Design of cable detection robot and image detection method

To detect surface damage to cables on a cable-stayed bridge automatically, a mechanism design method based on vision inspection and diameter measurement is proposed by combining computer vision and diameter measurement techniques. Furthermore, a detection system for the surface damages of cables is designed. An overall scheme for the defect detection system based on vision inspection and diameter measurement is proposed. The improved local gray contrast enhancement method is used to enhance the contrast of cable defect area, which effectively overcomes the problem of light reflection characteristics and makes the collected cable surface features not obvious. The improved maximum correlation method is used for threshold segmentation of the damaged image to better segment the parts related to defects in the image. Afterwards, the data obtained through diameter measurement are mined by employing the moving average method. Image enhancement, threshold segmentation, and diameter measurement methods are separately validated experimentally The structure of the robot is optimized to improve the vibration damping performance of the machine and improve the image acquisition quality. The results show that the system delivers recall ratios for type-I and II surface defects of cables reaching 80.4% and 85.2%, respectively and can accurately detect bulges on cable surfaces.