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

Autor: Joan R. Casas, Fernando J. Tenelema, Rick M. Delgadillo
Přispěvatelé: Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental, Universitat Politècnica de Catalunya. EC - Enginyeria de la Construcció
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
ISSN: 1573-2479
Popis: This is an Accepted Manuscript of an article published by Taylor & Francis Group in Structure and infrastructure engineering on 2021, available online at: http://www.tandfonline.com/10.1080/15732479.2021.1982994. 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.
Databáze: OpenAIRE