Papers by Author: Spilios D. Fassois

Abstract: The number of vibration response sensors required for structural damage detection andprecise localization on a continuous structural topology is investigated. For damage detection thestate–of–the–art of vibration based methods need a required number of sensors q that may be “low”compared to the number of structural modes m, that is q << m. Yet, the opposite is generally suggestedfor precise damage localization, that is q > m. In this study the hypothesis that a “low” numberof vibration response sensors, q << m, may, under certain conditions, suffice for precise damage localization,is postulated. This hypothesis is “proven” experimentally by demonstrating that preciselocalization is indeed possible using a single vibration response sensor and an advanced StructuralHealth Monitoring methodology on a laboratory 3D truss structure.

Abstract: The identification of the operational Wind Turbine (WT) dynamics is a challenging problem, due to both the complex dynamics and the non-stationarity of the vibration response. In this study the novel class of Generalized Stochastic Constraint (GSC) Time-dependent ARMA models is used for the identification of the non-stationary characteristics of acceleration vibration signals acquired in the tower top of an operating WT, in the fore-aft and lateral directions. The results demonstrate the improved performance of GSC-TARMA models compared to their conventional Smoothness Priors (SP) and Functional Series (FS) counterparts. The obtained models confirm the presence of cyclo-stationary and broader non-stationary behavior in WT vibration. The model based frozen time-varying modes of vibration are analyzed, and the modal components of the vibration accelerations are pictorially presented on the plane defined by the fore-aft and lateral axes.

Abstract: Statistical damage detection in a structure operating under different temperatures via vibration testing is addressed by means of a stochastic global model based approach. The approach relies upon novel global models of the Functionally Pooled (FP) form, which are capable of describing the dynamics under any temperature, and statistical decision making. In its present form the approach utilizes response (output–only) vibration data, although excitation–response data may be also used. Its effectiveness is confirmed via a large number of experiments performed on a smart composite beam under different temperatures within the [¡20; +20]oC range.

Abstract: This study aims at identifying the modal characteristics and their uncertainties for a smart composite beam. The problem is addressed via Vector AutoRegressive with eXogenous excitation (VARX) models. The advantages of VARX modeling include simplicity of implementation, high accuracy, parsimony of representation, and capability of handling modal uncertainties. Two different approaches to assess the modal parameter uncertainties are investigated. The first is based upon linearizing the function that relates the VARX model parameters with the modal parameters, whereas the second is based upon computer simulations using the Monte Carlo and the bootstrap schemes. The results indicate that VARX modeling captures the system dynamics and provides accurate modal parameters with tight confidence intervals.

Abstract: This work aims at the precise assessment of a recently introduced method that, in addition to damage detection, allows for complete and accurate damage identification (localization) and magnitude estimation. The method is based on Vector–dependent Functionally Pooled (VFP) models and is capable of offering an effective and precise solution in a unified framework. The effectiveness of the method is experimentally assessed via its application to a prototype GARTEURtype laboratory scale aircraft structure.