Automatic inspection method for solar cells
Automatic Detection of Defects in Solar Modules Using a Deep
this study, we propose a method for the automatic detection of solar defects within a single EL image of a solar PV cell. Our approach utilizes a lightweight convolutional neural network (L
Automatic Defect Inspection for Monocrystalline Solar Cell
An automatic defect inspection method for MSC interior using Electroluminescence (EL) imaging technology and a self-comparison method (SCM) is proposed to detect defects in the background with nonuniform luminance and complicated texture.
A CISG Method for Internal Defect Detection of Solar Cells in
To improve the intelligence and universality of inspection algorithms for different types of solar cells, this paper proposes a coarse-to-fine method based on a saliency map for solar cell
Automatic Defect Inspection for Monocrystalline Solar Cell Interior
An automatic defect inspection method for MSC interior using Electroluminescence (EL) imaging technology and a self-comparison method (SCM) is proposed to detect defects in the
Automated visual inspection of solar cell images using adapted
This study proposed an effective visual inspection method to detect defects in solar cells. The proposed method is based on adapted morphological and edge detection algorithms. This method uses multiple morphological and canny edge detection with adapted
Automatic Defect Inspection for Monocrystalline Solar Cell
(DOI: 10.1109/TIM.2021.3096602) The monocrystalline solar cell (MSC) interior is prone to miscellaneous defects that affect energy conversion efficiency and even cause fatal damage to the photovoltaic module. In this study, an automatic defect inspection method for MSC interior is presented. Electroluminescence (EL) imaging technology is utilized to visualize defects inside
Anomaly Detection and Automatic Labeling for Solar Cell Quality
and classification results of supervised models trained with automatic labels are comparable to the ones obtained from the models trained with manual labels. Keywords: Anomaly detection; Electroluminescence; Solar cells; Neural Networks 1. Introduction Quality inspection applications in industry are becoming very important. It is a requirement
Automatic Defect Inspection for Monocrystalline Solar Cell Interior
To improve the intelligence and universality of inspection algorithms for different types of solar cells, this paper proposes a coarse-to-fine method based on a saliency map for
Automatic inspection of surface crack in solar cell images
Based on image acquisition and computer vision technology, an automatic inspection method for solar cell surface crack was proposed. Through a series of image pre-processing methods to
A CISG Method for Internal Defect Detection of Solar Cells in
DOI: 10.1109/TIE.2021.3104584 Corpus ID: 238960545; A CISG Method for Internal Defect Detection of Solar Cells in Different Production Processes @article{Liu2022ACM, title={A CISG Method for Internal Defect Detection of Solar Cells in Different Production Processes}, author={Yu Liu and Jiaming Xu and Yilin Wu}, journal={IEEE Transactions on Industrial Electronics},
Solar cell crack inspection by image processing
DOI: 10.1109/BEPRL.2004.1308153 Corpus ID: 43759965; Solar cell crack inspection by image processing @article{Fu2004SolarCC, title={Solar cell crack inspection by image processing}, author={Zhuang Fu and Yanzheng Zhao and Liu Yang and Cao Qixin and Mingbo Chen and Zhang Jun and J. Lee}, journal={Proceedings of 2004 International
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
Adaptive automatic solar cell defect detection and classification
Therefore, this paper presents an automatic defect-inspection method for multi-cell monocrystalline PV modules with EL images. A processing routine is designed to extract the defect features of
Automated visual inspection of solar cell images using adapted
This study proposed an effective visual inspection method to detect defects in solar cells. The proposed method is based on adapted morphological and edge detection algorithms. This method uses multiple morphological and canny edge detection with adapted parameters to extract and highlight the objects on the solar cell. Then the detected
An Automatic Condition Detection Approach for Quality
The multi-stage solar cell manufacturing process includes sev-eral key stages, such as the epitaxy, evaporation, and welding stages, which may jointly affect the quality of cell chips. The...
