Genetic-Algorithm-Based Research on Key Technologies for Motion System Calibration and Error Control for the Precision Marking System

To counteract accuracy degradation in micrometer-scale precision marking—where the precision marking (PM) system denotes the precision marking platform and the Optical Microscope (OM) system denotes the camera-based visual guidance module—a genetic-algorithm-based framework for motion-system calibration and error control is introduced. A kinematic error model is established to capture multi-source coupled errors in the PM system, and the propagation mechanisms of axis misalignment, pose misregistration, and flatness-induced errors are analyzed. Building on this model, a GA-driven multi-objective calibration scheme and a coordinated optimization model jointly address axis-orthogonality correction, PM-OM extrinsic-pose calibration, and workpiece flatness compensation. Furthermore, a dynamic error-compensation framework leveraging real-time monitoring and adaptive adjustment sustains long-term high-precision marking. In post-calibration tests-after correcting axis orthogonality, aligning the PM-OM extrinsic pose, and compensating workpiece flatness, the PM system achieves dimensional accuracies of ±0.05, ±0.08, and ±0.10 μm for nominal 1, 2, and 3 μm marks, respectively, with positional accuracy better than ±0.2 μm. Marking consistency improves markedly, and the indentation force closely matches the target mark size, validating the approach. These techniques provide both theoretical and practical support for the engineering deployment of PM systems and are significant for improving the quality and productivity of micrometer-scale precision marking.