Prediction model of slurry pH based on mechanism and error compensation for mineral flotation process

Xiaoli Wang; Lei Huang; Chunhua Yang

doi:10.1016/j.cjche.2018.06.012

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Prediction model of slurry pH based on mechanism and error compensation for mineral flotation process

Selected Papers from the 28th Chinese Process Control Conference | Updated：2026-01-06

- Prediction model of slurry pH based on mechanism and error compensation for mineral flotation process
- Prediction model of slurry pH based on mechanism and error compensation for mineral flotation process
- 中国化学工程学报（英文版） 2018年26卷第8期页码：1766-1772
- Affiliations：
  
  School of Information Science and Engineering, Central South University,Changsha,China,410083
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2018.06.012
  中图分类号：
- 纸质出版：2018
- Accepted：
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Xiaoli Wang, Lei Huang, Chunhua Yang. Prediction model of slurry pH based on mechanism and error compensation for mineral flotation process[J]. 中国化学工程学报（英文版）, 2018,26(8):1766-1772.

Xiaoli Wang, Lei Huang, Chunhua Yang. Prediction model of slurry pH based on mechanism and error compensation for mineral flotation process[J]. Chin.J.Chem.Eng., 2018, 26(8): 1766-1772.
Xiaoli Wang, Lei Huang, Chunhua Yang. Prediction model of slurry pH based on mechanism and error compensation for mineral flotation process[J]. 中国化学工程学报（英文版）, 2018,26(8):1766-1772. DOI： 10.1016/j.cjche.2018.06.012.

Xiaoli Wang, Lei Huang, Chunhua Yang. Prediction model of slurry pH based on mechanism and error compensation for mineral flotation process[J]. Chin.J.Chem.Eng., 2018, 26(8): 1766-1772. DOI： 10.1016/j.cjche.2018.06.012.

摘要

Abstract

A suitable pH value of the slurry is a key to efficient mineral flotation. Considering the control delay problem of pH value caused by offline pH measurement

an integrated prediction model for pH value in bauxite froth flotation is proposed

which considers the effect of ore compositions on pH value. Firstly

a regression model is obtained for alkali (Na

) consumed by the reaction between ore and alkali. According to the first-order hydrolysis of the remaining alkali

a mechanism-based prediction model is presented for the pH value. Then

considering the complexity of the flotation mechanism

an error prediction model which uses time series of the error of the mechanism model as inputs is presented based on autoregressive moving average (ARMA) method to compensate the mechanism model. Finally

expert rules are established to correct the error compensation direction

which could reflect the dynamic changes during the process accurately and effectively. Simulation results using industrial data show that the presented model meets the needs of the industrial process

which laid the foundation for predictive

control of pH regulator.

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