Patent ID: 11875500
Assignee: WUHAN UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 7:
8. The failure diagnosis method as claimed in claim 1, wherein establishing the failure diagnosis model for the transformer based on the GSMallat-NIN-CNN network in Step 5 comprises:
integrating an NIN network and using a 1*1 convolutional kernel as a network function approximator, weighting fused images that are input by using multi-channel cascaded linear weighting, and replacing an original 5*5 convolutional layer with two layers of 3*3 convolution to reduce network parameters; and adding up fused images that are output to obtain an average by using GAP, and adopting the average as an output value of each class and input to a classifier for identification and classification, which replaces a process of dimensionality conversion on feature information at a fully connected layer, wherein by inputting the fused images into the classifier, the whole network performs two-dimensional computation by using the images and does not require matrix conversion, and wherein the whole network comprises four convolutional layers, two average-pooling layer, three ReLU layer, one Mlpc layer, and a global average-pooling layer.