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

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.

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

Disciplines:Other mechanical and manufacturing engineering not elsewhere classified