Drone-Assisted Vision for Advanced Offshore Wind Turbine Maintenance

Combining drone technology with intelligent computer vision for smart wind farm monitoring
Offshore renewable energy wind turbines

Drone-Assisted Vision for Advanced Offshore Wind Turbine Maintenance

Combining drone technology with intelligent computer vision for smart wind farm monitoring
Title: Drone-Assisted Vision for Advanced Offshore Wind Turbine Maintenance 
Funded by: PhD Studentship, EPSRC University Doctoral Landscape Award (UDLA) 
Dates: 2025-2029 
 
Drone-Assisted Vision for Advanced Offshore Wind Turbine Maintenance aims to develop an intelligent inspection and monitoring framework that combines unmanned aerial vehicles (UAVs), computer vision, and artificial intelligence to improve offshore wind turbine maintenance. Using drones equipped with high-resolution imaging sensors, the project aims to automate inspection, enabling rapid detection and assessment of structural defects, surface damage, and operational anomalies. The approach offers a safer, more efficient, and cost-effective alternative to traditional manual inspection methods while supporting the long-term reliability of offshore renewable energy assets. 
 

Project objectives

The project aims to develop advanced drone-based vision systems capable of autonomously inspecting offshore wind turbine components, including blades, towers, nacelles, and support structures. 
Key objectives include improving the accuracy and speed of defect detection, reducing inspection costs and downtime, enhancing worker safety by minimising hazardous manual inspections, and enabling predictive maintenance through continuous condition monitoring. 
The project also seeks to integrate artificial intelligence and computer vision algorithms to automatically identify issues such as cracks, erosion, corrosion, coating degradation, and structural damage, supporting data-driven maintenance decisions. 

By combining drone technology with intelligent computer vision, this project aims to transform offshore wind turbine maintenance from reactive inspections to proactive, data-driven asset management.

Dena BazazianDr Dena Bazazian
Lecturer in Robotics and Machine Vision

 
Offshore wind farms are becoming a critical component of global renewable energy infrastructure. However, maintaining offshore wind turbines presents significant operational challenges due to their remote locations, harsh environmental conditions, and large structural dimensions. 
Traditional inspection methods often require technicians to access turbines using vessels, cranes, rope-access techniques, or elevated platforms, resulting in high operational costs, extended downtime, and potential safety risks. Furthermore, the increasing scale and number of offshore wind installations have created a growing demand for faster and more reliable inspection methods capable of identifying defects before they develop into major failures. 
This project addresses these challenges by leveraging drones equipped with advanced imaging systems and AI-powered computer vision algorithms to automate turbine inspections. High-resolution visual data collected by drones can be analysed in real time or offline to detect signs of structural deterioration, blade damage, corrosion, and other defects that may impact turbine performance. 
The use of autonomous or semi-autonomous drone operations significantly reduces the need for manual inspections, improves safety, and enables more frequent monitoring of critical assets. By providing accurate and timely condition assessments, the system supports predictive maintenance strategies, reduces operational costs, minimizes turbine downtime, and contributes to the efficient and sustainable operation of offshore wind energy infrastructure. 

Centre for Decarbonisation and Offshore Renewable Energy 

In response to climate change imperatives, we are bringing together a critical mass of leading research and expertise from across the University of Plymouth. Through co-creation and collaboration with partners from business, government and key communities from across the globe, the Centre aims to be a beacon for the University’s whole-system transdisciplinary approach to solutions-oriented research, accelerating sustainable developments in decarbonisation and renewable energy.
Centre for Decarbonisation and Offshore Renewable Energy