基于AD-Census代价及目标检测的吊车防碰线技术

针对大型吊车在高压输电线路下施工易发生碰线事故的问题，提出一种基于目标检测和双目测距的方法来对风险进行管控。所提方法首先使用YOLOv4算法对输电线进行检测，然后考虑到双目相机处于不同拍摄角度会导致图像存在亮度差异的情况，提出了基于AD-Census代价的SGBM（Semi-Global Block Matching）双目测距算法对输电线进行测距。最后通过实验验证了所提方法的有效性。结果表明：该方法在检测输电线时平均置信度能够达到81.67%，在5~8米以内测量误差能够控制在0.4米以内，平均检测测距用时50ms。相比原始双目测距算法，改进算法的测量精度有一定提升。所提方法能够准确测量吊臂与输电线间的距离，对防止吊车碰线具有一定意义。

Technology of preventing cranes from touching wires based on AD-Census cost and object detection

Aiming at the problem of line collision accident of large cranes under transmission lines, a method based on object detection and binocular distance measurement is proposed to control the risk. Firstly, the proposed method uses YOLOv4 algorithm to detect the transmission lines. Then, considering that binocular cameras at different angles can lead to image brightness differences, A binocular ranging algorithm based on AD-Census cost SGBM (Semi-Global Block Matching) is proposed. Finally, the effectiveness of the proposed method is verified by experiments. The results show that the average confidence of the method can reach 81.67%, the measurement error can be controlled within 0.4 meters within 5~8 meters, and the average detection time is 50ms. Compared with the original binocular ranging algorithm, the measurement accuracy of the improved algorithm is improved to some extent. The proposed method can accurately measure the distance between the crane boom and the transmission line, which has certain significance to prevent the crane from hitting the line.