15 November 2017 Research on installation quality inspection system of high voltage customer metering device based on image recognition
Author Affiliations +
Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 1060521 (2017) https://doi.org/10.1117/12.2292655
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China
Abstract
With the rapid development of the scale of the power grid, the site construction and the operations environment is more widespread and more complex. The installation work of the high-voltage customer metering device is heavy, which is not standardized. In addition, managers supervise the site construction progress only through the person in charge of each work phrase. It is inefficient and difficult to control the multi-team and multi-unit cross work. Therefore, it is necessary to establish a scientific system to detect the quality of installation and management practices to standardize installation work of the metering device. Based on the research of image recognition and target detection system, this paper presents a high-voltage customer metering device installation quality inspection system based on digital image processing, image feature extraction and SVM classification decision. The experimental results show that the proposed scheme is feasible. And it can be used to accurately extract the metering components in the image, which can be also accurately and quickly classified. Our method is of great significance for the implementation and monitoring of the power system in installation and specification
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bei He, Bei He, Fu-li Yang, Fu-li Yang, Xue-dan Tao, Xue-dan Tao, Shi-liang Chang, Shi-liang Chang, Kang Wu, Kang Wu, } "Research on installation quality inspection system of high voltage customer metering device based on image recognition", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 1060521 (15 November 2017); doi: 10.1117/12.2292655; https://doi.org/10.1117/12.2292655
PROCEEDINGS
6 PAGES


SHARE
Back to Top