Adaptation of Cross Entropy optimisation to a dynamic Bridge WIM calibration problem

Dowling, Jason; O’Brien, Eugene J.; González, Arturo

doi:10.1016/j.engstruct.2012.05.047

Cited by 39 publications

(28 citation statements)

References 27 publications

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“…A further adaption of the CE optimisation process used here is in the substructuring of the problem. Each unknown is substantially independent of the other unknowns, and therefore objective subfunctions can be defined . The objective subfunctions are defined as the squared differences between each of the n displacements calculated for each of the p trial profiles,

d_{{normali}_{normalC}}

, and each of the n displacements from the measured profile,

d_{{normali}_{normalM}}

{({normald}_{i_{C}} - {normald}_{i_{M}})}^{2} \forall i = 1, 2, \dots n

…”

Section: Adapted Ce Optimisation Methodsmentioning

confidence: 99%

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Drive-by damage detection in bridges using the apparent profile

O’Brien

Keenahan

2014

Struct. Control Health Monit.

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Publication informationStructural Control and Health Monitoring, 22 (5) AbstractThe concept of using sensors on a passing vehicle, rather than on the bridge, is known as 'Drive-by' damage detection. The newly developed Traffic Speed Deflectometer (TSD) is a device used for pavement deflection measurements and is investigated here in numerical simulations as a means of bridge damage detection. A TSD vehicle model containing two displacement sensors is simulated crossing a simply supported finite element beam containing damage simulated as a loss in stiffness of one of the elements. An adapted Cross Entropy optimisation algorithm procedure is proposed to determine the apparent profile, where the displacements recorded by the sensors are used as the inputs. The time-shifted difference in the apparent profile is used as the damage indicator. Results show that this can be reliably used as a damage indicator in the presence of noise and changes in the transverse position of the vehicle on the bridge.

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d_{{normali}_{normalC}}

, and each of the n displacements from the measured profile,

d_{{normali}_{normalM}}

{({normald}_{i_{C}} - {normald}_{i_{M}})}^{2} \forall i = 1, 2, \dots n

…”

Section: Adapted Ce Optimisation Methodsmentioning

confidence: 99%

“…Dowling et al . use an adapted CE optimisation method to develop a calibration procedure for a moving force identification algorithm. The general system global mass and stiffness matrices of the bridge FE model are found by best fit optimisation to match field measurements.…”

Section: Introductionmentioning

confidence: 99%

Drive-by damage detection in bridges using the apparent profile

O’Brien

Keenahan

2014

Struct. Control Health Monit.

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“…More recently, Moving Force Identification (MFI) techniques have been applied to measured signals to improve the accuracy of the measured axle weights [7]. These techniques have been found to improve the accuracy of the systems but a report on the accuracy classification of several B-WIM installations found that current accuracy levels are sufficient for selecting vehicles to be weighed using static scales, but insufficient for direct enforcement [8].…”

Section: Introductionmentioning

confidence: 99%

Recent developments in bridge weigh in motion (B-WIM)

Lydon

Taylor

Robinson

et al. 2015

J Civil Struct Health Monit

138

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Bridge weigh in motion (B-WIM) uses accurate sensing systems to transform an existing bridge into a mechanism to determine actual traffic loading. This information on traffic loading can enable efficient and economical management of transport networks and is becoming a valuable tool for bridge safety assessment. B-WIM can provide site-specific traffic loading on deteriorating bridges, which can be used to determine if the reduced capacity is still sufficient to allow the structure to remain operational and minimise unnecessary replacement or rehabilitation costs and prevent disruption to traffic. There have been numerous reports on the accuracy classifications of existing B-WIM installations and some common issues have emerged. This paper details some of the recent developments in B-WIM which were aimed at overcoming these issues. A new system has been developed at Queens University Belfast using fibre optic sensors to provide accurate axle detection and improved accuracy overall. The results presented in this paper show that the fibre optic system provided much more accurate results than conventional WIM systems, as the FOS provide clearer signals at high scanning rates which require less filtering and less post-processing. A major disadvantage of existing B-WIM systems is the inability to deal with more than one vehicle on the bridge at the same time; sensor strips have been proposed to overcome this issue. A bridge can be considered safe if the probability that load exceeds resistance is acceptably low, hence B-WIM information from advanced sensors can provide confidence in our ageing structures.

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“…Previous research [5] has developed theoretical models for B-WIM and demonstrated that Tikhonov Regularization can be used to improve ill-conditioned Moses equations which occur when axles are closely spaced relative to the bridge span. More recently, moving force identification (MFI) techniques have been applied to measured signals to improve the accuracy of the measured axle weights [6,9,10]. These techniques have been found to improve the accuracy of the systems [5].…”

Section: Introductionmentioning

confidence: 99%

Improved axle detection for bridge weigh-in-motion systems using fiber optic sensors

Lydon

Robinson

Taylor

et al. 2017

J Civil Struct Health Monit

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Bridge weigh-in-motion (B-WIM) systems provide a non-destructive means of gathering traffic loading information by using an existing bridge as a weighing scale to determine the weights of vehicles passing over. In this research critical locations for sensors for the next-generation B-WIM were determined from a full 3D explicit finite element analysis (FEA) model. Although fiber optic sensors (FOS) have become increasingly popular in SHM systems there are currently no commercially available fiber optic WIM systems available. The FEA in this research facilitated the development of the first ever full fiber optic B-WIM and its potential has been demonstrated with the site installation of this system. The system combined nothing-on-the-road axle detection and alternative methods of measuring strain at the supports. The system was installed on a 20-m span beam and slab RC bridge in Northern Ireland and the results presented in this paper confirm the suitability of FOS in providing the clear defined peaks required for accurate axle detection in B-WIM.

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Adaptation of Cross Entropy optimisation to a dynamic Bridge WIM calibration problem

Cited by 39 publications

References 27 publications

Drive-by damage detection in bridges using the apparent profile

Drive-by damage detection in bridges using the apparent profile

Recent developments in bridge weigh in motion (B-WIM)

Improved axle detection for bridge weigh-in-motion systems using fiber optic sensors

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