Survey and application of sensor fault detection and isolation schemes

Control Engineering Practice

Volumn 19, Issue 7, 2011, Pages 658-674

  Samy, Ihab ^a   Postlethwaite, Ian ^b   Gu, Da Wei ^c  

^a CRANFIELD UNIVERSITY   (United Kingdom)

^b NORTHUMBRIA UNIVERSITY   (United Kingdom)

^c UNIVERSITY OF LEICESTER   (United Kingdom)

Author keywords

Fault accommodation; Fault isolation; Multiple sensor fault detection; Neural networks; UAV

Indexed keywords

COMPUTATIONAL SPEED; FAULT ACCOMMODATION; FAULT ISOLATION; FLIGHT DATA; LONGITUDINAL MOTION; MEASUREMENT NOISE; MODEL-BASED; MULTIPLE SENSOR FAULT DETECTION; NONLINEAR ENVIRONMENTS; NONLINEAR STRUCTURE; ONLINE LEARNING; PENTIUM PROCESSORS; PROCESSING TIME; REAL SYSTEMS; SENSOR FAULT; SENSOR FAULT DETECTION; SENSOR NOISE; SENSOR REDUNDANCY; SINGLE SENSOR; TIME GAP; UAV; WIND GUST;

DATA PROCESSING; NEURAL NETWORKS; SENSORS;

FAULT DETECTION;

EID: 79957944993     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.conengprac.2011.03.002     Document Type: Article

References (43)

