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Intelligent Control System and Optimization Method for Alkali Recovery Based on Dual Network Dual Server Architecture
Received:November 21, 2024  
DOI:10.11980/j.issn.0254-508X.2025.02.003
Key Words:alkali recovery process flow  dual network dual server architecture  advanced control algorithm  soft measurement  particle swarm optimization
Author NameAffiliationPostcode
TANG Wei College of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi Province, 710021
Shaanxi Xiwei Process Automation Engineering Co., Ltd.,Xianyang, Shaanxi Province, 712000 
712000
ZHENG Xiaohu* College of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi Province, 710021 710021
WANG Mengxiao Shaanxi Xiwei Process Automation Engineering Co., Ltd.,Xianyang, Shaanxi Province, 712000 712000
WANG Qilin Shaanxi Xiwei Process Automation Engineering Co., Ltd.,Xianyang, Shaanxi Province, 712000 712000
ZHOU Guoqing College of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi Province, 710021 710021
GAO Qifan College of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi Province, 710021 710021
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Abstract:Currently, most paper mills have poor emission reduction and decarbonization effects, and their level of informatization is relatively low. The alkali recovery section was taken as an example in this study, and an intelligent control system for alkali recovery based on a dual network and dual server architecture was propesed. The system was based on a dual ring Ethernet dual redundant server architecture, with Siemens S7-400 series PLC controller selected as the lower computer. Hardware such as CPU and I/O modules were designed with redundancy, providing stable and reliable decentralized control for alkali recovery, evaporation, combustion, and causticization sections. The upper computer was equipped with Web server, enterprise office internet, and remote service channel, which could not only enhance the information sharing capability within the system, but also realize remote diagnosis and maintenance of the system. Finally, advanced control algorithms were used to optimize and control the important parameters of each section. The practical application results showed that the system could not only effectively improve the treatment efficiency of black liquor, but also reduce energy loss in the production process. It also provided the basis for the intelligent and information-based transformation and upgrading of the alkali recovery section.
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