Modal identification and damage detection in structures using non-linear and non-stationary vibration response. Roy, T. B., Banerji, S., Panigrahi, S. K., Chourasia, A., Tirca, L., & Bagchi, A. Journal of Structural Engineering (India), 44(3):220 - 227, 2017. Damage index;Empirical Mode Decomposition;Frequency domain decomposition;Hilbert spectrum;Intrinsic Mode functions;Structural health monitoring (SHM);abstract bibtex Vibration based method for Structural Health Monitoring (SHM) utilizes the dynamic response of a structure measured using a set of sensors to identify the modal properties and potential damage in the structure. Signal processing tools are widely used for analyzing these response signals. Change in the dynamic characteristics of a structure can provide an indication of damage. However, a direct comparison of the vibration signals at different periods of time may not be sufficient to identify the modal properties and the damages. Therefore, it is important to analyze the vibration signals to extract the modal properties and the morphologies of the changes in these response-signals and correlate them with the types, location and magnitude of structural damage. This present article presents a set of novel techniques for system identification and damage detection in structures based on their vibration signals. The modal parameters are estimated using Frequency Domain Decomposition (FDD) and the response signals are decomposed into intrinsic mode functions (IMF) using empirical mode decomposition (EMD) technique. Those IMFs are then processed with Hilbert-Huang transform (HHT) to obtain their corresponding Hilbert spectra, which allows the estimation of the time-varying instantaneous properties of those response signals. Then a marginal Hilbert spectrum (MHS)-based technique has been applied on the Hilbert spectrum coefficients to calculate associated Damage Indices (DI). The proposed method was tested using experimental tests conducted on a cantilever steel beam prototype at the CBRI laboratory, Roorkee, India, and a three-storey steel frame at Concordia University, Canada. Modal parameters were identified from system identification and the damage locations were determined by comparing the DIs of the damaged steel beam and frame with that of the corresponding baseline (undamaged) structures.
@article{20174304310657 ,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2023 Elsevier Inc.},
copyright = {Compendex},
title = {Modal identification and damage detection in structures using non-linear and non-stationary vibration response},
journal = {Journal of Structural Engineering (India)},
author = {Roy, Timir Baran and Banerji, Srishti and Panigrahi, Soraj Kumar and Chourasia, Ajay and Tirca, Lucia and Bagchi, Ashutosh},
volume = {44},
number = {3},
year = {2017},
pages = {220 - 227},
issn = {09700137},
abstract = {Vibration based method for Structural Health Monitoring (SHM) utilizes the dynamic response of a structure measured using a set of sensors to identify the modal properties and potential damage in the structure. Signal processing tools are widely used for analyzing these response signals. Change in the dynamic characteristics of a structure can provide an indication of damage. However, a direct comparison of the vibration signals at different periods of time may not be sufficient to identify the modal properties and the damages. Therefore, it is important to analyze the vibration signals to extract the modal properties and the morphologies of the changes in these response-signals and correlate them with the types, location and magnitude of structural damage. This present article presents a set of novel techniques for system identification and damage detection in structures based on their vibration signals. The modal parameters are estimated using Frequency Domain Decomposition (FDD) and the response signals are decomposed into intrinsic mode functions (IMF) using empirical mode decomposition (EMD) technique. Those IMFs are then processed with Hilbert-Huang transform (HHT) to obtain their corresponding Hilbert spectra, which allows the estimation of the time-varying instantaneous properties of those response signals. Then a marginal Hilbert spectrum (MHS)-based technique has been applied on the Hilbert spectrum coefficients to calculate associated Damage Indices (DI). The proposed method was tested using experimental tests conducted on a cantilever steel beam prototype at the CBRI laboratory, Roorkee, India, and a three-storey steel frame at Concordia University, Canada. Modal parameters were identified from system identification and the damage locations were determined by comparing the DIs of the damaged steel beam and frame with that of the corresponding baseline (undamaged) structures.<br/>},
key = {Intrinsic mode functions},
keywords = {Damage detection;Mathematical transformations;Frequency domain analysis;Vibration analysis;Domain decomposition methods;Structural health monitoring;Composite beams and girders;Modal analysis;Parameter estimation;},
note = {Damage index;Empirical Mode Decomposition;Frequency domain decomposition;Hilbert spectrum;Intrinsic Mode functions;Structural health monitoring (SHM);},
}
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