Bridge Displacement Estimation Using a Co-Located Acceleration and Strain

Sarwar, Muhammad Zohaib; Park, Jong Woong

doi:10.3390/s20041109

Cited by 29 publications

(16 citation statements)

References 29 publications

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“…The snow load causes deflection (f max). Such a situation can be modeled by loading the straight beam [20,21]. Considering the elementary section of the beam (Figure 8).…”

Section: Methods and Assumptionsmentioning

confidence: 99%

Structural Health Monitoring System for Snow and Wind Load Measurement

Dziadak

2020

Electronics

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This article presents a system for monitoring the load caused by strong winds and snow on buildings’ roofs. An estimation of the total load on the structure is obtained by measuring the strain on the main roof girders. The system is based on a wireless sensor network structure. The measurement node uses metal strain gauges and strain sensors based on conductive carbon polymers. The application of such sensors allowed us to achieve a measurement resolution of 5.5 ustrain. The node is managed by an Atmeg8A microcontroller. The use of energy saving modes allows for a battery life of 6 months.

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“…The snow load causes deflection (f max). Such a situation can be modeled by loading the straight beam [20,21]. Considering the elementary section of the beam (Figure 8).…”

Section: Methods and Assumptionsmentioning

confidence: 99%

Structural Health Monitoring System for Snow and Wind Load Measurement

Dziadak

2020

Electronics

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“…Zhu et al [46] used a multi-rate Kalman filter approach to combine acceleration and strain data to estimate displacements in tall, slender structures. Sarwar et al [47] applied an adaptive Kalman filter to fuse collocated acceleration and strain measurements to estimate bridge displacements. Kalman filter-based data fusion has been widely employed for displacement estimation, and will be used for the application discussed herein.…”

Section: Application: Multimetric Displacement Estimationmentioning

confidence: 99%

Development and Validation of a Framework for Smart Wireless Strain and Acceleration Sensing

Lawal

Najafi

Hoang

et al. 2022

Sensors

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Civil infrastructure worldwide is subject to factors such as aging and deterioration. Structural health monitoring (SHM) can be used to assess the impact of these processes on structural performance. SHM demands have evolved from routine monitoring to real-time and autonomous assessment. One of the frontiers in achieving effective SHM systems has been the use of wireless smart sensors (WSSs), which are attractive compared to wired sensors, due to their flexibility of use, lower costs, and ease of long-term deployment. Most WSSs use accelerometers to collect global dynamic vibration data. However, obtaining local behaviors in a structure using measurands such as strain may also be desirable. While wireless strain sensors have previously been developed by some researchers, there is still a need for a high sensitivity wireless strain sensor that fully meets the general demands for monitoring large-scale civil infrastructure. In this paper, a framework for synchronized wireless high-fidelity acceleration and strain sensing, which is commonly termed multimetric sensing in the literature, is proposed. The framework is implemented on the Xnode, a next-generation wireless smart sensor platform, and integrates with the strain sensor for strain acquisition. An application of the multimetric sensing framework is illustrated for total displacement estimation. Finally, the potential of the proposed framework integrated with vision-based measurement systems for multi-point displacement estimation with camera-motion compensation is demonstrated. The proposed approach is verified experimentally, showing the potential of the developed framework for various SHM applications.

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“…The Kalman filter, actively studied for the accuracy enhancement in aerospace engineering, was also applied to the IDEAS [ 24 ]. IDEAS using FIR and Kalman filter has been widely adopted to indirectly estimate displacement based on the strain and acceleration data [ 25 , 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Structural Responses Estimation of Cable-Stayed Bridge from Limited Number of Multi-Response Data

Byun

Lee

Won

et al. 2022

Sensors

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A cable-stayed bridge is widely adopted to construct long-span bridges. The deformation of cable-stayed bridges is relatively larger than that of conventional bridges, such as beam and truss types. Therefore, studies regarding the monitoring systems for cable-stayed bridges have been conducted to evaluate the performance of bridges based on measurement data. However, most studies required sufficient measurement data for evaluation and just focused on the local response estimation. To overcome these limitations, Structural Responses Analysis using a Limited amount of Multi-Response data (SRALMR) was recently proposed and validated with the beam and truss model that has a simple structural behavior. In this research, the structural responses of a cable-stayed bridge were analyzed using SRALMR. The deformed shape and member internal forces were estimated using a limited amount of displacement, slope, and strain data. Target structural responses were determined by applying four load cases to the numerical model. In addition, pre-analysis for initial shape analysis was conducted to determine the initial equilibrium state, minimizing the deformation under dead loads. Finally, the performance of SRALMR for cable-stayed bridges was analyzed according to the combination and number of response data.

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Bridge Displacement Estimation Using a Co-Located Acceleration and Strain

Cited by 29 publications

References 29 publications

Structural Health Monitoring System for Snow and Wind Load Measurement

Structural Health Monitoring System for Snow and Wind Load Measurement

Development and Validation of a Framework for Smart Wireless Strain and Acceleration Sensing

Structural Responses Estimation of Cable-Stayed Bridge from Limited Number of Multi-Response Data

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