Optimization method of fault feature extraction of broken rotor bar in squirrel cage induction motors

Broken rotor bar (BRB) is one common fault of squirrel cage induction motors. When the BRB fault happens, the stator current of the induction motor contains a feature frequency component. The fault detection method based on the spectrum analysis of the stator current is commonly used. However, experiments show that the spectrum analysis of the stator current by directly using fast Fourier transform (FFT) is not suitable. In order to improve the sensitivity of the fault detection, the method of the adaptive notch filter (ANF) combining with FFT is presented. The stator current is analyzed by using the ANF, and then the suitable segment of the above analyzed results is chosen by using an optimization method. In the end, the feature of the BRB fault is extracted by using FFT to the above segment. Experiments show that this method can effectively inhibit the interference of the power frequency signal, and highlight the feature of the BRB fault, so this method is effective.