Detection of Bearing Fault in Induction Motor Based on Improved Adaptive Local Iterative Filtering

The stator current of induction motor is not affected by environmental interference, so it is widely used in the motor bearing fault detection. But weaker fault features are easily masked by strong noise, and are difficult to detect. Therefore, an improved adaptive local iterative filtering fault detection method is proposed. Aiming at the problem of poor noise reduction effect of adaptive local iterative filtering, a method for screening data is proposed, which solves the problem of excessive noise components, and improves the accuracy of fault identification. Experimental results show that the proposed method is very effective for bearing fault detection and has better performance than the original method.