Industrial Process Fault Detection Based on Entropy Score Contribution Analysis-Reference-Cited by-同舟云学术

Industrial Process Fault Detection Based on Entropy Score Contribution Analysis

Published:2022 Issue: Volume:10 Page:117646-117657
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Li Fei¹^ORCID,Liu Xiaoqiang²^ORCID,Shang Liangliang³^ORCID,Wang Guozhu⁴,Pan Ziwei¹,Sun Yining⁵

Affiliation:

1. Post-Doctoral Scientific Research Workstation, Ma’anshan University, Anhui, Ma’anshan, China

2. School of Electrical and Information Engineering, Anhui University of Technology, Anhui, Ma’anshan, China

3. School of Electrical Engineering, Nantong University, Jiangsu, Nantong, China

4. Department of Automatic Control, Henan Institute of Technology, Henan, Xinxiang, China

5. Hefei Institutes of Physical Science, Chinese Academy of Sciences, Anhui, Hefei, China

Funder

Youth Project of National Natural Science Foundation of China

Youth Project of Natural Science Foundation of Anhui Province

Key Research Project of Natural Science in Colleges and Universities of Anhui Province

Open Project of Anhui Provincial Key Laboratory of Special Heavy-Duty Robots

Ma’anshan University Postdoctoral Research Launch Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09934839.pdf?arnumber=9934839

Reference34 articles.

1. Industrial process fault detection and diagnosis framework based on enhanced supervised kernel entropy component analysis

2. A Multivariate Monitoring Method Based on Dual Control Chart

3. Fault diagnosis of nonlinear process based on KCPLS reconstruction

4. Nonlinear process fault detection with locally linear embedding of semi supervised sparse discriminant kernel;ren;J Nanjing Norm Univ Nat Sci Ed,2018

5. Fault Detection of Chemical Process Based on Functional Kernel Entropy Component Analysis