A Review on Data‐Driven Learning Approaches for Fault Detection and Diagnosis in Chemical Processes-Reference-Cited by-同舟云学术

A Review on Data‐Driven Learning Approaches for Fault Detection and Diagnosis in Chemical Processes

Published:2021-02-26 Issue:3 Volume:8 Page:239-259
ISSN:2196-9744
Container-title:ChemBioEng Reviews
language:en
Short-container-title:CBEN

Author:

Taqvi Syed Ali Ammar¹²,Zabiri Haslinda³,Tufa Lemma Dendena⁴,Uddin Fahim¹,Fatima Syeda Anmol³,Maulud Abdulhalim Shah³

Affiliation:

1. NED University of Engineering & Technology Department of Chemical Engineering 75270 Karachi Pakistan

2. NED University of Engineering and Technology Neurocomputation Lab, National Centre of Artificial Intelligence 75270 Karachi Pakistan

3. Universiti Teknologi PETRONAS Chemical Engineering Department 32610 Seri Iskandar, Perak Darul Ridzuan Malaysia

4. Addis Ababa Institute of Technology School of Chemical and Bioengineering King George VI St 1000 Addis Ababa Ethiopia

Publisher

Wiley

Subject

Industrial and Manufacturing Engineering,Filtration and Separation,Process Chemistry and Technology,Biochemistry,Chemical Engineering (miscellaneous),Bioengineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cben.202000027

Reference244 articles.

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2. S.KumarM K.Ganapathy N.Al Yahyaee A.Ayoub Abu Dhabi Int. Petroleum Exhibition & Conf. Abu Dhabi UAE November2016. DOI:https://doi.org/10.2118/183052‐MS

3. S. A.Fatima H.Zabiri S. A. A.Taqvi N.Ramli System Identification of Industrial Debutanizer Column inProc. of the 9th IEEE Int. Conf. on Control System Computing and Engineering (ICCSCE) IEEE New Jersey2020.

4. Fault Detection and Diagnosis in a Sour Gas Absorption Column Using Neural Networks

5. Injury Facts 1999 National Safety Council Itasca IL1999.

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