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Sensor Fault Detection for Rail Vehicle Suspension Systems with Disturbances and Stochastic Noises

Mao, Zehui, Zhan, Yanhao, Tao, Gang, Jiang, Bin, Yan, Xing-Gang (2016) Sensor Fault Detection for Rail Vehicle Suspension Systems with Disturbances and Stochastic Noises. IEEE Transactions on Vehicular Technology, 66 (6). pp. 4691-4705. ISSN 0018-9545. E-ISSN 1939-9359. (doi:10.1109/TVT.2016.2628054) (KAR id:58634)

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This paper develops a sensor fault detection scheme for rail vehicle passive suspension systems, using a fault detection observer, in the presence of uncertain track regularity and vehicle noises which are modeled as external disturbances and stochastic process signals. To design the fault detection observer, the suspension system states are augmented with the disturbances treated as new states, leading to an augmented and singular system with stochastic noises. Using system output measurements, the observer is designed to generate the needed residual signal for fault detection. Existence conditions for observer design are analyzed and illustrated. In term of the residual signal, both fault detection threshold and fault detectability condition are obtained, to form a systematic detection algorithm. Simulation results on a realistic vehicle system model are presented to illustrate the observer behavior and fault detection performance.

Item Type: Article
DOI/Identification number: 10.1109/TVT.2016.2628054
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Xinggang Yan
Date Deposited: 15 Nov 2016 11:49 UTC
Last Modified: 16 Feb 2021 13:39 UTC
Resource URI: (The current URI for this page, for reference purposes)
Yan, Xing-Gang:
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