融合多源信息的液压动力单元故障诊断方法  

Multi-source-information Based Fault Diagnosis Method of Hydraulic Power Unit

作　　者：武国营 葛伟凤 方传新 王鹏 黄磊 杨超[2] 蔡宝平[2] Wu Guoying;Ge Weifeng;Fang Chuanxin;Wang Peng;Huang Lei;Yang Chao;Cai Baoping(CNOOC Security & Technology Services Co.,Ltd.;College of Mechanical and Electronic Engineering,China University of Petroleum (Huadong))

机构地区：[1]中海油安全技术服务有限公司 [2]中国石油大学(华东)机电工程学院

出　　处：《石油机械》2019年第2期70-79,共10页China Petroleum Machinery

基　　金：国家重点研发计划项目"海洋石油天然气开采事故防控技术研究及工程示范"(2017YFC0804500);国家自然科学基金项目"海底复杂环境下深水采油树系统失效机理及故障诊断方法研究"(51779267);中央高校基本科研业务费专项资金资助项目(17CX05022)

摘　　要：针对液压动力单元中元件数量繁多、联系复杂,以及难以精确进行故障诊断的问题,提出了融合多源信息的贝叶斯网络故障诊断新方法,建立了液压动力单元单一故障失效模式的贝叶斯网络拓扑结构,开发了融合多源信息的故障诊断网络。利用Noisy-OR/MAX计算了故障诊断网络的条件概率参数;针对两故障并发模式,将观测信息节点加入已建立的单一故障模式诊断网络,辅助诊断液压动力单元的两故障并发失效。实例诊断结果表明:对单一失效的诊断,观测节点对诊断结果的影响不大,正确率均接近100%;对于两失效同时发生的情况,未考虑观测信息的模型出现了漏诊和误诊的问题,正确率不到50%,而考虑观测信息的模型能够正确诊断出所有两失效并发的情况,正确率达到100%。研究结果可为水下生产系统的故障诊断奠定基础。To address the problem of large number of components and complicated connection in the hydraulic power unit which makes it difficult to accurately diagnose the fault, a new Bayesian network fault diagnosis method based on multi-source information is proposed. A Bayesian network topology of single fault failure mode of the hydraulic power unit is established. A fault diagnosis network integrating multi-source information is developed. The conditional probability parameters of the fault diagnosis network are calculated using Noisy-OR/MAX. For the two simultaneous faults modes, the observation information nodes are added to the established single fault mode diagnosis network to assist diagnosing the two simultaneous faults of the hydraulic power unit. The case diagnosis results show that, for the diagnosis of single fault, the observation node has little effect on the diagnosis result, and the correct rate is close to 100%. For the case of two simultaneous faults, the model without the observation information has the problem of missed diagnosis and misdiagnosis, of which the correct rate is less than 50%. However, the model considering the observation information can correctly diagnose two simultaneous faults, and the correct rate reaches 100%. The study can lay the foundation for fault diagnosis of subsea production system.

关 键 词：水下生产系统 液压动力单元 故障诊断 贝叶斯网络 多源信息 

分 类 号：TE951[石油与天然气工程—石油机械设备]