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Measuring the predictive accuracy of various models of formability of Corus Tubular Blanks

机译:测量Corus管状坯料各种可成形性模型的预测准确性

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摘要

This paper assesses the predictive accuracy of various analytical models and one numerical model (a CART-ANFIS network) of springback that are available with the existing literature using the mean square error and its decomposition into systematic and random components as a comparative measure of predictive accuracy. The numerical model was found to have no systematic bias in the springback predictions made, whilst for the analytical models the systematic bias accounted for about 11% of the mean square error. The CART-ANFIS network also had the smallest MSE and the prediction errors made were all random in nature. The paper ends by giving some illustrations of the CART-ANFIS numerical model in finding the proper die contour to correct for springback so as to achieve right first-time manufacturing for a wide range of sheet steels.
机译:本文使用均方误差及其分解成系统和随机成分作为预测精度的比较指标,评估现有文献中可用的各种分析模型和一个回弹数值模型(CART-ANFIS网络)的预测精度。 。发现数值模型在做出的回弹预测中没有系统偏差,而对于分析模型,系统偏差约占均方误差的11%。 CART-ANFIS网络的MSE也最小,并且所产生的预测误差本质上都是随机的。本文最后给出了CART-ANFIS数值模型的一些说明,以找到合适的模具轮廓以校正回弹,从而实现对各种钢板的正确首次制造。

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