Intelligent Monitoring Algorithm for Transmission Lines Based on Lightning Fusion Technology

The traditional safety detection method for transmission lines heavily relies on manual inspection, which is not only inefficient but also limited by personnel experience, environmental factors, and inspection cycles. It is difficult to achieve real-time and accurate identification and warning of transmission line anomalies, and has significant limitations and safety hazards. In recent years, lightning fusion technology has emerged as an innovative solution that cleverly combines the high-precision ranging and speed measurement capabilities of advanced radar detection technology with the intuitive image recognition advantages of video surveillance technology. Through complex data processing algorithms, it achieves deep fusion and intelligent analysis of the two data. This article explores an intelligent monitoring algorithm for transmission lines based on lightning vision fusion technology, and proposes a monitoring system that combines deep learning (DL) algorithms to automatically capture and analyze environmental changes around transmission lines, significantly improving the timeliness and accuracy of transmission line monitoring. The experimental results show that this system not only significantly reduces manual intervention and operation costs, but also effectively avoids missed and false alarms, providing a more solid technical guarantee for the safe and stable operation of the power system (EPS).