基于模糊贝叶斯网络的水下生产系统 人因可靠性分析

近年，随着水下生产系统的应用范围不断扩大，人员在设计、运行、操作、维修维护等工作中造成的故障和失效问题逐渐凸显。人因导致的操作失效已成为水下生产可靠性中重要的风险因素。因此，有必要对水下生产系统进行人因可靠性分析，找出对人因失效概率影响较高的因素，提出改进措施，降低人为操作失误概率。本文通过构建水下生产系统人因风险因素体系，利用信度、效度指标验证了数据的合理性，并借助结构方程模型确定人因风险因素的权重系数，构建贝叶斯网络，利用模糊理论量化人因概率，实现对水下生产系统人因风险的预测和评估。最后通过南海某水下生产系统的实例分析，验证了该方法的适用性，为水下生产系统的人因风险预测和防范提供了参考依据

Human reliability analysis of subsea production system based on fuzzy bayesian network

In recent years, with the increasing application of subsea production system, the problem of malfunction and invalidation caused by personnel in design, operation, maintenance and so on is becoming more and more obvious. Human-induced operational failure has become an important risk factor for the reliability of subsea production. Therefore, it is necessary to analyze the human reliability of subsea production system and put forward corresponding measures to reduce the probability of human operation error. In this paper, the human factors risk factor system of subsea production system is established, the rationality of data is verified by reliability and validity, the weight coefficient of human factors risk is determined by structural equation model, and then the Bayesian network is constructed, the prediction and evaluation of human factors risk of subsea production system are realized by using MODULUS and theory of human factors probability. Finally, an example of a subsea production system in the South China Sea is given to verify the applicability of the method, which provides a reference for the prediction and prevention of the human risk in the subsea production system.