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Time-Varying Fault Diagnosis for Asynchronous Multisensor Systems Based on Augmented IMM and Strong Tracking Filtering
Joint Authors
Peng, Kai-xiang
Hu, Yanyan
Xue, Xiaoling
Jin, Zengwang
Source
Journal of Control Science and Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-02
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Electronic engineering
Information Technology and Computer Science
Abstract EN
A fault detection, isolation, and estimation approach is proposed in this paper based on Interactive Multimodel (IMM) fusion filtering and Strong Tracking Filtering (STF) for asynchronous multisensors dynamic systems.
Time-varying fault is considered and a candidate fault model is built by augmenting the unknown fault amplitude directly into the system state for each kind of possible fault mode.
By doing this, the dilemma of predetermining the fault extent as model design parameters in traditional IMM-based approaches is avoided.
After that, the time-varying fault amplitude is estimated based on STF using its strong ability to track abrupt changes and robustness against model uncertainties.
Through fusing information from multiple sensors, the performance of fault detection, isolation, and estimation is approved.
Finally, a numerical simulation is performed to demonstrate the feasibility and effectiveness of the proposed method.
American Psychological Association (APA)
Hu, Yanyan& Xue, Xiaoling& Jin, Zengwang& Peng, Kai-xiang. 2018. Time-Varying Fault Diagnosis for Asynchronous Multisensor Systems Based on Augmented IMM and Strong Tracking Filtering. Journal of Control Science and Engineering،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1183026
Modern Language Association (MLA)
Hu, Yanyan…[et al.]. Time-Varying Fault Diagnosis for Asynchronous Multisensor Systems Based on Augmented IMM and Strong Tracking Filtering. Journal of Control Science and Engineering No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1183026
American Medical Association (AMA)
Hu, Yanyan& Xue, Xiaoling& Jin, Zengwang& Peng, Kai-xiang. Time-Varying Fault Diagnosis for Asynchronous Multisensor Systems Based on Augmented IMM and Strong Tracking Filtering. Journal of Control Science and Engineering. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1183026
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1183026