Frequency extraction for bridges with rough surface by a moving test vehicle enhanced by a shaker

Yang, Y.B.; Huang, Chin-Kuo; Xu, H.; Wang, M.H.; Wang, Z.L.; Shi, Kang

doi:10.1016/j.engstruct.2022.114598

Cited by 15 publications

(3 citation statements)

References 60 publications

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“…The authors [19] also examined the feasibility of estimating bridge mode shapes from the vibration responses of several cargo trailers. The other frequency-based approaches [20] are made by Gonzalez et al [21] and Wang et al [22], while the mode shape-based approaches are also studied by Yang et al [23] and Malekjafarian et al [24].…”

Section: Sensors Installed On a Traveling Vehiclementioning

confidence: 99%

“…Identifying the bridge's natural frequency is difficult because vehicle frequency and road roughness interfere with bridge frequencies. This issue has been addressed by Yang et al [20]. They use vehicle-bridge contact response, which eliminates vehicle frequencies, and a shaker fixed on the bridge to enhance bridge vibration.…”

Section: Sensors Installed On a Traveling Vehiclementioning

confidence: 99%

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Numerical Verification of the Drive-By Monitoring Method for Identifying Vehicle and Bridge Mechanical Parameters

2023

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The PRE (numerical simulation-based vehicle and bridge parameter and road roughness estimation) method uses vehicle vibration data to identify the vehicle’s and bridge’s mechanical parameters and estimate road unevenness simultaneously. This method randomly assumes the mechanical parameters first. Secondly, it solves the vehicle’s IEP (input estimation problem) and the bridge’s DRS (dynamic response simulation) from the vehicle vibration data to obtain road profiles of the front and rear wheels. Repeat the random assumption of the mechanical parameters to minimize the residual between the obtained road unevenness because the road unevenness of the front and rear wheels are expected to match. To search for a better combination of the mechanical parameters, the MCMC (Monte Carlo Markov chain) algorithm is adopted in this paper. This paper also numerically simulates vehicle vibration data for the cases of the reduced-stiffness bridge model and examines whether this method can identify the position, range, and magnitude of stiffness reduction. The numerical simulation results show that bridge-stiffness reduction can be estimated reasonably.

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Section: Sensors Installed On a Traveling Vehiclementioning

confidence: 99%

Section: Sensors Installed On a Traveling Vehiclementioning

confidence: 99%

Numerical Verification of the Drive-By Monitoring Method for Identifying Vehicle and Bridge Mechanical Parameters

2023

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“…However, for multi-axle vehicles in which it is more difficult to install the sensors and measure the contact point response, Yang et al [ 36 ] turned to more feasible means by making the vehicle’s frequency much higher than that of the bridge; thus, the concept of a frequency-free measurement vehicle was proposed. To better eliminate the adverse effects of the road roughness and vehicle frequency simultaneously, Yang et al [ 37 ] intensified the bridge vibration by introducing a shaker. It was found that the shaker facilitates the VSM for bridges with rough surfaces, and that the combination of the contact response and a shaker has a wider range of applications.…”

Section: Introductionmentioning

confidence: 99%

Subspace Identification of Bridge Frequencies Based on the Dimensionless Response of a Two-Axle Vehicle

Quan,

Zeng,

Jin

et al. 2024

Sensors

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As an essential reference to bridge dynamic characteristics, the identification of bridge frequencies has far-reaching consequences for the health monitoring and damage evaluation of bridges. This study proposes a uniform scheme to identify bridge frequencies with two different subspace-based methodologies, i.e., an improved Short-Time Stochastic Subspace Identification (ST-SSI) method and an improved Multivariable Output Error State Space (MOESP) method, by simply adjusting the signal inputs. One of the key features of the proposed scheme is the dimensionless description of the vehicle–bridge interaction system and the employment of the dimensionless response of a two-axle vehicle as the state input, which enhances the robustness of the vehicle properties and speed. Additionally, it establishes the equation of the vehicle biaxial response difference considering the time shift between the front and the rear wheels, theoretically eliminating the road roughness information in the state equation and output signal effectively. The numerical examples discuss the effects of vehicle speeds, road roughness conditions, and ongoing traffic on the bridge identification. According to the dimensionless speed parameter Sv1 of the vehicle, the ST-SSI (Sv1 < 0.1) or MOESP (Sv1 ≥ 0.1) algorithm is applied to extract the frequencies of a simply supported bridge from the dimensionless response of a two-axle vehicle on a single passage. In addition, the proposed methodology is applied to two types of long-span complex bridges. The results show that the proposed approaches exhibit good performance in identifying multi-order frequencies of the bridges, even considering high vehicle speeds, high levels of road surface roughness, and random traffic flows.

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Identification of multiple bridge frequencies using a movable test vehicle by approximating axle responses to contact-point responses: theory and experiment

Zhou,

Deng

et al. 2024

J Civil Struct Health Monit

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Frequency extraction for bridges with rough surface by a moving test vehicle enhanced by a shaker

Cited by 15 publications

References 60 publications

Numerical Verification of the Drive-By Monitoring Method for Identifying Vehicle and Bridge Mechanical Parameters

Numerical Verification of the Drive-By Monitoring Method for Identifying Vehicle and Bridge Mechanical Parameters

Subspace Identification of Bridge Frequencies Based on the Dimensionless Response of a Two-Axle Vehicle

Identification of multiple bridge frequencies using a movable test vehicle by approximating axle responses to contact-point responses: theory and experiment

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