Defective crystalline silicon solar cells may be repaired using laser-based techniques if the problem is properly identified and characterized. This paper presents a novel system for the automation of solar cells repair that carries out the following tasks: 1) It detects and localizes cracks and shunts in solar cells from electroluminescence images; 2) It takes a decision on the laser process to repair faulty cells; 3) It automates the operation of a laser machine for processing solar cells. Regarding the analysis of electroluminescence images of solar cells, the proposed solution is able to discriminate the type of defect, which means a step-forward compared to state-of-the-art approaches. Moreover, it is to our knowledge the first solution that takes the results of such analysis to automate a process of laser-based repair. The proposed system paves the way for waste reduction in the production of solar cells by using repaired cells in custom-made solar modules.

1. Automated in-Line
Defect Classification and Localization
in Solar Cells for Laser-Based Repair
Jorge Rodríguez –Araújo, Antón García-Díaz
AIMEN Technology Center, Porriño, Spain
ISIE 2014, Istambul, 2-6-2014

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Index
1. Motivation and Innovative Character.
2. Proposed Solution.
3. Diagnostic and Defect Segmentation.
4. Repair Process Decision.
5. Experimental Results.
6. Conclusions and future work.
Index

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Motivation and Innovative Character

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Motivation and Innovative Character
• Solar cells are made of silicon (156x156mm).
• Monocrystalline and Polycrystalline silicon (more common materials).
• The manufacturing process produces defects.
Photovoltaic solar cells
busbars
front back

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Motivation and Innovative Character
• Electroluminescence imaging.
• Shunts and Cracks (most important).(> 50%)
• Lacks of metallization (less frequent) (< 20%).
• Finger interruptions (reduced effects). (> 58%)
• Shunts and Cracks may be repaired.
• Cutting or isolating using laser technology.
• New pieces of cells are obtained.
Defects
Detection

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Proposed Solution

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Proposed Solution
• Laser Repair System (laser process).
• Defects Inspector (defects identification and laser control).
• Data Input Block (electroluminescence provider).
Solar cell repair system

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Proposed Solution
• Cell Diagnostic (defects segmentation from EL).
• Repairing Decision (laser process decision).
• Cell Alignment (laser process correction).
Defects inspector

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Diagnostic and Defect Segmentation

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Diagnostic and Defect Segmentation
• Human experts examine EL images.
– Changes on texture.
– Changes on the shape of texture boundaries.
• Defect Diagnostic (texture based)
– Decomposition: for automatic features generation.
– Adaptation: for enhancement of features.
– Pixel level classification: for multiclass identification.
Bio-inspired texture approach
Texture approach
Defects
Log Gabor filters

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Diagnostic and Defect Segmentation
• Trained with only 4 images.
– 4 cracks presents.
– 4 shunts presents.
• Type of defect and boundary contour are identified.
Some examples of identified defects.
Pixel level identification

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Repair Process Decision

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Repair Process Decision
• Decision rules:.
– Isolate shunts not on a busbar.
– Cut shunts on a busbar or close to one.
– Cut pieces to remove cracks.
Solar cell repair decision
Examples of repair decision.

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Repair Process Decision
• Closing morphological operation.
• Inversion and thresholding.
• Edge detection and contour.
• Bounding box localization.
Cell location and alignment
Steps on cell localization.

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Experimental results

16. Experimental Results
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Laser-based repair unit
Camera perspective.
Scanner working area.
Laser repair system.

17. Experimental results
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Laser scanner calibration
Galvo-scanner working area.

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Experimental results
Calibration pictures

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Experimental results
Processing pictures

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Experimental results
Results pictures

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Experimental Results
• 47 cells considered.
• 45 cells repaired.
• 69% waste reduction.
Processing results
Defect
type
# of
Defects
TP FP FN Repaired
Shunts 43 43 4 0 42
Cracks 38 36 6 2 36
All 81 79 10 2 45*
* This value refers to the number of cells repaired.

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Conclusions and Future Work

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Conclusions and Future work
• Defect segmentation and classification.
• In-line solar cells repair system.
• Able to isolate and cut defects.
• 69% of rejected cells reutilization.
• Discriminate more defects, like metallization.
• More complex repair strategies.
• Isolation based on efficiency estimation.
Conclusions
Future work

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