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Adaptive sensor fault detection and identification using particle filter algorithms
Wei T.2; Huang Y.2; Chen C.L.P.2
2009-03-31
Source PublicationIEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
ISSN10946977
Volume39Issue:2Pages:201-213
AbstractSensor fault detection and identification (FDI) is a process of detecting and validating sensor's fault status. Because FDI guarantees system reliable performance, it has received much attention recently. In this paper, we address the problem of online sensor fault identification and validation. For a physical sensor validation system, it contains transitions between sensor normal and faulty states, change of system parameters, and a fusion of noisy readings. A common dynamic state-space model with continuous state variables and observations cannot handle this problem. To circumvent this limitation, we adopt a Markov switch dynamic state-space model to simulate the system: we use discrete-state variables to model sensor states and continuous variables to track the change of the system parameters. Problems in Markov switch dynamic state-space model can be well solved by particle filters, which are popularly used in solving problems in digital communications. Among them, mixture Kalman filter (MKF) and stochastic M-algorithm (SMA) have very good performance, both in accuracy and efficiency. In this paper, we plan to incorporate these two algorithms into the sensor validation problem, and compare the effectiveness and complexity of MKF and SMA methods under different situations in the simulation with an existing algorithm-interactive multiple models. © 2009 IEEE.
KeywordFault detection and isolation (FDI) Mixture Kalman filter (MKF) Monte Carlo technique Particle filter (PF) Sensor failure Sensor validation StochasticM-algorithm (SMA)
DOI10.1109/TSMCC.2008.2006759
URLView the original
Language英語
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Cited Times [WOS]:25   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Limitless Horse Power (LHP) LLC
2.University of Texas at San Antonio
Recommended Citation
GB/T 7714
Wei T.,Huang Y.,Chen C.L.P.. Adaptive sensor fault detection and identification using particle filter algorithms[J]. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews,2009,39(2):201-213.
APA Wei T.,Huang Y.,&Chen C.L.P..(2009).Adaptive sensor fault detection and identification using particle filter algorithms.IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews,39(2),201-213.
MLA Wei T.,et al."Adaptive sensor fault detection and identification using particle filter algorithms".IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 39.2(2009):201-213.
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