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熱軋帶鋼力學性能預測模型及其應用

Quality prediction model of the mechanical properties of hot-rolled steel strips and its application

  • 摘要: 為實現對熱軋帶鋼的屈服強度、抗拉強度、斷裂延伸率等力學性能的預測及控制,利用人工神經網絡技術,分別建立了根據生產工藝參數預測力學性能的質量模型,以及根據力學性能要求對生產工藝參數進行優化的逆質量控制模型.利用質量預測模型,分析得出屈服強度隨卷取溫度的上升而下降的變化規律,進而可以對組織性能進行在線調整,實現在線應用.

     

    Abstract: To predict and control the yield strength, tensile strength, and elongation of hot-rolled steel strips, a quality model, which could predict the mechanical properties of hot-rolled steel strips with technological parameters, and a reverse quality control model, which could optimize technological parameters with the mechanical properties, were established by applying the technology of artificial neural network. With the quality prediction model it was proved that the value of yield strength decrease with the increase of coiling temperature. Based on this, the mechanical properties of hot-rolled steel strips could be controlled through the real time regulation of coiling temperature to meet production requirements.

     

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