Surface Defect Detection on Optical Devices Based on Microscopic Dark-Field Scattering Imaging

In the laser system for inertial confinement fusion (ICF) [1] and [2], optical devices are essential parts of the power amplifier and the final optics assembly. Defects, such as point defects and line defects on the surface of optical devices, seriously affect the performance of the laser system for ICF. Image processing and pattern recognition technology is widely used for the detection of defects. In [3], laser profilometry is used to detect defects on the surface of power transmission belts. In [4], a defect detection system based on dark-field optical scattering images is designed and assembled for locating and determining the sizes of crystal-originated “particles” (COPs) on the polished surface of silicon wafers. In [5], a pulsed eddy current (PEC) thermography system is implemented for notch detection in carbon-fibre reinforced plastic (CFRP) samples and the proposed methods allow the user to observe the eddy current distribution in a structure using infrared imaging and to detect defects over a relatively wide area. In [6], a pit-count method based on computer-aided image processing is used for direct measurements of the cavitation erosion by evaluating the damage on the surface of the hydrofoil. In [7], methods based on image processing technology are proposed to detect the defects on the surface of ceramic tiles. In [8], a novel visual system is built to recognize erythema migrans. In the visual system, the GrowCut method improved with the new finger draw marker is used to detect potential erythema migrans skin lesion edge, and several methods are used for the classification of skin lesions into ellipses. In [9], several neural networks are used for the roughness prediction model of the steel surface machined by face milling. In [10], the regression model and the model based on the application of neural networks are used to predict the machined surface roughness in the face milling of aluminium alloy on a low-power cutting machine. An apparatus for detecting defects on the surface of optical devices was designed and constructed in the lab of the authors. A high-precision motorized linear stage and a high-precision motorized vertical stage are used to control the line-scan camera moving along the planned path. A series of microscopic dark-field scattering images are collected with the line-scan camera. There is translation transformation Surface Defect Detection on Optical Devices Based on Microscopic Dark-Field Scattering Imaging Yin, Y. – Xu, D. – Zhang, Z. – Bai, M. – Zhang, F. – Tao, X. – Wang, X. Yingjie Yin – De Xu – Zhengtao Zhang* – Mingran Bai – Feng Zhang – Xian Tao – Xingang Wang Chinese Academy of Sciences, Institute of Automation, Research Center of Precision Sensing and Control, China