An experimental study of the feasibility of phase‐based video magnification for damage detection and localisation in operational deflection shapes

Date

2019-01-08

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Wiley

Department

Type

Article

ISSN

0039-2103

Format

Free to read from

Citation

Civera M, Zanotti Fragonara L, Surace C. (2020) An experimental study of the feasibility of phase‐based video magnification for damage detection and localisation in operational deflection shapes. Strain, Volume 56, Issue 1, February 2020, Article number e12336

Abstract

Optical measurements from high‐speed, high‐definition video recordings can be used to define the full‐field dynamics of a structure. By comparing the dynamic responses resulting from both damaged and undamaged elements, structural health monitoring can be carried out, similarly as with mounted transducers. Unlike the physical sensors, which provide point‐wise measurements and a limited number of output channels, high‐quality video recording allows very spatially dense information. Moreover, video acquisition is a noncontact technique. This guarantees that any anomaly in the dynamic behaviour can be more easily correlated to damage and not to added mass or stiffness due to the installed sensors.

However, in real‐life scenarios, the vibrations due to environmental input are often so small that they are indistinguishable from measurement noise if conventional image‐based techniques are applied. In order to improve the signal‐to‐noise ratio in low‐amplitude measurements, phase‐based motion magnification has been recently proposed.

This study intends to show that model‐based structural health monitoring can be performed on modal data and time histories processed with phase‐based motion magnification, whereas unamplified vibrations would be too small for being successfully exploited. All the experiments were performed on a multidamaged box beam with different damage sizes and angles.

Description

Software Description

Software Language

Github

Keywords

damage detection, experimental modal analysis, motion magnification, structural health monitoring, video processing

DOI

Rights

Attribution-NonCommercial 4.0 International

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