Combined wavelet–Hilbert transform-based modal identification of road bridge using vehicular excitation

Mahato, Swarup; Teja, Meda Vinay; Chakraborty, Arunasis

doi:10.1007/s13349-017-0206-y

Cited by 21 publications

(11 citation statements)

References 47 publications

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“…If the MAC is 0, the intersection angle of the mode shape vector is 90°, indicating that the correlation between modes is weak. Conversely, if the MAC is close to 1, the correlation between modes is strong; a value between 0.95 and 1.00 is assumed to be acceptable for all practical purposes [ 44 , 45 ].…”

Section: Methodology Of Infrared Thermography Measurement and Datamentioning

confidence: 99%

Infrared Thermography Measurement for Vibration-Based Structural Health Monitoring in Low-Visibility Harsh Environments

Liu²,

Chung³

et al. 2020

Sensors

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In this study, infrared thermography is used for vibration-based structural health monitoring (SHM). Heat sources are employed as sensors. An acrylic frame structure was experimentally investigated using the heat sources as structural marker points to record the vibration response. The effectiveness of the infrared thermography measurement system was verified by comparing the results obtained using an infrared thermal imager with those obtained using accelerometers. The average error in natural frequency was between only 0.64% and 3.84%. To guarantee the applicability of the system, this study employed the mode shape curvature method to locate damage on a structure under harsh environments, for instance, in dark, hindered, and hazy conditions. Moreover, we propose the mode shape recombination method (MSRM) to realize large-scale structural measurement. The partial mode shapes of the 3D frame structure are combined using the MSRM to obtain the entire mode shape with a satisfactory model assurance criterion. Experimental results confirmed the feasibility of using heat sources as sensors and indicated that the proposed methods are suitable for overcoming the numerous inherent limitations associated with SHM in harsh or remote environments as well as the limitations associated with the SHM of large-scale structures.

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Section: Methodology Of Infrared Thermography Measurement and Datamentioning

confidence: 99%

Infrared Thermography Measurement for Vibration-Based Structural Health Monitoring in Low-Visibility Harsh Environments

Liu²,

Chung³

et al. 2020

Sensors

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“…However, HHT suffers from mode mixing and often leads to spurious frequencies. 33,34 In this paper, the hybrid WTs-OMA (weighted transmissibility and wavelet transform-based operational modal analysis) method is proposed to solve this problem. Given that the weighted transmissibility is capable of correctly detecting the system poles in the presence of a variety of input excitations, it is an appropriate approach for identifying the vibration modes and subsequently evaluating the ridges in the continuous wavelet transform.…”

Section: Introductionmentioning

confidence: 99%

“…Along with the development of wavelet transform for use in modal identification, Hilbert–Huang transform (HHT)‐based time–frequency analysis has also gained a lot of attention from the researchers in this field. However, HHT suffers from mode mixing and often leads to spurious frequencies 33,34 …”

Section: Introductionmentioning

confidence: 99%

Structural system identification based on combining weighted transmissibility and wavelet transform

Damadipour

Tarinejad

2021

Structural Contr & Hlth

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In this paper, an integrated method called WTs-OMA (weighted transmissibility and wavelet transform-based operational modal analysis) is proposed to identify the structural dynamic characteristics using the earthquake response of structures. The proposed method, which is a time-frequency domain method with both parametric and non-parametric characteristics, utilizes the effective and efficient capabilities of weighted transmissibility and wavelet transform to achieve a proper performance in modal parameter estimation. This method employs weighted transmissibility functions to identify natural frequencies and mode shapes and calculates the damping values using the skeletons or the single frequency signals obtained from wavelet transform of the correlation functions of seismic responses. In this research, a numerical model under El Centro earthquake excitation is used for performance validation of the proposed method; Furthermore, the Karun 3 arch dam is selected as a case study in which the dynamic characteristics of the structure are identified based on the seismic responses from the different earthquakes.

