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Fig 1.

The defect detection system for solar cells.

Notes: 1-conveyer belt, 2-the light source of WS4, 3-the camera of WS4, 4-the camera of WS3, 5-the telecentric, 6-the light source of WS3, 7-the camera of WS2, 8-the light source of WS2, 9-the camera of WS1, 10-the light source of WS1, 11-solar cell.

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Fig 1 Expand

Fig 2.

The field diagram of the image detection system.

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Fig 2 Expand

Fig 3.

The 5 types defects of solar cells.

Notes: (a) mismatch defect, (b) bubble defects, (c) cell-crack defects, (d) glass-crack defect, (e) glass-upside-down defect 1, (f) glass-upside-down defect 2.

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Fig 3 Expand

Table 1.

The defect datasets before and after image enhancement.

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Table 1 Expand

Fig 4.

The structure of YOLOv5s model.

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Fig 4 Expand

Fig 5.

The steps of K-means algorithm and the visualization of the clustering result of mismatch defects.

(a) The process of obtaining the optimal size of the anchor boxes by the K-means algorithm. (b) The visualization results of the clustering process for mismatch defects labeled boxes.

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Fig 5 Expand

Fig 6.

The comparison of 9 anchor boxes before and after clustered calculation.

(a) The 9 anchor boxes before K-means clustered calculation. (b) The 9 anchor boxes after K-means clustered calculation.

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Fig 6 Expand

Fig 7.

The loss and AP curves of default and improved anchor boxes.

(a) The loss curves. (b) The AP curves.

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Fig 7 Expand

Table 2.

The detection accuracy indicators of the YOLOv5s model.

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Table 2 Expand

Fig 8.

Test results of mismatch defects before and after the anchor boxes are improved.

(a) The detection results of original YOLOv5 model. (b) The detection results of YOLOv5 model with improved anchor boxes.

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Fig 8 Expand

Fig 9.

The structures of coupled head and decoupled head.

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Fig 9 Expand

Fig 10.

The variation process of various loss functions before and after model improvement.

(a) Loss curves for predicting category information, Cls_loss. (b) Loss curves for prediction boxes information, Reg_loss. (c) Loss curves for predicting the inclusion or exclusion of objects, Obj_loss.

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Fig 10 Expand

Fig 11.

The testing effectiveness comparison for general defects before and after the model is improved.

(a) The detection effectiveness comparison for cell-crack defects. (b) The detection effectiveness comparison for bubble defects. (c) The detection effectiveness comparison for glass-crack defects.

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Fig 11 Expand

Table 3.

Comparative experiments of general defect detection.

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Table 3 Expand

Table 4.

Detection results of three models for glass-upside-down defects.

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Table 4 Expand

Fig 12.

The classification detection scheme for solar cell defects.

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Fig 12 Expand

Table 5.

Detection result statistics of the classification detection scheme.

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Table 5 Expand