Abstract: The catenary pillar numberis an important positioning parameter for on-site operation and maintenance of railway power supply department. Based on convolution neural network, the automatic recognition method of catenary pillar number was combined with the actual characteristics of catenary image. The video image was preprocessed by normalization, and the actual pillar image was trained by convolution neural network. The distribution characteristics of catenary pillar number were considered in the process of the identifying. It improves the accuracy of pillar number recognition.The actual railway line data were used to test, and better recognition accuracy and faster recognition speed were obtained. The experimental results show that this method can assist the defect location in the railway infrastructure inspection system and guide on-site operation and maintenance.