A regularised solution to the bridge weigh-in-motion equations

O’Brien, Eugene J.; Rowley, C.W.; González, Arturo; Green, Mark F.

doi:10.1504/ijhvs.2009.027135

Cited by 46 publications

(25 citation statements)

References 17 publications

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“…An additional penalty term multiplied by a regularization parameter is added into the original minimization formulation to improve the condition of the original system. The regularization technique was reported to significantly improve the accuracy of the identified axle weights; however, as the vehicle dynamics becomes more noticeable, the convergence of the regularized solution becomes slower (O'Brien et al, 2009).…”

Section: Moses' Algorithmmentioning

confidence: 99%

State-of-the-art review on bridge weigh-in-motion technology

Cai

Deng

2016

Advances in Structural Engineering

191

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Weigh-in-motion technology is an effective tool that has been extensively used to monitor traffic on highways. Pavement-based weighin-motion systems usually have poor durability and will cause traffic interruption during their installation and maintenance process. The recently developed bridge weigh-in-motion technology provides a more convenient and cost-effective alternative to the pavement-based weigh-in-motion technology. Bridge weigh-in-motion systems can be installed without interrupting the traffic. Also, bridge weigh-in-motion systems have the potential to deliver better accuracy than pavement-based weigh-in-motion systems. Due to these significant advantages, the bridge weigh-in-motion technology has been playing an increasingly important role in bridge health monitoring and overweight truck enforcement, and many studies have been conducted to continuously improve the bridge weigh-inmotion technology. In this review, the common algorithms for bridge weigh-in-motion are discussed in detail, and the typical instrumentation of bridge weigh-in-motion systems is also introduced. Meanwhile, much effort is made to identify the remaining issues in the application of bridge weigh-in-motion technology, and the corresponding future research is proposed.

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Section: Moses' Algorithmmentioning

confidence: 99%

State-of-the-art review on bridge weigh-in-motion technology

Cai

Deng

2016

Advances in Structural Engineering

191

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“…In recent years there have been extensive developments in the area of BWIM, as documented in the literature (Lydon et al, 2015;Richardson et al, 2014). In the most sophisticated algorithms, the static equations of Moses (1979) have been replaced by a system of differential equations of motion in an approach known as moving force identification (González et al, 2008;Law and Fang, 2001;Law et al, 1999;OBrien et al, 2009;Rowley et al, 2009). The most recent moving force identification research is reported by Zhu et al (2013) and Corbaly et al (2014).…”

Section: Review Of Previous Weigh-in-motion Systemsmentioning

confidence: 99%

Bridge weigh-in-motion using fibre optic sensors

Lydon¹,

Taylor²,

Doherty³

et al. 2017

Proceedings of the Institution of Civil Engineers - Bridge Engi

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Bridge weigh-in-motion systems were introduced in the 1970s as a structural health monitoring tool for road bridges. They help bridge operators determine the cause of induced strain in bridges and collect statistics on vehicle weight, class and frequency. There have been over 3000 installations in 25 countries worldwide, which has led to vast improvements in data post-processing. However, existing systems are based on electrical resistance strain gauges, which can be prohibitive in achieving data for long-term monitoring of rural bridges due to power consumption. This paper introduces a new low-power system using fibre optic sensors, which has been pioneered in Northern Ireland. A series of fibre optic sensors were attached to the soffit of an existing integral bridge with a single span of 19 m. The site selection criteria and full installation process are described in this paper. A method of calibration was adopted using live traffic at the bridge site, based on which the accuracy of the system was determined. New methods of axle detection for bridge weigh-in-motion were investigated and verified in the field.

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“…Therefore, it can provide a solution for the long-term monitoring of our infrastructure. The B-WIM theory has been extended under a number of research initiatives [3][4][5][6], and more recently the ''BridgeMon'' project which finished in 2014 [7]. More recently, B-WIM systems have been used in conjunction with machine learning techniques to develop damage detection methods for railway bridges [8].…”

Section: Introductionmentioning

confidence: 99%

“…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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A regularised solution to the bridge weigh-in-motion equations

Cited by 46 publications

References 17 publications

State-of-the-art review on bridge weigh-in-motion technology

State-of-the-art review on bridge weigh-in-motion technology

Bridge weigh-in-motion using fibre optic sensors

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

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