Research of the Machinery Fault Diagnosis and Prediction Based on Support Vector Machine

被引：0
|
作者：
Qie, Xiujuan [1 ]
Zhang, Jing [1 ]
Zhang, Jiangya [1 ]
机构：
[1] HeBei Coll Sci & Technol, Dept Elect & Mech Engn, Shijiazhuang, Peoples R China
来源：
PROCEEDINGS OF THE 2015 3RD INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND INFORMATION TECHNOLOGY APPLICATIONS | 2015年 / 35卷
关键词：
Machinery fault diagnosis; Fault trend prediction; Support vector machine;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper analyzes the theory of support vector machines-SVM and discusses the algorithms of SVM classification and regression. After overviewed the SVM application research on machinery fault diagnosis and prediction recently, it discusses the, erits and deficiencies of SVM and the points out the bright application research on machinery fault diagnosis and prediction. It presents the SVM model for machine condition trend prediction. It is proved that SVM model has good predict ability for long time period by comparing the AR model and SVM model for a test system vibration signal.
引用
收藏
页码：635 / 639
页数：5
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