Framework for Flexural Rigidity Estimation in Euler-Bernoulli Beams Using Deformation Influence Lines

Zeinali, Yasha; Story, Brett

doi:10.3390/infrastructures2040023

Cited by 28 publications

(10 citation statements)

References 23 publications

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“…Static influence line deflection [15][16][17] Dynamic properties are not needed. The influencing factors are loading, stiffness, and mass of bridges.…”

Section: Methods Descriptionsmentioning

confidence: 99%

Bridge Health Monitoring via Displacement Reconstruction-Based NB-IoT Technology

et al. 2020

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An aged bridge’s performance is affected by degradation and becomes one of the major concerns in maintenance. A preliminary, simple and workable procedure of bridge damage detection is required to minimize maintenance costs. In the past, frequency is one of the most common indicators to detect damage occurrence. Recent research found that using frequency as a health indicator still has room to improve. Alternatively, dynamic displacement is used as an indicator in the current study. These dynamic displacements are reconstructed based on measured acceleration records from micro electro mechanical system (MEMS) sensors. The Newmark-beta method with Windows is proposed to acquire the reconstructed displacements of considered bridges. To demonstrate the accuracy and applicability of the proposed approach, three different experiments are carried out; (i) A small scale bridge with the implementation of MEMS acceleration sensors; (ii) a numerical complex finite element method (FEM) bridge model; (iii) an actual bridge with the implementation of MEMS acceleration sensors and narrow bandwidth Internet of things (NB-IoT) technology. The first experiment shows that the proposed method can successfully identify the difference between damaged/undamaged bridges and determine damage location. The second experiment indicates that the proposed method is able to identify the difference between stiffened/unstiffened bridges. The last experiment shows the applicability of the proposed method on an actual bridge health monitoring project.

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“…Static influence line deflection [15][16][17] Dynamic properties are not needed. The influencing factors are loading, stiffness, and mass of bridges.…”

Section: Methods Descriptionsmentioning

confidence: 99%

Bridge Health Monitoring via Displacement Reconstruction-Based NB-IoT Technology

et al. 2020

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“…However, the drawback of the proposal is that it requires deformation measurements at many locations along the length of the structure, which makes bridge closures likely. Zeinali et al (2017Zeinali et al ( , 2018 present a novel theoretical framework for estimating the flexural stiffness of a bridge deck using its deflection or rotation responses to a moving load. It is demonstrated through numerical and relatively simple experimental studies that the stiffness of the entire bridge span can be estimated.…”

Section: Rotation Measurement In Bridgesmentioning

confidence: 99%

Identifying damage in a bridge by analysing rotation response to a moving load

Hester

Huseynov

O’Brien

et al. 2019

Structure and Infrastructure Engineering

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This paper proposes a bridge damage detection method using direct rotation measurements. Initially, numerical analyses are carried out on a 1-D simply supported beam model loaded with a single moving point load to investigate the sensitivity of rotation as a main parameter for damage identification. As a result of this study, the difference in rotation measurements due to a single moving point load obtained for healthy and damaged states is proposed as a damage indicator. A relatively simple laboratory experiment is conducted on a 3 m long simply supported beam structure to validate the results obtained from the numerical analysis. The case of multi-axle vehicles is investigated through numerical analyses of a 1-D bridge model and a theoretical basis for damage detection is presented. Finally, a sophisticated 3-D dynamic Finite Element model of a 20 m long simply supported bridge structure is developed by an independent team of researchers and used to test the robustness of the proposed damage detection methodology in a series of blind tests. Rotations from an extensive range of damage scenarios were provided to the main team who applied their methods without prior knowledge of the extent or location of the damage. Results from the blind test simulations demonstrate that the proposed methodology provides a reasonable indication of the bridge condition for all test scenarios.

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“…One disadvantage of this method is its dependence on an accurate finite element model (FEM), which brings extra difficulties and errors to practical applications. Zeinali and Story (2017) proposed a theoretical framework for estimating the flexural rigidity based on the second derivative of DIL and identifying both the location and severity of damage. This damage quantification method can be performed without establishing FEMs, and its damage index has a clear physical meaning.…”

Section: Introductionmentioning

confidence: 99%

Damage quantification of beam structures using deflection influence line changes and sparse regularization

Chen

Zhao

Zhang

et al. 2021

Advances in Structural Engineering

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Influence line (IL) has emerged as very promising damage indices for bridge damage detection. This study proposed a method to localize and quantify damage in beam structures by estimating section flexibility change from deflection IL (DIL) change. To this end, the relationship between second derivative of DIL change and flexibility change was established. To remove noise interference in measurement, piecewise quadratic functions were used to fit and replace noisy DIL change curves, wherein the coefficients of quadratic function were determined via a sparse regularization method, considering the sparsity nature of damage that typically takes place in only a limited number of elements. The feasibility and accuracy of the proposed method are verified through numerical examples and laboratory experiments. Through four hypothetical damage scenarios of a simply supported beam with one or two damaged locations, its ability to quantify minor damage and its anti-noise robustness were well verified. Finally, a laboratory experiment on a simply supported aluminum beam illustrated that the location and extent of damage could be successfully identified in the single-damage and double-damage cases. The numerical and experimental results indicate that the proposed method is promising for future damage localization and quantification of bridge structures.

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Framework for Flexural Rigidity Estimation in Euler-Bernoulli Beams Using Deformation Influence Lines

Cited by 28 publications

References 23 publications

Bridge Health Monitoring via Displacement Reconstruction-Based NB-IoT Technology

Bridge Health Monitoring via Displacement Reconstruction-Based NB-IoT Technology

Identifying damage in a bridge by analysing rotation response to a moving load

Damage quantification of beam structures using deflection influence line changes and sparse regularization

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