Abstract:Aiming at the problems in automobile height regulator production that manual defect detection is laborintensive and timeconsuming, and traditional diagnosis method has poor applicability, an intelligent detection method based on improved convolution network is proposed using deep learning. In this method, convolution network is used to extract features, and residual network structure and separable convolution are added to the network, which improves the accuracy of deep network and reduces the parameter calculation amount. The improved structure mainly uses convolution layer, pooling layer, batch standardization layer and softmax layer, and introduces residual network structure and separable convolution. The experiment results show that the defect detection method for automobile height regulator based on improved convolution network has good recognition accuracy. In the detection experiment on multiple kinds of defects for automobile height regulator, the accuracy is above 99%, which is superior to that of the classical convolution network VGG16.