Wavelet-Entropy Approach for Detection of Bridge Damages Using Direct and Indirect Bridge Records

Tan, Chao; Elhattab, Ahmed; Uddin, Nasim

doi:10.1061/(asce)is.1943-555x.0000577

Cited by 26 publications

(7 citation statements)

References 38 publications

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“…Road and bridge health monitoring is mainly with the help of testing equipment for urban road and bridge bearing capacity and other aspects of the overall systematic inspection and evaluation through the monitoring results of a series of follow-up maintenance and repair work, the development of the program in order to achieve the desired purpose [9][10]. In this regard, the work must be based on science; the main purpose is to make the bridge safer, so bridge health monitoring is very important [11][12].…”

Section: Introductionmentioning

confidence: 99%

Research on Intelligent Monitoring Technology of Municipal Road and Bridge Engineering Construction and Quality

Wang

2024

Applied Mathematics and Nonlinear Sciences

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This study addresses quality control challenges in municipal road and bridge construction by introducing an intelligent monitoring approach. Utilizing three-dimensional laser scanning, we monitor roadbed settlement and deformation accurately. Compaction quality is assessed through vibration acceleration metrics from milling operations, applying a compaction monitoring value. Furthermore, a combination of regression models and stochastic processes in a Kriging function model evaluates the reliability of detecting bridge steel corrosion. In J city’s political road bridge analysis, we observed a differential settlement with the least affected areas showing subsidence within 250mm. In contrast, the most impacted point, B1, recorded a settlement of 2597mm in December. Compaction quality monitoring revealed that control error margins for E and CV indicators lie between −2.65% to 2.35% and −2.7% to 2.6%, respectively, demonstrating a narrower error range for E compared to CV.

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Section: Introductionmentioning

confidence: 99%

Research on Intelligent Monitoring Technology of Municipal Road and Bridge Engineering Construction and Quality

Wang

2024

Applied Mathematics and Nonlinear Sciences

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“…Contrary to the classical time-consuming in situ measurement methods, Yang et al [10] proposed to determine the natural frequencies of a road bridge from the measured dynamic response of crossing vehicles and later verified the proposed method through in situ tests [11]. The proposed technique, named vehicle-based indirect Structural Health Monitoring (iSHM) or 'drive-by' bridge SHM, provides a promising method, namely by using the indirect measurements from a moving vehicle [12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Application of Vehicle-Based Indirect Structural Health Monitoring Method to Railway Bridges—Simulation and In Situ Test

Reiterer,

Bettinelli,

Schellander

et al. 2023

Applied Sciences

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In recent years, the vehicle-based indirect Structural Health Monitoring (iSHM) method has been increasingly used to identify the dynamic characteristics of railway bridges during train crossings, and it has been shown that this method has several advantages compared to traditional SHM methods. A major advantage is that sensors are just mounted on the vehicle, and no sensors or data acquisition systems need to be installed on the railway bridge. In this paper, the application of the vehicle-based iSHM method is demonstrated numerically and experimentally for determining the natural frequencies of railway steel bridges during train crossing. The coupled linear equations of motion of the train-bridge multi-body system are derived, and train crossing simulations are conducted numerically, considering different train speeds. Three different railway bridges are considered, and the train-induced vibration responses are calculated for both the train multi-body system and the railway bridge models. Different representative evaluation points are chosen for the wheelsets, bogies, and car bodies of the considered vehicle. To calibrate the numerical model, the resonance frequencies of an existing single-span steel bridge are measured in situ by the application of forced vibration tests. Besides the executed in situ measurements of the bridge, the considered crossing vehicle is also instrumented with several accelerometers at the wheelsets, bogies, and car bodies, and the vibration responses of both the bridge and the crossing vehicle are measured simultaneously during the duration of several train crossings with different train speeds. The recorded vibration responses are analyzed in the frequency domain and compared with numerical simulation results. It is shown that the first bending frequency of the considered railway bridge can be clearly identified from the computed frequency response spectra and that the vehicle-based iSHM method provides a promising tool for identifying the dynamic characteristics of railway bridges.

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“…Wavelet transform based methods have been used to separate the bridge dynamic information from the vehicle dynamic response (Jian et al, 2020; Li et al, 2021). However, the selection for the optimal wavelet parameters is an arbitrary process that may cause uncertainties (Tan et al, 2020). Empirical mode decomposition (EMD) as a data-adaptive technique has been used to decompose vehicle response (Yang and Chang, 2009; Yang and Lee, 2018) into a set of intrinsic mode functions (IMFs).…”

Section: Introductionmentioning

confidence: 99%

Bridge modal identification based on successive variational mode decomposition using a moving test vehicle

Zhu

Guo

2022

Advances in Structural Engineering

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Bridge modal identification using an instrumented test vehicle as a moving sensor is promising but challenging. A key factor is to extract bridge dynamic components from vehicle responses measured when the bridge is operating. A new method based on an advanced adaptive signal decomposition technique, the successive variational mode decomposition (SVMD), has been developed to estimate the bridge modal parameters from the dynamic responses of a passing test vehicle. When bridge-related dynamic components are extracted from the decomposition, the natural excitation technique and/or random-decrement technique based fitting methods are used to estimate the modal frequencies and damping ratios of the bridge. Effects of measurement noise, moving speed and vehicle properties on the decomposition are investigated numerically. The superiority of SVMD in the decomposition is verified by comparing to another adaptive decomposition technique, the singular spectrum decomposition. The results of the proposed method confirm that the bridge modal frequencies can be identified from bridge related components with high accuracy, while damping ratio is more sensitive to the random operational load. Finally, the feasibility of the proposed method for bridge monitoring using a moving test vehicle is further verified by an in-situ experimental test on a cable-stayed bridge. The components related to the bridge dynamic responses are successfully extracted from vehicle responses.

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Wavelet-Entropy Approach for Detection of Bridge Damages Using Direct and Indirect Bridge Records

Cited by 26 publications

References 38 publications

Research on Intelligent Monitoring Technology of Municipal Road and Bridge Engineering Construction and Quality

Research on Intelligent Monitoring Technology of Municipal Road and Bridge Engineering Construction and Quality

Application of Vehicle-Based Indirect Structural Health Monitoring Method to Railway Bridges—Simulation and In Situ Test

Bridge modal identification based on successive variational mode decomposition using a moving test vehicle

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