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An aerostatic spindle is a core component in ultra-precision machine tools. The rotor of the spindle has extremely high manufacturing accuracy, which cannot be directly achieved via traditional machining, but always via manual grinding. The deterministic figuring theory is introduced into the machining of shaft parts, which overcomes many shortcomings of manual grinding. The manufacturing error of the shaft's surface contains different frequency components, which have different effects on its working performance and the figuring process. Because the deterministic figuring method can only correct the error within a limited frequency range, in order to ensure high efficiency and high precision of the figuring process, we need to use reasonable filtering parameters to filter out the error with unnecessary frequencies. In this paper, the influence of contour error with different frequencies and amplitudes on the air film are analyzed using computational fluid dynamics (CFD) software, and the amplitude–frequency analysis as a function of the power spectral density (PSD) characteristic curve is used to study the filtering parameters of the measured data. After the figuring experiment using the filtering parameters obtained from the analysis, the average roundness of the shaft converged from 0.419 μm to 0.101 μm, and the cylindricity converged from 0.76 μm to 0.35 μm. The precision reached the level of manual grinding, which proves the rationality of the analysis using filtering parameters in a shaft's deterministic figuring. [ABSTRACT FROM AUTHOR]

The application of ultra-precision shaft parts is widely used, such as the spindle core of the air bearing spindle in ultra-precision machine tools. The precision of the spindle core is extremely high, and it is very difficult to obtain directly by traditional Computer Numerical Control (CNC) machine tools but is mostly obtained by manual grinding, whose machining efficiency is greatly limited. Based on the deterministic figuring theory, this paper focuses on the ultra-precision roundness, optimizing the filtering parameters of the measurement error data and studying the generation mechanism of the removal function morphology; the shape of the removal function is adjusted by combining the analysis of the figuring ability and positioning error. Finally, the optimized removal function is used on an experimental steel shaft, the average roundness convergence ratio is 72% higher than that of the original removal function, and the roundness reaches a 0.1 μm level. The result shows that a reasonable filtering of measured data and the removal function adjusted for the surface feature can improve the efficiency and precision of deterministic figuring on shaft parts. [ABSTRACT FROM AUTHOR]