Automatic saw-mark detection in multicrystalline solar wafer images

Automatic saw-mark detection in multicrystalline solar wafer images
复制标题

DOI:
10.1016/j.solmat.2011.03.025
复制
发表时间:
2011-08
影响因子:
6.9
通讯作者:
Wei-Chen Li;D. Tsai
Wei-Chen Li;D. Tsai
中科院分区:
材料科学2区
文献类型:
--
作者:
Wei-Chen Li;D. Tsai

文献摘要

被引文献

相似文献

本文提出了一种光伏行业的自动缺陷检测方法,特别关注多晶硅太阳能硅片。提出了一种基于机器视觉的太阳能硅片表面锯痕缺陷自动检测方法。锯痕缺陷是在将硅锭切割成晶片时发生的严重缺陷。晶圆切割过程中锯痕缺陷的早期检测可以减少材料浪费并提高产量。多晶硅太阳能晶片表面呈现随机形状、尺寸和表面中晶粒的取向,使得锯痕缺陷的自动检测极其困难。所提出的锯痕检测方案包括两个主要过程:(1)傅立叶图像重建,以去除太阳能晶片图像的多颗粒背景和(2)在重建图像中的线检测过程,以定位锯痕。傅里叶变换(FT)是用来消除晶粒图案,并在重建图像中的非纹理表面的结果。由于锯痕水平地呈现在切片的晶片中,所以通过线检测过程单独地评估重构图像中的垂直扫描线。远离所寻找的线的像素然后可以被有效地识别为缺陷点。实验结果表明,该方法可以有效地检测各种锯痕缺陷,特别是黑线,白色线,和杂质的多晶太阳能晶片。
This paper presents a method of automatic defect inspection for the photovoltaic industry, with a special focus on multicrystalline solar wafers. It presents a machine vision-based scheme to automatically detect saw-mark defects in solar wafer surfaces. A saw-mark defect is a severe flaw that occurs when a silicon ingot is cut into wafers. Early detection of saw-mark defects in the wafer cutting process can reduce material waste and improve production yields. A multicrystalline solar wafer surface presents random shapes, sizes, and orientations of crystal grains in the surface, making the automatic detection of saw-mark defects extremely difficult. The proposed saw-mark detection scheme involves two main procedures: (1) Fourier image reconstruction to remove the multi-grain background of a solar wafer image and (2) a line detection process in the reconstructed image to locate saw-marks. The Fourier transform (FT) is used to eliminate crystal grain patterns and results in a non-textured surface in the reconstructed image. Since a saw-mark is presented horizontally in the sliced wafer, vertical scan lines in the reconstructed image are individually evaluated by a line detection process. A pixel far away from the line sought can then be effectively identified as a defect point. Experimental results show that the proposed method can effectively detect various saw-mark defects, specifically black lines, white lines, and impurities in multicrystalline solar wafers.