Mechanical Fault Identification of Permanent Magnet Synchronous Motor Based on Improved Wavelet Transform
Aiming at the problem of low recognition accuracy caused by the continuous correlation of mechanical fault parameters in permanent magnet synchronous motors,which makes it difficult to extract fault features,an improved wavelet transform based mechanical fault recognition technology for permanent magnet synchronous motors is studied.Establish a mathematical model for the synchronous state parameters of the stator and rotor in a permanent magnet synchronous motor,and obtain periodic data of various parameters under normal synchronous state of the motor based on the sine distribution of the three-phase equation.Use this value as the initial reference for fault state feature extraction.Using the high and low frequencies inside the permanent mag-net synchronous motor as feature extraction scales,the motor mechanical fault feature signal reconstruction and extraction are completed based on improved wavelet packet transform;Based on the Kalman filter residual estimation algorithm,calculate the fault residual value of the reconstructed signal,compare it with the initial state,and complete fault identification.After experi-mental verification,the proposed method has high recognition accuracy and can identify the three-phase stator current and mo-tor output torque under short-circuit faults,which has certain practical value.
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维普
