Numerical Studies on Bridge Inspection Using Data Obtained From Sensors on Vehicle

Yamamoto, Kyosuke; FUJIWARA, SACHIYO; TSUKADA, KENTO; Shin, Ryota; Okada, Yukihiko

doi:10.12783/shm2021/36324

Cited by 2 publications

(8 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When the estimated road unevenness matches the correct values [ 8 , 9 ], the mechanical parameters of the vehicle and bridge also mostly match the correct values. Therefore, the accurate estimation of road unevenness is essential.…”

Section: Discussionmentioning

confidence: 96%

“…The VBISI method verified in this study simultaneously estimates road unevenness and all mechanical parameters (mass, damping, stiffness) both of vehicle and bridge only from the position and vibration data of a traveling vehicle. The formulas of the VBISI method have already been published [ 7 , 8 , 9 ].…”

Section: Methodsmentioning

confidence: 99%

“…The authors proposed the VBI system identification (VBISI) method [ 7 , 8 , 9 ]. The VBISI method can simultaneously estimate vehicles’ and bridges’ mechanical parameters and road unevenness from vehicle vibration and location information, under the condition that both the wheelbase and total weight of the vehicle are known.…”

Section: Introductionmentioning

confidence: 99%

“…The numerical simulation of bridge vibration is combined with methods proposed in previous studies. The numerical validation of the VBISI method [ 7 , 8 , 9 ] has already shown the feasibility of this method. However, it is not verified in a field test.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Discussion on a Vehicle–Bridge Interaction System Identification in a Field Test

Shin

Okada

Yamamoto

2023

Sensors

Self Cite

View full text Add to dashboard Cite

For infrastructures to be sustainable, it is essential to improve maintenance and management efficiency. Vibration-based monitoring methods are being investigated to improve the efficiency of infrastructure maintenance and management. In this paper, signals from acceleration sensors attached to vehicles traveling on bridges are processed. Methods have been proposed to individually estimate the modal parameters of bridges and road unevenness from vehicle vibrations. This study proposes a method to simultaneously estimate the mechanical parameters of the vehicle, bridge, and road unevenness with only a few constraints. Numerical validation examined the effect of introducing the Kalman filter on the accuracy of estimating the mechanical parameters of vehicles and bridges. In field tests, vehicle vibration, bridge vibration, and road unevenness were measured and verified, respectively. The road surface irregularities estimated by the proposed method were compared with the measured values, which were somewhat smaller than the measured values. Future studies are needed to improve the efficiency of vehicle vibration preprocessing and optimization methods and to establish a methodology for evaluating accuracy.

show abstract

Section: Discussionmentioning

confidence: 96%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Discussion on a Vehicle–Bridge Interaction System Identification in a Field Test

Shin

Okada

Yamamoto

2023

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…This scheme extension can be realized by adding a bridge simulation process. The extended method is called the PRE (numerical simulation-based vehicle and bridge parameter and road roughness estimation in VBI system) method [30][31][32] in this study. The uniqueness of the PRE method is that it includes the identification process of the bridge system.…”

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

View full text Add to dashboard Cite

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.

show abstract

Numerical Studies on Bridge Inspection Using Data Obtained From Sensors on Vehicle

Cited by 2 publications

References 0 publications

Discussion on a Vehicle–Bridge Interaction System Identification in a Field Test

Discussion on a Vehicle–Bridge Interaction System Identification in a Field Test

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

Contact Info

Product

Resources

About