Export of defective photovoltaic modules

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 accurate is automatic defect detection in PV modules?

State-of-the-art framework is proposed for automatic defect detection in PV modules. Infrared images dataset of normal operating and defective PV modules is collected. Isolated and develop-model transfer deep learning frameworks are proposed. Isolated & transfer learned methods give 98.67% and 99.23% accuracy respectively.

What are the defects present in defective module images?

The defects present in defective module images are of types: failed cell interconnection, cell cracking, failed/resistive soldering bonds, etc. Few of the samples from the infrared images dataset are shown in Fig. 1. 4.2. Performance evaluation First we reported accuracy results of our models with cross validation approach.

Can El images detect defects on PV modules?

EL images provide high spatial resolution, which makes it possible to detect even finest defects on the surface of PV modules. However, the analysis of EL images is typically a manual process that is expensive, time-consuming, and requires expert knowledge of many different types of defects.

Can infrared images be used to identify defects in PV modules?

Isolated deep learning and develop-model transfer deep learning techniques are applied and compared. In addition, we also discuss the types of defects detectable in infrared images of PV modules, that can help in manual labelling for identifying different defect types upon access to new large data in future studies.

What is CNN-based identification of defective solar cells in electroluminescence imagery?

CNN-based identification of defective solar cells in electroluminescence imagery. The life span is an important aspect of photovoltaic (PV) modules. Electroluminescence (EL) imaging is an established technique for the visual inspection of PV modules. It enables identification of defects in solar cells that may impede the life span of the module.