DocumentCode :
1921131
Title :
A comparative study on modeling of a raw material blending process in cement industry using conventional and intelligent techniques
Author :
Kizilaslan, K. ; Ertugrul, S. ; Kural, A. ; Ozsoy, C.
Author_Institution :
Dept of Mech. Eng., Istanbul Tech. Univ., Turkey
Volume :
1
fYear :
2003
fDate :
23-25 June 2003
Firstpage :
736
Abstract :
The task of the raw material blending process in a cement factory is to mix the raw materials in order to produce cement raw meal for the kiln. One of the fundamental problems in the cement manufacture is ensuring that the cement raw meal is of the appropriate chemical composition. A raw meal with a good fineness and well-controlled chemical composition can improve the cement quality and the kiln operation performance. For achieving this purpose, an appropriate modeling of process is the first step to design a control system for the process. This paper summarizes the study of modeling the raw material blending process using intelligent techniques and comparison of results with classical system identification methods.
Keywords :
blending; cement industry; cements (building materials); feedforward neural nets; inference mechanisms; intelligent control; process control; raw materials; ARX model; backpropagation; cement industry; cement quality; chemical composition; control system design; feedforward neural network; intelligent control; modeling; raw material blending process; system Identification; Cement industry; Chemicals; Electrical equipment industry; Kilns; Milling machines; Neural networks; Neutrons; Production; Raw materials; System identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Applications, 2003. CCA 2003. Proceedings of 2003 IEEE Conference on
Print_ISBN :
0-7803-7729-X
Type :
conf
DOI :
10.1109/CCA.2003.1223529
Filename :
1223529
Link To Document :
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