基于Bayesian网络的常减压装置设备故障概率分析  

Fault probability analysis of atmospheric and vacuum distillation unit equipment based on Bayesian network

作　　者：宁志康 许述剑 刘曦泽 许可 屈定荣 NING Zhikang;XU Shujian;LIU Xize;XU Ke;QU Dingrong(SINOPEC Research Institute of Safety Engineering Co.,Ltd.,Qingdao Shandong 266104,China)

机构地区：[1]中石化安全工程研究院有限公司,山东青岛266104

出　　处：《中国安全生产科学技术》2022年第6期185-190,共6页Journal of Safety Science and Technology

摘　　要：为分析影响常减压蒸馏装置平稳运行的设备失效模式及故障部件,基于1151条设备故障数据,采用Bayesian网络分析方法,分别对离心泵、压缩机、电动机构建基于Bayesian网络的设备故障概率分析模型,分析故障部件、失效模式、故障后果之间的定量概率关系。研究结果表明:离心泵、压缩机、电动机停运的关键致因部件分别为轴承箱密封故障、活塞环故障、轴承故障,同时得到导致设备停运的故障部件敏感度排序。研究结果有助于提高设备故障风险防范及检维修工作效率,同时可为备件优化方案提供思路。In order to analyze the equipment failure modes and fault components that affect the smooth operation of atmospheric and vacuum distillation unit,based on 1151 equipment fault data,the Bayesian network analysis method was used to construct the equipment fault probability analysis model based on Bayesian network for the centrifugal pump,compressor and motor,respectively,and the quantitative probability relationship between fault component,failure mode and fault consequence was analyzed.The results showed that the key components causing the shutdown of centrifugal pump,compressor and motor were the seal fault of bearing box,piston ring fault and bearing fault,respectively.At the same time,the sensitivity ranking of fault components causing the shutdown of equipment was obtained.The analysis results are helpful to improve the risk prevention of equipment fault and the efficiency of inspection and maintenance,and provide ideas for the optimization scheme of spare parts.

关 键 词：设备故障 失效模式 常减压装置 BAYESIAN网络 

分 类 号：X937[环境科学与工程—安全科学]