基于模糊动态故障树的化工设备故障诊断方法研究  

Research on Failure Diagnosis Method of Chemical Equipment Based on Fuzzy Dynamic Fault Tree

作　　者：高迎平[1] 李洋[1] 常文韬[2] 尹立峰[2] 

机构地区：[1]河北工业大学,天津300000 [2]天津市环境保护科学研究院,天津300000

出　　处：《工业技术经济》2017年第4期48-54,共7页Journal of Industrial Technological Economics

基　　金：天津市科委项目"化工园区环境预警应急体系关键技术与示范"(项目编号:13RCGFSF14400)

摘　　要：本文针对化工设备故障具有模糊性、动态性的特点,提出了建立模糊动态故障树对其进行预测诊断,重点对模糊动态故障树定量分析方法进行了研究,提出了基于最小割集、割序的定量分析方法。该方法将模糊动态故障树分解为模糊静态子树和模糊动态子树,然后分别建立以最小割集和最小割序为基础的定量计算模型,同时引入了弱三角范数的概念以减少由于数据模糊性扩散而引起计算结果不准确的现象。最后给出了最小割集、割序和底部事件重要度的计算公式,分析了化工设备故障诊断的流程,并通过实例验证了该方法具有计算准确,效率高,通用性强的特点,适用于化工设备的故障诊断。In view of the fuzzy and dynamic characteristics of chemical equipment fault,a fuzzy dynamic fault tree is put forward to forecast and diagnose the faul.This research focuses on the quantitative analysis method of fuzzy dynamic fault tree,and proposes a quantitative analysis method based on the minimum cut set and cut sequence.The fuzzy dynamic fault tree is decomposed into fuzzy static subtree and fuzzy dynamic subtree.Then based on minimum cut set and minimal cut sequence,quantitative analysis models of fuzzy static subtrees and fuzzy dynamic subtree are established.In order to reduce inaccurate calculation results caused by diffusion of data fuzziness,the concept of weak t-norm is introduced into the two subtrees.Finally,the calculation formula of the minimum cut set,cut sequence and the bottom event importance are given,and the process of fault diagnosis of chemical equipment is analyzed.Through an example,the method is proved to be accurate,efficient and universal,and it can be applied to the fault diagnosis of chemical equipment.

关 键 词：化工设备故障 模糊动态故障树 最小割集 最小割序 弱三角范数 

分 类 号：F224[经济管理—国民经济]