Research on Multi-source Fusion Warning Method under Extreme Weather Conditions
The normal operation of power equipment is affected by extreme weather such as rainstorm and typhoon,hence,it is necessary to establish an effective fault warning model.The deep fusion neural network and multi-source data fusion method are used to establish a spatiotemporal prediction model for extreme weather.A fault analysis for transmission tower is used to es-tablish this method.The final MAE and RMSE of neural network are 0.5 and 0.2,respectively,which are both lower than other methods.In the landslide scenario,the damage probability of Towers 4 to 8 exceeded 0.5,and Tower 7 has the highest value of 0.79.The failure rate of tower gradually increases when rainfall increases.The proposed prediction model can predict the faults of power equipment under extreme weather and has better results.
万方数据
维普
