Project

Damage identification in composite materials using Machine Learning techniques for Structural health monitoring

Code

01CD8022

Duration

01 March 2023 → 29 February 2024

Funding

Regional and community funding: Special Research Fund

Promotor

Magd Abdel Wahab

Fellow

Muhammad Irfan Shirazi

Research disciplines

Engineering and technology
- Other mechanical and manufacturing engineering not elsewhere classified

Keywords

Structural health monitoring Damage detection Machine Learning Optimization algorithms YUKI algorithm Composites

Project description

Structural health monitoring (SHM) is a key concept in sustainability of large and small scale structures for damage detection and identification. Composites are an important class of materials used for many of these structures. In this regard, Machine learning (ML) has recently gained importance in SHM methodology. This project aims to explore further applications of ML for SHM.