The invention discloses a power
transformer winding fault diagnosis method based on a GSMallat-NIN-CNN network, and the method comprises the steps: carrying out the measurement of a vibration condition of a
transformer winding through a multi-channel sensor, and obtaining multi-source vibration data of a
transformer; converting the multi-source vibration data obtained by measurement into grayscaleimages by using GST
gray level transformation; decomposing each
grayscale image into a high-frequency component sub-image and a low-frequency component sub-
image layer by layer by adopting a Mallat
algorithm, and performing
image fusion on a high-frequency component sub-image and a low-frequency component sub-image; reconstructing the fused
grayscale images, and encoding the vibration
grayscale images according to the fault state of the transformer winding; establishing a transformer fault diagnosis model based on a GSMallat-NIN-CNN network; randomly initializing network parameters, dividinga
training set and a
test set, and training and optimizing the network through the
training set; and storing the trained network, and testing the network through the
test set. According to the method,t
noise in a multi-source
signal is effectively suppressed, the integrity of feature information is improved, the calculated amount is reduced, and the fault diagnosis accuracy is improved.