摘要
为了提高矿井风机故障诊断的准确率,结合案例推理研究设计了矿井风机故障诊断系统,该系统引入了群决策思想对多种相似度指标进行了综合,从而解决了因单一相似度指标对系统诊断结果带来的不确定性上的弊端,仿真试验表明,该系统能够有效地诊断出风机故障,能够高效地对风机的运行状态进行分析判断,为矿井安全提供了相应的保障。
To improve the accuracy rate of fault diagnosis for mine fan,a fault diagnosis system for mine fan based on case-based reasoning was researched and designed,the system,group decision was introduced to synthesize multiple similarity indexes,which solve the uncertain system diagnosis brought by single similarity index.The simulation experiment results showed that the system could effectively diagnose the faults and efficiently analyze the operating status of fan,so it could guarantee the mine safety.
出处
《中国煤炭》
北大核心
2016年第6期71-75,118,共6页
China Coal
基金
北京市属高等学校创新团队建设提升计划
北京工业职业技术学院科研项目(bgzykyz201402)
关键词
矿井风机
故障诊断
案例推理
群决策
mine fan
fault diagnosis
case-based reasoning
group decision
