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Photovoltatronics: intelligent PV-based devices for energy and …
Fig. 1 Research concepts and examples for the research area 1. (a) The ideal absorber-bandgap map to achieve the maximum solar-cell efficiency on Earth. 46 (b) Map of energy yield for 2015 using PV-cell with the ideal band-gap absorber. 46 (c) Concepts of sensitivity map and (d) sky map introduced in ref. 43 for detailed and accurate energy yield …
Convolutional Neural Network based Efficient Detector for ...
One of the challenges in the field of photovoltaics (PV) is the automation of defect detection in electroluminescent (EL) images of PV cells. This is due to the similarities between defects and the intricate nature of the background, which can make it difficult to accurately identify and distinguish defects.
Accurate detection and intelligent classification of solar cells ...
Defect detection in solar cells plays a significant role in industrial production processes [3]. Conventional methods of solar cell testing require contact with the samples, which can easily cause secondary pollution on the surface of the solar cells during production and processing [4].
Review A review of automated solar photovoltaic defect detection …
Recent state-of-the-art research has focused on Artificial intelligence (AI) and Machine Learning (ML) ... CNN based automatic detection of photovoltaic cell defects in electroluminescence images Energy, 189 (2019), Article 116319, 10.1016/j.energy.2019.116319 ...
Improved YOLOv8-GD deep learning model for defect detection in electroluminescence images of solar photovoltaic …
Semantic Scholar extracted view of "Improved YOLOv8-GD deep learning model for defect detection in electroluminescence images of solar photovoltaic modules" by Yukang Cao et al. DOI: 10.1016/j.engappai.2024.107866 Corpus ID: …
BAF-Detector: An Efficient CNN-Based Detector for Photovoltaic Cell Defect Detection …
BAF-Detector: An Efficient CNN-Based Detector for Photovoltaic Cell Defect Detection Binyi Su, Haiyong Chen, and Zhong Zhou, Member, IEEE Abstract—The multi-scale defect detection for photo-voltaic (PV) cell electroluminescence (EL) images is a deepens.
AutoFD: An Intelligent Electrical Fault detection techniques for …
To improve the efficiency and reliability of PV cell-powered IoT systems, detection and prediction of different defects in the PV cells have become critical. Several fault …
Intelligent Classification of Silicon Photovoltaic Cell Defects Based ...
The purpose is to improve the detection efficiency of Si-PV cell, to ensure the safety and reliability of Si-PV cell production process, to achieve large number of Si-PV cell defects detection and classification. First, the eddy current thermography system of Si-PV cells is established.
A lightweight network for photovoltaic cell defect detection in …
lightweight high-performance model for automatic defect detection of PV cells in electroluminescence(EL) images based on neural architecture search and knowledge …
Convolutional Neural Network based Efficient Detector for …
In response to this problem, we introduce the Efficient Long-Range Convolutional Network (ELCN) module, designed to enhance defect detection …
GCSC-Detector: A Detector for Photovoltaic Cell Defect Based on …
A Global Channel and Spatial Context Module (GCSC), which includes the channel and the spatial self-attention module, to adaptively capture the global rich context information, and establish the relationship between each channel and to improve the detection ability for small and weak defects. Due to the existence of many small and …
An efficient CNN-based detector for photovoltaic module cells defect detection …
Electroluminescence (EL) imaging provides a high spatial resolution for inspecting photovoltaic (PV) cells, enabling the detection of various types of PV cell defects. Recently, convolutional neural network (CNN) based automatic detection methods for PV cell defects using EL images have attracted much attention. ...
Intelligent Classification of Silicon Photovoltaic Cell Defects Based on Eddy Current Thermography and Convolution Neural Network …
In this article, defects in the production process of silicon photovoltaic (Si-PV) cells are urgently needed to be detected due to their serious impact on the n Intelligent Classification of Silicon Photovoltaic Cell Defects Based on Eddy Current Thermography and
Title: AI-Powered Dynamic Fault Detection and Performance …
AI-Powered Dynamic Fault Detection and Performance Assessment in Photovoltaic Systems. The intermittent nature of photovoltaic (PV) solar energy, driven …
A Hybrid Fuzzy Convolutional Neural Network Based Mechanism for Photovoltaic Cell Defect Detection With Electroluminescence Images
In the intelligent manufacturing process of solar photovoltaic (PV) cells, the automatic defect detection system using the Industrial Internet of Things (IIoT) smart cameras and sensors cooperated in IIoT has become a promising solution. Many works have been devoted to defect detection of PV cells in a data-driven way. However, because of the …
Defect Detection in Photovoltaic Module Cell Using CNN Model
The detection of defects in photovoltaic modules in an intelligent and automatic way especially when working on a large scale is highly recommended for their current. ... K., Saadouni, A., Chekired, F. (2024). Defect Detection in Photovoltaic Module Cell Using CNN Model. In: Hatti, M. (eds) IoT-Enabled Energy Efficiency Assessment of …
A lightweight network for photovoltaic cell defect detection in …
A lightweight network for photovoltaic cell defect detection in electroluminescence images based on neural architecture search and knowledge distillation Jinxia Zhanga,b,, Xinyi Chen a, Haikun Wei, Kanjian Zhang aKey Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation, Southeast University, Nanjing, 210096, …
Intelligent Inspection Method for Photovoltaic Modules Based on …
The economic analysis results demonstrate that the main cost of mc-Si PV modules production in China lies in raw materials and labor and the production of Multi-Si PV cells have the highest cost ...
