Small sample size fault data recognition based on the principal component analysis and kernel local Fisher discriminant analysis

doi:10.13245/j.hust.151203

IR > 机电工程学院

	Small sample size fault data recognition based on the principal component analysis and kernel local Fisher discriminant analysis
	Zhao, Rongzhen; Wang, Xuedong; Deng, Linfeng
	2015-12-23
发表期刊	Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition)
ISSN	16714512
卷号	43 期号:12 页码:12-16
摘要	Aiming at the dimension reduction of the small sample size fault data set, a new method in dimension reduction was proposed based on the combination of principal component analysis (PCA) and kernel local Fisher discriminant analysis. This method first used PCA to extract key information and dimension reduction of the data set, then the Gaussian kernel was used to map the feature subset to a high-dimensional liner space, and in this space, local Fisher discriminant analysis was applied to a train most discrimination classification feature set. Finally, a small sample size rotor fault data feature set were employed to verify this method. According to the result of dimension reduction, clear space between various faults categories and small distance in the similar class can be obtained. This method provide an effective way to solve the problem of small sample size rotor fault data set classification. © 2015, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
关键词	Discriminant analysis Failure analysis Fisher information matrix Principal component analysis Classification features Data dimension reduction Dimension reduction Fault data Gaussian kernels High-dimensional Local Fisher Discriminant Analysis Small Sample Size
DOI	10.13245/j.hust.151203
收录类别	EI
语种	中文
出版者	Huazhong University of Science and Technology
EI入藏号	20155201736657
EI主题词	Data reduction
EI分类号	723.2 Data Processing and Image Processing - 922 Statistical Methods - 922.2 Mathematical Statistics
来源库	Compendex
分类代码	723.2 Data Processing and Image Processing - 922 Statistical Methods - 922.2 Mathematical Statistics
引用统计	无
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/112806
专题	机电工程学院
作者单位	School of Mechanical and Electronical Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
第一作者单位	兰州理工大学
第一作者的第一单位	兰州理工大学
推荐引用方式 GB/T 7714	Zhao, Rongzhen,Wang, Xuedong,Deng, Linfeng. Small sample size fault data recognition based on the principal component analysis and kernel local Fisher discriminant analysis[J]. Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition),2015,43(12):12-16.
APA	Zhao, Rongzhen,Wang, Xuedong,&Deng, Linfeng.(2015).Small sample size fault data recognition based on the principal component analysis and kernel local Fisher discriminant analysis.Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition),43(12),12-16.
MLA	Zhao, Rongzhen,et al."Small sample size fault data recognition based on the principal component analysis and kernel local Fisher discriminant analysis".Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) 43.12(2015):12-16.