摘要
针对传统计算机辅助HAZOP分析中定量信息的丢失现象以及多危险源系统安全决策的困难,提出了基于模糊信息融合的HAZOP建模与推理方法.构建了系统HAZOP有向图知识模型,针对模型中不同属性的节点分别采用相应的模糊定量化处理方法;同时基于D-S证据理论,利用危险传播路径上相关节点之间的定量偏差信息进行模糊融合推理,给出系统存在的危险原因与后果,以及各自的融合信度,为系统安全决策提供依据.利用该方法对"涩-宁-兰"管线压气站燃压机组的运行状态进行模糊信息融合HAZOP分析,最终给出了系统各危险原因与后果的融合信度及排序,采取有效的安全措施避免事故发生.与传统HAZOP分析进行比对,工程应用结果证明了该方法能解决传统HAZOP定性分析的局限性与不确定性难题;当系统存在多危险源时,增强了系统安全决策的合理性.
This paper proposes a HAZOP modeling and reasoning method based on fuzzy information fusion theory, solving the problems of the loss of quantitative information and the difficulty of system safety decisions in traditional computer-aid HAZOP analysis. A systematical HAZOP directed graph knowledge model is developed by different fuzzy quantitative methods according to different property nodes in the system. Based on D-S evidence theory, the quantitative deviated information between relevant nodes on the path of hazard propagation is used for the fuzzy information reasoning, indicating the fusion reliability of hazard reasons and consequences of system respectively, which is the base of system safety decision. The results of fuzzy information fusion HAZOP analysis applied on the running states of gas turbine compressor unit in ＂Se-Ning-Lan＂ pipeline system, present the possible hazard reasons and consequences with their sorted fusion reliability, based on which the appropriate and effective safety measurements are taken into action to avoid accidents. The comparison with traditional HAZOP analysis shows that the method presented in the paper can solve the limitation and the uncertainty of traditional HAZOP qualitative analysis, and enhance the rationality of system safety decision under the existence of multi-hazard sources as well.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2009年第8期153-159,共7页
Systems Engineering-Theory & Practice
基金
国家863项目(2008AA06Z209)
北京市教育委员会共建项目专项资助
教育部新世纪优秀人才支持计划
中国石油天然气集团公司创新基金
