五轴卧加主轴系部件热变形测量建模与补偿研究

Thermal deformation measurement, modeling, and compensation for spindle system components in five-axis horizontal machining center

  • 摘要: 针对五轴卧加主轴系部件热变形测量与建模困难的问题,提出了一种多结构温度场-热变形分析、测量与模型构建的方法。建立主轴系关键部件的几何结构等效模型,并据此将3个刀尖点热误差分解成主轴、鞍座和立柱的9个误差项。参考有限元仿真的结果,设计同时测量多部件温度场和热变形的装置,并测量了主轴系在多工况下的热特性。以实测数据为基础,通过长短期记忆神经网络(long short-term memory, LSTM)建立了温度、转速和机械坐标等因素与每个误差分项间的关系。为检验模型预测的实时与准确性,设计了误差补偿实验,并成功将刀尖点AYZ向稳态误差分别降低4.44 μrad、5.83 μm、47.92 μm,精度提升55%、73%、74%。研究为机床的主轴系多部件结构热变形的溯源与建模研究提供了参考。

     

    Abstract: This study addresses the difficulty in measuring and modeling thermal deformation in a five-axis horizontal machining center's spindle system. A new method for analyzing, measuring, and modeling the multi-component temperature field and thermal deformation is proposed. First, an equivalent geometric model of key components was created. This model allowed the thermal error at 3 tool center points to be decomposed into 9 error components from the spindle, saddle, and column. A dedicated measurement device was then designed based on finite element simulation results. This device simultaneously captured temperature and deformation data of multiple components under various working conditions. Using the collected data, a long short-term memory (LSTM) network was employed to model the relationship between influencing factors (temperature, speed, coordinates) and each error component. An error compensation experiment validated the model's real-time performance and accuracy. The steady-state errors at the tool tip were reduced by 4.44 μrad (55%) in the A-axis, 5.83 μm (73%) in the Y-axis, and 47.92 μm (74%) in the Z-axis. This research provides a practical reference for tracing and modeling thermal deformation in complex machine tool spindle systems.

     

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