Aspheric grinding surface accuracy optimization by integrating sensitive geometric error detection and in-situ compensation processing - He, Xiangbo; Zhang, Kai; Li, Ruirui; Feng, Huiming; Peng, Yunfeng (Precision engineering, 2025)
In-situ compensation processing represents an efficacious strategy for enhancing the surface accuracy of aspheric grinding operations. However, during the compensation grinding process, geometric errors can induce deviations in the grinding trajectory, thereby adversely affecting the corrective outcomes for surface accuracy. Consequently, this study introduces an optimization method for aspheric grinding surface accuracy that integrates sensitive geometric error identification with in-situ compensation processing techniques, aiming to mitigate the impacts of geometric errors on compensation processing performance. Initially, a volumetric error model of the grinding machine was established based on multibody system theory, and the evolution pattern of the peak-to-valley (PV) values under the influence of geometric errors for various types of optical components was simulated and analyzed. Subsequently, using actual inverse kinematics, analytical expressions for the computer numerical control (CNC) code for compensating geometric errors across various motion axes of the grinder were derived. Thereafter, a geometric error-surface accuracy model (GE-SAM) was constructed to elucidate the interrelationship between geometric errors and surface accuracy. Based on this model, a global sensitivity analysis was employed to identify critical geometric error terms affecting the surface accuracy of aspheric grinding, which further streamlined the analytical expressions for the compensation CNC code. Finally, the efficacy of the proposed method was substantiated through experimental validation. The experimental results demonstrated that the surface accuracy optimization strategy proposed in this paper is more effective than the traditional in-situ compensation processing method. •GE-SAM is established to reveal the relationship between geometric error and PV.•Sensitivity analysis simplifies the expression of compensated motion commands.•Proposed surface accuracy optimization method integrates error identification with in-situ compensation processing.•Experimental validation shows proposed method over traditional method.