Journal ArticleDOI
Bayesian Networks in Fault Diagnosis
Baoping Cai,Huang Lei,Min Xie +2 more
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TLDR
Current gaps and challenges on use of BNs in fault diagnosis in the last decades with focus on engineering systems are explored and several directions for future research are explored.Abstract:
Fault diagnosis is useful in helping technicians detect, isolate, and identify faults, and troubleshoot. Bayesian network (BN) is a probabilistic graphical model that effectively deals with various uncertainty problems. This model is increasingly utilized in fault diagnosis. This paper presents bibliographical review on use of BNs in fault diagnosis in the last decades with focus on engineering systems. This work also presents general procedure of fault diagnosis modeling with BNs; processes include BN structure modeling, BN parameter modeling, BN inference, fault identification, validation, and verification. The paper provides series of classification schemes for BNs for fault diagnosis, BNs combined with other techniques, and domain of fault diagnosis with BN. This study finally explores current gaps and challenges and several directions for future research.read more
Citations
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Probabilistic graphical models in energy systems: A review
TL;DR: A comprehensive review of the PGM-based approaches published in the last decades is presented in this paper, which reveals the advantages, limitations and potential future research directions of PGMbased approaches for energy systems.
Journal ArticleDOI
Research on the fault diagnosis method for high-speed loom using rough set and Bayesian network
Proceedings ArticleDOI
A Bayesian-based Self-Diagnosis Approach for Alarm Prognosis in Communication Networks
TL;DR: This paper presents the alarm prognosis method based on Bayesian inference in order to estimate the health state and trend of the network given by an alarm take as evidence enters the network.
Journal ArticleDOI
Remaining useful life prediction considering degradation interactions of subsea Christmas tree: A multi-stage modeling approach
Xiao-Yu Shao,Yingying Wang,Baoping Cai,Yonghong Liu,Weifeng Ge,Yilu Liu,Xiangdi Kong,Q. Feng,Yiqi Liu,Zengkai Liu,Renjie Ji +10 more
TL;DR: In this article , a multi-stage model-based RUL estimation approach considering interactions is proposed, which is based on Bayesian networks (BNs) to identify and match the system degradation stage, and to deal with the uncertainty of parameters in the estimation.
Proceedings ArticleDOI
Netrca: An Effective Network Fault Cause Localization Algorithm
TL;DR: This paper proposes a novel algorithm named NetRCA which extracts effective derived features from the original raw data by considering temporal, directional, attribution, and interaction characteristics, and designs an ensemble model which combines XGBoost, rule set learning, attribution model, and graph algorithm, to fully utilize all data information and enhance performance.
References
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Book
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
Book
Bayesian networks and decision graphs
TL;DR: The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams, and presents a thorough introduction to state-of-the-art solution and analysis algorithms.
Journal Article
Big data: the management revolution.
Andrew McAfee,Erik Brynjolfsson +1 more
TL;DR: Big data, the authors write, is far more powerful than the analytics of the past, and executives can measure and therefore manage more precisely than ever before, and make better predictions and smarter decisions.
Journal ArticleDOI
A Review of Process Fault Detection and Diagnosis Part I : Quantitative Model-Based Methods
TL;DR: This three part series of papers is to provide a systematic and comparative study of various diagnostic methods from different perspectives and broadly classify fault diagnosis methods into three general categories and review them in three parts.
Journal ArticleDOI
A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches
TL;DR: The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade.