Non-linear feature identifications based on self-sensing impedance measurements for structural health assessment

This paper presents the application of a non-linear feature identification technique for structural damage detection. This method is coupled with the impedance-based structural health monitoring (SHM) method, which utilises electromechanical coupling properties of piezoelectric materials. The non-linear feature examined in this study is in the form of autoregressive coefficients in the frequency domain autoregressive model with exogenous (ARX) inputs, which explicitly considers non-linear system input/output relationships. The applicability of this non-linear feature for damage identification is investigated in various frequency ranges using impedance signals measured from a laboratory-test structure. The performance of the non-linear feature is also compared with those of linear features typically used in impedance methods. This paper reinforces the utility of non-linear features in SHM and suggests that their sensitivity in different frequency ranges may be leveraged for certain applications. Published by Elsevier Ltd.