Transmission Line Meteorological Risk Data Automatic Generation and Auxiliary Label Method

With the global warming, extreme weather phenomena occur frequently, which poses a serious threat to the safe operation of transmission lines. Aiming at the problem of in-completed meteorological risk data of historical transmission lines, in this paper, we propose a method that can automatically generate time series data and assist labels. The method is based on artificial intelligence technology, and comprises feature correlation analysis, data sample generation, data sample auxiliary labeling and other modules, it realizes the accurate prediction and effective management of meteorological risk of transmission lines. This paper introduces the technical principle and implementation steps of this method in detail. It provides strong support for risk early warning and emergency response in the power industry.