说明：  提出了基于主动学习SVM的局部放电模式识别方法。将主动学习的思想引用到“一对一”多分类SVM分类器,选用基于后验概率的釆样函数对放电样本进行选择,挑选出对分类器最有价值的样本进行训练。
(Puts forward the partial discharge pattern recognition method based on active learning SVM. Will reference to the one to one the ideology of active study of classification of SVM classifier, sample selection based on the calculation of posterior probability function of discharge samples to choose, pick out the most valuable training samples for classifier)