Photovoltaic panel defect dataset

What is PV el anomaly detection dataset?

We build a PV EL Anomaly Detection (PVEL-AD 1, 2, 3 ) dataset for polycrystalline solar cell, which contains 36 543 near-infrared images with various internal defects and heterogeneous background. This dataset contains anomaly free images and anomalous images with ten different categories.

Are defective solar cells affecting the power efficiency of solar modules?

The dataset contains 2,624 samples of 300x300 pixels 8-bit grayscale images of functional and defective solar cells with varying degree of degradations extracted from 44 different solar modules. The defects in the annotated images are either of intrinsic or extrinsic type and are known to reduce the power efficiency of solar modules.

How to identify solar panel faults?

The methodology involved in the fault classification and early detection of solar panel faults begins with the selection of the dataset. Two types of image datasets are used in this case, namely the aerial image dataset of solar panels and the electroluminescence image dataset of solar panel cells.

Is this the first public dataset for PV solar cell anomaly detection?

To the best of our knowledge, this is the first public dataset for PV solar cell anomaly detection that provides box-wise ground truth. Furthermore, this dataset can also be used for the evaluation of many computer vision tasks such as few-shot detection, one-class classification, and anomaly generation.

How accurate is the solar panel defect detection algorithm?

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.

How to detect a defect in solar panels?

In order to avoid such accidents, it is a top priority to carry out relevant quality inspection before the solar panels leave the factory. For the defect detection of solar panels, the main traditional methods are divided into artificial physical method and machine vision method.