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“…The evaluation of the health of structure using vibrational responses is based on the direct relationship among the varying structural physical properties such as mass and stiffness with the dynamic properties such as mode shapes, natural frequencies and modal damping values of the structure (Moughty and Casas, 2017). The robustness and accuracy of vibration-based signal processing techniques in diagnosing damages in a multi-degree of freedom structural system have made them of wider interest in their application in different fields such as rotating machines (Ozturk et al, 2010;Ali et al, 2015;Zurita-Mill an et al, 2016), aerospace structures (Aykan and Celik, 2009;Mahmoodi and Ahmadian, 2010), turbine (Rodriguez et al, 2007;Kumar et al, 2007), etc. Various studies in recent years have proposed several signal processing techniques such as statistical tools (Bearing and Caesarendra, 2017;Dron and Bolaers, 2004;Hui et al, 2017), frequency domain decomposition (Mekjavi c and Damjanovi c, 2016;Wu et al, 2019), wavelet transform (Yi et al, 2013;Bayissa et al, 2008;Zhang and Li, 2006), synchrosqueezed wavelet transform (Mahato and Chakraborty, 2019;Amezquita-Sanchez and Adeli, 2015;Perez-Ramirez et al, 2016;Liu et al, 2015), Hilbert-Huang transform (Chen et al, 2014;Liu et al, 2012;Yan and Miyamoto, 2006), Teager-Huang transform (Pan et al, 2018;Li et al, 2010), wavelet-Hilbert transform (Mahato et al, 2017) and others (Moughty and Casas, 2017;Amezquita-Sanchez and Adeli, 2016;Lorenzoni et al, 2019) which are applied on the collected vibration data determining the dynamic modal properties of the structure. The evaluation of vibration signals provides dynamic characteristics of the signals which help in identifying the damage locations in a structure.…”

Section: Introductionmentioning

confidence: 99%

Hilbert transform and spectral kurtosis based approach in identifying the health state of retrofitted old steel truss bridge

Sharma

Kumar

Vinayak

et al. 2021

WJE

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Purpose This study aims to include the diagnosis of an old concrete deck steel truss rural road bridge in the damaged and retrofitted state through vibration response signals. Design/methodology/approach The analysis of the vibration response signals is performed in time and time-frequency domains using statistical features-root mean square, impulse factor, crest factor, kurtosis, peak2peak and Stockwell transform. The proposed methodology uses the Hilbert transform in combination with spectral kurtosis and bandpass filtering technique for obtaining robust outcomes of modal frequencies. Findings The absence or low amplitude of considered mode shape frequencies is observed both before and after retrofitting of bridge indicates the deficient nodes. The kurtosis feature among all statistical approaches is able to reflect significant variation in the amplitude of different nodes of the bridge. The Stockwell transform showed better resolution of present modal frequencies but due to the yield of additional frequency peaks in the vicinity of the first three analytical modal frequencies no decisive conclusions are achieved. The methodology shows promising outcomes in eliminating noise and visualizing distinct modal frequencies of a steel truss bridge. Social implications The findings of the present study help in analyzing noisy vibration signals obtained from various structures (civil or mechanical) and determine vulnerable locations of the structure using mode shape frequencies. Originality/value The literature review gave an insight into few experimental investigations related to the combined application of Hilbert transform with spectral kurtosis and bandpass filtering technique in determining mode frequencies of a steel truss bridge.

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Combined wavelet–Hilbert transform-based modal identification of road bridge using vehicular excitation

Cited by 21 publications

References 47 publications

Infrared Thermography Measurement for Vibration-Based Structural Health Monitoring in Low-Visibility Harsh Environments

Infrared Thermography Measurement for Vibration-Based Structural Health Monitoring in Low-Visibility Harsh Environments

Structural system identification based on combining weighted transmissibility and wavelet transform

Hilbert transform and spectral kurtosis based approach in identifying the health state of retrofitted old steel truss bridge

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