RESUMEN
The machining-induced subsurface damage (SSD) on fused silica optics would incur damage when irradiated by intense lasers, which severely restricts the service life of fused silica optics. The high absorption of fused silica to 10.6 µm makes it possible to utilize pulsed CO2 laser to remove and characterize SSD by layer-by-layer ablation, which improves its laser-induced damage threshold. However, thermal stress during the laser ablation process may have an impact on SSD, leading to extension. Still, the law of SSD morphology evolution mechanism has not been clearly revealed. In this work, a multi-physics simulated model considering light field modulation is established to reveal the evolution law of radial SSD during the laser layer-by-layer ablation process. Based on the simulation of different characteristic structural parameters, two evolution mechanisms of radial SSD are revealed, and the influence of characteristic structural parameters on SSD is also elaborated. By prefabricating the SSD by femtosecond laser, the measurements of SSD during CO2 laser layer-by-layer ablation experiments are consistent with the simulated results, and three stages of SSD depth variation under two evolution processes are further proposed. The findings of this study provide theoretical guidance for effectively characterizing SSD based on laser layer-by-layer ablation strategies on fused silica optics.
RESUMEN
Sub-aperture polishing is a key technique for fabricating ultra-precision optics. However, the existence of the polishing errors that are difficult to be compensated by physical modeling seriously affects the manufacturing accuracy and efficiency of optical components. To address this problem, a data-based systematic error extraction and compensation (DSEC) method was proposed to enhance the polishing accuracy on optics. To maximize the extraction quality in a small dataset condition, the wavelet transform is introduced into the extraction process, and the uncertainty of the piston term in the interferometer measurement is improved by L1-norm optimization. Furthermore, two typical error sources (loss of polishing fluid in the edge and the robot trajectory error) are used to verify the effectiveness of the proposed method; in experimental verification, the root mean square (RMS) of the surface figure of a Ï85-mm mirror was decreased from 0.069λ to 0.017λ, and the RMS of the 610 × 440â mm mirrors was achieved at 0.019λ after the edge compensation, where the polishing accuracy can be improved by more than 4 times; additionally, the RMS of the surface figure with an effective aperture of 480 × 360â mm mirror was reached at 0.011λ after the trajectory error compensation, where the polishing accuracy can be improved by more than 2 times. The proposed DSEC model offers insights that will help achieve advancement in the sub-aperture polishing process.
RESUMEN
The industrial robot-based polisher has wide applications in the field of optical manufacturing due to the advantages of low cost, high degrees of freedom, and high dynamic performance. However, the large positioning error of the industrial robot can lead to surface ripple and seriously restrict the system performance, but this error can only be inefficiently compensated for by measurement before each processing at present. To address this problem, we discovered the period-phase evolution law of the positioning error and established a double sine function compensation model. In the self-developed robotic polishing platform, the results show that the Z-axis error in the whole workspace after compensation can be reduced to ±0.06m m, which reaches the robot repetitive positioning error level; the Spearman correlation coefficients between the measurement and modeling errors are all above 0.88. In the practical polishing experiments, for both figuring and uniform polishing, the ripple error introduced by the positioning error is significantly suppressed by the proposed model under different conditions. Besides, the power spectral density (PSD) analysis has shown a significant suppression in the corresponding frequency error. This model gives an efficient plug-and-play compensation model for the robotic polisher, which provides possibilities for further improving robotic processing accuracy and efficiency.