Drive-by bridge damage detection using non-specialized instrumented vehicle

Elhattab, Ahmed; Uddin, Nasim; O’Brien, Eugene J.

doi:10.3233/brs-170106

Cited by 12 publications

(7 citation statements)

References 10 publications

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“…Under high speed, the bridge frequency has dominated the response spectrum of the subtracted signal. Elhattab et al [25,26] have investigated the concept using an explicit VBI solver, which is included in a commercial Finite Element Program (LS-Dyna) and similar findings were observed. The approach was confined to numerical simulations and no field demonstration has been carried out.…”

Section: Introductionmentioning

confidence: 59%

Drive-By Bridge Frequency Identification under Operational Roadway Speeds Employing Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR)

Elhattab

Uddin

O’Brien

2018

Sensors

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Recently, drive-by bridge inspection has attracted increasing attention in the bridge monitoring field. A number of studies have given confidence in the feasibility of the approach to detect, quantify, and localize damages. However, the speed of the inspection truck represents a major obstacle to the success of this method. High speeds are essential to induce a significant amount of kinetic energy to stimulate the bridge modes of vibration. On the other hand, low speeds are necessary to collect more data and to attenuate the vibration of the vehicle due to the roughness of the road and, hence, magnify the bridge influence on the vehicle responses. This article introduces Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR) as a new technique, which possesses the ability to extract bridge dynamic properties from the responses of a vehicle that passes over the bridge at high speed. Stochastic Resonance (SR) is a phenomenon where feeble information such as weak signals can be amplified through the assistance of background noise. In this study, bridge vibrations that are present in the vehicle responses when it passes over the bridge are the feeble information while the noise counts for the effect of the road roughness on the vehicle vibration. UPSR is one of the SR models that has been chosen in this study for its suitability to extract the bridge vibration. The main contributions of this article are: (1) introducing a Frequency Independent-Stochastic Resonance model known as the FI-UPSR and (2) implementing this model to extract the bridge vibration from the responses of a fast passing vehicle.

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Section: Introductionmentioning

confidence: 59%

Drive-By Bridge Frequency Identification under Operational Roadway Speeds Employing Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR)

Elhattab

Uddin

O’Brien

2018

Sensors

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“…The spectra of the identified force in Figure 12(b) has two dominant peaks at 29.4 and 36.7 Hz corresponding to the two modal frequencies of the vehicle model. The apparent profile is defined as the profile of displacement at the contact point between the tire and the bridge surface [34] and it is calculated using the interaction forces and the identified displacement at the top of the two axles. A band pass filter with cut-off frequencies at 1.0 to 100.0 Hz is used to process the apparent profile to estimate the beam surface unevenness.…”

Section: Experimental Investigationmentioning

confidence: 99%

A Two-Step Drive-By Bridge Damage Detection Using Dual Kalman Filter

Zhu

Law

et al. 2020

Int. J. Str. Stab. Dyn.

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Drive-by bridge inspection using acceleration responses of a passing vehicle has great potential for bridge structural health monitoring. It is, however, known that the road surface roughness is a big challenge for the practical application of this indirect approach. This paper presents a new two-step method for the bridge damage identification from only the dynamic responses of a passing vehicle without the road surface roughness information. A state-space equation of the vehicle model is derived based on the Newmark-[Formula: see text] method. In the first step, the road surface roughness is estimated from the dynamic responses of a passing vehicle using the dual Kalman filter (DKF). In the second step, the bridge damage is identified based on the interaction force sensitivity analysis with Tikhonov regularization. A vehicle–bridge interaction model with a wireless monitoring system has been built in the laboratory. Experimental investigation has been carried out for the interaction force and bridge surface roughness identification. Results show that the proposed method is effective and reliable to identify the interaction force and bridge surface roughness. Numerical simulations have also been conducted to study the effectiveness of the proposed method for bridge damage detection. The vehicle is modeled as a 4-degrees-of-freedom half-car and the bridge is modeled as a simply-supported beam. The local bridge damage is simulated as an elemental flexural stiffness reduction. Effects of measurement noise, surface roughness and vehicle speed on the identification are discussed.The results show that the proposed drive-by inspection strategy is efficient and accurate for a quick review on the bridge conditions.

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“…Elhattab et al [19,20] investigated this concept using commercialized FE program (LS-Dyna). The program comprises an explicit solver, which is different from the implicit solver that has been employed in the previous studies to simulate the Vehicle-Bridge Interaction (VBI).…”

Section: Monitoring Of the Fundamental Bridge Frequencymentioning

confidence: 99%

Drive-by Bridge Damage Monitoring: Concise Review

Elhattab¹

2017

CERJ

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Recently in the area of bridge health monitoring, there is a shift towards the use of indirect measurements of a passing vehicle to assess the structural integrity of bridge structures, which is known as "Drive-by Bridge inspection." This approach is based on determining the dynamic characteristics of the bridge using the vehicle responses, such as bridge frequencies, bridge mode shapes, and even bridge stiffness and damping. The change in these characteristics over a period of time reflects the level of deterioration of the bridge's health condition. This article introduces a brief discussion on the development of this field of research since it was revealed. The article addresses the prominent studies in this domain, while some other work is not included for the sake of brevity in the paper. This article is a good starting point for those interested in researching this topic.

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Drive-by bridge damage detection using non-specialized instrumented vehicle

Cited by 12 publications

References 10 publications

Drive-By Bridge Frequency Identification under Operational Roadway Speeds Employing Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR)

Drive-By Bridge Frequency Identification under Operational Roadway Speeds Employing Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR)

A Two-Step Drive-By Bridge Damage Detection Using Dual Kalman Filter

Drive-by Bridge Damage Monitoring: Concise Review

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