A comparative study of black-box models for cement fineness pbkp_rediction using SCADA measurements of a closed circuit grinding

Abstract:

This paper presents a comparative study of three different modeling techniques for pbkp_redicting cement fineness using input-output SCADA measurements of the closed circuit grinding in a cement plant. The modeling approaches used are the following: statistical, artificial neural networks (ANN), and adaptive neuro-fuzzy inference system (ANFIS). The data set for generating the pbkp_redictive models are obtained from a database of the operation of the cement plant, UCEM-Guapan located in Azogues, Ecuador. Online validations of the proposed models allow the selection of the best approach and the most accurate models for cement fineness pbkp_rediction, Blaine and percentage passing the sieve No. 325.

Año de publicación:

2016

Keywords:

• Fineness Of Cement
• black-box model
• pbkp_rediction

Fuente:

rraae