Active fault diagnosis based on stochastic tests

Niels K. Poulsen; Henrik Niemann

International Journal of Applied Mathematics and Computer Science (2008)

  • Volume: 18, Issue: 4, page 487-496
  • ISSN: 1641-876X

Abstract

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The focus of this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow us to obtain a fast change detection/isolation by considering the output or an error output from the system. The classical cumulative sum (CUSUM) test will be modified with respect to the AFD approach applied. The CUSUM method will be altered such that it will be able to detect a change in the signature from the auxiliary input signal in an (error) output signal. It will be shown how it is possible to apply both the gain and the phase change of the output signal in CUSUM tests. The method is demonstrated using an example.

How to cite

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Niels K. Poulsen, and Henrik Niemann. "Active fault diagnosis based on stochastic tests." International Journal of Applied Mathematics and Computer Science 18.4 (2008): 487-496. <http://eudml.org/doc/207902>.

@article{NielsK2008,
abstract = {The focus of this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow us to obtain a fast change detection/isolation by considering the output or an error output from the system. The classical cumulative sum (CUSUM) test will be modified with respect to the AFD approach applied. The CUSUM method will be altered such that it will be able to detect a change in the signature from the auxiliary input signal in an (error) output signal. It will be shown how it is possible to apply both the gain and the phase change of the output signal in CUSUM tests. The method is demonstrated using an example.},
author = {Niels K. Poulsen, Henrik Niemann},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {active fault diagnosis; parametric faults; stochastic change detection; closed-loop systems; parameterization},
language = {eng},
number = {4},
pages = {487-496},
title = {Active fault diagnosis based on stochastic tests},
url = {http://eudml.org/doc/207902},
volume = {18},
year = {2008},
}

TY - JOUR
AU - Niels K. Poulsen
AU - Henrik Niemann
TI - Active fault diagnosis based on stochastic tests
JO - International Journal of Applied Mathematics and Computer Science
PY - 2008
VL - 18
IS - 4
SP - 487
EP - 496
AB - The focus of this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow us to obtain a fast change detection/isolation by considering the output or an error output from the system. The classical cumulative sum (CUSUM) test will be modified with respect to the AFD approach applied. The CUSUM method will be altered such that it will be able to detect a change in the signature from the auxiliary input signal in an (error) output signal. It will be shown how it is possible to apply both the gain and the phase change of the output signal in CUSUM tests. The method is demonstrated using an example.
LA - eng
KW - active fault diagnosis; parametric faults; stochastic change detection; closed-loop systems; parameterization
UR - http://eudml.org/doc/207902
ER -

References

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  1. Basseville M. and Nikiforov I. (1993). Detection of Abrupt Changes: Theory and Application, Prentice Hall, Englewood Cliffs, NJ. 
  2. Campbell S., Horton K. and Nikoukhah R. (2002). Auxiliary signal design for rapid multi-model identification using optimization, Automatica 38(8): 1313-1325. Zbl1010.93033
  3. Campbell S., Horton K., Nikoukhah R. and Delebecque F. (2000). Rapid model selection and the separability index, Proceedings of the IFAC Symposium Safeprocess 2000, Budapest, Hungary, pp. 1187-1192. 
  4. Campbell S. and Nikoukhah R. (2004a). Auxiliary Signal Design for Failure Detection, Princeton University Press, Princeton, NJ. Zbl1055.94036
  5. Campbell S. and Nikoukhah R. (2004b). Software for auxiliary signal design, Proceedings of the American Control Conference, Boston, MA, USA, pp. 4414-4419. 
  6. Frank P. and Ding X. (1994). Frequency domain approach to optimally robust residual generation and evaluation for model-based fault diagnosis, Automatica 30(5): 789-804. Zbl0799.93018
  7. Gustafsson F. (2000). Adaptive Filtering and Change Detection, Wiley & Sons, Chichester. 
  8. Kerestecioglu F. (1993). Change Detection and Input Design in Dynamic Systems, Research Studies Press, Baldock, Hertfordshire. Zbl0842.93004
  9. Kerestecioglu F. and Cetin I. (2004). Optimal input design for detection of changes towards unknown hypoteses, International Journal of System Science 35(7): 435-444. Zbl1062.93038
  10. Kerestecioglu F. and Zarrop M. (1994). Input design for detection of abrupt changes in dynamical systems, International Journal of Control 59(4): 1063-1084. Zbl0808.93063
  11. Niemann H. (2003). Dual Youla parameterization, IEE Proceedings - Control Theory and Applications 150(5): 493-497. 
  12. Niemann H. (2005). Fault tolerant control based on active fault diagnosis, Proceedings of the American Control Conference, Portland, OR, USA, pp. 2224-2229. 
  13. Niemann H. (2006). A setup for active fault diagnosis, IEEE Transactions on Automatic Control 51(9): 1572-1578. 
  14. Niemann H. and Poulsen N. (2005). Active fault diagnosis in closed-loop systems, Proceedings of the 16th IFAC World Congress, Prague, Czech Republic, (on DVD). Zbl1155.93427
  15. Nikoukhah R. (1994). Innovations generation in the presence of unknown inputs: Application to robust failure detection, Automatica 30(12): 1851-1867. Zbl0815.93080
  16. Nikoukhah R. (1998). Guaranteed active failure detection and isolation for linear dynamical systems, Automatica 34(11): 1345-1358. Zbl0961.93006
  17. Nikoukhah R., Campbell S. and Delebecque F. (2000). Detection signal design for failure detection: A robust approach, International Journal of Adaptive Control and Signal Processing 14: 701-724. Zbl0988.93078
  18. Poulsen N. and Niemann H. (2007). Stochastic change detection based on an active fault diagnosis approach, Proceedings of the 8th Conference on Diagnostics of Processes and Systems, DPS 2007, Słubice, Poland, pp. 113-120. 
  19. Tay T., Mareels I. and Moore J. (1997). High Performance Control, Birkhäuser, Boston, MA. Zbl0889.93001
  20. Zhang X. (1989). Auxiliary Signal Design in Fault Detection and Diagnosis, Springer Verlag, Heidelberg. Zbl0679.68207

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