Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator
Joint Authors
Zhang, Qinghua
Qin, Aisong
Hu, Qin
Sun, Guoxi
He, Jun
Lin, Shuiquan
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-22
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Remaining useful life (RUL) prediction can provide early warnings of failure and has become a key component in the prognostics and health management of systems.
Among the existing methods for RUL prediction, the Wiener-process-based method has attracted great attention owing to its favorable properties and flexibility in degradation modeling.
However, shortcomings exist in methods of this type; for example, the degradation indicator and the first predicting time (FPT) are selected subjectively, which reduces the prediction accuracy.
Toward this end, this paper proposes a new approach for predicting the RUL of rotating machinery based on an optimal degradation indictor.
First, a genetic programming algorithm is proposed to construct an optimal degradation indicator using the concept of FPT.
Then, a Wiener model based on the obtained optimal degradation indicator is proposed, in which the sensitivities of the dimensionless parameters are utilized to determine the FPT.
Finally, the expectation of the predicted RUL is calculated based on the proposed model, and the estimated mean degradation path is explicitly derived.
To demonstrate the validity of this model, several experiments on RUL prediction are conducted on rotating machinery.
The experimental results indicate that the method can effectively improve the accuracy of RUL prediction.
American Psychological Association (APA)
Qin, Aisong& Zhang, Qinghua& Hu, Qin& Sun, Guoxi& He, Jun& Lin, Shuiquan. 2017. Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator. Shock and Vibration،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1204835
Modern Language Association (MLA)
Qin, Aisong…[et al.]. Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator. Shock and Vibration No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1204835
American Medical Association (AMA)
Qin, Aisong& Zhang, Qinghua& Hu, Qin& Sun, Guoxi& He, Jun& Lin, Shuiquan. Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator. Shock and Vibration. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1204835
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1204835