基于支持向量机的矿井提升机制动系统的故障诊断

故障样本缺乏是制约智能故障诊断发展的重要原因,支持向量机是近年来提出的一种基于小样本的统计学习方法.将支持向量机分类算法应用到提升机制动系统的多类故障分类,并与BP神经网络进行对比研究,实验表明,支持向量机算法比BP神经网络具有更好的分类性能,且 "一对多"支持向量机的分类效果是最好的,更适合于提升机制动系统的故障诊断.

Fault Diagnosis of Mine Hoist Braking System Based on Support Vector Machine

The 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 ...