Abstract: At present, researches on transmission line faults caused by the coupling effect of icing and wind are few, an innovative algorithm is therefore proposed for analyzing the icing-wind disasters of transmission lines based on integrated fuzzy comprehensive evaluation (FCE) and support vector machine (SVM) method. Firstly, by analyzing the influencing factors and their types of typical ice-wind disasters, the key influencing indicators are extracted using FCE method, and the key indicators of wind speed and direction are corrected. And then, based on extraction of five indicators that are highly correlative to disasters, including temperature, relative humidity, wind speed, wind direction and landforms, a nonlinear SVM model with RBF kernel function is proposed for disaster analysis of small samples. Finally, the training samples and test samples are established from historical icing-wind caused faults and non icing-wind caused fault data. Simulation results show that the ice-wind disaster model established by integrated FCE and SVM can effectively judge the probability of ice-wind disaster, and realize the reliable ice-wind disaster analysis with small samples of data.

Key words: transmission line, fuzzy comprehensive evaluation (FCE), support vector machine (SVM), icing and wind disaster, fault analysis