Research on Defect Detection of Large-aperture Multi-faceted Optical Components

In inertial confinement fusion (ICF) systems, damage induced by high power lasers is one of the key factors for limiting the further improvement of energy density. Also, there is a close relationship between various defects and damage characteristics of optical components. Usually, the optical components detected in the system have a large-aperture and a variety of surface types. The defects have the characteristics of small scale, low distribution density and wide distribution range, etc. It is a great challenge to achieve multi-faceted detection with high precision and efficiency. In this paper, according to the requirements for micro defects detection on the surface of large-aperture optical components, a multimodal scanning detection method combining the bright-field and dark-field imaging (BDFI) is given. Based on the high sensitivity of dark-field microscopic imaging (DFMI), the ring illumination strategy of collimate light source is studied to locate defects globally. The coaxial illumination method is used to accurately detect the characteristic parameters of defects, which is able to realize the size quantification of multi-morphological defects. At the same time, in order to cope with the detection needs of large-aperture and multi-faceted optical components, the sub-aperture scanning method based on the distribution structure of geodesic sphere is proposed. The multi-aperture scanning path is automatically planned and the spatial distribution of defects is reconstructed with three-dimensional mapping. On this basis, by cooperating with the automatic motion device, automatic focus and high-speed automatic scanning of detection can be realized. The methods proposed in this paper can be accomplished for efficient detection of large-aperture optics with a resolution of 0.5 mu m for surface defects, which meets the needs of multi-faceted detection. Therefore, it is of great significance to guide the precision machining of optical components and support the process optimization, which has great importance for the final research results of the ICF system.