以输电线路覆冰的状态监测为背景,研究此背景下信息融合模型特征层的分类方法。探讨分析了BP神经网络和支持向量机解决问题的可行性,在实验室条件下用两种算法实现了信息融合模型特征层的分类并作了比较总结。 Taking the condition monitoring of icing on transmission lines as the background, the classification method of feature layer of information fusion model under this background is studied. The feasibility of solving BP neural network and support vector machine is analyzed. Two kinds of algorithms are used to classify the information fusion model ’s feature layer under laboratory conditions and make a comparison.