摘要
提出了一种针对异步电机匝间短路故障程度的诊断方法。把从异步电机定子端采集的失电残余电压进行频谱分析,提取其中部分高次谐波成分并与其中的基波成分对比,比值作为不同程度的匝间短路故障的特征向量,再利用BP神经网络进行仿真,得出诊断结果。实验表明,该方法能有效、准确地做出电机匝间短路故障程度的诊断。
A method for diagnosing extent of inter-turn short circuit in AC motor was proposed.The residual voltage,which was collected form stator winding of AC motor,was analysed by frequency spectrum.Their specific value was used to indicate eigenvalue vector of different inter-turn short circuit fault.Some higher harmonics and fundamental was extracted from frequency spectrum.Then eigenvalue vector was emulated by BP neural network.The result of diagnosing was obtained.The experiment demonstrated effectiveness and high accuracy rate of method,which was used to diagnose extent of inter-turn short circuit in AC motor.
出处
《煤矿机械》
北大核心
2011年第10期276-278,共3页
Coal Mine Machinery
关键词
失电残余电压
BP神经网络
异步电机
匝间短路
故障程度
residual voltage after AC dump
BP neural network
asynchronous motor
inter-turn short circuit
extent of fault
