CASIA OpenIR  > 数字内容技术与服务研究中心  > 智能技术与系统工程
A Fault Feature Reduction Method Based on Rough Set Attribute Reduction and Principal Component Analysis
Huang, Qiang1; Wang, Jian1; Su, Haixia1; Yang, Lu1; Ding, Zhaoping2; Zhang, Guigang1
2016
Conference Name2016 35th Chinese Control Conference (CCC)
Source PublicationControl Conference (CCC), 2016 35th Chinese
Conference Date2016年7月27-29日
Conference Place四川成都
AbstractRecently, precise diagnosis of faults is increasingly taken seriously, and the fault feature reduction is one of the key technologies to carry out accurate and reliable diagnosis. In this paper, a feature reduction method based on rough set attribute reduction and principal component analysis is proposed. Firstly the rough set attribute reduction is used to remove the irrelevant features, and then the principal component analysis is adopted to further reduce the features. Finally, the validity of the method is verified by the aero engine rotor fault data. Experimental results show that the proposed method can not only improve the accuracy of fault diagnosis, but also reduce the number of fault features and improve the diagnostic efficiency.
KeywordFeature Reduction Rough Set Attribute Reduction Principal Component Analysis Aero Engine Rotor Fault
DOI10.1109/ChiCC.2016.7554399
Indexed ByEI
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13021
Collection数字内容技术与服务研究中心_智能技术与系统工程
Corresponding AuthorWang, Jian
Affiliation1.Institute of Automation, Chinese Academy of Science
2.AVIX Jiangxi Hongdu Aviation Industry Group Company Ltd
Recommended Citation
GB/T 7714
Huang, Qiang,Wang, Jian,Su, Haixia,et al. A Fault Feature Reduction Method Based on Rough Set Attribute Reduction and Principal Component Analysis[C],2016.
Files in This Item: Download All
File Name/Size DocType Version Access License
07554399.pdf(317KB)会议论文 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Huang, Qiang]'s Articles
[Wang, Jian]'s Articles
[Su, Haixia]'s Articles
Baidu academic
Similar articles in Baidu academic
[Huang, Qiang]'s Articles
[Wang, Jian]'s Articles
[Su, Haixia]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Huang, Qiang]'s Articles
[Wang, Jian]'s Articles
[Su, Haixia]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 07554399.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.