In view of the frequent external force damage incidents of transmission lines, manual inspection and traditional monitoring equipment cannot find the hidden dangers in time and effectively. Therefore, an intelligent monitoring system for transmission lines based on image recognition technology is proposed. The system uses convolution neural network depth learning algorithm to train the model, which can intelligently identify the potential safety hazards of transmission lines. A new intelligent monitoring mode is established, which includes front-end image acquisition, wireless data transmission, background recognition and analysis, and hidden danger directional push. In Foshan area, the system realizes 24-hour real-time monitoring and early warning of transmission lines, improves the monitoring ability of hidden dangers caused by external forces, and effectively prevents line tripping accidents caused by large-scale construction machinery.