Fault Detection for Turbine Engine Disk Based on Adaptive Weighted One-Class Support Vector Machine
Joint Authors
Chen, Jiusheng
Zhang, Xiaoyu
Xu, Xingkai
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-28
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Fault detection for turbine engine components is becoming increasingly important for the efficient running of commercial aircraft.
Recently, the support vector machine (SVM) with kernel function is the most popular technique for monitoring nonlinear processes, which can better handle the nonlinear representation of fault detection of turbine engine disk.
In this paper, an adaptive weighted one-class SVM-based fault detection method coupled with incremental and decremental strategy is proposed, which can efficiently solve the time series data stream drifting problem.
To update the efficient training of the fault detection model, the incremental strategy based on the new incoming data and support vectors is proposed.
The weight of the training sample is updated by the variations of the decision boundaries.
Meanwhile, to increase the calculating speed of the fault detection model and reduce the redundant data, the decremental strategy based on the k-nearest neighbor (KNN) is adopted.
Based on time series data stream, numerical simulations are conducted and the results validated the superiority of the proposed approach in terms of both the detection performance and robustness.
American Psychological Association (APA)
Chen, Jiusheng& Xu, Xingkai& Zhang, Xiaoyu. 2020. Fault Detection for Turbine Engine Disk Based on Adaptive Weighted One-Class Support Vector Machine. Journal of Electrical and Computer Engineering،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1184050
Modern Language Association (MLA)
Chen, Jiusheng…[et al.]. Fault Detection for Turbine Engine Disk Based on Adaptive Weighted One-Class Support Vector Machine. Journal of Electrical and Computer Engineering No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1184050
American Medical Association (AMA)
Chen, Jiusheng& Xu, Xingkai& Zhang, Xiaoyu. Fault Detection for Turbine Engine Disk Based on Adaptive Weighted One-Class Support Vector Machine. Journal of Electrical and Computer Engineering. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1184050
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1184050