Machine learning algorithm for Structural Health Monitoring application
Lead Research Organisation:
Imperial College London
Department Name: Aeronautics
Abstract
TBC
Organisations
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R513052/1 | 01/10/2018 | 30/09/2023 | |||
| 2374790 | Studentship | EP/R513052/1 | 01/10/2018 | 31/03/2022 | Amin Salehzadeh Nobari |
| Description | The award has been split to two main sections: 1. Impact Classification (IC) 2. Damage Classification (DC) For IC, the objectives set (as consulted with the corresponding supervisor) has been completed and a paper corresponding to the findings were published to the sensors journal at MDPI publications. The achievements can be summarized as follows: A Machine Learning (ML) Algorithm was able to be trained to distinguish between different types of impacts on a composite plate, along with the impacts Energy (severity) and location.These findings and the ML algorithm can be further tested on larger composite structures and be further refined. For DC, the research is still ongoing and the objectives have been partially met as of now. |
| Exploitation Route | For IC, the findings can be used in the future on larger composite structures such as aircraft wing panels. For real life usage, it can speed up impact detection on aircraft and reduce costs and errors, and hence DC. |
| Sectors | Aerospace, Defence and Marine |