Anomaly Detection and Automatic Labeling for Solar Cell
This work presents a methodology to develop a robust inspection system, targeting these peculiarities, in the context of solar cell manufacturing. The methodology is divided into two phases: In the first phase, an anomaly detection model based on a Generative Adversarial Network (GAN) is employed.
Automatic inspection of surface crack in solar cell images
Based on image acquisition and computer vision technology, an automatic inspection method for solar cell surface crack was proposed. Through a series of image pre-processing methods to reduce noise and improve the post-processing capabilities. On this basis, using Gabor wavelets and LGBPHS method to obtain image features, in addition also need
Adaptive automatic solar cell defect detection and classification
An automatic method is proposed for solar cell defect detection and classification. An unsupervised algorithm is designed for adaptive defect detection. A
Adaptive automatic solar cell defect detection and classification
Herein, we propose an adaptive approach for automatic solar cell defect detection and classification based on absolute EL imaging. Specifically, we first develop an
Automatic Defect Inspection for Monocrystalline Solar Cell
To improve the intelligence and universality of inspection algorithms for different types of solar cells, this paper proposes a coarse-to-fine method based on a saliency map for solar...
Automatic Detection of Defects in Solar Modules Using a Deep
this study, we propose a method for the automatic detection of solar defects within a single EL image of a solar PV cell. Our approach utilizes a lightweight convolutional neural network (L-CNN) developed from scratch for feature extraction and a fully connected artificial neural network (ANN) for classifying functional and defective solar
Anomaly Detection and Automatic Labeling for Solar Cell Quality
This work presents a methodology to develop a robust inspection system, targeting these peculiarities, in the context of solar cell manufacturing. The methodology is
Adaptive automatic solar cell defect detection and classification
An automatic method is proposed for solar cell defect detection and classification. An unsupervised algorithm is designed for adaptive defect detection. A standardized diagnosis scheme is developed for statistical defect classification .
Automatic Defect Inspection for Monocrystalline Solar Cell
In this study, an automatic defect inspection method for MSC interior is presented. Electroluminescence (EL) imaging technology is utilized to visualize defects inside MSC. Also, accurate cell positioning is the precondition of full inspection, so a sigmoid-Hough-transform-based geometric segmentation (SHTGS) algorithm is designed to extract
6 FAQs about [Automatic inspection method for solar cells]
Is there an Automatic Defect inspection method for monocrystalline solar cells?
Abstract: The monocrystalline solar cell (MSC) interior is prone to miscellaneous defects that affect energy conversion efficiency and even cause fatal damage to the photovoltaic module. In this study, an automatic defect inspection method for MSC interior is presented.
Why is visual inspection important for solar cells?
The surface of solar cell products is critically sensitive to existing defects, leading to the loss of efficiency. Finding any defects in the solar cell is a significantly important task in the quality control process. Automated visual inspection systems are widely used for defect detection and reject faulty products.
How to automatically detect and classify defects in solar cells?
An adaptive approach to automatically detect and classify defects in solar cells is proposed based on absolute electroluminescence (EL) imaging. We integrate the convenient automatic detection algorithm with the effective defect diagnosis solution so that in-depth defect detection and classification becomes feasible.
How to detect a solar cell defect?
An automatic method is proposed for solar cell defect detection and classification. An unsupervised algorithm is designed for adaptive defect detection. A standardized diagnosis scheme is developed for statistical defect classification. Extensive experimental results verify the effectiveness of the proposed method.
What is adaptive automatic solar cell defect detection & classification method?
The proposed adaptive automatic solar cell defect detection and classification method mainly consists of the following three steps: solar cell EL image preprocessing, adaptive solar cell defect detection, and solar cell defect classification, as shown in Fig. 1.
Can a visual inspection system detect defects in solar cells?
The study introduces an automated visual inspection system utilizing mathematical morphology and edge-based region analysis to efficiently detect defects in solar cells, addressing computation complexity and cost constraints in real-time quality control procedures and production lines. 2.
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