Intermittent fault detection in nonstationary processes via a Wald‐based control chart

Summary In this article, the problem of intermittent fault (IF) detection is investigated for nonstationary processes in the multivariate statistics framework. By combining the moving window technique with maximum likelihood estimation (MLE), the moving window Wald‐based control chart is proposed to...

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Bibliographic Details
Published in:International journal of adaptive control and signal processing 2024-09, Vol.38 (9), p.2952-2971
Main Authors: Liu, Yifan, Zhao, Yinghong, Gao, Ming, Sheng, Li
Format: Article
Language:English
Subjects:
Control charts
fault detectability
Fault detection
intermittent fault
Iterative algorithms
Maximum likelihood estimation
nonstationary processes
Simulated annealing
Wald test
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Summary:Summary In this article, the problem of intermittent fault (IF) detection is investigated for nonstationary processes in the multivariate statistics framework. By combining the moving window technique with maximum likelihood estimation (MLE), the moving window Wald‐based control chart is proposed to realize the detection of IFs in nonstationary processes. The computational efficiency and the convergence properties are discussed for the designed iterative algorithm of MLE. Then, necessary and sufficient conditions are presented to guarantee the detectability of IFs with the consideration of window lengths. Moreover, the alarm delays are analyzed for the appearance and disappearance of IFs. In virtue of the above analysis, the optimal window length is derived by minimizing the supremum of alarm delays. In order to estimate the time of IFs' appearance and disappearance, an algorithm is designed with the inspiration of simulated annealing strategy. Finally, a simulation on rotary steerable drilling tool system is provided to verify the effectiveness of the proposed method.
ISSN:0890-6327
1099-1115
DOI:10.1002/acs.3852