Research and application of CNN-based transmission line hazard identification technology

With the rapid development of the power industry, the safety and reliability of transmission lines have become a focal point of attention. In this study, a new method for front-end hazard identification of transmission line images using convolutional neural networks (CNN) based on deep learning technology is investigated. Transmission line images are collected and a deep learning model is established for image analysis and defect recognition. Preprocessing techniques such as image enhancement, segmentation, and denoising are applied to improve the quality and analysis effectiveness of the collected images. Field verification demonstrates the feasibility and effectiveness of this method, indicating its significant application value in enhancing the safety of transmission lines.