Icing image of Baoji power transmission line in January 2025

The data processing and analysis methods are as follows: meteorological data is located and matched with stations using the Haversine formula, evaluated for reliability using weighted methods, and finely processed using interpolation methods. It is then input into the WRF numerical weather model to simulate key meteorological elements; The icing image is preprocessed, wire pixel extraction, and width measurement are completed through machine vision technology to calculate the icing thickness; After feature engineering processing, multi-source data is used to train the XGBoost risk assessment model.

The final results show that after fine processing of meteorological data, the relative error is ≤ 10%, the monitoring error of ice cover thickness is ≤ 3%, and the prediction error is ≤ 5%. The visualization system based on the three types of data can accurately predict and grade the probability of ice cover tripping for 1-3 hours and 3-6 hours, providing reliable data support for intelligent operation and maintenance of the power grid.