关键词: 图像处理, 开关状态, 目标检测, 直线检测

Abstract:

Aiming at the problems of high maintenance cost of equipment and long application landing period, and according to the advantages of Building Information Modeling（BIM）, which is consistent with the real scene space, flexible and adjustable scene perspective, and can simulate various lighting conditions, a method of equipment switch state detection is proposed based on LSD（Line Segment Detector） and deep learning. By detecting the line segment information of the image and selecting the line segment based on the edge features of the switch box, the position of the switch box in the image is framed to generate the image data set, which is then input to YOLOv3（You Only Look Once version3） network training to generate deep learning model. Finally, the deep learning network framework is deployed to the edge devices, and the operation state of the switch box in the real environment is detected on the edge side. Experimental results show that the proposed method can recognize the working state of the switch box in BIM environment in a short time, which has good adaptability to the real environment.

Key words: image processing, switch status, target detection, line detection