The trainset transformer is the core equipment to ensure the stable operation of high-speed railroads,while the frequency response method is an effective method to detect the state of the transformer windings.In order to improve the accuracy of the diagnosis of on-board transformer winding state,combining the transient signals with the frequency re-sponse method,this paper proposed a trainset transformer winding state diagnosis method based on the frequency re-sponse and image feature extraction.Firstly,a simulation platform was built for testing on-board transformer winding faults to obtain the frequency response curves of different fault types and fault locations,and to combine the amplitude-frequency and phase-frequency curve information by using the Gram-like matrix set.Secondly,the density hierarchy method was converted to a pseudo-color image to extract the corresponding grayscale covariance matrix and grayscale difference matrix eigenvalues,and to finally diagnose the winding faults according to the pelican-optimized support vector machine method.The experimental validation results show that in the case of on-board transformer winding fault,the pseudo-color image can reflect the fault information,which is conducive to image analysis and feature extraction.The di-agnosis method for the state of trainset transformer winding based on frequency response and image feature extraction can identify the typical types and locations of the on-board transformer winding faults.
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