Fault isolation based on Bayesian fused lasso

Fault detection and isolation (FDI), which is a critical part of modern industrial systems, plays a key role in the maintainability, safety, and reliability of processes. Existing FDI approaches are dependent on varying degrees of knowledge of the process, limiting their implementation in practical...

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Bibliographic Details
Published in2017 Chinese Automation Congress (CAC) pp. 2778 - 2783
Main Authors Shenbo Zhang, Zhengbing Yan, Ping Wu, Zhengjiang Zhang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2017
Subjects
Bayes methods
Bayesian fused lasso
Degradation
Fault diagnosis
fault isolation
fault probability
Input variables
Monitoring
Principal component analysis
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Summary:Fault detection and isolation (FDI), which is a critical part of modern industrial systems, plays a key role in the maintainability, safety, and reliability of processes. Existing FDI approaches are dependent on varying degrees of knowledge of the process, limiting their implementation in practical industrial processes. Based on the least absolute shrinkage and selection operator (lasso), this paper proposes Bayesian fused lasso to overcome the above-mentioned problem. The fault isolation problem is converted into a quadratic programming problem with constraints, which can be solved satisfactorily by the Bayesian fused lasso. Ultimately, the probability distribution of every fault variable can be obtained. In the case of unknown fault directions, fault isolation is carried out. Therefore, the possibility of misdiagnosis was reduced. The reliability and effectiveness of the proposed method are illustrated with the case.
DOI:10.1109/CAC.2017.8243248