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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DissertationDOI
Model-based diagnosis and prognosis of induction motors under stator winding fault
TL;DR: This thesis aims to develop a model-based diagnosis and prognosis framework using the electrical fault parameters and propose techniques to address the aforementioned challenges.
Journal ArticleDOI
Paraconsistent analysis network for uncertainties treatment in electric power system fault section estimation
Júlio César Ribeiro,Ghendy Cardoso,Viviane Barrozo da Silva,Aecio de Lima Oliveira,Antonio Carlos Duarte Ricciotti,Paulo de Tarso Carvalho de Oliveira +5 more
TL;DR: In this paper, a Paraconsistent Annotated Logic with annotation of two values (PAL2v) is proposed to detect and treat uncertainties in fault section estimation (FSE) in an electric power system.
Journal ArticleDOI
Using discrete Bayesian networks for diagnosing and isolating cross-level faults in HVAC systems
TL;DR: Wang et al. as discussed by the authors presented a discrete Bayesian Network (DisBN)-based method for diagnosing cross-level faults in an HVAC system commonly used in commercial buildings.
Journal ArticleDOI
AutoConf: New Algorithm for Reconfiguration of Cyber-Physical Production Systems
Kaja Balzereit,Oliver Niggemann +1 more
TL;DR: In this paper , a hybrid automaton is used to model the CPPS and a specification of the controller to construct a QSM, which is based on propositional logic and represents the reconfiguration context.
Journal ArticleDOI
Structured sparsity modeling for improved multivariate statistical analysis based fault isolation
TL;DR: In this article, a fault isolation framework based on structured sparsity modeling is proposed to improve the fault diagnosis capability of multivariate statistical methods, which relies on the reconstruction based contribution analysis and the process structure information can be incorporated into the reconstruction objective function.
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.