模糊融合技术在电机故障诊断中的应用  

Application of Fuzzy Fusion to Motor Fault Diagnosis

作　　者：朱朝鹏[1] 郝伟[1] 郝旺身[1] 王瑞欣[1] 

机构地区：[1]郑州大学振动工程研究所,郑州450001

出　　处：《煤矿机械》2013年第9期300-302,共3页Coal Mine Machinery

基　　金：河南省教育厅科学技术研究重点项目(13A460673)

摘　　要：电机运行及故障有着复杂的物理(机、磁和电)演变历程,而传统的诊断方式是基于单参数特征,存在很大的不确定性。针对电机故障诊断系统中的多种状态监测与诊断技术,利用模糊信息融合原理实现对电机运行状态及故障的全参数综合评价,从而提高故障诊断的快速性与准确性。通过实例分析表明该诊断模型的可行性。There is a complex physical （machine, magnetic and electric） processing during the motor normal and fault operating. Traditional motor diagnostic methods are based on single-parameter characteristic, and diagnostic results are uncertain. To reduce such uncertainty, the fuzzy information fusion technology was introduced with multiple sensors condition monitoring and diagnostic technology, which would takes the full parameters for comprehensive evaluation of the motor failure. The result of the example shows that the diagnostic model could improve the evaluation process and the accuracy of fault diagnosis.

关 键 词：电机 模糊融合 故障诊断 多传感器 

分 类 号：TH17[机械工程—机械制造及自动化]