An Intelligent Robotic System for Surface Defect Detection on Stay Cables: Mechanical Design and Defect Recognition Framework

Surface defects on stay cables are primary contributors to wire corrosion and breakage. Traditional manual inspection methods are inefficient, inaccurate, and pose safety risks. Recently, cable-climbing robots have shown significant potential for surface defect detection, but existing designs are constrained by large size, limited operational speed, and complex installation, restricting their field applicability. This study presents an intelligent robotic system for detecting cable surface defects. The system features a dual-wheel driving mechanism, and a computer vision–based defect recognition framework is proposed. Image preprocessing techniques, including histogram equalization, Gaussian filtering, and Sobel edge detection, are applied. Interfering information, such as sheath edges and rain lines, is removed using the Hough Line Detection Algorithm and template matching. The geometry of identified defects is automatically calculated using connected component analysis and contour extraction. The system’s performance is validated through laboratory and field tests. The results demonstrate easy installation, adaptability to cable diameters from 70 mm to 270 mm and inclination angles from 0° to 90°, and a maximum speed of 26 m/min. The proposed defect recognition framework accurately identifies typical defects and captures their morphological characteristics, achieving an average precision of 92.37%.