A bridge-monitoring tool based on bridge and vehicle accelerations

Hester, David; González, Arturo

doi:10.1080/15732479.2014.890631

Cited by 24 publications

(15 citation statements)

References 38 publications

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“…The quasi-static method derives from the works presented in [9,10], which are focused on a bridge for road transportation. The method applied in these papers consists of filtering the signals with a moving average filter with a window length that is equal to the period of the first mode of vibration of the bridge, to cancel the dynamic components of the acceleration, and to extract the quasi-static component.…”

Section: Quasi-static Methodsmentioning

confidence: 99%

“…Two different approaches can be investigated for data-processing, basically differing in the frequency range of the acceleration data considered. The first approach considered in this paper originates from the work described in González, A., & Hester, D. [9,10], focused on a bridge for road transportation. In the mentioned work, data generated by the vehicle passage are filtered to cancel the dynamic components due to the bridge modes of vibration, so that the remaining signal is representative of the quasi-static deflection of the bridge in response to the moving loads.…”

Section: Introductionmentioning

confidence: 99%

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A Feasibility Study of the Drive-By Method for Damage Detection in Railway Bridges

2019

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Damage identification and localization in railway bridges is a widely studied topic. Strain, displacement, or acceleration sensors installed on the bridge structure are normally used to detect changes in the global behavior of the structure, whereas approaches like ultra-sonic testing, acoustic emission, and magnetic inspection are used to check a small portion of structure near localized damage. The aim of this paper is to explore another perspective for monitoring the structural status of railway bridges, i.e., to detect structural damage from the dynamic response of the train transiting the bridge. This approach can successfully be implemented in the case of resonant bridges, thanks to the high level of acceleration generated, but its application becomes more challenging when the excitation frequencies due to train passage do not excite the first mode of vibration of the bridge. The paper investigates the feasibility of the method in the latter case, through numerical simulations of the complete train-track-bridge system. Accelerations on axleboxes and bogies are processed through suitable algorithms to detect differences arising when the train crosses a defective bridge or a healthy one. The results outline the main operational parameters affecting the method, the best placement for sensors, and the best frequency range to be considered in the signal processing, also addressing the issues that are related to track irregularity. Good performance can be achieved in the case of short bridges, but a few practical issues must be tackled before the method could be tested in practice.

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Section: Quasi-static Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Feasibility Study of the Drive-By Method for Damage Detection in Railway Bridges

2019

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“…Therefore, an effective method of bridge damage detection is important to detect damage quickly when it occurs. In recent years, many methods of bridge damage detection have been proposed for road authorities to maintain an acceptable level of bridge safety [5]. These methods are classified using levels of damage identification.…”

Section: Introductionmentioning

confidence: 99%

Using Statistical Analysis of an Acceleration-Based Bridge Weigh-In-Motion System for Damage Detection

et al. 2020

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This paper develops a novel method of bridge damage detection using statistical analysis of data from an acceleration-based bridge weigh-in-motion (BWIM) system. Bridge dynamic analysis using a vehicle-bridge interaction model is carried out to obtain bridge accelerations, and the BWIM concept is applied to infer the vehicle axle weights. A large volume of traffic data tends to remain consistent (e.g., most frequent gross vehicle weight (GVW) of 3-axle trucks); therefore, the statistical properties of inferred vehicle weights are used to develop a bridge damage detection technique. Global change of bridge stiffness due to a change in the elastic modulus of concrete is used as a proxy of bridge damage. This approach has the advantage of overcoming the variability in acceleration signals due to the wide variety of source excitations/vehicles—data from a large number of different vehicles can be easily combined in the form of inferred vehicle weight. One year of experimental data from a short-span reinforced concrete bridge in Slovenia is used to assess the effectiveness of the new approach. Although the acceleration-based BWIM system is inaccurate for finding vehicle axle-weights, it is found to be effective in detecting damage using statistical analysis. It is shown through simulation as well as by experimental analysis that a significant change in the statistical properties of the inferred BWIM data results from changes in the bridge condition.

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“…Many approaches developed over the past decade are based on the VBI (Chen et al 2007;Law and Zhu 2009;Fujino and Siringoringo 2011;Sun et al 2013;Hester and Gonzalez 2014;Malekjafarian et al 2015). These structural damage detection approaches can be divided into three categories: those based on bridge responses, those based on vehicle responses and those based on both vehicle and bridge responses.…”

Section: Structural Health Monitoring Based On Vehicle-bridge Interacmentioning

confidence: 99%

“…The results show that the moving sensor approach is more effective than the fixed sensor. However, the vehicle acceleration is more sensitive to road surface roughness and measurement noise, and less reliable than direct bridge measurements (Hester and Gonzalez 2014).…”

Section: Z T H T U X T H T Y X T T R Xmentioning

confidence: 99%

Structural Health Monitoring Based on Vehicle-Bridge Interaction: Accomplishments and Challenges

Zhu

Law

2015

Advances in Structural Engineering

136

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The use of the vehicle-bridge interaction (VBI) data for structural health monitoring has received considerable interest in the last decade. Compared with the traditional bridge health monitoring, the VBI based approach allows the target bridges to be monitored or assessed under operating conditions. The VBI system has time-variant features and the vehicle can serve as a moving exciter and a mobile sensor in the system. Many bridge damage identification techniques based on VBI have been developed, and they could be divided into three categories, namely, technique based on the bridge responses, technique based on the vehicle responses and technique based on both the vehicle and bridge responses. This paper presents a review on the structural health monitoring based on VBI and the challenges for its general implementation in practice.

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A bridge-monitoring tool based on bridge and vehicle accelerations

Cited by 24 publications

References 38 publications

A Feasibility Study of the Drive-By Method for Damage Detection in Railway Bridges

A Feasibility Study of the Drive-By Method for Damage Detection in Railway Bridges

Using Statistical Analysis of an Acceleration-Based Bridge Weigh-In-Motion System for Damage Detection

Structural Health Monitoring Based on Vehicle-Bridge Interaction: Accomplishments and Challenges

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