Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지
DOI QR코드

DOI QR Code

Model-Free Hybrid Fault Detection and Isolation For UAV Inertial Measurement Sensors

무인기 관성측정 센서의 비모델 복합 고장진단기법

  • 김승균 (서울대학교 기계항공공학부 항공우주공학) ;
  • 김유단 (서울대학교 기계항공공학부 항공우주공학)
  • Published : 2005.03.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, a redundancy management system for aircraft is studied, and FDI (Fault Detection and Isolation) algorithm of inertial sensor system is proposed. UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional FDI method cannot isolate multiple faults in a triple redundancy system. In this paper, hardware based FDI technique is proposed, which combines a parity equation approach with the wavelet based technique, which is a model-free FDI method. To verify the effectiveness of the proposed FDI method, numerical simulations are performed.

Keywords

References

  1. S. K. Yung, and D. W Clarke, 'Local sensor validation', Measurement and Control, vol. 22, no. 2, pp. 132-141, 1989 https://doi.org/10.1177/002029408902200502
  2. R. N. Clark, P. M. Frank, and R. J. Patton, Fault Diagnosis in Dynamic Systems: Theory and Applications, Prentice Hall, New York,1989
  3. R. J. Patton, P. M. Frank, and R. N. Clark, Issues of Fault Diagnosis for Dynamic Systems, Springer-Verlag, London, 2000
  4. Q. Zhang, and Y. Yan, 'A wavelet-based approach to abrupt fault detection and diagnosis of densors', IEEE Trans. on Instrument and Measurement, vol. 50, no. 5,pp. 1389-1393,2001 https://doi.org/10.1109/19.963215
  5. R. Isermann, and P. Balle, 'Trends in the application of model-based fault detection and diagnosis of technical processes', Control Engineering Practice, vol. 5,no. 5, pp. 709-719,1997 https://doi.org/10.1016/S0967-0661(97)00053-1
  6. E. C. Larson, B. E. Parker Jr., and B. R. Clark, 'Model-based sensor and actuator fault detection and isolation', Proceedings of the American Control Conference, Anchorage, AK, pp. 4215-4219, May 2002 https://doi.org/10.1109/ACC.2002.1024593
  7. P. M. Frank, 'Fault diagnosis in dynamic system using analytical and knowledge based redundancy-a survey and some new results', Automatica, vol. 26, no. 3, pp. 459-474, 1990 https://doi.org/10.1016/0005-1098(90)90018-D
  8. R. J. Patton, 'Robust model based fault diagnosis: the state of the art', Prodeedings of IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, Espoo, Finland, pp.1-24,1994
  9. R. Isermann, 'Model based fault detection and diagnosis methods', Control Engineering Practice, vol. 5, no. 5, pp. 639-652,1997 https://doi.org/10.1016/S0967-0661(97)00046-4
  10. I. Daubechies, Ten Lectures on Wavelets, SIAM, Philadelphia, 1992
  11. A. Bogges, and F. J. Narcowich, A First Course in Wavelets with F ourier Analysis, Prentice Hall, Upper Saddle River, NJ, 2001
  12. R. M. Rao and A. S. Bopardikar, Wavelet Transforms. Addison Wesley Longman, 1998
  13. X. Li, 'Discrete wavelet transform for tool breakage monitoring', International Journal of Machine Tools and Manufacture, vol. 39, no. 12, pp. 1935-1944,1999 https://doi.org/10.1016/S0890-6955(99)00021-8
  14. J. D. Johnson, 'Real-time identification of flutter boundaries using the discrete wavelet transform', Journal of Guidance, Control, And Dynamics, vol. 25, no. 2, pp. 334-339,2002 https://doi.org/10.2514/2.4886
  15. F. Botella, 'A real-time earthquake detector with prefiltering by wavelets', Computers and Geosciences, vol. 29, no. 7, pp. 911-919,2003 https://doi.org/10.1016/S0098-3004(03)00099-2
  16. S. Santoso, E. J. Powers, W. M. Grady, and P. Hofmann, 'Power quality assessment via wavelet transform analysis', IEEE transactions on Power Delivery, vol. 11, no. 2, pp. 924-930, 1996 https://doi.org/10.1109/61.489353
  17. S. Mallat, 'A theory for multiresolution signal decomposition: the wavelet representation', IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 11, no. 7, pp. 674-693, 1989 https://doi.org/10.1109/34.192463
  18. M. Misiti, Y. Misiti, G. Oppenheim, and J-H. Poggi, 'Wavelet toolbox for use with MATLAB, user's guide version 2', The Mathworks, Inc., pp. 6-62~6-65, 2002