光学元件亚表面损伤深度的无损荧光检测方法

侯晶; 王洪祥; 王储; 王景贺; 朱本温

doi:10.11918/j.issn.0367-6234.201707091

Chinese

您当前的位置：

首页 >

文章列表页 >

光学元件亚表面损伤深度的无损荧光检测方法

更新时间：2026-10-23

- 光学元件亚表面损伤深度的无损荧光检测方法
- Nondestructive fluorescence detection method for subsurface damage depth of optics
- 哈尔滨工业大学学报 2018年50卷第7期页码：17-22
- 作者机构：
  
  1. 哈尔滨工业大学机电工程学院,哈尔滨,150001
  2. 中国工程物理研究院激光聚变研究中心,四川,绵阳,621900
- 作者简介：
- 基金信息：
  
  国防基础科研科学挑战专题(JCKY2016212A506-0503);国家自然科学基金(51475106)
- DOI：10.11918/j.issn.0367-6234.201707091
  中图分类号： TG115.28
- 纸质出版：2018
- 稿件说明：
移动端阅览
侯晶, 王洪祥, 王储, 等. 光学元件亚表面损伤深度的无损荧光检测方法[J]. 哈尔滨工业大学学报, 2018,50(7):17-22.

HOU Jing, WANG Hongxiang, WANG Chu, et al. Nondestructive fluorescence detection method for subsurface damage depth of optics[J]. 2018, 50(7): 17-22.
侯晶, 王洪祥, 王储, 等. 光学元件亚表面损伤深度的无损荧光检测方法[J]. 哈尔滨工业大学学报, 2018,50(7):17-22. DOI： 10.11918/j.issn.0367-6234.201707091.

HOU Jing, WANG Hongxiang, WANG Chu, et al. Nondestructive fluorescence detection method for subsurface damage depth of optics[J]. 2018, 50(7): 17-22. DOI： 10.11918/j.issn.0367-6234.201707091.

摘要

为了实现光学元件亚表面损伤的低成本、快速、准确检测，提出一种光学元件亚表面损伤深度无损荧光检测方法.在研磨和抛光加工过程中添加纳米荧光量子点溶液作为标记物，量子点受到激发光辐照后能够产生荧光现象，然后利用激光共聚焦显微镜进行逐层扫描以获取被测样品不同深度处的切片图像，当扫描深度达到某一特定值时，荧光强度开始由强变弱，通过特征点荧光强度的变化最终确定光学元件的亚表面损伤深度.自行开发了亚表面损伤深度无损检测软件，检测软件具有图像阈值处理、亮点自动识别、图像显示和曲线表征等功能，可以实现光学元件亚表面损伤深度的快速无损检测.将无损检测结果与损伤性检测结果进行了对比分析，结果表明两种检测方法相对误差在10%以内，验证了提出的无损荧光检测方法的有效性.

Abstract

A nondestructive detection method of subsurface damage depth was proposed

in which nano-fluorescent quantum dots were added as marker in grinding and polishing process

and the quantum dots were excited by light and produced fluorescence

then the slice images of the samples at different depths were obtained by laser confocal microscopy. When the scanning depth reached a certain value

the fluorescence intensity became weak and the subsurface damage depth was determined by fluorescence intensity change of the feature points. A nondestructive detection software of subsurface damage depth

which has functions of image threshold processing

bright spot automatic recognition

image display and curve characterization

is developed and it can realize the rapid detection of subsurface damage depth. The results of non-destructive detection and damage detection were compared

and it showed that the relative error between the two detection methods was less than 10%

which verified the effectiveness of the proposed method.

关键词

Keywords

references

浏览量

599

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

Shearlet变换与核各向异性扩散的图像噪声抑制

基于航模辅助观测的车辆轨迹提取方法

结合产生式模型和RCC方法的极化SAR图像分类算法

正交雅可比-傅里叶矩的亚像素边缘定位

面向工业检测的图像快速去直线运动模糊方法