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Development of a weighted probabilistic risk assessment method for offshore engineering systems using fuzzy rule-based Bayesian reasoning approach

机译：基于模糊规则的贝叶斯推理方法开发海上工程系统加权概率风险评估方法

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摘要

This study presents a new safety methodology that is capable of transforming qualitative expert judgement into probabilistic risk outcomes for offshore engineering systems. In the framework, fuzzy set theory is applied to describe variables. Fuzzy data of each input is expressed in terms of the belief degree format representing the extent to which the fuzzy data belongs to the associated fuzzy set. Such data is subsequently combined to derive appropriate consequents using a fuzzy rule approach considering the weights of each input. The information generated in the antecedent and consequent of each rule are then synthesized to reach the fuzzy conclusions using the Bayesian reasoning approach. Such fuzzy conclusions are defuzzified and consequently transformed into the probabilistic nature. The framework is validated using two axioms and demonstrated by a risk study of the propulsion malfunction of an offshore Floating Production, Storage and Offloading (FPSO) during tandem offloading operations. The results are consistent with the axioms since the outcomes are sensitive to the minor alterations of input data and weights. It is concluded that the new approach produces reasonable results considering input weights and the logicality between inputs and outputs without losing too much useful information in the inference process.
机译：这项研究提出了一种新的安全方法，该方法能够将定性专家判断转换为海上工程系统的概率风险结果。在该框架中，应用模糊集理论来描述变量。每个输入的模糊数据以表示该模糊数据属于相关模糊集的程度的置信度格式表示。随后考虑到每个输入的权重，使用模糊规则方法将此类数据组合以得出适当的结果。然后，使用贝叶斯推理方法，对在每个规则的先行和随后产生的信息进行综合，以得出模糊的结论。这种模糊的结论被去模糊，从而转变为概率性质。该框架使用两个公理进行了验证，并通过对串联卸载作业中海上浮式生产，存储和卸载（FPSO）的推进故障的风险研究进行了证明。结果与公理一致，因为结果对输入数据和权重的微小变化敏感。结论是，新方法在考虑输入权重以及输入和输出之间的逻辑性的情况下产生合理的结果，而不会在推理过程中丢失太多有用的信息。

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