负载连续变化时鼠笼电机早期转子断条故障诊断

Fault diagnosis of incipient broken rotor bars for squirrel-cage induction motor under continuous variable load condition

负载连续变化时,鼠笼电机定子电流表现为非平稳信号,因此基于快速傅里叶变换的电机电流信号特征分析(MCSA)方法难以有效诊断早期转子断条故障。提出了一种负载连续变化时鼠笼电机早期转子断条故障诊断新方法。首先对定子暂态电流作希尔伯特变换以消除基频影响,然后对得到的解析信号包络线作离散小波变换,根据提取到的故障特征频率2sf演变图谱判断是否发生了转子断条故障,最后结合小波能量给出故障状态定量分析。在3 kW电机实验台上对所提出的方法进行实验验证,实验结果证实了所提方法的有效性。

Under continuous variable load condition, the stator current of squirrel-cage induction motor is a non-stationary signal, therefore the motor-current-signature analysis （MCSA） method based on fast Fourier transform （FFT） can hardly diagnosis the incipient broken rotor bar defect. This paper proposes a novel fault diagnosis method for the incipient broken rotor bars of squirrel-cage induction motor operating under continuous variable load condition. Firstly, the Hilbert transformation is performed on the stator transient current to eliminate the effect of the fundamental frequency. Then, the discrete wavelet transformation is conducted on the envelope of the obtained analytic signal ; and according to the faulty frequency 2sf characteristic pattern, it is judged if the broken rotor bar defect occurs. Finally, combining the wavelet energy techniques, the quantitative analysis of the fault state is given. The experiment verification was performed on a 3kw motor experiment test bench; the experiment results prove the effectiveness of the proposed method.