Adaptive filter feature identification for structural health monitoring in an aeronautical panel

Abstract

This article presents an approach to structural health monitoring (SHM) using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage of using a RLS filter is the clear possibility to perform an online SHM procedure because the identification is also valid for nonstationary linear systems. An online damage-sensitive index feature is computed based on portions of the autoregressive coefficients normalized by the square root of the sum of the squares. The proposed method is then used in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. To test this hypothesis, the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize damages in the structure. The article concludes by exploring the applicability and drawbacks of the method and proposes some implementation suggestions.