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Automatic
surface defect inspection in multicrystalline solar wafers Solar power is an
attractive alternative source of electricity. Multicrystalline solar cells
dominate the market share owing to their lower manufacturing and material
costs. The surface quality of solar wafer critically determines the
conversion efficiency of the solar cell. In this research, three surface
defect inspection techniques are presented for identifying low-contrast
defects in non-textured surfaces (for backside solar cells) and detecting
small local defects in inhomogeneous surfaces (for solar wafers). The first two solar
cells/wafers surface inspection algorithms use a Hough-like line detection
method to identify defect points on 1D gray-level profiles of scan lines in
the image. The conventional Hough transform requires a sufficient number of
points lying exactly on the same straight line at a given parameter
resolution so that the accumulator will show a distinct peak in the parameter
space. It fails to detect a line in a non-stationary signal. The first
proposed Hough-like algorithm can effectively detect the low-contrast defects
in the unevenly-illuminated surface of a backside solar cell. In the second
proposed method, the inhomogeneous background of multicrystalline grains in a
solar wafer image can be effectively removed by properly selecting the
band-rejection region in the Fourier spectrum, and then the proposed
Hough-like line detection technique is used to identify saw-mark defects in a
solar wafer. The third surface defect inspection method is based on the
two-dimensional discrete wavelet transform, and is applied to the detection
of various defect types. It takes the energy difference between two
consecutive decomposition levels as a clue to enhance the discriminant
features extracted in individual decomposition levels and generates a better discriminant measure for identifying defects with
scattering and blurred edges. Experimental results have shown that the
proposed methods perform effectively for detecting low-contrast bump in the
unevenly-illuminated backside solar cell, and various defects of stain,
saw-mark, fingerprint and contaminant in the inhomogeneous solar wafer
surface. Keywords: Machine
vision; Surface inspection; Defect detection; Multicrystalline solar wafer;
Hough transform; Fourier transform; Wavelet transform. |
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《Experimental Results》 【Solar cell backside inspection】
【Solar wafer inspection-Fourier
reconstruction method】
【Solar wafers inspection-Wavelet-Based
Defect Detection】
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of
row gray-level profiles; (a4)-(d4) detection results
of
column gray-level profiles; (a5)-(d5) the union of
