基于灰色自举法的高速加工中心热误差动态预测

Taomei Lv, Fannian Meng, Jiangping Tao
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引用次数: 0

摘要

热误差一直是影响高速加工中心加工精度的关键因素。如何预测高速加工中心的热误差,是热误差补偿的前提和基础。针对这一问题,提出了一种灰色自提模型,并首次应用于高速加工中心的热误差预测。实验研究表明,采用灰色自strap模型的预测精度很高,预测结果的相对误差最大值、最小值和平均值分别为7.72%、1.19%和4.48%,预测区间的可靠性证明为100%。实现了点预测和区间预测,解决了高速加工中心热误差的动态评价问题。
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Dynamic prediction for thermal error of high-speed machine center using grey bootstrap
Thermal error is always the key factor which affects processing precision of high-speed machine center. How to predict the thermal error of the high-speed machine center, is the prerequisite and foundation of thermal error compensation. To solve this problem, a grey bootstrap model is proposed, which is first used thermal error prediction of high-speed machine center. Experimental study shows that the prediction accuracy is very high using grey bootstrap model, and the maximum, the minimum and the mean of the relative errors of the predicted results are respectively 7.72%, 1.19% and 4.48%, and the reliability of the predicted interval is proved to be 100%. The point prediction and interval prediction are actualized, which solve the problem of dynamic evaluation of thermal error of high-speed machine center.
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