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RESEARCH ON ACCURACY DESIGN FOR REMANUFACTURED MACHINE TOOLS

机译:再制造机床精度设计研究

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Accuracy design has a direct effect upon the performance of remanufactured machine tools. Since one of the chief tasks of remanufacturing old machine tools is to improve the geometric accuracy of important components (guide-ways, lead-screws).Using multi-body theory, total accuracy model of remanufactured 3-axis machine tool including geometric errors of updated and maintained parts was constructed. According to the accuracy testing principle for machine tools, basic geometric error components were identified from the testing accuracy of the aforementioned parts in the meaning of statistics. Then the accuracy model was used to predict the volumetric errors of remanufactured machine tool for given accuracy of parts. By solving the inverse accuracy model, a new kind method of accuracy design was presented. Utilizing hybrid approach of BP neural network and genetic algorithm, the new method reached the global optimal allocation of parts accuracy and the balance between linear errors and angle errors. The production has been applied in remanufacturing of old machine tools to afford a guide for choosing and maintaining parts accuracy.
机译:精度设计直接影响再制造机床的性能。由于再制造旧机床的主要任务之一是提高重要组件的几何准确性(导向方式,铅螺丝)。使用多体理论,再制造的3轴机床的总精度模型,包括几何误差构建更新和维护零件。根据机床的准确性测试原理,基本几何误差分量从上述统计意义中的上述部件的测试精度识别。然后使用精度模型来预测用于给定零件精度的再制造机床的体积误差。通过求解逆精度模型,提出了一种新的精度设计方法。利用BP神经网络和遗传算法的混合方法,新方法达到了零件精度的全局最优分配和线性误差与角度误差之间的平衡。该生产已应用于旧机床的再制造,以提供选择和维护零件精度的指南。

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