Development of a Dynamically Conformal Clamping Inspection Robot for Overhead Power Lines Based on Infrared Strand Breakage Detection

Abstract

To address the challenges of insufficient wind resistance stability and low detection accuracy for strand breakage defects during overhead power line inspection, this study proposes a dual-mode inspection robot solution integrating a Dynamic Conforming Pressing (DCP) mechanism and an infrared vision system. Firstly, a dual-mode inspection robot with flight-to-walking mode transition capability was designed and developed. The robot incorporates a multi-spring buffered DCP structure to enhance operational stability under wind loads. Subsequently, an efficient infrared vision detection system was established based on the YOLO11 framework, integrating the ShuffleNetV2 lightweight backbone network with BiFPN multi-scale feature fusion mechanisms, and validated on a strand breakage defect dataset. Experimental results indicate that the DCP-equipped robot reduces stabilization time by over 40% under wind loads of 4 m/s, 8 m/s, and 12 m/s. Meanwhile, the enhanced YOLO11 model achieves a mean Average Precision (mAP) of 0.991 with an inference speed of 85.26 FPS, surpassing the performance of Faster R-CNN, YOLOv5, and YOLOv8. This research demonstrates the effective integration of mechanical stability and intelligent perception capabilities, providing critical technical support for advancing the intelligence and reliability of power line inspection systems.