosis technique and the major tasks in designing a model-based fault diagnosis system.

References

  1. 1.
    Alcorta-Garcia, E., Frank, P.M.: On the relationship between observer and parameter identification based approaches to fault detection. In: Proc. of the 14th IFAC World Congress, vol. N, pp. 25–29 (1996) Google Scholar
  2. 12.
    Basseville, M., Nikiforov, I.: Detection of Abrupt Changes – Theory and Application. Prentice-Hall, Englewood Cliffs (1993) Google Scholar
  3. 15.
    Blanke, M., Kinnaert, M., Lunze, J., Staroswiecki, M.: Diagnosis and Fault-Tolerant Control. Springer, Berlin (2003) MATHGoogle Scholar
  4. 25.
    Chen, J., Patton, R.J.: Robust Model-Based Fault Diagnosis for Dynamic Systems. Kluwer Academic, Boston (1999) MATHCrossRefGoogle Scholar
  5. 32.
    Delmaire, G., Cassar, J.P., Starroswiekci, M.: Identification and parity space approaches for fault detection in SISO systems including modelling errors. In: Proc. of the 33rd IEEE CDC, pp. 1767–1772 (1994) Google Scholar
  6. 35.
    Ding, S.X., Ding, E.L., Jeinsch, T.: An approach to analysis and design of observer and parity relation based FDI systems. In: Proc. 14th IFAC World Congress, pp. 37–42 (1999) Google Scholar
  7. 60.
    Frank, P.M.: Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy – A survey. Automatica 26, 459–474 (1990) MATHCrossRefGoogle Scholar
  8. 61.
    Frank, P.M.: Enhancement of robustness in observer-based fault detection. Internat. J. Control 59, 955–981 (1994) MathSciNetMATHCrossRefGoogle Scholar
  9. 62.
    Frank, P.M.: Analytical and qualitative model-based fault diagnosis – A survey and some new results. Eur. J. Control 2, 6–28 (1996) MATHGoogle Scholar
  10. 63.
    Frank, P.M., Ding, S.X., Marcu, T.: Model-based fault diagnosis in technical processes. Trans. Inst. Meas. Control 22, 57–101 (2000) Google Scholar
  11. 65.
    Frank, P.M., Ding, X.: Survey of robust residual generation and evaluation methods in observer-based fault detection systems. J. Process Control 7(6), 403–424 (1997) CrossRefGoogle Scholar
  12. 74.
    Gertler, J.J.: Analytical redundancy methods in fault detection and isolation. In: Proc. the 1st IFAC/IMACS Symp. SAFEPROCESS ’91 (1991) Google Scholar
  13. 75.
    Gertler, J.J.: Diagnosing parametric faults: From parameter estimation to parity relation. In: Proc. of ACC 95, pp. 1615–1620 (1995) CrossRefGoogle Scholar
  14. 76.
    Gertler, J.J.: Fault Detection and Diagnosis in Engineering Systems. Dekker, New York (1998) Google Scholar
  15. 79.
    Gertler, J.: Survey of model-based failure detection and isolation in complex plants. IEEE Control Syst. Mag. 3, 3–11 (1988) CrossRefGoogle Scholar
  16. 84.
    Gustafsson, F.: Adaptive Filtering and Change Detection. Wiley, New York (2000) Google Scholar
  17. 90.
    Hou, M., Mueller, P.: Fault detection and isolation observers. Internat. J. Control 60, 827–846 (1994) MathSciNetMATHCrossRefGoogle Scholar
  18. 96.
    Isermann, R.: Process fault detection based on modeling and estimation methods – A survey. Automatica 20, 387–404 (1984) MATHCrossRefGoogle Scholar
  19. 98.
    Isermann, R.: Fault Diagnosis Systems. Springer, Berlin (2006) Google Scholar
  20. 108.
    Kinnaert, M.: Fault diagnosis based on analytical models for linear and nonlinear systems – A tutorial. In: Proc. of IFAC SAFEPROCESS, pp. 37–50 (2003) Google Scholar
  21. 120.
    Mangoubi, R.: Robust Estimation and Failure Detection. Springer, New York (1998) CrossRefGoogle Scholar
  22. 139.
    Patton, R.J.: Robust model-based fault diagnosis: The state of the art. In: Proc. of IFAC Symp. SAFEPROCESS, pp. 1–27 (1994) Google Scholar
  23. 141.
    Patton, R.J., Frank R, P.M. (eds.): Fault Diagnosis in Dynamic Systems, Theory and Applications. Prentice-Hall, Englewood Cliffs (1989) Google Scholar
  24. 142.
    Patton, R.J., Frank R, P.M. (eds.): Issues of Fault Diagnosis for Dynamic Systems. Springer, London (2000) Google Scholar
  25. 157.
    Simani, S., Fantuzzi, S., Patton, R.J.: Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques. Springer, London (2003) Google Scholar
  26. 167.
    Venkatasubramanian, V., Rengaswamy, R., Yin, K., Kavuri, S.: Review of process fault detection and diagnosis part I: Quantitative model-based methods. Comput. Chem. Eng. 27, 293–311 (2003) CrossRefGoogle Scholar
  27. 181.
    Willsky, A.S.: A survey of design methods for failure detection in dynamic systems. Automatica 12, 601–611 (1976) MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Steven X. Ding
    • 1
  1. 1.Inst. Automatisierungstechnik und Komplexe Systeme (AKS)Universität Duisburg-EssenDuisburgGermany

Personalised recommendations