To solve the problem of low manual efficiency in button surface defect detection and no need to classify button surface defects,a button surface defect detection model based on DEEP SVDD(DEEP support vector data description)and improved VGG16(visual geometry group)was proposed.BN(batch normalization)layer was added to VGG16 to accelerate network convergence.SE(squeeze-and-excitation)attention module was introduced to improve the ability of network feature extraction.The full connection layer was replaced by global average pooling to reduce the number of model parameters and make the model more robust.Experimental results show the AUC values of the improved model in DEEP SVDD for two methods.AUCs of Soft boundary method and the first class method are increased by 7.7％and 5.9％respectively,both of which are higher than 96％.The single sheet detection time is only 4.5 ms.The performance of the model meets the actual requirements.
维普
万方数据