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Sensor fault diagnosis of nonlinear processes based on structured kernel principal component analysis

✍ Scribed by Kechang Fu; Liankui Dai; Tiejun Wu; Ming Zhu

Book ID
107504731
Publisher
South China University of Technology and Academy of Mathematics and Systems Science, CAS
Year
2009
Tongue
English
Weight
342 KB
Volume
7
Category
Article
ISSN
1672-6340

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## Abstract The aim of this paper is to propose a novel real‐time process monitoring and fault diagnosis method based on the principal component analysis (PCA) and kernel Fisher discriminant analysis (KFDA). There is a need to develop this method in order to overcome the inherent limitations of the