摘要
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。
A new algorithm of nondestructive, automatic and high-speed inspection is proposed for dark-field image to be used to inspect online optic component damage on high power laser system. This algorithm is based on the theory of clustering in pattern recognition. The position of the damage can be automatically analyzed according to this algorithm from its dark-field image. Then, according to the characteristics of damage image, the two-directional （2D） scanning way can be used to obtain a continuous damage block without leaving out any damage pixel. Theories analysis and experiment show that the algorithm can determine the position of optical component damage and analyze the damage dimensions accurately and automatically.
出处
《中国激光》
EI
CAS
CSCD
北大核心
2006年第8期1109-1112,共4页
Chinese Journal of Lasers
关键词
光学器件
模式识别
聚类
暗场成像
在线检测
optical devices
pattern recognition
clustering
dark-field image
online inspection
