Phase-Based Motion Magnification in outdoor conditions: Robustness and Natural Frequency extraction
| dc.contributor.advisor | Petrunin, Ivan | |
| dc.contributor.advisor | Zanotti Fragonara, Luca | |
| dc.contributor.author | El Sayah, Thierry | |
| dc.date.accessioned | 2025-07-10T12:00:11Z | |
| dc.date.available | 2025-07-10T12:00:11Z | |
| dc.date.freetoread | 2025-07-10 | |
| dc.date.issued | 2021-12 | |
| dc.description | Zanotti Fragonara, Luca - Associate Supervisor | |
| dc.description.abstract | In this study, Phase-Based Motion Magnification is combined with 2D Point Tracking to enhance data extraction under noisy outdoor conditions. The aim is to investigate whether the use of Phase Based Motion Magnification along with 2D PT can increase accuracy of frequencies extracted in robust conditions. The study presents three experiments: a fixed wing on a shaker machine, a light pole and a building. Frequencies are extracted in all three experiments and compared against previous research and finite element analysis. Finally, the study touches on ways to automate the suggested procedure. | |
| dc.description.coursename | MSc by Research in Aerospace | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/24184 | |
| dc.language.iso | en | |
| dc.publisher | Cranfield University | |
| dc.publisher.department | SATM | |
| dc.rights | © Cranfield University, 2021. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder. | |
| dc.subject | 2D Point Tracking | |
| dc.subject | Convolutional Neural Networks | |
| dc.subject | Denoising | |
| dc.subject | Automation | |
| dc.subject | data extraction | |
| dc.subject | frequency accuracy | |
| dc.title | Phase-Based Motion Magnification in outdoor conditions: Robustness and Natural Frequency extraction | |
| dc.type | Thesis | |
| dc.type.qualificationlevel | Doctoral | |
| dc.type.qualificationname | MRes |