A novel imbalanced fault diagnosis method integrated <scp>KLFDA</scp> with improved cost‐sensitive learning <scp>ANBSVM</scp>-Reference-Cited by-同舟云学术

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A novel imbalanced fault diagnosis method integrated KLFDA with improved cost‐sensitive learning ANBSVM

Published:2022-10-13 Issue:4 Volume:101 Page:1943-1952
ISSN:0008-4034
Container-title:The Canadian Journal of Chemical Engineering
language:en
Short-container-title:Can J Chem Eng

Author:

Jiang Xue¹²³^ORCID,Xu Yuan¹²,Ke Wei⁴,Zhang Yang¹²,Zhu Qunxiong¹²,He Yanlin¹²^ORCID

Affiliation:

1. College of Information Science & Technology Beijing University of Chemical Technology Beijing China

2. Engineering Research Center of Intelligent PSE Ministry of Education of China Beijing China

3. Department of Chemical and Biomolecular Engineering National University of Singapore Singapore Singapore

4. School of Applied Sciences Macao Polytechnic Institute Macao SAR China

Funder

China Scholarship Council

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Chemical Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cjce.24602

Reference35 articles.

1. A fault detection method based on horizontal visibility graph‐integrated complex networks: Application to complex chemical processes

2. Early and extremely early multi-label fault diagnosis in induction motors

3. Novel Pattern-Matching Integrated KCVA with Adaptive Rank-Order Morphological Filter and Its Application to Fault Diagnosis

4. Survey on the theoretical research and engineering applications of multivariate statistics process monitoring algorithms: 2008-2017

5. Application of fault monitoring and diagnosis in process industry based on fourth order moment and singular value decomposition

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