High Precision Freeform Inspection Method Based on Absolute Position Trigger Normal Vector Measurement

To accomplish ultra-precise non-contact scanning of freeform, this paper proposes a technique for measuring normal vectors using differential confocal absolute position triggering (NDCAPT), and using the accurately obtained normal vector (NV) to reconstruct the freeform under test (FUT) profile. Firstly, the absolute zero position of laser differential confocal (LDC) is used to trigger the position-sensitive detector (PSD) to collect the spot centroid position (SCP) at the focus, eliminating the influence of the defocus of sampling point (SP) on the SCP. Secondly, a defocus distance estimation model based on proximal policy optimization (PPO) to analysis of the light spot is established. Through deep learning to track the profile of freeform to improve the scanning efficiency. Finally, a NV reconstruction model of freeform is constructed. Based on the high precision NVs measured, the profile of freeform can be accurately reconstructed. The preliminary experimental results show that the profile measurement accuracy of this method is better than ±50 nm. By implementing precision NV metrology, it is possible to realize high-precision inspection of freeform, and reduces the demand for high precision reference monitoring framework and displacement measurement methods in the profile measurement of freeform.