Power data monitoring system and method

• Main Authors: ZOU QINGLIN, CHENG HAIYAN, FU SHUANG, CHI XIAOBING, GUO ZIPEI, JIANG ZAIXIN, SU YIFENG, QIU LONGFU
• Format: Patent
• Language: Chinese; English
• Published: 09.02.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; 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 power equipment monitoring system and method, which mainly utilize a machine vision technology to realize fault detection and classification of power equipment, and comprisesan image acquisition module used for acquiring image information of the power equipment; an image preprocessing module used for preprocessing the image information acquired by the image acquisition module to obtain a preprocessed image; and a data analysis module used for inputting the preprocessed images into the trained deep learning model, and obtaining the fault type and grade of the equipment after processing. According to the scheme provided by the invention, the accuracy and efficiency of inspection can be improved, the dependence on manpower can be greatly reduced or eliminated, and the stability of power equipment and lines is enhanced. 本发明公开了一种电力设备监测系统与方法，主要利用机器视觉技术实现对电力设备的故障检测和分类，包括图像采集模块，所述图像采集模块用于采集电力设备的图像信息；图像预处理模块，对所述图像采集模块采集的图像信息进行预处理，得到预处理后的图像；数据分析模块，将预处理后的图像输入至训练好的深度学习模型，处理后得到设备的故障类型和等级。本发明提出的方案