Marginal Hilbert spectrum and instantaneous phase difference as total damage indicators in bridges under operational traffic loads

Abstract

The challenges and future trends in the development of signal processing tools are being widely used for damage identification in bridges. Therefore, it is important to analyse the vibration signals in order to attain effective damage characterization. In this paper, the non-linear and non-stationary dynamic response of bridges under operational loads is studied. First, the signals are decomposed into intrinsic mode functions (IMF) by a novel Improved Completed Ensemble EMD with Adaptive Noise technique (ICEEMDAN). Hilbert-Huang transform is used to obtain their corresponding Hilbert spectra. The marginal Hilbert spectrum (MHS) of each IMF and the instantaneous phase difference (IPD) are proposed as total damage indicators (DI), in the sense that they are able to detect, localize and quantify damage under transient vibration due to traffic. The methodology was tested in two case studies: (i) a numerical model of a two-span steel bridge (ii) a dynamic test conducted on a real steel arch bridge subjected to a series of artificial damages. The experimental and real case results from the damage indices based on the extracted features demonstrate the robustness and more sensitivity of the novel Improved Completed Ensemble EMD with Adaptive Noise technique (ICEEMDAN) in addressing the damage location.

Keywords:

• Hilbert-Huang transform
• empirical mode decomposition
• damage identification
• Marginal Hilbert spectrum
• phase difference
• transient vibration
• traffic loads

Acknowledgements

The first author acknowledges the financial support received from Peruvian Ministry of Education with the Bicentennial Generation Scholarship (PRONABEC program) for the great support on his PhD studies. The authors wish to express their sincere gratitude to Prof. Eleni Chatzi, ETH Zurich, for providing the detailed numerical bridge data. The authors also thank the Prof. Chul-Woo Kim, Kyoto University, for having granted access to the experimental datasets of the steel arch bridge.

Disclosure statement

No potential conflict of interest was reported by the author(s).