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Efficient Cell Segmentation from Electroluminescent Images of Single-Crystalline Silicon Photovoltaic Modules and Cell-Based Defect Identification Using Deep Learning with Pseudo-Colorization
| Content Provider | MDPI |
|---|---|
| Author | Lin, Horng-Horng Dandage, Harshad Lin, Keh-Moh Lin, You-Teh Chen, Yeou-Jiunn |
| Copyright Year | 2021 |
| Abstract | Solar cells may possess defects during the manufacturing process in photovoltaic (PV) industries. To precisely evaluate the effectiveness of solar PV modules, manufacturing defects are required to be identified. Conventional defect inspection in industries mainly depends on manual defect inspection by highly skilled inspectors, which may still give inconsistent, subjective identification results. In order to automatize the visual defect inspection process, an automatic cell segmentation technique and a convolutional neural network (CNN)-based defect detection system with pseudo-colorization of defects is designed in this paper. High-resolution Electroluminescence (EL) images of single-crystalline silicon (sc-Si) solar PV modules are used in our study for the detection of defects and their quality inspection. Firstly, an automatic cell segmentation methodology is developed to extract cells from an EL image. Secondly, defect detection can be actualized by CNN-based defect detector and can be visualized with pseudo-colors. We used contour tracing to accurately localize the panel region and a probabilistic Hough transform to identify gridlines and busbars on the extracted panel region for cell segmentation. A cell-based defect identification system was developed using state-of-the-art deep learning in CNNs. The detected defects are imposed with pseudo-colors for enhancing defect visualization using K-means clustering. Our automatic cell segmentation methodology can segment cells from an EL image in about |
| Starting Page | 4292 |
| e-ISSN | 14248220 |
| DOI | 10.3390/s21134292 |
| Journal | Sensors |
| Issue Number | 13 |
| Volume Number | 21 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-06-23 |
| Access Restriction | Open |
| Subject Keyword | Sensors Industrial Engineering Electroluminescence Image Single-crystalline Silicon Photovoltaic Module Cell Segmentation Defect Detection Pseudo-colorization |
| Content Type | Text |
| Resource Type | Article |
