Application of PCA and SVM in Fault Diagnosis of Mine Hoist

摘要：

This paper studies the application of principal component analysis (PCA) and support vector machines (SVM) in fault diagnosis of mine hoist system. In this paper, the PCA is used for feature extraction and data reduction from original features of gearbox. With the features reduced from gearbox and the features from hydraulic system and wire rope, the training of multi-class SVM is carried out using the multi-class optimization algorithm based on one class and is applied to perform the faults identification. The results show that this method using PCA has the better performance of classification process than that without PCA.

作者: Yanwei Chang Yaocai Wang Tao Liu

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

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）