Image processing was applied to detect the defects automatically which included black pieces, fragmentations, broken grids and cracks. The defects were classified, and then, the locations of defects were marked. Their experimental results showed that their system could improve the defect detection’s efficiency on solar cell products.
Nevertheless, review papers proposed in the literature need to provide a comprehensive review or investigation of all the existing data analysis methods for PV system defect detection, including imaging-based and electrical testing techniques with greater granularity of each category's different types of techniques.
An automated EL image pre-processing pipeline for solar cell defect detection . To identify the module region, the background in the image is removed. A histogram is first used by mapping the spectral colour of the pixel intensity values to the binned colour ranges. This yields a background of colour purple (Fig. 7 (b)).
The main focus of the research was to detect visible defects on solar cells. The main contribution of this work is using webcam camera to develop a robust and low-cost hardware installation system. A combination of multiple-use morphology and edge detection techniques was accommodated to detect the defects.
This paper proposed a solar cell inspection system based on automated visual inspection system (AVIS). The main focus of the research was to detect visible defects on solar cells. The main contribution of this work is using webcam camera to develop a robust and low-cost hardware installation system.
Although several review papers have investigated recent solar cell defect detection techniques, they do not provide a comprehensive investigation including IBTs and ETTs with a greater granularity of the different types of each for PV defect detection systems.
An efficient and portable solar cell defect detection system
data augmentation process to overcome the overÞtting and data scarcity problems. In [ 8], two different methods were proposed for auto-matic detection of the photoelectric cell cracks.
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Research on multi-defects classification detection method for solar ...
In view of the surface defect characteristics in the manufacturing process of solar cells, the common surface defects are divided into three categories, which include difficult-detecting defects (mismatch), general defects (bubble, glass-crack and cell-crack) and easy-detecting defects (glass-upside-down). Corresponding to different types of ...
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Research on multi-defects classification detection method for solar ...
In view of the surface defect characteristics in the manufacturing process of solar cells, the common surface defects are divided into three categories, which include difficult-detecting …
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A review of automated solar photovoltaic defect detection …
Therefore, it is crucial to identify a set of defect detection approaches for predictive maintenance and condition monitoring of PV modules. This paper presents a comprehensive review of different data analysis methods for defect detection of PV systems with a high categorisation granularity in terms of types and approaches for each technique.
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Defect detection on solar cells using mathematical ...
In this paper, we proposed a non-contact and nondestructive automated visual inspection system that was able to perform defect detection using image processing and fuzzy …
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Solar Cell Surface Defect Detection Based on Improved YOLO v5
Abstract: A solar cell defect detection method with an improved YOLO v5 algorithm is proposed for the characteristics of the complex solar cell image background, variable defect morphology, and large-scale differences. First, the deformable convolution is incorporated into the CSP module to achieve an adaptive learning scale and perceptual ...
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An Efficient YOLOX-Based Method for Photovoltaic Cell Defect Detection
Therefore, this paper proposes a high-efficiency photovoltaic cell defect detection method based on improved YOLOX. First, the transfer learning training strategy is adopted to accelerate model convergence, which can also avoid the problem of insufficient accuracy due to the small number of defect samples. Secondly, to suppress the interference ...
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Solar Cell Surface Defect Detection Based on Optimized YOLOv5
Traditional vision methods for solar cell defect detection have problems such as low accuracy and few types of detection, so this paper proposes an optimized YOLOv5 model for more accurate …
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An improved hybrid solar cell defect detection approach using ...
Electroluminescence (EL) imaging is one of the main non-destructive inspection methods for quality assessment in the Photovoltaic (PV) module production …
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An Efficient YOLOX-Based Method for Photovoltaic Cell Defect …
Therefore, this paper proposes a high-efficiency photovoltaic cell defect detection method based on improved YOLOX. First, the transfer learning training strategy is …
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Accurate detection and intelligent classification of solar cells ...
Addressing this issue, this paper combines neural networks with photoluminescence detection technology and proposes a novel neural network model for the …
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A review of automated solar photovoltaic defect detection …
Methods based on CV are considered one of the main directions in DIP of EL imaging for automated solar cell defect detection [36]. They have been mainly categorised into three groups: 1) local scheme-based methods, in which the local image features (e.g., gradient, texture, local intensity contrast, etc.) are extracted, and defective regions are then segmented …
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An improved hybrid solar cell defect detection approach using ...
