Another significant aspect of this study is that the Efficientb0 model has been trained from scratch using infrared solar module images. The purpose of this approach is to optimize the model’s ability to detect faults in photovoltaic panels.
The results obtained indicate that the proposed method has significant potential for detecting faults in photovoltaic panels. Training the model from scratch has allowed for better processing of infrared images and more precise detection of faults in the panels.
In this study, the use of an artificial intelligence model is proposed to detect faults in photovoltaic panels. The study was conducted on a dataset consisting of images obtained from infrared solar modules, and the proposed model relies on deep learning techniques, with the Efficientb0 model as its primary foundation.
These results indicate average values of 93.93% accuracy, 89.82% F1-score, 91.50% precision, and 88.28% sensitivity, respectively. The proposed method in this study accurately classifies photovoltaic panel defects based on images of infrared solar modules. 1. Introduction
The results of comparative experiments on the solar panel defect detection data set show that after the improvement of the algorithm, the overall precision is increased by 1.5%, the recall rate is increased by 2.4%, and the mAP is up to 95.5%, which is 2.5% higher than that before the improvement.
Even though EL inspection needs some time and experienced specialists, it has become the main method for defect detection of PV cells due to its excellent performance. In this paper, an automatic method is proposed for solving the limits.
A review of automated solar photovoltaic defect detection …
Camera enhanced compressive light beam induced current sensing for efficient defect detection in photovoltaic cells Sol. Energy, 183 ( 2019 ), pp. 212 - 217, 10.1016/j.solener.2019.02.055 View PDF View article View in Scopus Google Scholar
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Photovoltaic Panel Intelligent Detection Method Based on …
Therefore, this paper proposes an intelligent detection method for photovoltaic power panels based on the improved Faster-RCNN target detection algorithm to analyze and identify images …
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A deep learning based approach for detecting panels in photovoltaic …
Liu L Wang D Li J Wang S (2023) An Efficient Hot Spot Detection Method with Small Sample Learning for Photovoltaic Panels 2023 6th International Conference on Artificial Intelligence and Big Data (ICAIBD) 10.1109/ICAIBD57115.2023.10206126 (673-678) Online publication date: 26-May-2023
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Deep learning based automatic defect identification of photovoltaic ...
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 Electroluminescence (EL) image generation method for the limit of EL image samples; and (2) an efficient model for automatic defect classification ...
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A deep learning based approach for detecting panels in …
In this paper, we address the problem of PV Panel Detection using a Convolutional Neural Network framework called YOLO. We demonstrate that it is able to …
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Solar panel defect detection design based on YOLO v5 algorithm
Defects of solar panels can easily cause electrical accidents. The YOLO v5 algorithm is improved to make up for the low detection efficiency of the traditional defect …
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Enhanced Fault Detection in Photovoltaic Panels Using CNN …
This paper presents an innovative explainable AI model for detecting anomalies in solar photovoltaic panels using an enhanced convolutional neural network (CNN) and the VGG16 architecture. The model effectively identifies physical and electrical changes, such as dust and bird droppings, and is implemented using the PyQt5 Python tool to create a ...
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Deep learning based automatic defect identification of …
This paper presented a deep learning-based defect detection of PV modules using electroluminescence images through addressing two technical challenges: (1) providing …
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Fault Detection in Solar Energy Systems: A Deep Learning …
This study aims to develop methods for detecting faults in photovoltaic panels using infrared solar module images. To achieve this goal, the "Efficientb0" model, a pre-trained deep learning network, has been preferred. The use of a pre-trained model has facilitated faster and more effective learning of the data. Another significant aspect ...
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TransPV: Refining photovoltaic panel detection accuracy …
The use of generative AI techniques will be explored to generate synthetic data, thereby enhancing the representation of various PV panel types. Additionally, we will leverage transfer learning to improve the model''s generalization capability, enabling it to be applied to the detection of different PV panel types. Moreover, we will investigate ...
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TransPV: Refining photovoltaic panel detection accuracy through a ...
