Micro-hole aerostatic bearings are important components in micro-low-gravity simulation of aerospace equipment, and the accuracy of micro-low-gravity simulation tests is affected by them. In order to eliminate the influence of air resistance on the attitude control accuracy of remote sensing satellites and achieve high fidelity of micro-low-gravity simulation tests, in this study, a design and parameter optimization method was proposed for micro-hole aerostatic bearings for a vacuum environment. Firstly, the theoretical analysis was conducted to investigate the impact of various bearing parameters and external conditions on the bearing load capacity and mass flow. Subsequently, a function model describing the variation in bearing load capacity and mass flow with bearing parameters was obtained utilizing a BP neural network. The parameters of aerostatic bearings in a vacuum environment were optimized using the non-dominated sorting genetic algorithm (NSGA-II) with the objectives of maximizing the load capacity and minimizing the mass flow. Subsequently, experimental tests were conducted on the optimized bearings in both atmospheric and vacuum conditions to evaluate their load capacity and mass flow. The results show that in a vacuum environment, the load capacity and mass flow of aerostatic bearings are increased compared to those in standard atmospheric conditions. Furthermore, it has been determined that the optimal solution for the bearing’s load capacity and mass flow occurs when the bearing has an orifice aperture of 0.1 mm, 36 holes, and an orifice distribution diameter of 38.83 mm. The corresponding load capacity and mass flow are 460.644 N and 11.816 L/min, respectively. The experimental and simulated errors are within 10%; thus, the accuracy of the simulation is verified.

Aerostatic spindles are indispensable in the ultra-precision manufacturing field due to their high accuracy and low friction. However, rotor manufacturing errors will affect the thickness and uniformity of the air film, thereby limiting the improvement and application of the aerostatic spindle. To explore this issue, this paper presents theoretical modelling and experimental work. Rotor cylindricity errors were first evaluated based on manufacturing errors, and a calculation model of the film thickness considering rotor cylindricity errors was established. By solving the dynamic Reynolds equation considering cylindricity errors, the dynamic stiffness and damping of aerostatic spindles were obtained. The influence mechanism of rotor cylindricity errors on the dynamic stiffness and damping coefficients of the rotor–bearing system was revealed. The stiffness coefficients K_xx, K_yy, and K_xy are more sensitive to the saddle-shaped errors, and the stiffness coefficient K_yx and both damping coefficients are more closely related to bucket-shaped errors. Regarding the influence of the cylindricity errors’ extremal position, the main and cross stiffness coefficients are sensitive to saddle-shaped errors and bucket-shaped errors, respectively; the main and cross-damping coefficients are sensitive to bucket-shaped errors. Under the effect of three kinds of error shapes, when the rotor cylindricity errors value is less than 1 μm, the dynamic stiffness and damping coefficients are conducive to improving the dynamic characteristics of the rotor–bearing system. Multiple rotors were manufactured, and their cylindricity errors were measured, and then the dynamic characteristics of the assembled aerostatic spindles with these rotors were tested. It was found that the dynamic stiffness of spindles with saddle-shaped errors is larger than that of spindles with conical-shaped errors, and the greater the error values are, the worse the rotation accuracy. The experimental results are consistent with the theoretical findings, thus verifying the feasibility and validity of the established theoretical model. This study improves the error tolerance design accuracy of rotors and thereby enhances the dynamic performance of aerostatic spindles.