A novel chemical composition estimation model for cement raw material blending process

Yaoyao Bao; Yuanming Zhu; Weimin Zhong; Feng Qian

doi:10.1016/j.cjche.2018.12.024

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A novel chemical composition estimation model for cement raw material blending process

Process Systems Engineering and Process Safety | Updated：2026-01-06

- A novel chemical composition estimation model for cement raw material blending process
- A novel chemical composition estimation model for cement raw material blending process
- 中国化学工程学报（英文版） 2019年27卷第11期页码：2734-2741
- Affiliations：
  
  Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology,Shanghai,China,200237
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2018.12.024
  中图分类号：
- 纸质出版：2019
- Accepted：
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Yaoyao Bao, Yuanming Zhu, Weimin Zhong, 等. A novel chemical composition estimation model for cement raw material blending process[J]. 中国化学工程学报（英文版）, 2019,27(11):2734-2741.

Yaoyao Bao, Yuanming Zhu, Weimin Zhong, Feng Qian. A novel chemical composition estimation model for cement raw material blending process[J]. Chinese Journal of Chemical Engineering, 2019, 27(11): 2734-2741.
Yaoyao Bao, Yuanming Zhu, Weimin Zhong, 等. A novel chemical composition estimation model for cement raw material blending process[J]. 中国化学工程学报（英文版）, 2019,27(11):2734-2741. DOI： 10.1016/j.cjche.2018.12.024.

Yaoyao Bao, Yuanming Zhu, Weimin Zhong, Feng Qian. A novel chemical composition estimation model for cement raw material blending process[J]. Chinese Journal of Chemical Engineering, 2019, 27(11): 2734-2741. DOI： 10.1016/j.cjche.2018.12.024.

摘要

Abstract

Raw material blending process is an essential part of the cement production process. The main purpose of the process is to guarantee a certain oxide composition for the raw meal at the outlet of the mill by regulating the four raw materials. But the chemical compositions of raw materials vary from time to time

resulting in difficulties to control the oxide compositions to a predefined value. Therefore

a novel algorithm to estimate the chemical compositions of the raw materials is developed. The paper mainly consists of two parts. In model construction part

a novel constrained least square model is proposed to overcome the deviation introduced by long-term drift of the material components

and the model parameters are estimated with an online strategy. And in validation part

the approach is implemented to two examples including datasets from simulation model and the actual industrial process. The final results show the effectiveness of the proposed method.

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