Title :
Online Modeling for Combined Cement Grinding System via Extreme Learning Machine
Author :
Hengtao Liu;Zhugang Yuan;Qiang Zhang;Zhe Su
Author_Institution :
School of Electrical Engineering, University of Jinan, Shandong Province, 250022, China
Abstract :
In order to use the method based on model to study the accurate control of cement combined grinding system, and improve its automatic control level, this paper proposes a extreme learning machine (ELM) online modeling method for combined cement grinding system. First of all, this paper analyzes the process of combined grinding system, based on the analysis of the process, we know that the speed of circulating fan and the current of out mill grinding have a strong correlation, and are suitable for input and output of Combined Cement Grinding System; Secondly, use the mean filter to preprocess the data collected in the field; And then, use the method of extreme learning machine established the online modeling of cement combined grinding which use circulation fan speed as inputs, and out mill grinding hoist current as output; Finally the simulation shows that the method is effective.
Keywords :
"Data models","Filtering","Neurons","Analytical models","Prediction algorithms","Process control","Predictive models"
Conference_Titel :
Information and Automation, 2015 IEEE International Conference on
DOI :
10.1109/ICInfA.2015.7279515