Deep learning-based automatic detection of multitype …
Automatic defect detection in electroluminescence (EL) images of photovoltaic (PV) modules in production line remains as a …
A Review on Defect Detection of Electroluminescence …
The past two decades have seen an increase in the deployment of photovoltaic installations as nations around the world try to play their part in dampening the impacts of global warming. The …
Electrical Pulsed Infrared Thermography and supervised learning for PV cells defects detection …
Photovoltaic cells with broken gate, hidden crack, scratch and hot spot defects were detected based on pulsed electric infrared thermography method. • Supervised learning, LDA and QDA algorithms, are used to process …
An efficient CNN-based detector for photovoltaic module cells defect detection …
Semantic Scholar extracted view of "An efficient CNN-based detector for photovoltaic module cells defect detection in electroluminescence images" by Qing Liu et al. DOI: 10.1016/j.solener.2023.112245 Corpus …
Defect detection of photovoltaic modules based on improved
This section briefly overviews the detection method of photovoltaic module defects based on deep learning. Deep learning is considered a promising machine learning technique and has been adopted ...
High-efficiency low-power microdefect detection in photovoltaic cells …
Semantic Scholar extracted view of "High-efficiency low-power microdefect detection in photovoltaic cells via a field programmable gate array-accelerated dual-flow network" by Haoxuan Wang et al. DOI: 10.1016/j.apenergy.2022.119203 Corpus ID: 248734800 High ...
Photovoltaic Cell Defect Detection Based on Weakly Supervised …
Recently, convolutional neural networks (CNNs) have proven successful in automating the detection of defective photovoltaic (PV) cells within PV modules. Existing studies have built a CNN based on fully supervised learning, which requires a training dataset consisting of PV cell images annotated according to whether the individual cells are defective. …
PD-DETR: towards efficient parallel hybrid matching with …
In order to detect PV cell defects faster and better, a technology called the PV cell Defects DEtection Transformer (PD-DETR) is proposed. To address the issue of …
Sensors | Free Full-Text | Deep-Learning-Based …
In this paper, we propose a deep-learning-based defect detection method for photovoltaic cells, which addresses two technical challenges: (1) to propose a method for data enhancement and category …
A novel framework on intelligent detection for module defects of …
Solar Photovoltaic (PV) industry has achieved rapid development in recent years. However, it is difficult and costly to detect the micro fault area in a large PV power plant due to environmental factors and missing data. …
Photovoltaic Cell Defect Detection Model based-on Extracted …
A method for classifying between the normal and a defective solar cell was implemented using EL imaging with selected digital image processing techniques through the Support Vector Machine (SVM) classifier. Electroluminescence (EL) imaging is used to analyze the characteristics of solar cells. This technique provides various details about …
A novel framework on intelligent detection for module defects of …
This section presents the framework on intelligent detection for module defects of PV plants combining the visible and infrared images. The framework consists of …
Module defect detection and diagnosis for intelligent maintenance of solar photovoltaic …
I–V was the most common defect detection technique for PV plants and the cell cracks (0.23) and hot-spots (0.18) were the most reported defects [9]. AI and IoT applied in the defect detection are analyzed in Ref. [ 10 ] and an IoT and AI-based smart configuration was suggested.
Intelligent monitoring of photovoltaic panels based on infrared detection …
CNN based automatic detection of photovoltaic cell defects in electroluminescence images Energy, 189 (2019 ... Akram M.W., Li G., Jin Y., et al. Automatic detection of photovoltaic module defects in infrared images with isolated and develop-model transfer, () ...
Energies | Free Full-Text | Anomaly Detection Algorithm for Photovoltaic Cells …
With the proposed goal of "Carbon Neutrality", photovoltaic energy is gradually gaining the leading role in energy transformation. At present, crystalline silicon cells are still the mainstream technology in the photovoltaic industry, but due to the similarity of defect characteristics and the small scale of the defects, automatic defect …
Accurate detection and intelligent classification of solar cells …
Accurate detection and intelligent classification of solar cells defects based on photoluminescence images: ... Korkmaz et al. [16] proposed an effective method for detecting faults in photovoltaic cells. This method involved the design of …
An efficient and portable solar cell defect detection system
The photovoltaic (PV) system industry is continuously developing around the world due to the high energy demand, even though the primary current energy source is fossil fuels, which are a limited source and other sources are very expensive. Solar cell defects are a major reason for PV system efficiency degradation, which causes …
Deep learning based automatic defect identification of photovoltaic ...
The maintenance of large-scale photovoltaic (PV) power plants is considered as an outstanding challenge for years. This paper presented a deep learning-based defect detection of PV modules using electroluminescence images through addressing two technical challenges: (1) providing a large number of high-quality …
GCSC-Detector: A Detector for Photovoltaic Cell ...
Then embed this module into the YOLOv7 model to form our Global Channel and Spatial Context Detector (GCSC-Detector) to improve the detection ability for small and weak defects. The experimental results show that the mAP50 of this method reaches 84.8% on the large-scale photovoltaic EL dataset PVEL-AD and it is superior to …
Deep learning based automatic defect identification of photovoltaic module using electroluminescence images …
The maintenance of large-scale photovoltaic (PV) power plants is considered as an outstanding challenge for years. This paper presented a deep learning-based defect detection of PV modules using electroluminescence images through addressing two technical ...