转炉炼钢终点磷的智能预报

谢书明; 陶  钧; 柴天佑

引用本文:	谢书明,陶钧,柴天佑.转炉炼钢终点磷的智能预报[J].控制理论与应用,2003,20(4):555~559.[点击复制]
	XIE Shu-ming,TAO Jun,CHAI Tian-you.Intelligent method for BOF endpoint phosphorus estimation[J].Control Theory and Technology,2003,20(4):555~559.[点击复制]

转炉炼钢终点磷的智能预报

Intelligent method for BOF endpoint phosphorus estimation

摘要点击 2092 全文点击 1712 投稿时间：2001-01-10 修订日期：2002-07-12

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DOI编号 10.7641/j.issn.1000-8152.2003.4.015

2003,20(4):555-559

中文关键词转炉炼钢模糊建模遗传算法神经网络

英文关键词 BOF steelmaking fuzzy inference model genetic algorithms neural network

基金项目国家重点基础研究发展计划973(2002cb312201); 国家自然科学基金(60074019)

作者	单位	E-mail
谢书明	沈阳工业大学电气工程学院, 辽宁沈阳 110023	xiesm@btamail.net.cn
陶钧	上海宝信软件股份公司, 上海 201900	neutao@etang.com
柴天佑	东北大学自动化研究中心, 辽宁沈阳 110006

中文摘要

提出了一种用于预报转炉炼钢终点磷含量的智能方法, 在该方法中, 采用模糊推理和遗传算法, 其中模糊推理用于估算转炉熔池的磷含量, 而模糊推理模型中的各个系数则由遗传算法辨识与优化. 为了提高熔池磷的估算精度, 同时还设计了一种神经网络以补偿来自模糊推理过程的误差. 仿真结果表明了该方法的有效性.

英文摘要

An intelligent model was introduced to estimate the bath endpoint phosphorus content for basic oxygen furnace (BOF) steelmaking. In the model, the fuzzy inference and genetic algorithms (GA) were used. The BOF endpoint [P] content was estimated by fuzzy inference model, and the parameters for the fuzzy model were optimized by genetic algorithms. For improving the precision of the endpoint estimation, an artificial neural network (ANN) was designed to compensate for the fuzzy inference error. And the simulation results show the validity of this method.