Recent Advancements and Future Trends in Indirect Bridge Health Monitoring

Singh, Pahup; Mittal, Shivank; Sadhu, Ayan

doi:10.1061/ppscfx.sceng-1259

Cited by 18 publications

(5 citation statements)

References 107 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since the vehicle's wheels are not always on the nodes exactly, when the wheel is not on the nodes, the Hermitian cubic interpolation function is employed to distribute the CP force to its two adjacent nodes. For example, in Figure 1, if it is assumed that the frst two wheels are on the bridge's fth element and the two rear wheels are on its r th element, the transmission between the CP force and nodal force can be calculated by equations ( 5)- (7).…”

Section: Interaction Modelmentioning

confidence: 99%

See 1 more Smart Citation

Bridge Frequency Scanning Using the Contact-Point Response of an Instrumented 3D Vehicle: Theory and Numerical Simulation

Lin

Zhang

2023

Structural Control and Health Monitoring

View full text Add to dashboard Cite

Scanning the bridge’s frequencies from the passing vehicle’s vibration data has been frequently investigated recently. However, in previous studies, vehicles were typically simplified to quarter- or half-car models, and apparent disparity could be observed between the models and real vehicles. To make the vehicle model more practical, in this study, a 3D vehicle model is built to extract the bridge’s frequencies from vehicle vibrations. For the first time, equations for calculating the contact-point (CP) response of the 3D vehicle model are derived with tire damping. Furthermore, residual CP responses between front and rear wheels are utilized to eliminate the inverse effects of road roughness, making the bridge frequencies outstanding in the frequency domain. The robustness of the proposed method is tested under different influence factors, and two possible measurement errors are as follows: the sensor position and axle distance when applying the proposed method in engineering. Results show that the proposed method performs stably under the influence of different road roughness classes and tire damping. Bridge frequencies can be identified when the vehicle is travelling at a highway speed (108 km/h in this study). Environmental noises can submerge the bridge’s high-order frequencies but have little influence on the low-frequency range. High bridge damping will restrain the transmission of bridge vibration to the vehicle, making high-order bridge frequencies less visible. In addition, the errors introduced by a vehicle body sensor position can be eliminated when calculating the CP responses for tires, thus will not influence bridge frequency identification. To avoid possible errors induced by manual measurement of the axle distance, a novel cross-correlation function-based method is employed, which is verified effective and practical for calculating residual CP responses.

show abstract

Section: Interaction Modelmentioning

confidence: 99%

“…In addition, the proposed method can ft various bridges and thus can be potential to extract a large number of bridges' frequencies rapidly without interrupting the ongoing trafc. Due to the above reasons, the characteristics of the VSM idea attract much interest from scholars all over the world [6,7].…”

Section: Introductionmentioning

confidence: 99%

Bridge Frequency Scanning Using the Contact-Point Response of an Instrumented 3D Vehicle: Theory and Numerical Simulation

Lin

Zhang

2023

Structural Control and Health Monitoring

View full text Add to dashboard Cite

show abstract

“…The American Infrastructure Report Card 2021 (ASCE 2021) highlighted the importance of protecting aging civil infrastructure, revealing that one-third of America’s infrastructure is vulnerable to rapid deterioration. Over the last several years, there has been significant development in SHM technologies to undertake robust, rapid, and remote structural inspection [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. However, traditional SHM techniques face significant implementation challenges under adverse weather and busy operational conditions worldwide.…”

Section: Introductionmentioning

confidence: 99%

Augmented Reality-Based Real-Time Visualization for Structural Modal Identification

Carter,

Sakr,

Sadhu

2024

Sensors

Self Cite

View full text Add to dashboard Cite

In the era of aging civil infrastructure and growing concerns about rapid structural deterioration due to climate change, the demand for real-time structural health monitoring (SHM) techniques has been predominant worldwide. Traditional SHM methods face challenges, including delays in processing acquired data from large structures, time-intensive dense instrumentation, and visualization of real-time structural information. To address these issues, this paper develops a novel real-time visualization method using Augmented Reality (AR) to enhance vibration-based onsite structural inspections. The proposed approach presents a visualization system designed for real-time fieldwork, enabling detailed multi-sensor analyses within the immersive environment of AR. Leveraging the remote connectivity of the AR device, real-time communication is established with an external database and Python library through a web server, expanding the analytical capabilities of data acquisition, and data processing, such as modal identification, and the resulting visualization of SHM information. The proposed system allows live visualization of time-domain, frequency-domain, and system identification information through AR. This paper provides an overview of the proposed technology and presents the results of a lab-scale experimental model. It is concluded that the proposed approach yields accurate processing of real-time data and visualization of system identification information by highlighting its potential to enhance efficiency and safety in SHM by integrating AR technology with real-world fieldwork.

show abstract

“…This method, first proposed by Yang et al [7], has recently gained significant recognition. The main objective in this research direction is to find a reliable method to determine the vertical vibration responses of desired locations on a bridge without the need for expensive fixed sensors or with minimal sensor requirements [8,9]. For example, Malekjafarian and O'Brien [10] developed a method for identifying bridge mode shapes using short time frequency domain decomposition (STFDD) of responses measured in a passing vehicle.…”

Section: Introductionmentioning

confidence: 99%

A Mobile Sensing Framework for Bridge Modal Identification through an Inverse Problem Solution Procedure and Moving-Window Time Series Models

Talebi-Kalaleh,

Mei

2023

Sensors

View full text Add to dashboard Cite

With the rise and development of smart infrastructures, there has been a great demand for installing automatic monitoring systems on bridges, which are key members of transportation networks. In this regard, utilizing the data collected by the sensors mounted on the vehicles passing over the bridge can reduce the costs of the monitoring systems, compared with the traditional systems where fixed sensors are mounted on the bridge. This paper presents an innovative framework for determining the response and for identifying modal characteristics of the bridge, utilizing only the accelerometer sensors on the moving vehicle passing over it. In the proposed approach, the acceleration and displacement response of some virtual fixed nodes on the bridge is first determined using the acceleration response of the vehicle axles as the input. An inverse problem solution approach based on a linear and a novel cubic spline shape function provides the preliminary estimations of the bridge’s displacement and acceleration responses, respectively. Since the inverse solution approach is only capable of determining the response signal of the nodes with high accuracy in the vicinity of the vehicle axles, a new moving-window signal prediction method based on auto-regressive with exogenous time series models (ARX) is proposed to complete the responses in the regions with large errors (invalid regions). The mode shapes and natural frequencies of the bridge are identified using a novel approach that integrates the results of singular value decomposition (SVD) on the predicted displacement responses and frequency domain decomposition (FDD) on the predicted acceleration responses. To evaluate the proposed framework, various numerical but realistic models for a single-span bridge under the effect of a moving mass are considered; the effects of different levels of ambient noise, the number of axles of the passing vehicle, and the effect of its speed on the accuracy of the method are investigated. The results show that the proposed method can identify the characteristics of the three main modes of the bridge with high accuracy.

show abstract

Recent Advancements and Future Trends in Indirect Bridge Health Monitoring

Cited by 18 publications

References 107 publications

Bridge Frequency Scanning Using the Contact-Point Response of an Instrumented 3D Vehicle: Theory and Numerical Simulation

Bridge Frequency Scanning Using the Contact-Point Response of an Instrumented 3D Vehicle: Theory and Numerical Simulation

Augmented Reality-Based Real-Time Visualization for Structural Modal Identification

A Mobile Sensing Framework for Bridge Modal Identification through an Inverse Problem Solution Procedure and Moving-Window Time Series Models

Contact Info

Product

Resources

About