Details of the Project
Structural health monitoring (SHM) is vital for ensuring the safety and reliability of engineering structures such as bridges, buildings, wind turbines, aircraft, and civil infrastructure. Shape sensing technologies also have growing importance in robotics, human motion analysis, and surgical instrumentation. Fibre Bragg Grating (FBG) sensors are widely used due to their high resolution, robustness in harsh environments, and ability to be multiplexed into arrays, enabling real-time shape tracking without visual contact.
Despite these advantages, current FBG-based systems face limitations in achieving cost-effective, high-resolution localisation, defect identification, and predictive modelling of defect evolution. Addressing these challenges requires a new generation of sensing approaches.
This project, conducted in collaboration with Airbus, Insensys, and Target3D, aims to develop and validate an AI-driven polarimetric dual optical frequency comb (DOFC) technique for monitoring structural defects in composite laminates used in aerospace and renewable energy industries. By combining advanced photonic sensing with machine learning, the research will deliver:
- Enhanced localisation and classification of defects in composite materials.
- Predictive modelling of defect evolution under operational conditions.
- Cost-effective sensing solutions adaptable to industrial environments.
The outcomes will represent a significant advance in shape sensing technologies and optical frequency comb applications, with strong potential for industrial adoption and societal benefit in sustainable energy and aerospace safety.