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Soft Sensor - Based Artificial Neural Networks and Fuzzy Logic. Application to Quality Monitoring in Hot Rolling

机译:基于软传感器的人工神经网络和模糊逻辑。在热轧中的质量监测应用

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On line quality monitoring is an important domain particularly in the complex processes where the characteristic of the product quality is difficult to measure directly. Soft sensor based modelling and monitoring techniques can be considered as an alternative to solve such complex problem. We consider in this work a contribution for product quality monitoring in hot rolling. Data mining and modelling based Artificial Neural Network (ANN) is used to determine optimal model. Deviations between optimal and actual conditions characterised by dynamic properties of residual are used as a tool to compute a quality index in basis of fuzzy reasoning. Application in hot rolling shows that this approach can be recommended as part of a tool of on line quality monitoring and classification.
机译:在线质量监测是一个重要的领域,特别是在复杂的过程中,产品质量的特性难以直接测量。基于软传感器的建模和监控技术可以被视为解决这些复杂问题的替代方案。我们考虑在这项工作中,在热轧中的产品质量监测的贡献。基于数据挖掘和建模的人工神经网络(ANN)用于确定最佳模型。最佳和实际条件之间的偏差,其特征在于残留的动态性质用作基于模糊推理来计算质量指标的工具。在热轧中的应用表明,这种方法可以推荐作为在线质量监测和分类的工具的一部分。

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