Optimal fault-detection filtering for non-Gaussian systems via output PDFs
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Dynamic multiple-fault diagnosis with imperfect tests
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Denoising of event-related potential signal based on wavelet method
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
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This paper presents a wavelet-based analytical redundancy method for the detection of faults in dynamic systems. In the proposed approach, consistency checks are carried out after band-limiting the signals under consideration to specific frequency ranges. For this purpose, the discrete wavelet transform is used to establish the frequency bands of analysis and a finite impulse response filter is employed to check the dynamic consistency of the data within each band. The filter weights can be adjusted by a simple parametric identification procedure on the basis of data acquired under normal operating conditions. The proposed method is illustrated by using experimental fault data from an analog computer, which was adjusted to emulate the dynamic response of a servomechanism, as well as simulated data representing a sensor fault scenario in the operation of a Boeing 747 aircraft. For comparison, a standard Luenberger observer fault detection scheme is also employed. The results show that the wavelet method compares favorably with the observer-based scheme in terms of sensitivity to the fault effect, false alarms, and nondetected faults.