Classification of Cupping Test Results for Strip Welds Based on Deep Learning
In order to realize the automatic classification of the cupping test results of crescent edge of strip weld,a classification method based on lightweight network is de-signed.Firstly,data enhancement is used to expand the number of samples in the dataset,then the Grad-CAM algorithm is introduced to visualize the intermediate layer of the test model in the form of heat maps.Finally,a migration learning training method for the freez-ing feature extraction part is designed in conjunction with the visualization of the intermedi-ate layer of the MobileNet V3 network,and the four types of lightweight networks are tested in comparison,the experimental results show that the MobileNet V3 network based on migration learning has a better ability to classify the defects.
万方数据
维普
