Assessment of a multiple model based parametric method for output-only vibration-based damage detection for a population of like structures

Abstract

This study focuses on the problem of vibration-based damage detection for a population of like structures. Although nominally identical, like structures exhibit variability in their characteristics due to variability in the materials and manufacturing. This inevitably leads to variability in the dynamics, which may be so significant as to mask deviations due to damage. Damage detection via conventional vibration-based methods, using a common threshold in the decision making mechanism thus becomes highly challenging. The study presents a detailed assessment of a recently introduced Multiple Model (MM) based AutoRegressive (AR) model parameter method aiming at addressing this problem. The assessment is based on high numbers of experimental test/inspection cases using composite beams damaged via impact, as well as comparisons with the corresponding conventional (single model based) method. The results confirm significant improvement over the method's conventional counterpart. A sensitivity analysis additionally indicates that the method is relatively insensitive to the model order, but sensitive to the specific beams selected as baseline (training) ones; in fact their selection may lead to excellent results.