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This paper takes PV defect detection as the center of the discussion. First of all, the common photovoltaic defect detection methods are analyzed and discussed, and then further control …
Object detection algorithms [27] have focused on accuracy and speed to avoid problems, such as high false detection rates and difficult deployment. Therefore, the objective …
Experimental tests show that the detection accuracy reaches 92.0%, which is far superior to similar detection networks. Conferences > 2023 3rd International Confer... The article proposes a high-precision algorithm for detecting defects in photovoltaic panels, which can detect and classify damaged areas in the images.
Machine vision-based approaches have become an important direction in the field of defect detection. Many researchers have proposed different algorithms 11, 15, 16 for photovoltaic panel defect detection by creating their own datasets.
The photovoltaic DC detection method utilizes the characteristics of arc light, ... It is evident that even when the false positive rate (FPR) is equal to 0, the model true positive …
The shortage of fossil fuels and environmental pollution have promoted the rise of renewable power generation. The solar energy is one of the famous renewable resources. The defect …
Based on the intrinsic connection between the surface magnetic field and the internal current of PV panels, this article proposes a current distribution reconstruction and busbar current …
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 …
Solar photovoltaic (PV) systems are becoming increasingly popular because they offer a sustainable and cost-effective solution for generating electricity. PV panels are the …
For effective fault detection methods, modelling the PV system mathematically plays an important key on the accuracy of the classification technique. This is because it has a …
As the defects present on the PV panels can lead to the change in both the power generation efficiency and the heat flow of the panel, the available PV panel condition …
The proposed model has been validated on two big PV plants in the south of Italy with an outstanding [email protected] exceeding 98% for panel detection, a remarkable [email …
This paper presents an innovative approach to detect solar panel defects early, leveraging distinct datasets comprising aerial and electroluminescence (EL) images. The …
We employ the Polarized Self Attention (PSA) mechanism to address feature fusion conflicts across various levels within the deep learning model, thereby enhancing …
The article proposes a high-precision algorithm for detecting defects in photovoltaic panels, which can detect and classify damaged areas in the images. The algorithm uses a parallel cross …
Photovoltaic (PV) cell defect detection has become a prominent problem in the development of the PV industry; however, the entire industry lacks effective technical means. …
The performance of a photovoltaic panel is affected by its orientation and angular inclination with the horizontal plane. This occurs because these two parameters alter the amount of solar energy ...
These simulations were conducted using the Cali-Thermal Solar Panels and Solar Panel Infrared Image Datasets, with evaluation metrics such as the Jaccard Index, Dice …
The VarifocalNet is an anchor-free detection method and has higher detection accuracy 5. To further improve both the detection accuracy and speed for detecting photovoltaic module defects, a detection method of photovoltaic module defects in EL images with faster detection speed and higher accuracy is proposed based on VarifocalNet.
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 …
An improved regression loss function is proposed to improve the accuracy of detecting defects in photovoltaic modules. The new loss function is based on the position information of the...
These methods utilize computer vision, image processing, and data analysis techniques to enable the detection and classification of PV panel defects in an efficient and accurate manner at the same time.
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