Abstract:Currently, during the deep mining and application of the electric grid data, it can be instituted that, though electric enterprises have accumulated plenty of data which refer to the equipment data of operation and defects, the application of the data still stay in the stage of eliminating defects management and simple statistical analysis, the important information which are involved in the equipment defect text cannot be detected efficiently, accurately and intelligently, moreover, problems cannot be reflected promptly in terms of the selection and maintenance of equipment. This paper takes the disconnector as an example, based on the 30-year account data (1987-2016) and the 10-year defect data (2007-2016) from the Product Management System (PMS) of State Grid Corporation. By filling the missing values and regularizing data, the basic data are processed, data visualization analysis can be carried out based on the visualization tool of Baidu ECharts platform. By combining with the model construction of defects index, the potential law and relationship of the data can be deeply excavated in terms of the time distribution, type and equipment models of the defects occurred. Finally, according to the analysis results, reasonable suggestions and solutions can be put forward to the problems existing in the selection, operation and maintenance of disconnectors, which provides a new idea for improving the management level of disconnector equipment.