Sparse Gaussian Feature Learning for Nonlinear Industrial Fault Diagnosis-Reference-Cited by-同舟云学术

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Sparse Gaussian Feature Learning for Nonlinear Industrial Fault Diagnosis

Published:2022-08-15 Issue: Volume: Page:
ISSN:
Container-title:2022 34th Chinese Control and Decision Conference (CCDC)
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Author:

Zhang Jianfeng¹,Zhao Chunhui¹,Ding Jinliang²,Sun Youxian¹,Li Xianling³

Affiliation:

1. Zhejiang University,State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering,Hangzhou,China,310027

2. Northeastern University,State Key Laboratory of Synthetical Automation for Process Industries,Shenyang,China,110819

3. Wuhan 2nd Ship Design and Research Institute,Science and Technology on Thermal Energy and Power Laboratory,Wuhan,China,430205

Funder

National Science Fund for Distinguished Young Scholars

State Key Laboratory of Industrial Control Technology

Zhejiang University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10032843/10032844/10033492.pdf?arnumber=10033492

Reference29 articles.

1. Fault Diagnosis in Chemical Processes Based on Class-Incremental FDA and PCA

2. Fault Diagnosis Method of Joint Fisher Discriminant Analysis Based on the Local and Global Manifold Learning and Its Kernel Version

3. Fault Diagnosis Based on Weighted Extreme Learning Machine With Wavelet Packet Decomposition and KPCA

4. Sparse Exponential Discriminant Analysis and Its Application to Fault Diagnosis

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