化工学报 ›› 2012, Vol. 63 ›› Issue (9): 2904-2912.DOI: 10.3969/j.issn.0438-1157.2012.09.037

• 过程系统工程 • 上一篇    下一篇

基于粒子滤波联合估计的气相聚乙烯质量指标在线估计

赵众1, 郜娜1, 潘高峰2   

  1. 1. 北京化工大学信息科学与技术学院, 北京 100029;
    2. 中国石油锦西石化分公司, 辽宁 锦州 125001
  • 收稿日期:2012-06-05 修回日期:2012-06-20 出版日期:2012-09-05 发布日期:2012-09-05
  • 通讯作者: 赵众
  • 作者简介:赵众(1970-),男,博士,教授。
  • 基金资助:

    国家自然科学基金项目(60974065)。

Polymer properties on-line estimation for gas-phase polyethylene based on particle filtering joint estimation

ZHAO Zhong1, GAO Na1, PAN Gaofeng2   

  1. 1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China;
    2. PetroChina Jinxi Petrochemical Company, Jinzhou 125001, Liaoning, China
  • Received:2012-06-05 Revised:2012-06-20 Online:2012-09-05 Published:2012-09-05
  • Supported by:

    supported by the National Natural Science Foundation of China(60974065).

摘要: 针对气相聚乙烯生产中各种复杂的工况造成在线估计精度下降的现象,基于乙烯聚合机理并利用特征建模方法建立了聚乙烯质量指标预测模型,结合扩展卡尔曼滤波,提出了粒子滤波联合估计方法,即将状态和修正系数组成增广状态向量,实现对质量指标预测模型的在线滤波修正,并分析了基于粒子滤波估计的收敛性。所提方法在中石化某气相聚乙烯装置的长周期运行结果证实了所提方法的可行性和有效性,为实施聚乙烯装置的先进控制奠定了基础。

关键词: 气相聚乙烯, 特征建模, 粒子滤波, 联合估计, 扩展卡尔曼滤波

Abstract: Due to the lack of suitable on-line polymer property measurements,the control of multi-grade product quality in industrial polymerization reactors is difficult.In this article,a predictive model of polymer properties is deduced for industrial polyethylene process by combining the first principle model and the feature modeling scheme.Combining the extended Kalman filtering,a method of design the particle filtering joint estimation is proposed to update the estimation of polymer properties based on the off-line lab analysis data in this article.The application results of the proposed method to an industrial gas-phase polyethylene plant have verified its effectiveness and feasibility.With the proposed method,multi-grade polymer properties of industrial gas-phase polyethylene process can be on-line estimated and make it possible for achieving the advanced on-line multi-grade product quality control.

Key words: polyethylene, feature modeling, particle filtering, joint estimation, extended Kalman filter

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