Permanent magnet synchronous motor demagnetization fault diagnosis method and system based on semi-supervised classifier

Abstract

The invention discloses a permanent magnet synchronous motor demagnetization fault diagnosis method and system based on a semi-supervised classifier. The method comprises the steps of collecting a magnetic flux leakage signal on the surface of a permanent magnet synchronous motor; performing symmetric dot matrix image generation on the magnetic flux leakage signal of the one-dimensional time domain to obtain a two-dimensional symmetric dot matrix image; inputting the symmetric dot matrix image into a wavelet scattering convolutional network for feature extraction to obtain a feature vector; and inputting the feature vector into a pre-trained semi-supervised depth rule classification diagnostor to obtain a demagnetization fault diagnosis result. According to the method, a one-dimensional time domain signal is expanded to a two-dimensional symmetric dot matrix image, complex signal processing is avoided, accurate fault diagnosis under small sample data can be realized based on the semi-supervised depth rule classifier, and the problem that actual equipment cannot be popularized and applied due to small data volume in fault diagnosis is solved.

Description

technical field [0001] The invention relates to a permanent magnet synchronous motor fault diagnosis technology, in particular to a permanent magnet synchronous motor demagnetization fault diagnosis method and system based on a semi-supervised classifier. Background technique [0002] With the continuous development of high-performance rare earth permanent magnet materials and power electronics technology, permanent magnet synchronous motors (PMSM) have been widely used in industrial production, electric vehicles, aerospace and other fields. However, factors such as high operating temperature, armature reaction, and mechanical vibration will cause irreversible demagnetization failures of permanent magnet synchronous motors. Such failures can reduce the efficiency of industrial equipment and even cause property damage and casualties. Therefore, the research on demagnetization fault diagnosis of permanent magnet synchronous motor is very important. Demagnetization faults can...

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Problems solved by technology

[0008] The technical problem to be solved by the present invention: Aiming at the above-mentioned problems of the prior art, a semi-supervised classifier-based permanent magnet synchronous motor demagnetization fault diagnosis method and system are provided. The present invention extends the one-dimensional time-domain signal to a two-dimensional image, Avoiding complicated signal processing, based on the semi-supervised deep rule classifier, it can realize accurate fault diagnosis under small sample data, and solve the problem that the actual equipment cannot be popularized and applied due to the small amount of data in the fault diagnosis

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