论文部分内容阅读
基于强激光系统光学元件损伤的在线暗场成像检测,提出了一种无损、自动、快速检测的新算法。该算法根据模式识别中的聚类理论,对光学元件损伤的暗场图像实现了损伤斑块位置的自动检测分析。同时,根据损伤的暗场图像特点,用双向扫描方式得到了无遗漏点的损伤连续斑块,实现了损伤斑块尺度的自动检测。理论分析和实验均显示,损伤暗场自动检测图像的快速聚类算法能实现光学元件损伤位置和损伤尺度的准确、自动分析。
Based on the on-line dark field imaging detection of optical components in strong laser system, a new algorithm of non-destructive, automatic and rapid detection is proposed. According to the clustering theory in pattern recognition, this algorithm realizes the automatic detection and analysis of the location of the damaged plaque on the dark field image of optical element damage. At the same time, according to the characteristics of the dark field image of damage, continuous plaque without any missing points is obtained by bidirectional scanning method, and the automatic detection of the damaged plaque scale is realized. Both theoretical analysis and experiments show that the fast clustering algorithm for automatically detecting the image in the dark field can achieve accurate and automatic analysis of the damage location and damage scale of optical components.