Modal properties identification of damped bridge using improved vehicle scanning method

Yang, D.S.; Wang, C.M.

doi:10.1016/j.engstruct.2022.114060

Cited by 32 publications

(19 citation statements)

References 36 publications

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“…Furthermore, Yang et al [ 43 ] argued that the contact-point (CP) response does not contain vehicle frequencies that hamper identifying the bridge mode shapes and frequencies. This observation was verified through numerical simulations [ 43 ] and an in situ test [ 44 ] and use of CP response to estimate the mode shapes has become more popular afterwards [ 23 , 39 , 42 , 43 , 44 , 45 , 46 ].…”

Section: Introductionmentioning

confidence: 80%

“…Although some researchers used time–frequency domain techniques [ 16 , 17 , 24 , 25 , 26 , 27 ], the majority of the most recent vehicle scanning methods in the literature apply two mode shape identification approaches to construct the bridge mode shapes: (i) using signal segmentation with an OMA tool [ 28 , 29 , 30 , 31 , 32 , 33 , 34 ], and (ii) using signal decomposition together with Hilbert transform [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ]. This study involves three of the most recent VSM methods proposed in the literature for estimating mode shapes.…”

Section: Vehicle Scanning Methodsmentioning

confidence: 99%

“…The final approach used in mode shape estimation is based on using a signal decomposition technique to extract the bridge’s modal components from the vehicle’s acceleration response and determine the mode shapes by applying the Hilbert transform (HT) to the obtained components. Yang et al [ 35 ] conducted the pioneering work using this approach where the modal components of bridge are extracted using a digital filter such as band-pass filter [ 35 , 36 , 37 , 38 ], elliptic filter [ 39 ], or a recently introduced two-peak spectrum idealized filter [ 40 ]. Alternatively, a blind source separation algorithm such as empirical mode decomposition (EMD) [ 41 ] or variational mode decomposition (VMD) [ 42 ] can be used to extract the narrow-band components of the vibrations measured on the vehicle that correspond to the bridge modal frequencies.…”

Section: Introductionmentioning

confidence: 99%

“…To address this gap in the literature, this paper, for the first time, investigates the effectiveness of three state-of-the-art vehicle scanning methods [ 31 , 39 , 42 ] in estimating the mode shapes of bridges seated on elastic supports. For this, we developed numerical models of two bridges, one single- and one two-span, that are seated on elastic supports.…”

Section: Introductionmentioning

confidence: 99%

“…The numerical analyses were conducted for three different scenarios for each bridge: (i) assuming a smooth road profile, (ii) considering the effects of road roughness, and (iii) sending a lead vehicle to increase the vibration amplitudes and to attenuate the adverse effects of road roughness. We then used the methods summarized in [ 31 , 39 , 42 ] separately to estimate the bridge mode shapes for each scenario. We paid special attention to the modal displacement estimates at the edges of the bridge, i.e., over or close to the elastic supports, because none of the three methods was previously tested on bridges that are seated on elastic supports, which have very different modal amplitudes at the support locations compared to their simply supported counterparts.…”

Section: Introductionmentioning

confidence: 99%

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Efficacy of Vehicle Scanning Methods in Estimating the Mode Shapes of Bridges Seated on Elastic Supports

Demirlioglu

Gönen

Erduran

2023

Sensors

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This study systematically assesses the efficacy of the vehicle scanning methods (VSM) in accurately estimating the mode shapes of bridges seated on elastic supports. Three state-of-the-art VSM methods are employed to obtain the mode shapes of bridges using the vehicle data during its travel. Two of the evaluated methods use a signal decomposition technique to extract the modal components of the bridge from the contact point of the response while the third one relies on the segmentation of the measured signals along the bridge deck and applying an operational modal analysis tool to each segmented signal to estimate the mode shapes. Numerical analyses are conducted on one single- and one two-span bridge, considering smooth and rough road profiles, different vehicle speeds, and presence of lead vehicle. The accuracy of the numerical models used in developing and assessing vehicle scanning models is tested, and the results of the study demonstrate the method using a half-car vehicle model and signal decomposition technique shows robustness against increasing vehicle speeds and road roughness while the method applying the segmentation of the measured signals provides relatively accurate mode shape estimates at the bridge edges at low speed, although the three methods have their limitations. It is also observed that simplified bridge and vehicle models can hide potential challenges that arise from the complexity of actual vehicle and bridge systems. Considering that a significant number of bridges worldwide are built on elastic supports, the practical success of vehicle scanning methods depends on their ability to handle elastic boundary conditions with reliability. Therefore, the article provides valuable insights into the capabilities and limitations of the current vehicle scanning methods, paving the way for further advancements and refinements in these techniques.

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