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Fault Detection Characterization, Design, and Reliability Analysis Open Access


Other title
fault detection
Type of item
Degree grantor
University of Alberta
Author or creator
Yang, Shuonan
Supervisor and department
Zhao, Qing (Electrical and Computer Engineering)
Examining committee member and department
Chen, Tongwen (Electrical and Computer Engineering)
Dubljevic, Stevan (Chemical and Materials Engineering)
Zhao, Qing (Electrical and Computer Engineering)
Zhang, Youmin (Mechanical & Industrial Engineering, Concordia University)
Tavakoli, Mahdi (Electrical and Computer Engineering)
Department of Electrical and Computer Engineering
Control Systems
Date accepted
Graduation date
Doctor of Philosophy
Degree level
This thesis develops fault detection characterization, design, and reliability analysis within a real-time, multilayered fault detection and diagnosis (FDD) framework proposed according to fault tolerant control systems (FTCS). With the development of sophisticated control and monitoring systems, it has become more challenging to carry out routine maintenance, tuning, troubleshooting, and thus keep the systems operate in their desired or optimal states. Nevertheless, the system is required to present competitive performance and timely response to abnormal conditions. Compared with pure data-driven FD techniques, integrated schemes with model-based FD approaches utilize the available inherent dynamic relationship among various signals hence can render more precise diagnosis results. Fitting in the FTCS scope, the real-time integrated FDD framework is thus highlighted as a strategic solution platform, where various specific FD approaches may be conceived and realized. Within the framework, research has been carried out in various aspects, including but not limited to fault detection (FD) design/characterization, real-time frequency estimation, and reliability of fault detection. Firstly, as the major part of the thesis, FD design/characterization takes up more than two chapters where analytical forms characterizing the (first) detection/hitting time (FHT) are developed based on the general-likelihood ratio (GLR) detection method. Both probability expressions and single-valued performance indices are proposed for both additive and multiplicative faults. Secondly, as a substantial technical solution promoted by FD techniques, online frequency estimation has been researched using the gradient estimator approach with leakage. In the last research topic, semi-Markov kernel modeling and real-time reliability are discussed with respect to long term fault and detector sequences. The characterization and design plans have been tested on practical data sequences and industrial system models, demonstrating the feasibility of implementation.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
S. Yang, Q. Zhao, “Probability distribution characterisation of fault detection delays and false alarms,” IET Control Theory & Applications, 6(7), 2012, pp. 953–962.S. Yang, Q. Zhao, “Real-time frequency estimation for sinusoidal signals with application to robust fault detection,” Int. J. Adapt. Control Signal Process, 26, 2012, DOI: 10.1002/acs.2308.S. Yang, Q. Zhao, “Statistical characterization of the GLR based fault detection,” Proc. American Control Conference, 2011, pp. 3778–3783.S. Yang, Q. Zhao, “Real-time frequency estimation of sinusoids with low-frequency disturbances,” Proc. American Control Conference, 2011, pp. 4275–4280.

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