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首页> 外文会议>Machine Vision Applications in Industrial Inspection XIV; Electronic Imaging Science and Technology >Flushing analysis by machine vision and fuzzy logic at molten steel for the automation process
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Flushing analysis by machine vision and fuzzy logic at molten steel for the automation process

机译：通过机器视觉和模糊逻辑对钢水进行冲洗分析以实现自动化过程

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For the homogenisation of the molten steel it is necessary to rinse the melting bath. Therefore two porous plugs are installed in the bottom of the casting ladle through which the gas is blown into the ladle. The movement of the melting surface is chaotic. Other process stages, which are distortions to the image processing system, like steam or mechanical parts moving within the scene have to be taken into consideration too. Standard straight forward analytic algorithms fail. The uncertainties cannot be handled in a proper way. We decided to use a RGB binary converter followed by a fuzzy classifier. If the flushing is active molten steel breaks through the slag. This molten steel areas show a certain colour spectrum. The RGB-binary conversation is necessary to detect the molten cast breaking the slag. The size of these colour areas is direct proportional to the intensity of the flushing. The fuzzy block felts the results of the binary conversation and splits them into the intensity grades. This method allows the detection of five stages of the flushing under the given conditions at the melting process and it is able to detect steam or other disturbing parts moving through the scene as well.
机译：为了使钢水均匀化，必须冲洗熔池。因此，两个多孔塞被安装在浇铸钢包的底部，气体通过该塞子被吹入钢包。熔化表面的运动是混乱的。还必须考虑其他处理阶段，这些阶段会对图像处理系统造成扭曲，例如蒸汽或机械零件在场景中移动。标准的直接分析算法失败。不确定性不能以适当的方式处理。我们决定使用后跟模糊分类器的RGB二进制转换器。如果进行冲洗，则钢水会冲破炉渣。该钢水区域显示出一定的色谱。 RGB二进制对话对于检测打破炉渣的熔融铸件是必要的。这些颜色区域的大小与冲洗强度成正比。模糊块感受二进制对话的结果，并将其分为强度等级。该方法允许在熔化过程中在给定条件下检测冲洗的五个阶段，并且还能够检测穿过场景的蒸汽或其他干扰部分。

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