基于支持向量机的矿井提升机制动系统的故障诊断

he Shortage of fault samples is one of the main reasons that restrict the development of intelligent fault diagnosis,support vector machine (SVM) is a statistic learning method based on less samples proposed in the last decade. In this paper,the classification algorithm of support vector machine is used to deal with the multiclass fault classification problem in mine hoist braking system intelligent fault diagnosis. Comparing with BP neural network method,the experimental results show that the SVM method has higher classification performance than BP neural network,and one-against-all SVM method is the best,which is more suitable to apply to fault diagnosis of mine hoist braking system.