Identification of damping in a bridge using a moving instrumented vehicle

González, Arturo; O’Brien, Eugene J.; McGetrick, Patrick

doi:10.1016/j.jsv.2012.04.019

Cited by 229 publications

(95 citation statements)

References 36 publications

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“…In this model, VBI is represented as a coupled system which is a well-accepted approach in the literature [32,34,49]. A Half-car model with 4 degrees of freedom (DOFs) is implemented in MATLAB to simulate the interaction between the vehicle and the bridge.…”

Section: Vehicle-bridge Interaction Modelmentioning

confidence: 99%

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Damage detection using curvatures obtained from vehicle measurements

O’Brien

Martínez

Malekjafarian

et al. 2017

J Civil Struct Health Monit

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This paper describes a new procedure for bridge damage identification through drive-by monitoring. Instantaneous Curvature (IC) is presented as a means to determine a local loss of stiffness in a bridge through measurements collected from a passing instrumented vehicle. Moving Reference Curvature (MRC) is compared with IC as a damage detection tool. It is assumed that absolute displacements on the bridge can be measured by the vehicle. The bridge is represented by a finite element (FE) model. A Half-car model is used to represent the passing vehicle. Damage is represented as a local loss of stiffness in different parts of the bridge. 1% random noise and no noise environments are considered to evaluate the effectiveness of the method. A generic road surface profile is also assumed. Numerical simulations show that the local damage can be detected using IC if the deflection responses can be measured with sufficient accuracy. Damage quantification can be obtained from MRC.

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Section: Vehicle-bridge Interaction Modelmentioning

confidence: 99%

“…Five damage identification parameters can be highlighted: (i) frequency [28][29][30], (ii) damping [31][32][33], (iii) mode shapes [30,34,35], (iv) accelerations [36][37][38] and (v) curvatures. Curvature methods are usually focused on the mode shape and the deflection [39].…”

Section: Introductionmentioning

confidence: 99%

Damage detection using curvatures obtained from vehicle measurements

O’Brien

Martínez

Malekjafarian

et al. 2017

J Civil Struct Health Monit

View full text Add to dashboard Cite

show abstract

“…The vehicle is fitted with sensors, such as accelerometers, on its axles to monitor vibration thus aiming to reduce the need for (a) on-site SHM installations on the bridge which can be expensive and (b) expensive laser-based technology and sensors currently used in inertial road profilometers. Methods have been proposed and developed which target identification of bridge dynamic properties such as frequency [9,10], damping [11], mode shapes [12] and modal curvatures [13] based on post-processing of on-vehicle sensor measurements, showing some promise. However, these types of methods, summarised by Malekjafarian et al [7], lack comprehensive experimental verification, with very few field trials reported in the literature.…”

Section: Introductionmentioning

confidence: 99%

Implementation of a drive-by monitoring system for transport infrastructure utilising smartphone technology and GNSS

McGetrick

Hester

Taylor

2017

J Civil Struct Health Monit

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Ageing and deterioration of infrastructure are a challenge facing transport authorities. In particular, there is a need for increased bridge monitoring in order to provide adequate maintenance, prioritise allocation of funds and guarantee acceptable levels of transport safety. Existing bridge structural health monitoring (SHM) techniques typically involve direct instrumentation of the bridge with sensors and equipment for the measurement of properties such as frequencies of vibration. These techniques are important as they can indicate the deterioration of the bridge condition. However, they can be labour intensive and expensive due to the requirement for on-site installations. In recent years, alternative low-cost indirect vibration-based SHM approaches have been proposed which utilise the dynamic response of a vehicle to carry out 'drive-by' pavement and/or bridge monitoring. The vehicle is fitted with sensors on its axles thus reducing the need for on-site installations. This paper investigates the use of lowcost sensors incorporating global navigation satellite systems (GNSS) for implementation of the drive-by system in practice, via field trials with an instrumented vehicle. The potential of smartphone technology to be harnessed for drive-by monitoring is established, while smartphone GNSS tracking applications are found to compare favourably in terms of accuracy, cost and ease of use to professional GNSS devices.

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“…The properties of a moving vehicle can be identified from the bridge vibration data [1]. Similarly, the bridge dynamic parameters can also be derived from the vibration data measured from an instrumented vehicle moving on a bridge [2,3].…”

Section: Introductionmentioning

confidence: 99%