摘要
矿用电机车蓄电池的故障检测中,常见的检测结果仍停留在“好坏”的二元判断中,而不能对具体的故障原因进行判断以及对故障程度做出定量评价。为解决此问题,提出一种基于模糊专家系统的故障诊断方法。首先将模糊现象与因素之间的关系用数学式进行描述;然后创建逻辑推理机制,从而完成对矿用电机车蓄电池特定领域系统的故障诊断分析以及健康度评价。结果表明,该故障诊断方法可以满足矿用电机车蓄电池故障诊断的实时性与准确性要求。
In the fault detection of accumulator of mine electric locomotive,the common detection results still remain in the binary judgment of"good or bad",but can not judge the specific fault cause and make quantitative evaluation of the fault degree.To solve this problem,proposed a fault diagnosis method based on fuzzy expert system.Firstly,the relationship between fuzzy phenomena and factors was described by mathematical formula.Then a logical reasoning mechanism was created,so as to complete the fault diagnosis analysis and health evaluation of the specific field system of the accumulator for mining electric locomotive.The results show that this fault diagnosis method can meet the real-time and accuracy requirements of the fault diagnosis of accumulator for mine electric locomotive.
作者
周仕保
Zhou Shibao(School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan 232001,China)
出处
《煤矿机械》
2023年第10期176-179,共4页
Coal Mine Machinery
关键词
矿用电机车
蓄电池
模糊专家系统
故障诊断
mine electric locomotive
accumulator
fuzzy expert system
fault diagnosis
