Looking to list your PhD opportunities? Log in here.
About the Project
Recent advancements and cost reductions in unmanned aerial vehicle (UAV)technology have led to the adoption of UAVs equipped with thermal cameras to inspect solar photovoltaic (PV) installations. However, recent techniques such as electroluminescence (EL) imaging offer a higher level of image detail and qualitative insight than conventional IR thermography imaging; hence, this project aims to utilize a fast and accurate drone-based thermal and EL inspection applied to PV installations. Therefore, the ultimate objective is to correlate the thermal and EL images and discover the PV faults and defects, such as cracks, hotspots, potential induced degradation (PID), and failure in bypass diodes.
Entry requirements:
Candidates should have (or expect to obtain) a minimum of a UK upper second class honours degree (2.1) or equivalent in Electronic and Electrical Engineering, Physics, Computer Science, Mathematics or a closely related subject.
How to apply:
Applicants should apply via the University’s online application system at https://www.york.ac.uk/study/postgraduate-research/apply/. Please read the application guidance first so that you understand the various steps in the application process.
Funding Notes
Email Now
Why not add a message here
The information you submit to University of York will only be used by them or their data partners to deal with your enquiry, according to their privacy notice. For more information on how we use and store your data, please read our privacy statement.

Search suggestions
Based on your current searches we recommend the following search filters.
Check out our other PhDs in York, United Kingdom
Check out our other PhDs in United Kingdom
Start a New search with our database of over 4,000 PhDs

PhD suggestions
Based on your current search criteria we thought you might be interested in these.
Oral delivery of insulin for diabetes therapy: Development and evaluation of insulin loaded polymer/lipid based carrier systems
Kingston University
Development of novel macrophage high-throughput cell-based phenotypic assay for drug screening
Anglia Ruskin University ARU
Deep-learning for semantic-based information extraction from natural language
Anglia Ruskin University ARU