On Random Vibration Based Robust Damage Detection for a Population of Composite Aerostructures Under Variable and Non-measurable Excitation

Abstract

AbstractThe problem of random vibration response based robust and unsupervised damage detection for a population of composite aerostructures is addressed. The focus is on the achievement of robustness which is of paramount importance as manufacturing variability within the population and flight condition variability are practically inevitable. Two robust damage detection methods are postulated based on Multiple-Input Single-Output (MISO) Transmittance Function (TF) stochastic AutoRegressive with eXogenous pseudo-eXcitation (ARX) type representations for eliminating the effects of non-measurable excitation. Robustness to manufacturing variability is achieved via Multiple Model (MM) representations (the MM-TF-ARX method) or Principal Component Analysis (the PCA-TF-ARX method). The achievable detection performance is assessed via Monte Carlo ANSYS-based simulations with a population of 120 composite beams subject to manufacturing thickness variability, two distinct turbulence-like excitation profiles, and three early-stage crack damage scenarios. The results, in terms of Receiver Operating Characteristics curves, indicate excellent damage detection performance for the MM-TF-ARX method, yet inferior for its PCA-TF-ARX counterpart.KeywordsPopulation based SHMComposite structuresRobust damage detectionVibration-based SHMStatistical time series methods