Nonlinear and non-stationary detection for measured dynamic signal from bridge structure based on adaptive decomposition and multiscale recurrence analysis

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Abstract

To test the nonlinearity and non-stationarity of measured dynamic signals from a bridge structure with high-level noise and dense modal characteristics, a method that combines the adaptive signal decomposition with the recurrence analysis is proposed to solve the difficulty of testing nonlinearity and non-stationarity of bridge structure signals. A novel white noise assistance and cluster analysis are introduced to the ensemble empirical mode decomposition to alleviate mode-mixing issues and generate single-mode intrinsic mode functions. Combining the hypothesis-testing scheme of nonstationary and nonlinear synchronization and surrogate techniques, a data-driven recurrence quantification analysis method is proposed and a novel recurrence quantification measure pairs are set up. To demonstrate the efficacy of the proposed methodology, complex signals, which are collected from a carefully instrumented model of a cable-stayed bridge, are utilized as the basis for comparing with traditional nonlinear and non-stationary test methods. Results show that the proposed multiscale recurrence method is feasible and effective for applications to a nonlinear and non-stationary test for real complex civil structures.

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Zhang, E., Shan, D., & Li, Q. (2019). Nonlinear and non-stationary detection for measured dynamic signal from bridge structure based on adaptive decomposition and multiscale recurrence analysis. Applied Sciences (Switzerland), 9(7). https://doi.org/10.3390/app9071302

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