SCI和EI收录∣中国化工学会会刊

›› 2008, Vol. 16 ›› Issue (4): 650-655.

• • 上一篇    下一篇

Research and Implementation of Decreasing the Acetic Acid Consumption in Purified Terephthalic Acid Solvent System

徐圆, 朱群雄   

  1. College of Information Science & Technology, Beijing University of Chemical Technology, Beijing 100029, China
  • 收稿日期:2007-07-11 修回日期:2008-04-27 出版日期:2008-08-28 发布日期:2008-08-28
  • 通讯作者: ZHU Qunxiong, E-mail: zhuqx@mail.buct.edu.cn
  • 基金资助:
    the National Natural Science Foundation of China(60774079);the National High Technology Research and Development Program of China(2006AA04Z184);Sinopec Science&Technology Development Project of China(205073)

Research and Implementation of Decreasing the Acetic Acid Consumption in Purified Terephthalic Acid Solvent System

XU Yuan, ZHU Qunxiong   

  1. College of Information Science & Technology, Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2007-07-11 Revised:2008-04-27 Online:2008-08-28 Published:2008-08-28
  • Supported by:
    the National Natural Science Foundation of China(60774079);the National High Technology Research and Development Program of China(2006AA04Z184);Sinopec Science&Technology Development Project of China(205073)

摘要: Decreasing the acetic acid consumption in purified terephthalic acid (PTA) solvent system has become a hot issue with common concern. In accordance with the technical features, the electrical conductivity is in direct proportion to the acetic acid content. General regression neural network (GRNN) is used to establish the model of electrical conductivity on the basis of mechanism analysis, and then particle swarm optimization (PSO) algorithm with the improvement of inertia weight and population diversity is proposed to regulate the operating conditions. Thus, the method of decreasing the acid loss is derived and applied to PTA solvent system in a chemical plant. Cases studies show that the precision of modeling and optimization are higher. The results also provide the optimal operating conditions, which decrease the cost and improve the profit.

关键词: acetic acid consumption, purified terephthalic acid solvent system, general regression neural network, particle swarm optimization

Abstract: Decreasing the acetic acid consumption in purified terephthalic acid (PTA) solvent system has become a hot issue with common concern. In accordance with the technical features, the electrical conductivity is in direct proportion to the acetic acid content. General regression neural network (GRNN) is used to establish the model of electrical conductivity on the basis of mechanism analysis, and then particle swarm optimization (PSO) algorithm with the improvement of inertia weight and population diversity is proposed to regulate the operating conditions. Thus, the method of decreasing the acid loss is derived and applied to PTA solvent system in a chemical plant. Cases studies show that the precision of modeling and optimization are higher. The results also provide the optimal operating conditions, which decrease the cost and improve the profit.

Key words: acetic acid consumption, purified terephthalic acid solvent system, general regression neural network, particle swarm optimization