Abstract

Bridge infrastructures are continuously subject to degradation due to aging and excess loading, placing users at risk. It has now become a major concern worldwide, where the majority of bridge infrastructures are approaching their design life. This compels the engineering community to develop robust methods for continuous monitoring of bridge infrastructures including the loads passing over them. Here, a moving load identification method based on the explicit form of Newmark-β method and Generalized Tikhonov Regularization is proposed. Most of the existing studies are based on the state space method, suffering from the errors of a large discretization and a low sampling frequency. The accuracy of the proposed method is investigated numerically and experimentally. The numerical study includes a single simply supported bridge and a three-span continuous bridge, and the experimental study includes a single-span simply supported bridge installed by sensors. The effects of factors such as the number of sensors, sensor locations, road roughness, measurement noise, sampling frequency and vehicle speed are investigated. Results indicate that the method is not sensitive to sensor placement and sampling frequencies. Furthermore, it is able to identify moving loads without disruptions when passing through supports of a continuous bridge, where most the existing methods fail.

Highlights

  • When a bridge is subjected to a moving vehicle exposed to a forced vibration test, there is no need for traffic interruption and extensive experimental arrangements

  • Et al [15] carried out an experimental study to compare four different methods of moving load identification

  • To explore the effect of vehicle speed on the accuracy of moving load identification, the car was pulled over the bridge at speeds of 0.47, 0.75 and 0.94 m/s, and the sampling frequency was set at 200 Hz

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Summary

Introduction

Condition assessment of bridge structures based on vibration measurements has attracted increasing interest among researchers. Uncertainty in the bridge structural responses due to road surface roughness, and the effect of measurement noise, and speed were not studied They did not consider the modal characteristic of the vehicle, including mass, damping and stiffness, and the method did not investigate a multispan continuous bridge. Et al [27] proposed a state space method based on the Galerkin weak formulation and compared the method with a conventional state space method and the explicit form of the Newmark-β method They verified their results numerically by a single-span supported truss subject to a moving force, but the physical properties of the vehicle, speed, the road surface roughness and the effect of the number of spans were not included in their study.

Road Surface Roughness
Dynamic Model of a Vehicle
Dynamic Model of a Bridge
Vehicle-Bridge Coupled Model
Moving Load Identification Formulations
Represention of the Explicit Form of the Newmark-β Method for Moving Loads
Regularized Solution for Moving Load Identification
3.3.Procedure
Numerical Study 1
1: Simply-Supported
Effect of the Number of Sensors and Noise Level
Effect of Vehicle Velocity and Road Roughness Level
2: Three-Span
The Effect of Noise Level and Vehicle Speed
Effect of noise on load identification at road roughness level
The relative error of the identified forces at noise
Experimental Test
11. Experimental of the vehicle-bridge
15. Hammer
16. Acceleration
Signal Processing
Moving Load Identification Verification
The Effect of N f (the Number of Terms in the Generalized Orthogonal Function)
The Effect of Different Measurement Arrangements
The Effect of Sampling Frequency
The Effect of Vehicle Speed
Findings
Conclusions

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