DCA-Based Real-Time Residual Useful Life Prediction for Critical Faulty Component
Joint Authors
Zhou, Funa
Gao, Yulin
Wang, Jiayu
Source
Journal of Control Science and Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-21
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Electronic engineering
Information Technology and Computer Science
Abstract EN
Residual useful life (RUL) prediction is significant for condition-based maintenance.
Traditional data-driven RUL prediction method can only predict fault trend of the system rather than RUL of a specific system component.
Thus it cannot tell the operator which component should be maintained.
The innovation of this paper is as follows: (1) Wavelet filtering based method is developed for early detection of slowly varying fault.
(2) Designated component analysis is introduced as a feature extraction tool to define the fault precursor of a specific component.
(3) Exponential life prediction model is established by nonlinear fitting of the historical RUL and the fault size characterized by the statistics used.
Once online detection statistics is obtained, real-time RUL of the critical component can be predicted online.
Simulation shows the effectiveness of this algorithm.
American Psychological Association (APA)
Zhou, Funa& Wang, Jiayu& Gao, Yulin. 2017. DCA-Based Real-Time Residual Useful Life Prediction for Critical Faulty Component. Journal of Control Science and Engineering،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1173570
Modern Language Association (MLA)
Zhou, Funa…[et al.]. DCA-Based Real-Time Residual Useful Life Prediction for Critical Faulty Component. Journal of Control Science and Engineering No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1173570
American Medical Association (AMA)
Zhou, Funa& Wang, Jiayu& Gao, Yulin. DCA-Based Real-Time Residual Useful Life Prediction for Critical Faulty Component. Journal of Control Science and Engineering. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1173570
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1173570