Modeling and Optimization of a Roll-Type Electrostatic Separation Process Using Artificial Neural Networks

Author

Touhami, Seddik ; Medles, Karim ; Dahou, Omar ; Tilmatine, Amar ; Bendaoud, Abdelber ; Dascalescu, Lucian

Author_Institution

Dept. of Electr. Eng., Univ. Djillali Liabes, Sidi Bel Abbes, Algeria

Volume

49

Issue

4

fYear

2013

fDate

July-Aug. 2013

Firstpage

1773

Lastpage

1780

Abstract

The aim of this paper is the development of a procedure for the optimization of electrostatic separation processes using artificial neural networks (ANNs) in association with genetic algorithms. The objective was to maximize the insulation product, the control variables being the high voltage that supplies the electrode system and the rotation speed of the roll electrode. The ANN model is compared with that obtained using the classical experimental design methodology. The predicted optimum is confirmed by experiment.

Keywords

electrostatic precipitators; electrostatics; genetic algorithms; insulation; neural nets; artificial neural networks; control variables; electrode system; genetic algorithms; insulation product; roll electrode; roll-type electrostatic separation process; rotation speed; Artificial neural networks (ANNs); electrostatic separator; genetic algorithms (GAs);

fLanguage

English

Journal_Title

Industry Applications, IEEE Transactions on

Publisher

ieee

ISSN

0093-9994

Type

jour

DOI

10.1109/TIA.2013.2256451

Filename

6495477