Pregled bibliografske jedinice broj: 295190
Software Sensors for Monitoring of the Solid Waste Composting Process
Software Sensors for Monitoring of the Solid Waste Composting Process // Proceedings of 33rd International Conference of SSCHE / J. Markoš and V. Štefuca (ur.).
Bratislava: SSCHE, 2006. (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 295190 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Software Sensors for Monitoring of the Solid Waste Composting Process
Autori
Bolf, Nenad ; Kopčić, Nina ; Briški, Felicita ; Gomzi, Zoran
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of 33rd International Conference of SSCHE
/ J. Markoš and V. Štefuca - Bratislava : SSCHE, 2006
ISBN
80-227-2409-2
Skup
33rd International Conference of SSCHE
Mjesto i datum
Tatranské Matliare, Slovačka, 22.05.2006. - 26.05.2006
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
aerobic composting; process modeling and identification; neural network; soft sensor
Sažetak
This article deals with solid waste aerobic management process identification using empirical kinetic mathematical and neural network-based models. Composting of tobacco solid waste is carried within aerobic closed thermally insulated column reactor of 25 L effective volume. The experiments have been carried under adiabatic condition at different constant air flow rates of 0.3, 0.6 and 0.9 dm3 min-1 of volatile substance under the adiabatic conditions. Three soft sensors using kinetic and neural network-based models have been developed aiming to estimate conversion that cannot be measure in the continuously manner. Neural network models based on NFIR (Nonlinear Finite Impulse Response) and NARX (Nonlinear AutoRegressive model with eXogenous inputs) identification methods have been used. The neural networks have been trained by the adaptive gradient method using cascade learning. After the process models have been developed, the conversion during the course of the process is estimated. Results obtained by experiment, kinetic model, and neural network models have been compared. It was found that the selected models describe aerobic composting fairly well and confirm the hypothesis that the released heat is proportional to the biodegradation process. The developed neural-network models show that the neural networks are capable to be applied as intelligent software sensors giving the possibility of continuous process monitoring. The models have potential to be used for inferential control of composting process.
Izvorni jezik
Engleski
Znanstvena područja
Kemijsko inženjerstvo
POVEZANOST RADA
Projekti:
125-1251963-1964 - Softverski senzori i analizatori za motrenje i vođenje procesa (Bolf, Nenad, MZOS ) ( CroRIS)
Ustanove:
Fakultet kemijskog inženjerstva i tehnologije, Zagreb