Fault Diagnosis of Pump Based on Support Vector Machines

摘要：

The support vector machines (SVM) is a machine-learning algorithm based on statistical learning theory (STL), which aims at the optimal solution in the available information rather than just the optimal solution when the sample number tends towards infinitely large. So it has desirable classification ability even if with fewer samples. The basic theory and classification methods of SVM are introduced in this paper. Fault diagnosis of pump based on SVM is discussed and the result proves that SVM really has preferable ability of classification.

作者: Yongjun Hu Xiaodong Yang Jianbin Guo Ruifeng Zhao

作者单位: School of Information and Electrical Engineering China University of Mining and Technology Xuzhou 22 School of Information and Electrical Engineering China University of Mining and Technology Xuzhou,22 School of Information and Electrical Engineering China University of Mining and Technology Xuzhou 22

会议类型: 国际会议

会议名称: Fourth International Conference on Impulsive and Hybrid Dynamical Systems(ICIHDS 2007)(第四届国际脉冲和混合动力系统学术会议)

会议地点: 南宁

会议语种:英文

在线出版日期: 2007-07-20（万方平台首次上网日期，不代表论文的发表时间）