Predicting mechanical properties of cold- rolled low carbon steel based on magnetic parameter measurement using ANFIS model

M. Eftekhari, M. Moallem, M. A. Ghadamyari, Hosein Monajati, Davood Asefi, Abbas Kamranian Marnani
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引用次数: 4

Abstract

In this paper, a novel method for predicting mechanical properties of cold- rolled low carbon steel based on magnetic parameter measurement using Adaptive Neuro Fuzzy Inference System (ANFIS) is presented. The Yield Stress (YS) and Ultimate Tensile Strength (UTS) are predicted using two ANFIS models on the basis of B-H curve parameter measurement. B-H curve parameter measurement is carried out using a measurement system specially developed for this project. Using this system, remanence (Br), coercive force (Hc), harmonic components of the field intensity, and flux density are extracted and used as input parameters of the ANFIS models. The individual influence of different input parameters is evaluated and compared with metallurgical test results. The ANFIS models show good performance and the results are in agreement with the experimental data. The developed models can be used as an on-line, non-destructive evaluation technique in steel mill factories.
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基于磁参数测量的冷轧低碳钢力学性能ANFIS模型预测
提出了一种基于自适应神经模糊推理系统(ANFIS)磁参数测量预测冷轧低碳钢力学性能的新方法。在B-H曲线参数测量的基础上,采用两种ANFIS模型预测了屈服应力(YS)和极限抗拉强度(UTS)。B-H曲线参数测量采用了专门为本工程开发的测量系统。利用该系统提取剩余力(Br)、矫顽力(Hc)、场强谐波分量和磁通密度,并将其作为ANFIS模型的输入参数。评估了不同输入参数的个体影响,并与冶金试验结果进行了比较。该模型具有良好的性能,其结果与实验数据吻合较好。所建立的模型可作为钢厂在线无损评价技术。
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