Abstract
<jats:p>With the continuous expansion of distribution network scale, traditional manual live distribution operations suffer from low efficiency and high safety risks, especially on high-voltage lines and in complex environments. This paper proposes an intelligent bypass cable lifting system for unmanned live distribution network operations. This system uses multi-parameter sensors to collect real-time voltage, current, temperature, and line displacement data. Combined with edge computing and intelligent decision-making algorithms, it enables real-time monitoring, anomaly detection, and automatic optimization and adjustment of bypass cables. Experimental results show that the system achieves a data acquisition relative error of less than 2%, anomaly detection accuracy of 91.7% to 100%, and intelligent operation time is reduced by approximately 41.5% compared to traditional manual operations, while safety incidents are reduced by 100%. This system significantly improves operation efficiency and safety, providing reliable technical support for unmanned live distribution network operations.</jats:p>