大数据分析的激光辅助超精密加工轨迹跟踪研究

Research on laser assisted ultra precision machining trajectory tracking based on big data analysis

辅助设备采集到的超精密加工设备姿态数据的准确性会影响后期轨迹跟踪精度。结合大数据分析,设计一种激光辅助超精密加工轨迹跟踪方法。该方法利用大数据分析技术中的采集技术,结合激光传感器,采集机械臂加工末端姿态大数据,并利用大数据分析技术当中的预处理技术实施预处理,包括精简、去噪以及补点。计算实际加工轨迹与预期加工轨迹之间的误差,通过误差大数据实时调整实时加工轨迹,让其向预期加工轨迹靠拢,减少误差累积,以达到提高轨迹跟踪精度的目的。结果表明:所研究方法应用下,激光辅助超精密实际加工轨迹与预期加工轨迹之间的平均误差均小于0.1 mm,达到超精密加工标准,说明所研究方法的加工轨迹跟踪精度提高,在一定程度上改善了超精密加工工艺。

The accuracy of ultra precision machining equipment attitude data collected by auxiliary equipment will affect the later trajectory tracking accuracy. Combined with big data analysis, a laser assisted ultra precision machining trajectory tracking method is designed in this paper. In this method, the acquisition technology of big data analysis technology and laser sensor are used to collect the big data of manipulator processing end attitude, and the preprocessing technology of big data analysis technology is used to implement preprocessing, including simplification, denoising and point filling. Calculate the error between the actual machining trajectory and the expected machining trajectory, adjust the real-time machining trajectory in real time through the error big data, make it close to the expected machining trajectory, and reduce the error accumulation, so as to improve the trajectory tracking accuracy. The results show that the average error between the actual laser assisted ultra precision machining trajectory and the expected machining trajectory is less than 0.1 mm. Reaching the ultra precision machining standard, it shows that the machining trajectory tracking accuracy of the research method is improved, and the ultra precision machining process is improved to a certain extent.