@misc{104a0e346e1344f896de165a0bc0783d,
title = "Structural Damage Detection under Environmental and Operational Variability: An Exploration of Two New Vibration-based Schemes",
abstract = "The objective of structural health monitoring (SHM) is to ascertain if a structure is damaged or not based on measured data. Numerous approaches to detect damage have been put forth, such as those based on physical modelling or data-driven methodologies. The prerequisite for using data-driven methods is that damage is known to alter the dynamic properties, such as, stiffness, mass or energy dissipation of a structure which will directly alter the dynamic response. However, structures are in realistic scenarios subject to environmental and operational variabilities that potentially camouflage damage-induced changes in the dynamic response, hence leading to poor damage detectability. This thesis proposes two new vibration-based schemes which deals with the issues associated with environmental and operational variabilities. The result of this thesis exemplify the importance of considering the variabilities in a damage detection scheme in order to increase the structural reliability. ",
keywords = "structural health monitoring, vibration-based structural health monitoring, damage detection, environmental and operational variability, closed-loop, open-loop, output feedback, cointegration, artificial neural network, pca, eigenstructure assignment, wind turbine blades, accelerometer, vibration, big data",
author = "Qadri, {Bilal Ali}",
note = "Dissertation not published.",
year = "2020",
language = "English",
series = "Ph.d.-serien for Det Ingeni{\o}r- og Naturvidenskabelige Fakultet, Aalborg Universitet",
publisher = "Aalborg Universitetsforlag",
}