Mohamed N Nounou, Hazem N Nounou, Nour Basha, Byanne Malluhi

Advances in Data-Driven Modeling, Fault Detection, and Fault Identification

Applications to Chemical Processes

• Broschiertes Buch

Produktbeschreibung

Advances in Data-Driven Modeling, Fault Detection, and Fault Identification: Applications to Chemical Processes is an accumulation of research on data-driven modeling techniques, and their application towards robust modeling, fault detection and fault identification. The book covers a wide range of basic to advanced empirical techniques in comprehensive detail, and provides a easyto-read guide for academic or industrial researchers that are interested in applying these techniques towards their respective fields. The book starts with exposing the scope of the book, in addition to a brief rundown of the methods discussed, and their importance to academic research and industrial applications. It will also describe some of the chemical processes that will be used to validate and compare the various data-driven techniques, which include the Tennessee Eastman Process and a Fischer-Tropsch bench scale setup. It discusses a first category of the methods, that covers basic and advanced robust empirical techniques, followed by a second category of the methods discussed, that covers prominent empirical statistical charts used to detect faults in multivariate systems, and finally a third category of the methods, that covers conventional and novel multiclass classification machine learning techniques that can be used to accurately differentiate in batch or real-time between different fault classes in industrial process or academic applications.

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Produktdetails

• Verlag: Elsevier Science
• Seitenzahl: 500
• Erscheinungstermin: 1. Mai 2025
• Englisch
• ISBN-13: 9780443334825
• ISBN-10: 044333482X
• Artikelnr.: 71810205

Autorenporträt

Mohamed Nounou is a professor of Chemical Engineering at Texas A&M University-Qatar. He received the B.S. degree (Magna Cum Laude) from Texas A&M University, College Station, in 1995, and the M.S. and Ph.D. degrees from the Ohio State University, Columbus, in 1997 and 2000, respectively, all in chemical engineering. From 2000 to 2002, he was with PDF Solutions, a consulting company for the semiconductor industry, in San Jose, CA. In 2002, he joined the Department of Chemical and Petroleum Engineering at the United Arab Emirates University. In 2006, he joined the Chemical Engineering Program at Texas A&M University at Qatar, where he is currently a professor. He has received research funding over $5M and published more than 190 refereed journal and conference papers and book chapters. He also served as an associate editor and in technical committees of several international journals and conferences. His research interests include process modeling, monitoring, estimation, system biology, and intelligent control. He is a senior member of the American Institute of Chemical Engineers (AIChE) and a senior member of the Institute of Electrical and Electronics Engineers (IEEE).

Inhaltsangabe

1. Introduction
2. Modeling
3. Fault detection
4. Fault identification
5. Appendix