基于模糊故障诊断的电机故障诊断专家系统设计--以电动汽车驱动电机为例  

Design of Expert System for Motor Fault Diagnosis Based on Fuzzy Fault Diagnosis:Take the Driving Motor of an Electric Vehicle as an Example

作　　者：覃卓庚[1] QIN Zhuo-geng(Guangzhou Nanyang Polytechnic Vocational College,Guangzhou 510925,China)

机构地区：[1]广州南洋理工职业学院,广州510925

出　　处：《内燃机与配件》2021年第17期202-204,共3页Internal Combustion Engine & Parts

基　　金：2019年广州市科技项目“电动汽车电机驱动系统的故障诊断专家系统开发”项目编号201904010118;广州南洋理工职业学院2019年校级科研课题:电动汽车电机驱动系统故障诊断推理机的设计NY-2019KYYB-26。

摘　　要：为了改善电动汽车驱动电机故障诊断效率和诊断精准度,本文选择遗传算法和模糊故障诊断方法作为研究工具,设计一套新型电机故障诊断专家系统。该系统利用传感器采集电机作业状态数据,经过模糊处理,按照模糊规则,调动知识库和数据库,对电机作业状态进行诊断。测试结果显示,本系统在电机故障诊断精准度为99.8%,响应时间控制在200μs以内,较传统系统性能有了很大改善。In order to improve the efficiency and accuracy of fault diagnosis of electric vehicle drive motors,this paper selects genetic algorithms and fuzzy fault diagnosis methods as research tools to design a new set of motor fault diagnosis expert systems.The system uses sensors to collect motor operating status data,and after fuzzy processing,according to fuzzy rules,the knowledge base and database are mobilized to diagnose the motor operating status.The test results show that the accuracy of the system's motor fault diagnosis is 99.8%,and the response time is controlled within 200,which has greatly improved the performance of the traditional system.

关 键 词：模糊故障诊断 遗传算法 电动汽车驱动电机 

分 类 号：TM307[电气工程—电机]