 A novel method for risk-informed decision-making under non-ideal Instrumentation and Control conditions through the application of Bayes’ TheoremTu Guang Tan, Sunghyon Jang and Akira Yamaguchi Reliability Engineering and System Safety, 2019, vol. 188, issue C, 463-472 Abstract: Instrumentation and Control systems are often assumed to break and give no readings under certain conditions, but working perfectly otherwise. In reality, aleatory and epistemic factors create a grey area where operators are often unsure of the validity of sensor measurements. Through the use of Bayes’ Theorem, this paper proposes a novel approach that first characterizes both aleatory and epistemic uncertainty, and then combines all available information in a Bayesian network, in order to produce quantitative estimates of unobservable variables in the system. Uncertainties are also propagated from sources to results in a natural manner. The approach was applied to a test case, and was able to identify a Vessel Break transient with quantitative probabilities in a timely manner despite the information being scarce, uncertain, and heterogeneous. The approach was thus demonstrated to be a possible alternative method for decision-making under such non-ideal conditions. Keywords: Instrumentation and Control; Uncertainty; Risk-informed decision-making; Bayesian network (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:188:y:2019:i:c:p:463-472 DOI: 10.1016/j.ress.2019.03.051 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
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