复杂工业过程的黑盒建模

G. Horváth, B. Pataki, G. Strausz
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引用次数: 11

摘要

本文介绍了建立林茨-多纳维茨(LD)转炉黑箱模型的一些重要经验。LD转炉炼钢是一个复杂的物理化学过程,许多变量对炼钢质量有影响。在这个过程中,一个转炉被装满废铁、熔化的生铁和许多添加剂,然后用纯氧吹穿,烧掉不需要的污染物。整个过程的复杂性以及有许多无法考虑的影响这一事实使这项任务变得困难。事实证明,整个建模任务中最重要的一步可能是对大量数据的分析,选择相关参数,并找到良好的策略来处理缺失和有偏差的数据。本文详细介绍了数据分析的步骤,总结了构建几种不同神经模型的动机以及在整个项目中获得的一般经验。
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Black-box modeling of a complex industrial process
This paper deals with some important experiences gained from building a black-box model of a Linz-Donawitz (LD) steel converter. Steelmaking with an LD converter is a complex physico-chemical process where many variables have effects on the quality of the resulted steel. During the process a converter is filled with waste iron, melted pig iron and many additives, then it is blasted through with pure oxygen to burn out the unwanted contamination. The complexity of the whole process and the fact that there are many effects that cannot be taken into consideration make this task difficult. It turned out that perhaps the most important step of the whole modeling task was the analysis of the large amount of data, the selection of relevant parameters and to find good strategy to deal with missing and biased data. The paper details the steps of data analysis, summarizes both the motivations of constructing several different neural models and the general experiences obtained through the whole project.
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