Incipient fault diagnosis of dynamical systems using online approximators

• Published in: IEEE transactions on automatic control Vol. 43; no. 11; pp. 1612 - 1617
• Main Authors: Demetriou, M.A., Polycarpou, M.M.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.1998; Institute of Electrical and Electronics Engineers
• Subjects: Algorithm design and analysis; Applied sciences; Automatic control; Computer science; control theory; systems; Control systems; Control theory. Systems; Delay lines; Delay systems; Exact sciences and technology; Fault detection; Fault diagnosis; Linear systems; Miscellaneous; Riccati equations; Robust stability; Non linear estimation; Stability; Failure detection; Robustness; Performance analysis; Dynamical system; Non linear system; Fault diagnostic
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/9.728881

Detection of incipient (slowly developing) faults is crucial in automated maintenance problems where early detection of worn equipment is required. In this paper, a general framework for model-based fault detection and diagnosis of a class of incipient faults is developed. The changes in the system dynamics due to the fault are modeled as nonlinear functions of the state and input variables, while the time profile of the failure is assumed to be exponentially developing. An automated fault diagnosis architecture using nonlinear online approximators with an adaptation scheme is designed and analyzed. A simulation example of a simple nonlinear mass-spring system is used to illustrate the results.