引用本文:陈春华,于丰,毛志忠.烟气制酸气体净化系统建模与参数辨识[J].控制理论与应用,2015,32(6):832~836.[点击复制]
CHEN Chun-hua,YU Feng,MAO Zhi-zhong.Modeling and parameter identification of the flue gas purification system of flue gas acid-making[J].Control Theory and Technology,2015,32(6):832~836.[点击复制]
烟气制酸气体净化系统建模与参数辨识
Modeling and parameter identification of the flue gas purification system of flue gas acid-making
摘要点击 2554  全文点击 1016  投稿时间:2014-05-05  修订日期:2015-01-21
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DOI编号  10.7641/CTA.2015.40401
  2015,32(6):832-836
中文关键词  烟气制酸  烟气净化系统  机理建模  参数辨识
英文关键词  flue gas acid-making  flue gas purification system  mechanistic modeling  parameter identification
基金项目  国家自然科学基金项目(61333006)资助.
作者单位邮编
陈春华 东北大学 信息科学与工程学院 110819
于丰* 东北大学 信息科学与工程学院 110819
毛志忠 东北大学 信息科学与工程学院 
中文摘要
      烟气压力作为工业烟气制酸工艺中的重要参数, 对制酸过程中硫的转化起到重要的作用. 在进行转化过程前, 烟气的净化系统会对烟气压力产生重大影响. 对于烟气制酸气体净化系统关于烟气压力的建模工作目前还不多见. 本文在通过分析烟气净化系统工作原理后, 建立了工业烟气制酸气体净化系统中干燥塔、\!\!电除尘器和动力波子系统关于烟气压力输入输出关系的机理模型. 针对模型中未知的参数, 将其视为恒定不变的状态, 进而将各个子模型合并为一个特殊的EKF模型. 结合EKF算法的推导思路, 提出一种递归参数辨识方法, 用于对模型中的未知参数进行在线辨识. 使用现场测量数据对模型参数的辨识以及对烟气压力估计的结果验证了模型以及算法的有效性.
英文摘要
      As an essential factor, the flue gas pressure plays an important role in the industrial gas sulphuric acid production. Before the transformation process, the flue gas purification system has a significant impact on the flue gas pressure. However, modeling of the flue gas pressure in the purification system has been rarely mentioned in the related literatures at present. In this paper, a mechanical system model is proposed to describe the relationship between the input and output pressure of the subsystem drying tower, electric precipitation and dynamic wave in the flue gas purification system in flue gas acid-making plant. Taking the time-invariant parameters as a special kind of system states, we combine the three subsystem models into a special EKF model. Inspired by the EKF algorithm, we propose a recursive parameter identification method to identify the model parameters online. The results of parameter identification and estimation of flue gas pressure based on measurements show the validity of the proposed mechanistic model and the identification algorithm.