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Kategorie szczegółowe BISAC

Data-Driven and Model-Based Methods for Fault Detection and Diagnosis

ISBN-13: 9780128191644 / Angielski / Miękka / 2020 / 322 str.

Majdi Mansouri; Mohamed-Faouzi Harkat; Hazem N. Nounou
Data-Driven and Model-Based Methods for Fault Detection and Diagnosis Majdi Mansouri Mohamed-Faouzi Harkat Hazem N. Nounou 9780128191644 Elsevier - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Data-Driven and Model-Based Methods for Fault Detection and Diagnosis

ISBN-13: 9780128191644 / Angielski / Miękka / 2020 / 322 str.

Majdi Mansouri; Mohamed-Faouzi Harkat; Hazem N. Nounou
cena 574,40
(netto: 547,05 VAT:  5%)

Najniższa cena z 30 dni: 569,69
Termin realizacji zamówienia:
ok. 30 dni roboczych
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Darmowa dostawa!
Kategorie:
Inne
Kategorie BISAC:
Technology & Engineering > Chemical & Biochemical
Wydawca:
Elsevier
Język:
Angielski
ISBN-13:
9780128191644
Rok wydania:
2020
Ilość stron:
322
Waga:
0.43 kg
Wymiary:
22.86 x 15.24 x 1.7
Oprawa:
Miękka
Wolumenów:
01
Dodatkowe informacje:
Bibliografia

1. Introduction2. Linear latent variable approaches for fault detection3. Nonlinear latent variable approaches for fault detection4. Multiscale latent variable (MSLV) approaches for fault detection5. Interval latent variable (ILV) approaches for fault detection6. Model based approaches for fault detection7. Conclusions and Perspectives

Dr. Majdi Mansouri received the engineering degree in Electrical Engineering in 2006 from the Higher School of Communication of Tunisia (SUPCOM), Tunisia. He received his master degree of Electrical Engineering from the School of Electronic, Informatique and Radiocommunications in Bordeaux (ENSEIRB), France, in 2008. He received his PhD degree of Electrical Engineering from the University of Technology of Troyes (UTT), France, in 2011. In December 2019, he received the degree of HDR (Accreditation To Supervise Research) of Applied Mathematics and Statistics for Electrical Engineering from University of Orleans in France. He joined the Electrical Engineering Program at Texas A&M University at Qatar, in 2011, where he is currently an Associate Research Scientist. He has over ten years of research and practical experience in systems engineering and signal processing. His work focuses on the utilization of applied mathematics and statistics concepts to develop statistical data and model driven techniques and algorithms for modeling, estimation, fault detection, fault classification, monitoring and diagnosis, which aim to improve process operations and enhance the data validation. Dr. Majdi Mansouri is the author of more than 150 refereed journal and conference publications and book chapters, and has worked on several projects as lead principal investigator (LPI) and principal investigator (PI). Dr. Mansouri is a member of IEEE. Dr. Mohamed-Faouzi HARKAT received his Eng. degree in Automatic control from Annaba University, Algeria in 1996, his Ph.D. degree from Institut National Polytechnique de Lorraine (INPL), France in 2003. He is now Professor in the Department of Electronics at Annaba University, Algeria. His research interests include fault diagnosis, process modelling and monitoring, multivariate statistical approaches and neural networks. Dr. Harkat is the author of more than 100 refereed journal and conference publications and book chapters. Dr. Hazem N. Nounou (SM'08) is a professor in the Electrical and Computer Engineering Program and the Assistant Dean for Academic and Student Services at Texas A&M University at Qatar. From 20015-2017, he was the holder of Itochu Professorship. 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 Ohio State University, Columbus, in 1997 and 2000, respectively, all in electrical engineering. In 2001, he was a Development Engineer for PDF Solutions, a consulting firm for the semiconductor industry, in San Jose, CA. Then, in 2001, he joined the Department of Electrical Engineering at King Fahd University of Petroleum and Minerals in Dhahran, Saudi Arabia, as an Assistant Professor. In 2002, he moved to the Department of Electrical Engineering, United Arab Emirates University, Al-Ain, UAE. In 2007, he joined the Electrical and Computer Engineering Program at Texas A&M University at Qatar, Doha, Qatar, where he is currently a professor. He published more than 200 refereed journal and conference papers and book chapters. He served as an Associate Editor and in technical committees of several international journals and conferences. His research interests include data-based control, monitoring and fault detection, intelligent and adaptive control, control of time-delay systems, system biology, and system identification and estimation. Dr. Nounou is a senior member of IEEE. Dr. 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).



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