Exponential Local Fisher Discriminant Analysis with Sparse Variables Selection: A Novel Fault Diagnosis Scheme for Industry Application

Exponential Local Fisher Discriminant Analysis with Sparse Variables Selection: A Novel Fault Diagnosis Scheme for Industry Application

Local Fisher discriminant analysis (LFDA) has been widely applied to dimensionality reduction and fault classification fields. However, it often suffers from small sample size (SSS) problem and incorporates all process variables without emphasizing the key faulty ones, thus leading to degraded fault...

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Bibliographic Details
Main Authors: Zhengping Ding, Yingcheng Xu, Kai Zhong
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Machines
Subjects:
matrix exponential
SSS problem
sparse variables selection
fault diagnosis
Online Access:https://www.mdpi.com/2075-1702/11/12/1066

Internet

https://www.mdpi.com/2075-1702/11/12/1066

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