不可见脉冲激光的聚焦系统

傅星; 李纪楷; 齐慧

doi:10.3788/OPE.20172513.0012

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不可见脉冲激光的聚焦系统

现代应用光学 | 更新时间：2020-08-13

- 不可见脉冲激光的聚焦系统
- Autofocus system for invisible pulsed laser
- 光学精密工程 2017年25卷第10s期页码：12-19
- 作者机构：
  
  天津大学精密仪器与光电子工程学院天津,300072
- 作者简介：
- 基金信息：
  
  高等学校学科创新引智计划资助项目（No.B07014）()
- DOI：10.3788/OPE.20172513.0012
  中图分类号： TP394.1;TN249
- 收稿日期：2017-05-31，
  
  修回日期：2017-06-11，
  
  纸质出版日期：2017-11-25
- 稿件说明：
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傅星, 李纪楷, 齐慧. 不可见脉冲激光的聚焦系统[J]. 光学精密工程, 2017,25(10s): 12-19

FU Xing, LI Ji-kai, QI Hui. Autofocus system for invisible pulsed laser[J]. Editorial Office of Optics and Precision Engineering, 2017,25(10s): 12-19
傅星, 李纪楷, 齐慧. 不可见脉冲激光的聚焦系统[J]. 光学精密工程, 2017,25(10s): 12-19 DOI： 10.3788/OPE.20172513.0012.

FU Xing, LI Ji-kai, QI Hui. Autofocus system for invisible pulsed laser[J]. Editorial Office of Optics and Precision Engineering, 2017,25(10s): 12-19 DOI： 10.3788/OPE.20172513.0012.

摘要

为了解决不可见脉冲激光加工系统中的位置定位与聚焦问题，介绍了一种实用的激光加工系统结构，并提出了基于该系统结构的适用于不可见脉冲激光的位置定位与自动聚焦方法。首先，CCD采集不可见激光的一个脉冲加工样品表面的瞬间的图像。接着，对该图像通过合适的阈值进行二值化处理，提取图像中的亮点区域，再通过灰度重心法得到该亮点区域的几何中心的亚像素坐标值，这一坐标即为激光的焦点位置。然后，分析多个时域的图像清晰度评价算子，并对图像的各个分量进行研究，得到了由Sobel梯度算子评价样品表面图像的绿色分量的自动聚焦算法。之后，提出了采用以焦点位置为中心的局部图像来进行评价的局部自动聚焦算法。实验结果表明：位置定位的精度为1个像素，自动聚焦的精度为1

m。同时，以上所述的位置定位与聚焦方法可以有效地提高激光加工系统加工不同参数的样品形貌的能力，满足了更多不同的加工需求。

Abstract

It is more difficult for invisible laser to position locating and local autofocus in the invisible pulse laser processing system. In this paper

a useful laser processing system was introduced

and the methods of the position locating and autofocus were proposed based on the system. First

the image of the interaction between one pulse laser and the sample surface was captured by CCD. Then

the image was turned into binary image by a proper threshold value. Extracting the area of the light spot

the coordinate of the subpixel of the centroid of the focused laser spot was calculated by the gray centroid method. Meanwhile several operators were employed to evaluate the sharpness of the image in time domain

thus analyzing different components of the imagein the operators. Subsequently

the autofocus algorithm was presented based on the evaluation of green component of the sample surface with Sobel gradient operator.Furthermore

the local autofocus algorithm was proposed based on the local image centered with the focused laser spot rather than the whole image to reduce the error of the global autofocus algorithm. Experimental results show that the precision of the position locating algorithm is 1 pixeland the accuracy of the autofocus algorithm is 1

which indicatethat the proposed autofocus methodcan improve the performance of laser processing systems to meet the increasing need of the laser processing.

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