Journal ArticleDOI
Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches
TLDR
The paper concludes that BN is a superior technique in safety analysis because of its flexible structure, allowing it to fit a wide variety of accident scenarios.About:
This article is published in Reliability Engineering & System Safety.The article was published on 2011-08-01. It has received 573 citations till now. The article focuses on the topics: Fault tree analysis & System safety.read more
Citations
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Proceedings ArticleDOI
The application of interval Bayesian network method in the reliability assessment of substation bus arrangement
TL;DR: A substation bus arrangement reliability assessment method based on interval Bayesian Network is proposed, which considers the effects of parameters' uncertainties on system reliability indices throughout the calculation process.
Journal ArticleDOI
Fault Tree Analysis of Pantograph Type Current Collector Based on Ontology Modeling
TL;DR: Based on the analysis of the structure, working principle and failure mode of the Pantograph type current collector, fault tree of the pantograph was established in this article, and a lot of expert knowledge has been collected to support this diagnose process.
Journal ArticleDOI
Third-Party Damage Model of a Natural Gas Pipeline Based on a Bayesian Network
Baikang Zhu,Xuehong Yang,Jun Wang,Chuanhui Shao,Feiquan Li,Bingyuan Hong,Debin Song,Jian Guo +7 more
TL;DR: The top five factors that have significant influence on third-party damage, are safety investment, the completeness of equipment, safety inspection frequency, the management of residents along the pipeline, and safety performance, with the posteriori probability in the model.
Journal Article
Development and ranking of safety performance indicators using Bayesian network and Analysis Hierarchical Process Case study: Work at height of the Oil and Gas refinery construction phase
TL;DR: A new model for the development of safety performance indicators using the probability risk assessment model and applying experts' opinions is presented to measure the safety performance of construction operations.
References
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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 ArticleDOI
Improving the analysis of dependable systems by mapping fault trees into Bayesian networks
TL;DR: It is shown that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former, i.e. reliability of the Top Event or of any sub-system, criticality of components, etc.
Book
Introduction to reliability engineering
TL;DR: Reliability and Rates of Failure, Loads, Capacity, and Reliability, and System Safety Analysis; Quality and Its Measures; and Answers to Odd--Numbered Exercises.
Journal ArticleDOI
Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas
TL;DR: A bibliographical review over the last decade is presented on the application of Bayesian networks to dependability, risk analysis and maintenance and an increasing trend of the literature related to these domains is shown.
Book
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
Uffe Kjærulff,Anders L. Madsen +1 more
TL;DR: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks.