Positioning error compensation for machining center by support vector regression

Liu Dahai
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Abstract

To improve the positioning accuracy of a certain type of bridge gantry machining center, a positioning error compensation method based on support vector regression (SVR) is presented. After analyzing the influence of training data sets distribution, and pointing out that SVR may have a substandard performance when the training data are distributed sparsely at neighborhood of outliers or distributed in a small range, a training data sets constructing criterion is proposed. SVR is employed in position error compensation of a bridge gantry machining center to establish the model of the positioning error, actual positioning error compensation effects shows that the positioning accuracy and compensation operating efficiency are improved effectively.
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基于支持向量回归的加工中心定位误差补偿
为提高某型桥式龙门加工中心的定位精度,提出了一种基于支持向量回归(SVR)的定位误差补偿方法。在分析了训练数据集分布的影响后,指出当训练数据稀疏分布在离群点附近或分布在小范围内时,支持向量回归算法的性能可能不合格,提出了一个训练数据集构造准则。将SVR应用于某桥式龙门加工中心的位置误差补偿中,建立了定位误差模型,实际定位误差补偿效果表明,该方法有效地提高了定位精度和补偿运行效率。
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