Fault detection using machine learning based dynamic ICA-distributed CCA: Application to industrial chemical process-Reference-Cited by-同舟云学术

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Fault detection using machine learning based dynamic ICA-distributed CCA: Application to industrial chemical process

Published:2024-06 Issue: Volume:11 Page:100156
ISSN:2772-5081
Container-title:Digital Chemical Engineering
language:en
Short-container-title:Digital Chemical Engineering

Author:

Ali Husnain^ORCID,Zhang Zheng^ORCID,Safdar Rizwan,Rasool Muhammad Hammad,Yao Yuan^ORCID,Yao Le,Gao Furong

Publisher

Elsevier BV

Reference33 articles.

1. Multiscale Detection of Chemical Process using Improved Distributed CCA-Wavelet Approach;Ali;IFAC-PapersOnLine,2023

2. Fault diagnosis by using multi-scale signed directed graph;Ali;AIP Conference Proceedings,2022

3. Multiscale Principal Component Analysis-Signed Directed Graph Based Process Monitoring and Fault Diagnosis;Ali;ACS Omega,2022

4. Multiscale monitoring of industrial chemical process using wavelet-entropy aided machine learning approach;Ali;Process Safety and Environmental Protection,2023

5. Computational applications using data driven modeling in process Systems: A review;Bishnu;Digital Chemical Engineering,2023

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Robust statistical industrial fault monitoring: A machine learning-based distributed CCA and low frequency control charts;Chemical Engineering Science;2024-11

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