| 引用本文: | 乔景慧,周晓杰,柴天佑.水泥生料预分解过程智能优化设定控制[J].控制理论与应用,2011,28(11):1534~1540.[点击复制] |
| QIAO Jing-hui,ZHOU Xiao-jie,CHAI Tian-you.Intelligent optimal-setting control for cement raw meal pre-calcining process[J].Control Theory and Technology,2011,28(11):1534~1540.[点击复制] |
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| 水泥生料预分解过程智能优化设定控制 |
| Intelligent optimal-setting control for cement raw meal pre-calcining process |
| 摘要点击 1893 全文点击 1533 投稿时间：2010-09-25 修订日期：2010-12-09 |
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| DOI编号 10.7641/j.issn.1000-8152.2011.11.CCTA101129 |
| 2011,28(11):1534-1540 |
| 中文关键词 分解炉 预热器 生料预分解过程 智能优化设定 生料分解率 |
| 英文关键词 calciner preheater pre-calcining process of raw meal intelligent optimal-setting decomposition rate of raw meal |
| 基金项目 国家重点基础研究发展计划资助项目(2009CB320601); 国家自然科学基金资助项目(61020106003); 高等学校学科创新引智计划资助项目(B08015); 教育部科学技术研究重大资助项目(308007). |
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| 中文摘要 |
| 在生料预分解过程中, 由于生料边界条件频繁变化, 致使产品的质量指标生料分解率过低或过高, 从而增加了回转窑的负荷或导致最低一级旋风筒下料管堵塞. 为了解决上述问题, 本文提出了一个智能优化设定方法, 由回路预设定模块、分解率预报模块、前馈补偿模块、反馈补偿模块组成. 这个方法能够根据生料边界条件的变化在线调整控制回路的设定值. 所提出的方法已经成功应用于酒钢宏达水泥生料预分解过程, 取得了显著的应用效果. 工业应用表明所提出的智能优化设定方法能够将生料分解率稳定在工艺范围内. |
| 英文摘要 |
| In the pre-calcining process of raw meal, boundary conditions of raw meal(i.e., flow, ingredients and particle size) are varying frequently; the decomposition rate of raw meal(RMDR) cannot be kept in the desirable ranges. This causes the declination of the production rate per hour and the blockage in the lower feeding tubes. To solve this problem, we propose an intelligent setting-control system in which the set-points of control loops are adjusted online according to the variations of the boundary conditions of raw meal. This system consists of four modules: a control-loop pre-setting module, a feedback compensation module based on the fuzzy rules, a feedforward compensation module based on the fuzzy rules and a soft measurement module for RMDR. This method has been successfully applied to the pre-calcining process the raw meal of Jiuganghongda Cement Plant in China and its efficiency has been validated by the practical application results. Industrial applications show that the proposed intelligent optimization method maintains the rate of decomposition of raw material in processes within a stable range. |