Electroluminescence (EL) imaging is one of the main non-destructive inspection methods for quality assessment in the Photovoltaic (PV) module production industry. EL test reveals PV cell defects such as micro cracks, broken cells, finger interruptions and provides detailed information about production quality.
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Image Defect Detection and Segmentation Algorithm of Solar Cell …
The surface defect detection method of solar cells based on machine learning has become one of the main research directions because of its high efficiency and convenience. For this reason, this paper proposes an improved fusion model based on VGGNet and U-Net++, which is used for defect detection and segmentation of EL images of solar cells. In ...
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Image Defect Detection and Segmentation Algorithm of Solar Cell …
The surface defect detection method of solar cells based on machine learning has become one of the main research directions because of its high efficiency and convenience. For this reason, …
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Adaptive automatic solar cell defect detection and classification …
Solar cell defect classification: Based on the adaptive detection result, we further propose a heuristic method to classify the solar cell defect types from an electrical viewpoint. According to our previous work, the injection-current-dependent absolute EL intensity loss rate of the defects is proved to constitute the key issues that quantitatively diagnose the defect types. …
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Image Defect Detection and Segmentation Algorithm of Solar Cell …
The use of infrared or electroluminescence(EL) images of solar cell modules for defect detection is a very important method in non-destructive testing. Traditionally, this work is done by skilled technicians, which is time-consuming and susceptible to subjective factors. The surface defect detection method of solar cells based on machine learning has become one of the main …
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Research on multi-defects classification detection method for solar ...
vant scholars have introduced deep learning methods into solar cells defect detection, and achieved good results that are difficult to by the conventional image analysis …
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Solar cell surface defect inspection based on multispectral ...
Similar and indeterminate defect detection of solar cell surface with heterogeneous texture and complex background is a challenge of solar cell manufacturing. The traditional manufacturing process relies on human eye detection which requires a large number of workers without a stable and good detection effect. In order to solve the problem, a visual …
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Accurate detection and intelligent classification of solar cells ...
Addressing this issue, this paper combines neural networks with photoluminescence detection technology and proposes a novel neural network model for the classification and grading of defects in solar cells. Firstly, the YOLOv5 model is optimized and adjusted for algorithm and network structure.
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Defect detection on solar cells using mathematical ...
In this paper, we proposed a non-contact and nondestructive automated visual inspection system that was able to perform defect detection using image processing and fuzzy logic techniques. The image processing techniques involved thresholding, mathematical morphology, and edge detection operators.
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Solar Cell Surface Defect Inspection Based on Multispectral ...
Many existing solar cell defect detection methods focus on the analysis of electroluminescence (EL) infrared images un-der 1000nm-1200nm wave length. Chiou et al.[16] developed a regional growth detection algorithm to extract cracks defect Solar Cell Surface Defect Inspection Based on Multispectral Convolutional Neural Network Kun Liu liukun@hebut .cn 1 The School of …
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Solar Cell Surface Defect Detection Based on Improved YOLO v5
Abstract: A solar cell defect detection method with an improved YOLO v5 algorithm is proposed for the characteristics of the complex solar cell image background, variable defect morphology, and large-scale differences. First, the deformable convolution is …
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Research on multi-defects classification detection method for solar ...
vant scholars have introduced deep learning methods into solar cells defect detection, and achieved good results that are difficult to by the conventional image analysis and processing methods. The gallium arsenide solar cells studied in this paper are applied in aerospace field, its struc-
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Review of Microcrack Detection Techniques for Silicon Solar Cells
EL equipment with a CCD camera . plus lens filter has been used to capture the emissions and filter. out visible spectrum for automatic detection of subfacial cracks. in solar cells [82]. An ...
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Research on Online Defect Detection Method of Solar …
For solar cell defect detection, Chen et al. [] proposed a cell crack defect detection scheme based on structure perception designing the structure similarity measure (SSM) function, using the nonmaximum value …
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A review of automated solar photovoltaic defect detection systems ...
Therefore, it is crucial to identify a set of defect detection approaches for predictive maintenance and condition monitoring of PV modules. This paper presents a …
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(PDF) Research on Online Defect Detection Method of …
Research on Online Defect Detection Method of Solar Cell Component Based on Lightweight Convolutional Neural Network . November 2021; International Journal of Photoenergy 2021(1):1-13; DOI:10.1155 ...
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Solar Cell Surface Defect Detection Based on Optimized YOLOv5
Traditional vision methods for solar cell defect detection have problems such as low accuracy and few types of detection, so this paper proposes an optimized YOLOv5 model for more accurate and comprehensive identification of defects in solar cells.
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