【摘要】 为了准确预测铣刀在加工过程中的磨损量,提出一种基于粒子群算法的支持向量回归机的优化算法用于对铣刀磨损量的建模与预测。通过粒子群算法,优化输入不同维度的特征向量的支持向量回归机的建模,得到特征向量维度的最优解和对应的支持向量回归机训练参数,建立了铣刀磨损量的预测模型。通过随机选取的真实样本,验证了该模型的准确性。更多还原

【Abstract】 In order to accurately predict the wear of the milling cutter in the process of machining,a new algorithm based on particle swarm optimization was proposed to model and predict the wear of milling cutter. The modeling of support vector regression model which was inputted the eigenvectors of different dimensions was optimized. The optimal solution of the eigenvector dimension and the corresponding support vector regression machine training parameters were obtained,and the prediction model of wear of milling cutter was established through particle swarm. The accuracy of the model was verified by a random selection of real samples.更多还原