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A New “User-friendly” Blast Furnace Advisory Control System Using a Neural Network Temperature Profile Classifier

机译:使用神经网络温度曲线分类器的新型“用户友好型”高炉咨询控制系统

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The adaptation of blast furnaces to the new technologies has increased the operation information so that the sensor information can be known at every moment. However this often results in the supply of excessive data volume to the plant operators. This paper describes an industrial application for self-organized maps (SOM) in order to help them make decisions regarding blast furnace control by means of pattern recognition and the matching of temperature profiles supplied by the thermocouples placed on the above burden. The classification of patterns via easy color coding indicates to the operator what the blast furnace operational situation is, thus making the necessary corrections easier.
机译:高炉适应新技术增加了操作信息,因此可以随时了解传感器信息。但是,这通常导致向工厂操作员提供过多的数据量。本文介绍了自组织地图(SOM)的工业应用,以帮助他们通过模式识别和匹配上述负担的热电偶提供的温度曲线来做出有关高炉控制的决策。通过容易的颜色编码对图案进行分类,从而向操作员指示高炉的运行状况,从而使必要的校正变得容易。

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