RBF–ARX model of an industrial furnace for drying olive pomace

► We model a real furnace, fuelled with orujo, used to dry olive pomace. ► We apply a radial basic functions–auto-regression with exogenous variables (ARXs–RBFs) method. ► Root-mean-square error and r2 are used to validate the ARX–RBF model. Drying operations are common in food industries. One of th...

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Bibliographic Details
Published in:Energy conversion and management 2012-12, Vol.64, p.106-112
Main Authors: Casanova-Peláez, P.J., Cruz-Peragón, F., Palomar-Carnicero, J.M., Dorado, R., López-García, R.
Format: Article
Language:English
Subjects:
Applied sciences
Auto-regression
Devices using thermal energy
Dryers
Energy
Energy. Thermal use of fuels
Exact sciences and technology
Neuronal network
Rotary dryer
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Summary:► We model a real furnace, fuelled with orujo, used to dry olive pomace. ► We apply a radial basic functions–auto-regression with exogenous variables (ARXs–RBFs) method. ► Root-mean-square error and r2 are used to validate the ARX–RBF model. Drying operations are common in food industries. One of the main components in a drying system is the furnace. The furnace operation involves heat–mass transfer and combustion, thus it demands a complex mathematic representation. Since autoregressive methods are simple, and help to simulate rapidly a system, we model a drying furnace of olive pomace via an auto-regression with exogenous variables (ARXs) method. A neural network of radial basic functions (RBFs) defines the ARX experimental relation between the amounts of dry pomace (moisture content of 15%) used like fuel and the temperature of outlet gases. A real industrial furnace is studied to validate the proposed model, which can help to control the drying process.
ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2012.04.013