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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Journal ArticleDOI
Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review With Special Focus on Data-Driven Methods
Xingang Zhao,Junyung Kim,Kyle Warns,Xinyan Wang,Pradeep Ramuhalli,Sacit M. Cetiner,Hyun Gook Kang,Michael Golay +7 more
TL;DR: In this article, the authors provide an updated method-centric review of the full PHM suite in NPPs focusing on data-driven methods and advances since the last major survey article was published in 2015.
Journal ArticleDOI
Fault Diagnosis in the Field of Additive Manufacturing (3D Printing) Using Bayesian Networks
TL;DR: A new approach for fault diagnosis in the field of additive manufacturing (3d printing) using artificial intelligence will be given, based on the marriage of the Bayesian Networks theory and data acquisition techniques.
Journal ArticleDOI
Fault Diagnosis Methodology of Redundant Closed-Loop Feedback Control Systems: Subsea Blowout Preventer System as a Case Study
Xiangdi Kong,Baoping Cai,Yonghong Liu,Hongmin Zhu,Chao Yang,Chun Tao Gao,Yiqi Liu,Zengkai Liu,Renjie Ji +8 more
TL;DR: In this paper , a causality-based method is proposed for the fault diagnosis of closed-loop feedback control systems with multiple modular redundancy, which consists of four layers, which are sensors, performances, monitors, and faults, respectively.
Journal ArticleDOI
Cubic Dynamic Uncertain Causality Graph: A New Methodology for Modeling and Reasoning About Complex Faults With Negative Feedbacks
TL;DR: The fundamental idea is to continuously generate the cubic causality graph online according to the sequential observations by discarding the restrictive Markov and conditional independence assumptions, and the efficient and rigorous inference algorithm is thus proposed.
Journal ArticleDOI
Resilience Measure of Network Systems by Node and Edge Indicators
Chao Zhang,Xin Xu,Hongyan Dui +2 more
TL;DR: The results show that node-related and edge-related indicators are both suitable to measure local stability, and nodes always have a greater influence on network resilience than edges.
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.