Pregled bibliografske jedinice broj: 1022659
Fouling Detection in Industrial Heat Exchanger Using Neural Network Models
Fouling Detection in Industrial Heat Exchanger Using Neural Network Models // The 12th EUROPEAN CONGRESS OF CHEMICAL ENGINEERING//Book of abstracts
Firenca, Italija: Italian Association of Chemical Engineering (AIDIC), 2019. str. 2055-2057 (poster, međunarodna recenzija, prošireni sažetak, znanstveni)
CROSBI ID: 1022659 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Fouling Detection in Industrial Heat Exchanger Using Neural Network Models
Autori
Ujević Andrijić, Željka ; Bolf, Nenad ; Brzović, Adriana ; Dorić, Hrvoje
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, prošireni sažetak, znanstveni
Izvornik
The 12th EUROPEAN CONGRESS OF CHEMICAL ENGINEERING//Book of abstracts
/ - : Italian Association of Chemical Engineering (AIDIC), 2019, 2055-2057
ISBN
978-88-95608-75-4
Skup
12th European Congress of Chemical Engineering (ECCE 12) ; 5th European Congress of Applied Biotechnology (ECAB 5)
Mjesto i datum
Firenca, Italija, 15.09.2019. - 19.09.2019
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Fouling detection ; Neural networks ; Fault detection ; Preventive maintenance
Sažetak
An online monitoring system is developed for a shell and tube heat exchanger at hydrocracking plant. Neural network models are developed using inferential variables (temperature and flow rates of hot and cold stream) for predicting heat exchanger outlet temperatures. The deviation between predicted and actual values indicates performance degradation due to fouling. The developed models are designed to establish an on-line monitoring system for maintaining operating efficiency of refinery plants.
Izvorni jezik
Engleski
Znanstvena područja
Kemijsko inženjerstvo
POVEZANOST RADA
Ustanove:
Fakultet kemijskog inženjerstva i tehnologije, Zagreb
