Prediction of component concentrations in sodium aluminate liquor using stochastic configuration networks
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ORIGINAL ARTICLE
Prediction of component concentrations in sodium aluminate liquor using stochastic configuration networks Wei Wang1,2
•
Dianhui Wang2,3
Received: 29 August 2019 / Accepted: 3 February 2020 Ó Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract Online measuring of component concentrations in sodium aluminate liquor is essential and important to Bayer alumina production process. They are the basis of closed-loop control and optimization and affect the final product quality. There are three main components in sodium aluminate liquor, termed caustic hydroxide, alumina and sodium carbonate (their concentrations are represented by cK , cA and cC , respectively). They are obtained off-line by titration analysis and suffered from larger time delays. To solve this problem, a hybrid model for cK and cA is proposed by combining a mechanism model and a stochastic configuration network (SCN) compensation model. An SCN-based model for cC is also proposed using the estimated values of cK and cA from the hybrid model. A real-world application conducted in Henan Branch of China Aluminum Co. Ltd demonstrates the effectiveness of the proposed modelling techniques. Experimental results show that our proposed method performs favourably in terms of the prediction accuracy, compared against the regress model, BP neural networks, RBF neural networks and random vector functional link model. Keywords Stochastic configuration networks Industrial data modelling Component concentrations Sodium aluminate liquor
1 Introduction Sodium aluminate liquor is an intermediate product throughout the whole process of Bayer alumina production. The main component concentrations of sodium aluminate liquor cK , cA and cC are the foundation for indicator control in the procedure of original ore pulp preparation, digestion, decomposition and evaporation. Due to the nonlinearity characteristics of sodium aluminate liquor, such as easy precipitation, large viscosity, high concentration and strong corrosiveness, online measuring of component concentrations is quite difficult and usually they are obtained through & Dianhui Wang [email protected] 1
College of Information Engineering, Dalian Ocean University, Dalian 116023, China
2
State Key Laboratory of Synthetical Automation for Process Industry, Northeastern University, Shenyang 110819, China
3
Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC 3086, Australia
artificial sampling and laboratory titration analysis, which is not only complicated and costly, but also suffers from larger time delays as well. Therefore, online estimate of component concentrations in sodium aluminate liquor is significant to implement process optimization and control of the alumina industry. The existing methods of estimating cK , cA and cC can be classified into two categories. One is based on the principle of reagent titration [15, 16], including photometric titration, potentiometric titrati
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