PV_EL_HDR_BW_Test_DB

This dataset contains high-resolution (500 DPI) images and experimental measurements of photovoltaic cells power output degradation under 84 progressively induced different damage conditions. Each damage condition is described by a 3-images-set (Near-IR Electroluminescence, Near-IR Black/White, Visible HDR for a total of 252 images); for each damage level are also reported the corresponding performance measurements under controlled conditions and a detailed verbal description, encompassing both categorical and qualitative aspects. This dataset is intended for research on degradation modeling and lifetime prediction, fault detection and diagnosis, damage–performance relationship analysis with machine learning and computer vision applications as well as an LLM-RAG approach. Further images and measures are intended to be added in future versions.

The dataset includes:
- 84 Experimental 3-image-sets (total 252 images; each images-set is composed by 3 images: HDR, EL, BW) (PNG format)
- Image files data (CSV)
- Electrical performance measurements (voltage, current, power output) and verbal description of damage as identified through visual inspection (CSV)
- Metadata describing cell type, naming conventions, experimental parameters (TXT)
## Usage Notes: The dataset is provided **as-is**. Users are responsible for validating and interpreting the data.
## Licensing and Attribution: This dataset is licensed under the **Creative Commons Attribution 4.0 International (CC BY 4.0)** license.
## Possible PV_EL_HDR_BW_Test_DB Dataset Applications
This dataset, comprising damaged solar cell images alongside corresponding power output recordings can support a wide range of research activities across engineering, materials science, and data science. Key possible research uses include: Degradation modeling and lifetime prediction; Fault detection and diagnosis; Damage–performance relationship analysis; Machine learning and computer vision applications, also with LLM-RAG approach; Reliability and robustness assessment; Maintenance and mitigation strategy evaluation;Simulation and model validation; Energy yield and economic impact studies; Synthetic data generation.
Overall, this dataset is valuable for both fundamental research on degradation mechanisms and applied research aimed at improving monitoring, reliability, and cost-effectiveness of photovoltaic systems.