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Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set
Joint Authors
Li, Yuan
Yu, Haibin
Xie, Yanhong
Li, Jinna
Zhang, Cheng
Source
Journal of Applied Mathematics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-10-16
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
A novel fault detection technique is proposed to explicitly account for the nonlinear, dynamic, and multimodal problems existed in the practical and complex dynamic processes.
Just-in-time (JIT) detection method and k-nearest neighbor (KNN) rule-based statistical process control (SPC) approach are integrated to construct a flexible and adaptive detection scheme for the control process with nonlinear, dynamic, and multimodal cases.
Mahalanobis distance, representing the correlation among samples, is used to simplify and update the raw data set, which is the first merit in this paper.
Based on it, the control limit is computed in terms of both KNN rule and SPC method, such that we can identify whether the current data is normal or not by online approach.
Noted that the control limit obtained changes with updating database such that an adaptive fault detection technique that can effectively eliminate the impact of data drift and shift on the performance of detection process is obtained, which is the second merit in this paper.
The efficiency of the developed method is demonstrated by the numerical examples and an industrial case.
American Psychological Association (APA)
Li, Jinna& Li, Yuan& Yu, Haibin& Xie, Yanhong& Zhang, Cheng. 2012. Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set. Journal of Applied Mathematics،Vol. 2012, no. 2012, pp.1-17.
https://search.emarefa.net/detail/BIM-1029012
Modern Language Association (MLA)
Li, Jinna…[et al.]. Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set. Journal of Applied Mathematics No. 2012 (2012), pp.1-17.
https://search.emarefa.net/detail/BIM-1029012
American Medical Association (AMA)
Li, Jinna& Li, Yuan& Yu, Haibin& Xie, Yanhong& Zhang, Cheng. Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set. Journal of Applied Mathematics. 2012. Vol. 2012, no. 2012, pp.1-17.
https://search.emarefa.net/detail/BIM-1029012
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1029012