Power transmission wire wind damage early warning method and terminal based on deep learning

• Main Authors: WAN PENG, XU WEIJIA, MAI XIAOQING, WANG LIANG, WANG BO, GONG FANKUI, LI GUIYING, WANG WEI, ZHANG LIJUAN, HE NINGHUI, LI MEI, ZHANG ZHENYU, SHI YUANYUAN, CAI BING, LIU SHITAO, JIA LU, ZHANG LIZHONG, CHEN PENG, WU MINRONG, GUO FEI, SHA WEIGUO, ZHAN GUOHONG, MA WEI, QIN FAXIAN
• Format: Patent
• Language: Chinese; English
• Published: 07.02.2020
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a transmission line wind damage early warning method and a terminal based on deep learning, and the method comprises the following steps: starting a camera to collect an imageif the current wind power level exceeds a first threshold value; performing instance segmentation and comparison on the acquired image and a pre-stored safe distance image through a deep learning model, and determining the offset amplitude of the power transmission wire and the ratio of the distance between every two phase sequence wires A, B and C to the safe distance; and if the deviation amplitude is not smaller than a second threshold value or any distance ratio is not larger than a third threshold value, sending out an early warning prompt. According to the power transmission wire wind damage early warning method and the terminal based on deep learning, wind damage early warning of the power transmission wire can be achieved, and losses are reduced. 本发明公开了一种基于深度学习的输电导线风害预警方法及终端，该方法包括以下步骤：若当前风力级别超过第一阈值，启动摄像头采集