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. Numerous methods are proposed to deal with defect detection and solar cell inspection.
El-Rashidy et al. proposed a portable solar cell defects detection method based on K-means, MobileNetV2 and linear discriminant algorithms. This method uses feature extraction to describe defective and non-defective to categorize different defects and then identify the defective cells.
T able 4: Studies of detecting the defects of solar cells using hybrid models. models requires more computational resources. precision and robustness. electroluminescence of solar cells is challenging. Many 27 48] to address this problem. In [ 30 ], the authors (BAFPN) for solar defect detection. The BAFPN is an FPN.
We published an automatic computer vision pipeline of identifying solar cell defects. Tools can handle field images with a complex background (e.g., vegetation). Tools can be applied to other kinds of defects with transfer learning. We compared the performance of classification and object detection neural networks.
The proposed method is based on adapted morphological and edge detection algorithms. This method uses multiple uses of morphological and canny edge detection with adapted parameters to extract and highlight the objects on a solar cell.
various solar cell defects. Other image classifier models to detect and classify Si-PV cell faults. Another novel [ 28]. In this work, the short-term features represent denoising auto-encoder (SDAE). In contrast, the CNNs. This work concludes that such a combination of solar cells compared with other methods. and various defects.
In this paper, data analysis methods for solar cell defect detection are categorised into two forms: 1) IBTs, which depend on analysing the deviations of optical …
Similar and indeterminate defect detection of solar cell surface with heterogeneous texture and complex background is a challenge of solar cell manufacturing. …
the performance of multiple PV cells using EL detection method. The outcome of this article proves that micro cracks at least reduces the output power of a PV cells by 2.5%. The …
The defects of solar cell component (SCC) will affect the service life and power generation efficiency. In this paper, the defect images of SCC were taken by the …
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 …
The classification method begins with an image of a single PV cell and classifies the cell into a category (e.g., intact cell, cracked cell, cell with solder disconnection, etc.). We …
In this paper, data analysis methods for solar cell defect detection are categorised into two forms: 1) IBTs, which depend on analysing the deviations of optical …
The research presents an efficient visual inspection method that combines mathematical morphology and edge-based region analysis for accurate detection and …
Another predominantly used method to detection solar cells micro cracks is the Electroluminescence (EL). This method is the form of luminescence in which electrons are …
Solar cells or photovoltaic systems have been extensively used to convert renewable solar energy to generate electricity, and the quality of solar cells is crucial in the …
The appropriate hyperparameters, algorithm optimizers, and loss functions were employed to achieve optimal performance in the seven-class classification 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, …
inspection methods. The physical detection method relies on personal experience and involves more limitations for efficiency and precision, while the visual …
We investigated two strategies of identifying defects: object detection and classification. The object detection method starts with an image of an entire solar module and …
Studies of detecting the defects of solar cells using a deep learning approach. …
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, …
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 …
Considering the diversity and complexity of solar cells surface defects, the classification detection method is proposed for different defects, and the comprehensive …
We investigated two strategies of identifying defects: object detection and classification. The object detection method starts with an image of an entire solar module and …
Abstract: 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 …
Studies of detecting the defects of solar cells using a deep learning approach. …
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 …