1. An, Y. (1998). A design of fault tolerant flight control systems for sensor and actuator failures using on-line learning neural networks. Ph.D. Thesis. Morgantown, West Virginia: Dept. of Mech. and Aerospace Eng.
2. Alessandri A., Caccia M., Veruggio G. Fault detection of actuator faults in unmanned underwater vehicle. Control Engineering Practise 1999, 7:357-368.
3. Betta G., Pietrosanto A. Instrument fault detection and isolation: State of the art and new research trends. IEEE Transactions on Instrumentation and Measurement 2000, 49(1):100-107.
4. Buonanno, A., & Cook, M.V. (2005). An aerodynamic simulation model of the Eclipse UAV, Internal Report FLAV-A01-002.
5. Campa G., Fravolini M.L., Napolitano M., Seanor B. Neural networks sensor validation for the flight control system of a B777 research model. American Control Conference 2002, 1:412-417.
6. Campa, G., Krishnamurty, M., Gautam, M., Napolitano, M. R., & Perhinschi, M. (2006). A neural network based sensor validation scheme for heavy-duty diesel engines. In Proceedings of the 14th Mediterranean Conference on Control and Automation, Ancona, Italy.
7. Capriglione D., Liguori C., Pianese C., Pietrosanto A. Online sensor fault detection, isolation and accommodation in automotive engines. IEEE Transactions on Instrumentation and Measurement 2003, 52(4):1182-1189.
8. Chiang, C.Y., Juang, J.C., & Youssef, H. (1994). Neural network approach to aircraft fault detection, isolation and estimation design. AIAA-1994-273.
9. Clark R.N. Instrument fault detection. IEEE Transactions on Aerospace and Electronic Systems 1978, 14(3):456-465.
10. FAA (2007). Unmanned Aircraft Systems (UAS) Certifications and Authorizations. U.S. Dept. of Transportation. Accessed 5 November 2007. http://www.faa.gov/aircraft/air_cert/design_approvals/uas/cert/.
11. Franchi P.La Grand designs: An EC-funded research project has unveiled its proposals for a new generation of aircraft that are intended to give Europe the edge in the civil UAV sector. Flight International 2005, 109-114.
12. Frank, P.M. (1987) Advanced fault detection and isolation schemes using nonlinear and robust observers. In: Proceedings of the 10th IFAC congress on automatic control (pp. 63-68). Vol. 3. Munchen.
13. Frank P.M. Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy- A survey and some new results. Automatica 1990, 26(3):459-474.
14. Fravolini, M.L., Campa, G., Napolitano, K. & Song, Y. (2001). Minimal resource allocating networks for aircraft SFDIA. In IEEE international conference on advanced intelligent mechatronics. Como, Italy.
15. Gertler J. Survey of model-based failure detection and isolation in complex plants. IEEE Control Systems magazine 1988, 8:3-11.
16. Heredia, G., Ollero, A., Mahtani, R., Remub, V., & Mausial, M. (2005). Detection of Sensor Faults in Autonomous Helicopters. In Proceedings of the 2005 IEEE international conference on robotics and automation. Barcelona, Spain.
17. Huang, W., Wang, K., & Chen, Q. (1996). Sensor failure detection and data recovery based on neural network. AIAA-1996-2932.
18. Isermann R., Balle P. Trends in the application of model-based fault detection and diagnosis of technical processes. Control Engineering Practise 1997, 5:709-719.
19. Isermann, R. 2004. Model based fault detection and diagnosis-Status and applications. In Proceedings of the 16th Symposium on Automatic Control in Aerospace. St. Petersburg.
20. Isermann R. Process fault detection based on modelling and estimation methods: A survey. Automatica 1984, 20:387-404.
21. Kadirkamanathan V., Niranjan M. A function estimation approach to sequential learning with neural networks. Neural Computing 1993, 5:954-975.
22. Larder B., Azzam H., Trammel C., Vossler G. Smith industries HUMS: Changing the M from monitoring to management. IEEE Aerospace Conference Proceedings 2000, 6:449-455.
23. Li Y., Sundararajan N., Saratchandran P. Analysis of minimal radial basis function network algorithm for real time identification of nonlinear dynamic systems. IEEE Control Theory and Application 2000, 4:476-484.
24. Mattern, D., Jaw, L., Guo, T. H., Graham, R., & McCoy, W. (1998). Using neural networks for sensor validation. AIAA-1998-3547.
25. Moller, J., Litt, J., & Guo, T. H. (1998). Neural network based sensor validation for turboshaft engines. AIAA-1998-3605.
26. Montgomery R.C., Caglayan A.K. Failure accommodation in digital flight control systems by Bayesian decision theory. Journal of Aircraft 1976, 13(2):69-75.
27. Motyka, P., Bonnice, W., Hall, S., & Wagner, E. (1985). The evaluation of failure detection and isolation algorithms for restructurable control. NASA Contractor Report 177983.
28. Napolitano, M., Neppach, C., Casdorph, V., & Innocenti, M. (1994). Sensor failure detection, identification and accommodation using online learning neural architectures. AIAA-1994-3598.
29. Napolitano M., Neppach C., Casdorph V., Innocenti M. Neural network based scheme for sensor failure detection, identification and accommodation. AIAA Journal of Guidance Control and Dynamics 1995, 18(6):1280-1286.
30. Napolitano, M., Windon, D., Casanova, J., & Innocenti, M. (1996). A comparison between Kalman filter and neural network approaches for sensor validation. AIAA-1996-3894.
31. Napolitano, N., An, Y., Seanor, B., Pispistos, S., & Martinelli, D. (1999). Application of a neural sensor validation scheme to actual Boeing B737 flight data. In Proceedings of the AIAA guidance navigation and control conference.
32. Napolitano M., An Y., Seanor B. A fault tolerant flight control system for sensor and actuator failures using neural networks. Aircraft Design 2000, 3:103-128.
33. Neppach, C., & Casdorph, V. (1995). Sensor failure detection, identification and accommodation in a system without sensor redundancy. AIAA-1995-11.
34. Osder S. Practical view of redundancy management application and theory. AIAA Journal of Guidance, Control and Dynamics 1999, 22(1):12-21.
35. Patton R.J., Frank P.M., Clark R.N. Fault diagnosis in dynamic systems-theory and applications 1989, Prentice Hall, London.
36. Samy, I., Postlethwaite, I., & Gu, D. (2008). Neural network based sensor validation scheme demonstrated on an Unmanned Air (UAV) model In Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico, Dec, 9-11, 2008.
37. Samy I., Postlethwaite I., Gu D. A comparative study of NN and EKF based SFDA schemes with application to a nonlinear UAV model. International Journal of Control 2010, 83:1025-1043.
38. Samy I., Postlethwaite I., Gu D. SFDIA of consecutive sensor faults using neural networks-demonstrated on a UAV. International Journal of Control 2010, 83:2308-2327.
39. Sheng, W., Giampiero, C., Napolitano, M., & Fravolini, M. (2002). Online learning RBF neural networks for sensor validation. AIAA-2002-4996.
40. Trammel C., Vossler G., Feldmann M. UK Ministry of Defence generic health and usage monitoring system (GenHUMS). Journal of Aircraft Engineering and Aerospace Technology 1997, 69:414-422.
41. Willsky A.S. A survey of design methods for failure detection in dynamic systems. Automatica 1976, 12(6):601-611.
42. Willsky, A.S., Deyst, J.J., & Crawford, B.S. (1974). Adaptive filtering and self-test methods for failure detection and compensation. In Proceedings of the American Control Conference. Austin, USA.
43. Wong K.C. Aerospace industry opportunities in Australia-unmanned aerial vehicles (UAVs). Department of Aeronautical Engineering, University of Sydney 2007.