Random-vibration-based damage detection and precise localization on a lab–scale aircraft stabilizer structure via the Generalized Functional Model Based Method

Abstract

The problem of random-vibration-based damage diagnosis, including detection and localization, for a lab–scale aircraft stabilizer structure is addressed. Diagnosis is based on the recently introduced Generalized Functional Model Based Method, which utilizes a simple data-based model – instead of large-scale finite element type models – in the inspection phase and is capable of estimating the damage coordinates and their uncertainty region. The focus of the work is on assessing the achievable detection performance and localization accuracy under constraints on the number of deployed sensors and the excitation bandwidth, both reflecting practical limitations relating to potential in-flight implementation. The damage scenarios simulate local stiffness reduction via the addition of a small mass at any point on the structure. While the method has been recently employed with structures consisting of one-dimensional elements, it is presently and for the first time challenged with the considerably more complex problem of damage localization on a two-dimensional structural element. The method’s details, including the transformation of functional boundary constraints into simple ones within the context of the associated optimization problem, are illustrated. The results obtained with a large number of experiments, using only two vibration sensors and limited, low-frequency signal bandwidth, demonstrate excellent damage detection and remarkably accurate localization, thus indicating the method’s high potential for effective damage diagnosis.