A Fault Feature Reduction Method Based on Rough Set Attribute Reduction and Principal Component Analysis
文献类型：会议论文
| 作者 | Huang, Qiang1 ; Wang, Jian1; Su, Haixia1; Yang, Lu1; Ding, Zhaoping2; Zhang, Guigang1
|
| 出版日期 | 2016 |
| 会议日期 | 2016年7月27-29日 |
| 会议地点 | 四川成都 |
| 关键词 | Feature Reduction Rough Set Attribute Reduction Principal Component Analysis Aero Engine Rotor Fault |
| DOI | 10.1109/ChiCC.2016.7554399 |
| 英文摘要 | Recently, 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. |
| 会议录 | Control Conference (CCC), 2016 35th Chinese
 |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/13021]  |
| 专题 | 数字内容技术与服务研究中心_智能技术与系统工程 |
| 通讯作者 | Wang, Jian |
| 作者单位 | 1.Institute of Automation, Chinese Academy of Science 2.AVIX Jiangxi Hongdu Aviation Industry Group Company Ltd |
| 推荐引用方式 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]. 见:. 四川成都. 2016年7月27-29日. |
入库方式： OAI收割
来源：自动化研究所
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