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A Novel Strong Tracking Fault Prognosis Algorithm
Joint Authors
Li, Tianmei
Zhang, Qi
Jiang, Wei
Zheng, Jian-Fei
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-06-08
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Improving the ability to track abruptly changing states and resolving the degeneracy are two difficult problems to particle filter applied to fault prognosis.
In this paper, a novel strong tracking fault prognosis algorithm is proposed to settle the above problems.
In the proposed algorithm, the artificial immunity algorithm is first introduced to resolve the degeneracy problem, and then the strong tracking filter is introduced to enhance the ability to track abruptly changing states.
The particles are updated by strong tracking filter, and better particles are selected by utilizing the artificial immune algorithm to estimate states.
As a result, the degeneracy problem is resolved and the accuracy of the proposed fault prognosis algorithm is improved accordingly.
The feasibility and validity of the proposed algorithm are demonstrated by the simulation results of the standard validation model and the DTS200 system.
American Psychological Association (APA)
Zhang, Qi& Jiang, Wei& Li, Tianmei& Zheng, Jian-Fei. 2015. A Novel Strong Tracking Fault Prognosis Algorithm. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1074437
Modern Language Association (MLA)
Zhang, Qi…[et al.]. A Novel Strong Tracking Fault Prognosis Algorithm. Mathematical Problems in Engineering No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1074437
American Medical Association (AMA)
Zhang, Qi& Jiang, Wei& Li, Tianmei& Zheng, Jian-Fei. A Novel Strong Tracking Fault Prognosis Algorithm. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1074437
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074437