Application and Research of Image Recognition Technology in Transmission Line Loss Detection

Transmission line loss detection is crucial in the process of electric power transmission. This paper proposes a deep learning-based method for detecting transmission line losses. This method utilizes deep learning models such as Convolutional Neural Networks (CNNs) to extract features and classify image data of transmission lines, achieving automatic detection and localization of line loss defects. The paper comprehensively examines the influencing factors of transmission line loss detection and analyzes in detail the line loss detection methods based on image recognition technology, including line loss extraction, line breakage detection, and identification of the causes of line loss. Experimental results demonstrate that this method has high detection accuracy and fast detection speed, meeting the requirements of practical inspection. To further validate the effectiveness of deep learning technology in transmission line loss detection, this paper also conducts extensive experiments and comparative analyses. By comparing with traditional detection methods and other deep learning models, the proposed method in this paper exhibits significant advantages in terms of detection accuracy, detection speed, and generalization ability.