Research on Fusion Model Method for Corrosion Damage Detection of Switch Sliding Baseplate

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As the core component of railways, the switch sliding baseplate has a bad operating environment, and its surface is prone to corrosion. Existing methods, including traditional methods, ultrasonic detection, and image processing, have difficulty in extracting corrosion features and being applied in practice. To solve the above problems, the Residual Neural Network 50 (ResNet50) model, a deep learning model, is introduced in this paper. To solve the problems of gradient explosion and weak corrosion in the model, a new fusion model, VGG-ResNet50-corrosion (VGGRES50_Corrosion), is proposed in this paper. First of all, for the problem that there is no public dataset, this study conducts a neutral salt spray corrosion test and collects the image features and corrosion depth parameters of skateboard corrosion in different time periods as the dataset to test the performance of the model. Then, corrosion thickness is introduced as a modified variable in the ResNet50 network, and a new network, VGGRES50_Corrosion, is introduced by blending the improved model with the Visual Geometry Group-16 (VGG16) network through a model fusion strategy. Finally, a model test and ultrasonic contrast test are designed to verify the performance of the model. In the model test, the recognition accuracy of the fusion model is 98.98% higher than that of other models, which effectively solves the shortcoming of the gradient explosion's weak generalization ability under a small sample model. In the ultrasonic comparison experiment, the mean relative errors of this method and ultrasonic detection method are 4.08% and 46.14%, respectively, and the mean square errors are 1.86 h and 15.01 h, respectively. The prediction result of deep learning is better than that of ultrasonic piecewise linear fitting. It has been proved that VGGRES50_Corrosion can identify the degree of corrosion of slip switches more effectively, and it has great significance in improving the corrosion detection efficiency of slip switches.