Real-time identification of foundation damage in high-Pile Wharves: Nonlinear feature change point analysis in dynamic characteristics under wave excitation

Abstract

Waves are a common excitation form for wharves. The responses of pile foundation in high-pile wharves under such excitation exhibit pronounced nonlinear and non-stationary characteristics, compromising the robustness of damage detection methods. To address this challenge, this paper first introduces a method using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and spectral feature analysis, aimed at extracting the overall characteristic sub-signals to resolve multi-type signal aliasing. Secondly, the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is employed to isolate the nonlinear dynamic features of the response under wave excitation. Thirdly, the Weighted Residual Cumulative Sum (WRCUSUM) method is developed to monitor changes in response characteristics online, thereby enabling the identification of damage occurrence and its timing. Further, the efficacy of the proposed method has been validated through high-pile wharf experiments conducted at various damage levels. This approach not only offers a novel solution for online damage detection under wave excitation but also introduces a new strategy for non-destructive testing across offshore engineering applications.