Intelligent Control and Algorithm Optimization of Overhead Conductor Peeling Device

The traditional peeling method is labor-intensive and inefficient, and the peeling accuracy is difficult to guarantee. The intelligent control system proposed in this paper integrates advanced sensor technology and intelligent control algorithm to realize accurate and optimal control of peeling process. The hardware part includes non-contact diameter sensor, insulation layer thickness sensor, etc., to monitor conductor parameters in real time; In software design, adaptive peeling algorithm and fault detection and diagnosis algorithm are adopted to enhance the reliability of the system. In this study, a hybrid optimization strategy combining machine learning and genetic algorithm (GA) was selected, and the peeling depth was predicted by support vector machine (SVM) model, and the peeling parameters were optimized by GA. The experimental results show that the hybrid optimization strategy can effectively improve the performance of the peeling device, and the peeling accuracy error is mostly controlled within ±0.05mm, and the peeling efficiency gradually improves and tends to be stable with the optimization process. This research not only improves the automation level of peeling operation, but also provides strong support for the intelligent transformation of power and communication industries.