基于逆变器直流侧电流的异步电机转子断条和偏心混合故障诊断

Diagnosis of Broken Bars and Eccentricities Faults in Asynchronous Motors Based on DC-Side Current of DC-AC Converts

电机发生早期故障时,出现在定子电流中的故障特征频率分量很弱,容易被基波分量的泄漏淹没。很多文献通过各种变换方法将电流的基波分量转化为直流量,以减少频谱泄漏来突出故障特征分量。基于变频器驱动的异步电机,通过分析发现定子电流中的基波分量转化为逆变器直流侧电流中的直流分量,定子电流中的各种故障特征频率分量和逆变器直流侧电流中的频率分量存在对应关系。提出了一种基于逆变器直流侧电流的异步电机转子和偏心混合故障诊断方法,采集逆变器直流侧电流信号,并用MUSIC算法进行频率估计,具有很好的实时性。试验结果证明,提出的方法是一种简单有效的方法。

When incipient faults occured in motors,fault signature frequency component in stator current was very weak and easy to be drowned by the leak of fundamental component.Some literature convert fundamental components to DC component through different transform method,reduce the leak of fundamental component,and make the fault signature frequency component more prominent.Based on the asynchronous motors driven by the AC-DC-AC converter,discovered that the fundamental component in stator currents was converted to the DC component,and different faultssignature frequency components in stator currents correspond to the frequency component in the DC-side current.A new method was proposed for broken bars and eccentricities faults diagnosis based on the DC-side current.The method only acquired the DC-side current signal and carried on frequency estimation by MUSIC algorithm,has the very good timeliness.Experimental results showed that the method was a simple and effective method.