首页> 外国专利> CALIBRATION FUNCTION DETERMINATING METHOD FOR IMPROVING PREDICTION ACCURACY OF ROLL FORCE OF FINAL PASS DURING ROLLING OF STEEL PLATE

CALIBRATION FUNCTION DETERMINATING METHOD FOR IMPROVING PREDICTION ACCURACY OF ROLL FORCE OF FINAL PASS DURING ROLLING OF STEEL PLATE

机译:钢板轧制过程中提高最终合格轧制力预测精度的校准功能确定方法

摘要

PURPOSE: A method for improving prediction accuracy of roll force which not only reduces time and cost burdens through experiment, but also far increases reliability compared to the experiment by improving prediction accuracy of roll force using data of actual rolling results is provided. CONSTITUTION: The calibration function determinating method for improving prediction accuracy of roll force of final pass during rolling of steel plate comprises the steps of obtaining correction coefficients (A1) through regression analysis between actual roll force results of final pass and each calculated factors by classifying data of the total actual rolling results per operating condition groups; obtaining correction function (β) by dividing roll force regression equation obtained using correction coefficients (A1) per each concerned groups by a predicted roll force value; examining the corrected roll force values with actual data after correcting the predicted roll force values of final pass using the obtained correction function (β); and further increasing model accuracy by consistently repeating a series of the above steps as accumulating data of actual rolling results.
机译:目的:提供一种提高轧制力预测精度的方法,该方法不仅减少了实验的时间和成本负担,而且通过使用实际轧制结果的数据提高轧制力的预测精度,与实验相比,还大大提高了可靠性。组成:一种用于提高钢板轧制过程中最终道次轧制力预测精度的校准函数确定方法,包括以下步骤:通过对最终道次的实际轧制力结果与各个计算因子进行分类分析,通过回归分析获得校正系数(A1)每个工况组的实际总轧制结果为多少;通过将使用每个相关组的校正系数(A1)获得的侧倾力回归方程除以预测侧倾力值来获得校正函数(β);在使用获得的校正函数(β)校正最终通过的预测轧制力值之后,利用实际数据检查校正轧制力值。通过不断重复上述一系列步骤来累积实际轧制结果数据,从而进一步提高模型精度。

著录项

  • 公开/公告号KR100325539B1

    专利类型

  • 公开/公告日2002-02-07

    原文格式PDF

  • 申请/专利权人 POSCO;

    申请/专利号KR19970077439

  • 发明设计人 SIM MU GYEONG;POLIA YEVGENI;

    申请日1997-12-29

  • 分类号B21B37/58;

  • 国家 KR

  • 入库时间 2022-08-22 00:29:53

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