In the inertial confinement fusion system (ICF), surface scratches of the large diameter optical surface appear as dot lines (punctate scratches). This kind of scratches is only detected under a high microscope magnification system. This can be caused by the blemishes on the optical processing technology and shallow scratches (< 25<i>nm</i> ). As a result, it can have an impact on the relevant calculation of the width and length of the scratches. Besides, this kind of scratches has a serious impact on the ICF, such as system damage. To solve this problem, this paper proposes the image pattern charter of punctate scratches based on the existing surface defects detection system (SDES). Finally, it proposes an algorithm of scratches based on the linearity differential detection and connectivity. That is, using coordinate transformation and direction differential-threshold discrimination, the scratches can be connected effectively and calculated exactly. Experimental results show that punctate scratches parts can be connected correctly, and the accuracy of the calculated length reaches 95%. Also, the improved algorithm applies to the arc-shaped scratches, which is based the block image processing. Currently, this algorithm can be applied to connect and calculate the shallow scratches accurately and precisely on large fine optics in the ICF system. Thus it can also decrease the misdetection rate of nonconforming super-smooth optics in the ICF system.
The high-resolution detecting system based on machine vision for defects on large aperture and super-smooth surface uses a novel ring telecentric lighting optical system detecting the defects on the sample all round and without blind spots. The scattering light induced by surface defects enters the adaptive and highly zoom microscopic scattering dark-field imaging system for defect detecting and then forms digital images. Sub-aperture microscopic scanning sampling and fast stitching on the surface is realized by using precise multi-axis shifting guided scanning system and a standard comparison board based upon binary optics is used to implement fast calibration of micron-dimension defects detected actually. The pattern recognition technology of digital image processing which can automatically output digitalized surface defects statements after scaling is established to comprehensively evaluate defects. This system which can reach micron-dimension defect resolution can achieve detections of large aperture components of 850 mm × 500 mm, solve the durable problem of subjective uncertainty brought in by human visual detection of defects and achieve quantitative detection of defects with machine vision.
Based on microscopic imaging and sub-aperture stitching technology, Surface defect detection system realizes the automatic quantitative detection of submicron defects on the macroscopic surface of optical components, and solves quality control problems of numerous large- aperture precision optical components in ICF (Inertial Confinement Fusion) system. In order to improve the testing efficiency and reduce the number of sub-aperture images, the large format CCD (charged-coupled device) camera is employed to expand the field of view of the system. Large format CCD cameras are usually mosaicked by multi-channel CCD chips, but the differences among the intensity-grayscale functions of different channels will lead to the obvious gray gap among different regions of image. It may cause the shortening and fracture of defects in the process of the image binarization , and thereby lead to the misjudgment of defects. This paper analyzes the different gray characteristics in unbalance images, establishes gray matrix mode of image pixels, and finally proposes a new method to correct the gray gap of CCD self-adaptively. Firstly, by solving the inflection point of the pixel level curve in the gray histogram of the original image, the background threshold is set, and then the background of the image is obtained; Secondly, pixels are sampled from the background and calculated to get the gray gap among different regions of the image; Ultimately, the gray gap is compensated. With this method, an experiment is carried out to adjust 96 dual-channel images from testing a fused silica sample with aperture 180mm×120mm. The results show that the gray gap of the images on different channel is reduced from 3.64 to 0.70 grayscale on average. This method can be also applied to other CCD mosaic camera.
The digital calibration method, which is employed in the Surface Defects Evaluation System (SDES) for the defects evaluation of large fine optical surfaces, is presented in this paper. A criterion board, which comes from special design and careful fabrication, is employed to relate the dimensions of the defects and those of their images. The calibration procedure, including collecting of calibration images, digital image processing and calibration function fitting, is described in detail in this paper. Calibration experiments on scratch width and dig diameter were carried out at three different microscope magnification conditions. Experiment results show that following the proposed digital calibration method, micron-sized defects distributed sparsely on a large-aperture fine optical surface can be evaluated with micron accuracy and high efficiency.