摘要
针对目前矿用定向钻机故障依靠人工经验、处理速度慢等问题,文中提出一种基于故障树的定向钻机故障诊断专家系统。采用故障树分析,以矿用定向钻机泵站的典型故障构建故障树模型,通过故障树底事件的概率向上计算中间事件和顶事件的概率,进而获得底事件的概率重要度。根据故障树模型和产生式规则在SQL Server软件中建立专家知识库,储存专家处理故障的知识;再使用正向推理策略对推理机进行设计,通过产生式规则和故障树分析判断故障类型以及故障发生的概率。最后,通过Visual Studio软件开发故障诊断专家系统。经模拟测试,所设计的专家系统能够有效提高矿用定向钻机的故障诊断效率,并快速定位故障类型和原因,可为进一步研究钻机智能故障诊断和健康监测奠定基础。
In allusion to the fault diagnosis of current mining directional drilling rigs,which relies on manual experience and has slow processing speed,a fault diagnosis expert system based on fault tree is proposed.The typical faults of the mining directional drilling rig pumping station are used to construct the fault tree model by means of the fault tree analysis,and the bottom-up calculation of the probability of intermediate and top events is conducted with the probability of the bottom event of the fault tree,so that the probability importance of the bottom event is obtained.The expert knowledge base is established in SQL Server software according to the fault tree model and production rules to store the knowledge of experts in handling faults.The forward reasoning strategy is used to design the inference engine,and the fault type and the probability of the fault occurrence are analyzed and judged by the production rules and fault tree.The Visual Studio software is used to develop the expert system for fault diagnosis.The simulation testing results show that the designed expert system can improve the fault diagnosis efficiency of mining directional drilling rigs,quickly determine fault types and fault causes,and lay a foundation for further research on intelligent fault diagnosis and health monitoring of drilling rigs.
作者
李兆奎
田慕琴
宋建成
LI Zhaokui;TIAN Muqin;SONG Jiancheng(National&Provincial Joint Engineering Laboratory of Mining Intelligent Electrical Apparatus Technology,Taiyuan University of Technology,Taiyuan 030024,China)
出处
《现代电子技术》
2022年第22期121-125,共5页
Modern Electronics Technique
基金
山西省重点研发计划项目(202003D111008)
山西省重点自然基金项目(201901D111008(ZD))。
关键词
定向钻机
专家系统
故障诊断
故障树模型
知识库建立
仿真测试
directional drilling rig
expert system
fault diagnosis
fault tree model
knowledge base establishment
simulation testing
