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投稿时间：2012-12-03
投稿时间：2012-12-03
中文摘要: 提出了一种基于传统报警方式触发的电站故障自诊断专家系统.以除氧器为诊断对象,采用报警状态信息触发专家推理过程,利用实时征兆以及规则库进行故障类型的有效实时诊断.现场测试表明,诊断结果准确,且具有一定的容错性.
Abstract:A power plant fault-located self-diagnosis expert system based on the traditional alarm triggering is proposed.With the deaerator as the object of diagnosis,it applies the information of alarm status to trigger expert inference,through real-time symptoms and rule base to diagnose the type of faults on line at the same time.Field tests show that in addition to the accurate diagnosis,it also has a good fault tolerance.
文章编号：20130118 中图分类号： 文献标志码：
基金项目:
引用文本：
牛百芳,张洪星,辛浩,等.除氧器故障自诊断专家系统设计与研发[J].上海电力大学学报,2013,29(1):73-76.
NIU Baifang,ZHANG Hongxing,XIN Hao,et al.Design and Development of New Method of Deaerator Fault Self-diagnosis Expert System[J].Journal of Shanghai University of Electric Power,2013,29(1):73-76.
牛百芳,张洪星,辛浩,等.除氧器故障自诊断专家系统设计与研发[J].上海电力大学学报,2013,29(1):73-76.
NIU Baifang,ZHANG Hongxing,XIN Hao,et al.Design and Development of New Method of Deaerator Fault Self-diagnosis Expert System[J].Journal of Shanghai University of Electric Power,2013,29(1):73-76.