The use of generative AI techniques will be explored to generate synthetic data, thereby enhancing the representation of various PV panel types. Additionally, we will leverage …
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A Photovoltaic Panel Defect Detection Method Based on the …
Aiming at the current PV panel defect detection methods with insufficient accuracy, few defect categories, and the problem that defect targets cannot be localized, this paper proposes a PV panel defect detection model based on the YOLOv7 algorithm.
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A Photovoltaic Panel Defect Detection Method Based on the …
Aiming at the current PV panel defect detection methods with insufficient accuracy, few defect categories, and the problem that defect targets cannot be localized, this paper proposes a PV …
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Fault Detection in Solar Energy Systems: A Deep Learning …
This study aims to develop methods for detecting faults in photovoltaic panels using infrared solar module images. To achieve this goal, the "Efficientb0" model, a pre-trained …
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Enhanced Fault Detection in Photovoltaic Panels Using CNN …
This paper presents an innovative explainable AI model for detecting anomalies in solar photovoltaic panels using an enhanced convolutional neural network (CNN) …
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Methodology for automatic fault detection in photovoltaic …
1. Introduction. Automatic fault detection in photovoltaic (PV) systems has acquired great relevance worldwide, as expressed by (Pierdicca et al., Citation 2018), (Rao et al., Citation 2019), and (Lu et al., Citation 2019).This is due to the necessity of keeping this type of system functioning properly for as long as possible.
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Research on detection method of photovoltaic cell surface dirt …
In view of the reduced power generation efficiency caused by ash or dirt on the surface of photovoltaic panels, and the problems of heavy workload and low efficiency faced by manual detection ...
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Improving Solar Panel Efficiency: A CNN-Based System for Dust Detection …
Our model achieved an 85% recognition rate for dust detection, which could significantly improve solar panel efficiency. By automating the detection and cleaning process, we can maximize electricity generation and make solar power a viable option for sustainable energy production. Download conference paper PDF. Similar content being viewed by others. A Dual …
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Enhancing Solar Plant Efficiency: A Review of Vision-Based ...
This work aims to review vision-based monitoring techniques for the fault detection of photovoltaic (PV) plants, i.e., solar panels. Practical implications of such systems include timely fault identification based on data-driven insights and problem resolution, resulting in enhanced energy outputs, extended lifetime spans for PV panels, cost ...
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Photovoltaic Panel Fault Detection and Diagnosis Based on a …
The number of photovoltaic power plants is increasing rapidly and consequently their stability, efficiency and safety have become more important. In view, it is necessary to regularly detect, diagnose and maintain photovoltaic modules in a timely manner. In this work, a new image classification network based on the MPViT network structure is designed to solve …
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Photovoltaic Panel Intelligent Detection Method Based on …
Therefore, this paper proposes an intelligent detection method for photovoltaic power panels based on the improved Faster-RCNN target detection algorithm to analyze and identify images taken during UAV inspection. First, photovoltaic module images are collected by UAV equipped with infrared thermal imaging cameras. Next, the collected PV module ...
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Solar panel defect detection design based on YOLO v5 algorithm
Defects of solar panels can easily cause electrical accidents. The YOLO v5 algorithm is improved to make up for the low detection efficiency of the traditional defect detection methods. Firstly, it is improved on the basis of coordinate attention to obtain a LCA attention mechanism with a larger target range, which can enhance the sensing range ...
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Detection Method of Photovoltaic Panel Defect Based on …
accuracy, this paper improves it and explores an efficient panel defect detection method. The main contributions of the research work are summarized as follows: (1) Atrous convolution and attention mechanism are introduced to improve the precision and recall rate of the model. (2) The proposed model is superior to the existing network models in infrared image defect detection …
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Enhanced Fault Detection in Photovoltaic Panels Using CNN …
Overall, it enhances power generation efficiency and prolongs the lifespan of photovoltaic systems, while minimizing environmental risks. Evolution of installed solar capacity from 2004 to 2023 [4 ...
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Fault detection and diagnosis in photovoltaic panels …
Photovoltaic solar panels require high initial investments, and it is necessary to use advanced and efficient methods that lead to the maintainability and reliability of these systems, extending their life cycle and …
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