基于人工神经网络的永磁同步电动机供电不平衡及缺相故障诊断  

Failure Diagnosis of Unbalanced Voltage Supply and Phase Loss in PMSM Based on ANN

作　　者：许慧颖[1] 许允之[2] 戚慧[2] 

机构地区：[1]中国联通沈阳分公司,辽宁沈阳110000 [2]中国矿业大学信电学院,江苏徐州221116

出　　处：《煤矿机电》2015年第6期34-38,共5页Colliery Mechanical & Electrical Technology

摘　　要：近年来永磁同步电动机逐步成为应用广泛的工业拖动设备,由于电网供电电压不平衡等,使永磁同步电动机发生故障。因此着重于三相电压不平衡故障的诊断以及与电动机单相或缺相故障的鉴别,提出基于提取定子线电流和电源电压基波中三次谐波的人工神经网络方法。所有模拟使用有限元分析软件进行,该方法通过实验验证,有很高的准确性,是一种有效的故障诊断方法。Recently, the permanent magnet synchronous motors （PMSM） is one of the most attractive electric machine in industrial applications. Unbalanced voltage power supply is common and it easily makes the faults happen in PMSM. Therefore, focus on the diagnosis of unbalanced fault of three phase voltage, or the single phase of motor, or the identify of phase loss symptoms, proposes the artificial neural network （ANN） based on stator current extraction and three phase harmonic waves of power voltage fundamental wave. All the simulation are processed by FEA （finite element analysis） software. The experiment verifies that the method is effective with high efficiency.

关 键 词：永磁同步电动机(PMSM) 故障检测 单相故障 电源电压不平衡 人工神经网路(ANN) 

分 类 号：TP277.3[自动化与计算机技术—检测技术与自动化装置]