A platform for research: civil engineering, architecture and urbanism
Damage localization in offshore structures using shaped inputs
Input shaping is an active control procedure by which vibrations in a structural subdomain are suppressed. Recently, a scheme based on shaped inputs has been proposed for damage localization purposes; cast on the premise that the vibration signature of a structural domain in a damaged phase will be identical to the signature of the healthy, reference counterpart if, for the same loading conditions, the subdomain containing damage is inactive in terms of vibrations. The methodological idea is, thus, to apply controllable inputs that are shaped such that particular vibration quantities (depending on the type of damage one seeks to localize) are suppressed in one subdomain at the time, hereby resulting in damage being localized when the vibration signature induced by the shaped inputs in the damaged phase corresponds to that obtained in the reference phase. The present paper treats an application study that illustrates the damage localization scheme in simulations on a finite element (FE) model of an offshore jacket structure exposed to stochastic plane wave fields generated from a directional wave spectrum, and with fluid-structure interaction considered in terms of the Morison equation. In both structural phases, that is, the reference and the damaged one with a single mass perturbation, four inputs to be shaped are applied, and the resulting displacements are extracted from a single spatial location within the model. It is contended that the damage can be localized when suppressing displacements near or, ideally, directly at its location.
Damage localization in offshore structures using shaped inputs
Input shaping is an active control procedure by which vibrations in a structural subdomain are suppressed. Recently, a scheme based on shaped inputs has been proposed for damage localization purposes; cast on the premise that the vibration signature of a structural domain in a damaged phase will be identical to the signature of the healthy, reference counterpart if, for the same loading conditions, the subdomain containing damage is inactive in terms of vibrations. The methodological idea is, thus, to apply controllable inputs that are shaped such that particular vibration quantities (depending on the type of damage one seeks to localize) are suppressed in one subdomain at the time, hereby resulting in damage being localized when the vibration signature induced by the shaped inputs in the damaged phase corresponds to that obtained in the reference phase. The present paper treats an application study that illustrates the damage localization scheme in simulations on a finite element (FE) model of an offshore jacket structure exposed to stochastic plane wave fields generated from a directional wave spectrum, and with fluid-structure interaction considered in terms of the Morison equation. In both structural phases, that is, the reference and the damaged one with a single mass perturbation, four inputs to be shaped are applied, and the resulting displacements are extracted from a single spatial location within the model. It is contended that the damage can be localized when suppressing displacements near or, ideally, directly at its location.
Damage localization in offshore structures using shaped inputs
Ulriksen, Martin Dalgaard (author) / Bernal, Dionisio (author) / Nielsen, Morten Eggert (author) / Damkilde, Lars (author)
2017-01-01
Ulriksen , M D , Bernal , D , Nielsen , M E & Damkilde , L 2017 , ' Damage localization in offshore structures using shaped inputs ' , Procedia Engineering , vol. 199 , 646 , pp. 2282-2287 . https://doi.org/10.1016/j.proeng.2017.09.273
Article (Journal)
Electronic Resource
English
Damage Localization in Systems with Unknown Inputs
British Library Online Contents | 2007
|Damage Assessment of Offshore Structures
British Library Conference Proceedings | 1995
|Damage Types in Offshore Structures
Wiley | 2021
|Damage detection in offshore structures using neural networks
British Library Online Contents | 2010
|Damage detection in offshore structures using neural networks
Online Contents | 2010
|