融合多种算法的堆垛机诊断专家系统

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英文篇名：Fault Diagnosis Expert System with Multiple Algorithms for Stackers 作者：吕婷 ; 杨涛 英文作者：LYU Ting;YANG Tao;Department of Information and Intelligence,Anhui Vocational College of Electronics and Information Technology;Robot Technology Used for Special Environment Key Laboratory of Sichuan Province,School of Information Engineering,Southwest University of Science and Technology; 关键词：堆垛机 ; 故障诊断 ; 贝叶斯网络 ; 专家系统 ; 故障树分析 英文关键词：Stacker;;Fault diagnosis;;Bayesian network;;Expert system;;Fault tree analysis 中文刊名：ZDYB 英文刊名：Process Automation Instrumentation 机构：安徽电子信息职业技术学院信息与智能系;西南科技大学信息工程学院特殊环境机器人技术四川省重点试验室; 出版日期：2018-01-17 出版单位：自动化仪表 年：2018 期：v.39;No.437 基金：川渝中烟四川烟草工业有限责任公司(2013-2014年度)科技基金资助项目([2013]165号) 语种：中文; 页：ZDYB201801003 页数：5 CN：01 ISSN：31-1501/TH 分类号：15-18+22

摘要

针对堆垛机设备在运行过程中呈现的复杂性、不确定性等问题,设计了基于故障树和贝叶斯网络的混合诊断专家系统。采用故障树分析技术对堆垛机进行故障建模,得到最小割集,建立了以规则为知识表示形式的规则库。根据输入的故障征兆系统自动寻找匹配的故障事实库,建立了以该事件作为顶事件的故障树,并转化得到相应的贝叶斯网络,形成了基于规则的推理和贝叶斯网络的概率计算混合诊断机制。该方法有效利用了故障树分析和贝叶斯网络两种算法的优势,为复杂机器的故障诊断提供了一种新途径。试验表明,该系统有效解决了传统诊断专家系统存在的推理模式单一、知识获取困难等问题。概率计算混合诊断机制是一种快速诊断堆垛机的可行方式。
        According to the complexity and uncertainty of the stackers during operating,the hybrid fault diagnosis expert system based on fault tree and Bayesian network are designed. By using fault tree analysis technology,the model of stacker is established,and the minimum cut set is obtained,thus the rule base is constructed with the rules as the knowledge representation. In accordance with the input failure symptom system,the system automatically searches the exactly matched fault fact,and builds the fault tree that with the fact as the top event. Then the corresponding Bayesian network istransfromed based on the fault tree. The hybrid diagnosis mechanism is realized based on the rule-based reasoning and Bayesian network-based probability computation. The method is simple and flexible; the advantages of both the fault tree analysis and Bayesian network are used to provide a new way for fault diagnosis of complex machines. The tests show that the system effectively resolves the difficulty of single reasoning mode of traditional expert system. The probability calculation mixed diagnosis mechanism is a feasible way to diagnose trackers quickly.

引文

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