Protection and Control of Modern Power Systems | |
Fast image recognition of transmission tower based on big data | |
Jiawen Wang1  Sheng Huang2  Yihui Zeng3  Bin Lin3  Zhuangli Hu3  Qinzhang Sun3  Hengbin Xu3  Xiangyuan Luo3  Tong He3  Jianming Liang3  | |
[1] College of Electrical and Information Engineering, Hunan University;Department of Electrical Engineering, Technical University of Denmark;Foshan power supply bureau, Guangdong Power Grid Company; | |
关键词: Big data; Deep learning; Image recognition; Transmission tower; Tree barrier modeling; | |
DOI : 10.1186/s41601-018-0088-y | |
来源: DOAJ |
【 摘 要 】
Abstract Big data technology is more and more widely used in modern power systems. Efficient collection of big data such as equipment status, maintenance and grid operation in power systems, and data mining are the important research topics for big data application in smart grid. In this paper, the application of big data technology in fast image recognition of transmission towers which are obtained using fixed-wing unmanned aerial vehicle (UAV) by large range tilt photography are researched. A method that using fast region-based convolutional neural networks (Rcnn) convolutional architecture for fast feature embedding (Caffe) to get deep learning of the massive transmission tower image, extract the image characteristics of the tower, train the tower model, and quickly recognize transmission tower image to generate power lines is proposed. The case study shows that this method can be used in tree barrier modeling of transmission lines, which can replace artificial identification of transmission tower, to reduce the time required for tower identification and generating power line, and improve the efficiency of tree barrier modeling by around 14.2%.
【 授权许可】
Unknown