AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (2.3 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Status assessment and management strategy of a large bridge based on massive real time data

CCCC-TDC Environmental Engineering Co., Ltd., Tianjin 300461, China
HCIG Communications Investment Co., Ltd., Shijiazhuang, Hebei 050051, China
Show Author Information

Abstract

This study aims to enhance the understanding of the state of large-scale bridge structures by accurately analyzing the structural changes of bridges through extensive real-time monitoring data. By conducting a comparative analysis of field load test data and simulation calculations of linear models, this research seeks to provide a precise assessment of structural indices, identify potential risks, and develop appropriate preventive measures. Using a domestic long-span suspension bridge as a case study, the bridge beam is conceptualized as a multi-degree-of-freedom structure, allowing for the application of linear structural vibration mode decomposition methods. During the on-site load testing, a structural health monitoring system is employed to collect real-time data, which facilitates the calculation of deflection and strain values for each control section under static load conditions. Additionally, the frequency response function, unit pulse response function, and covariance-related functions are utilized to derive the modal parameters of the structure during dynamic load testing. The health monitoring system’s measurements of strain, deflection, and modal parameters are then compared with the analytical results from the tests, while also verifying the operational integrity of the monitoring system. By referencing the assessment methodology for site load tests, this research analyzes the data mining from health monitoring systems to evaluate the bridge’s load-bearing capacity during testing, as well as for subsequent evaluations of the bridge’s structural health and operational status. The experimental findings demonstrate that the load testing equipment and health monitoring system effectively capture significant vehicle loading and unloading events. Furthermore, the analysis of the acquired vibration data yields reliable modal parameters, with deflection calibration coefficients and relative residual coefficients meeting established criteria. The calculated frequencies are found to exceed the theoretically predicted values, indicating that the global stiffness of the structure aligns with design specifications and that the mechanical properties comply with regulatory standards. This reflects the feasibility and effectiveness of the monitoring-based evaluation index system and methodology employed in this study.

References

[1]
Sun, L.M., Zhang, Q.W. Large-span bridges and their health monitoring systems in China[C]//International Symposium on Integrated Life-cycle Design & Management of Infrastructure. 2007.
[2]

Li, H., Ou, J.P. Design and implementation of health monitoring systems for cable-stayed bridges (Ⅱ): implementations[J]. China Civil Engineering Journal, 2006, 39(4): 45–53.

[3]

Masood, M.A., Masood, N.K., Ullah, F.K. Bridge vibration energy harvesting for wireless IoT-based structural health monitoring systems: A review[J]. Journal of Intelligent Material Systems and Structures, 2023, 34(19): 2209–2239.

[4]

Xu, J.F., Feng, Z.M., Li, H.W., et al. Study on vibration amplitude and force identification of cables of cable-stayed bridge based on dynamic monitoring[J]. Journal of Highway and Transportation Research and Development , 2022, 39(2): 111–116.

[5]

Lakshmi, K., Apte, P. A damage detection technique using bridge influence surfaces for structural health monitoring of bridges[J]. Recent Trends in Civil Engineering, 2022, 274: 865–874.

[6]

Wang, C., Zhong, J.W., Zhu, H.P. Fatigue assessment of steel box girder based on measured stress of health monitoring system[J]. Journal of Wuhan University of Science and Technology, 2012, 34(12): 103–107.

[7]

Xu, J.L., Dong, Y.K., Zhang, Z.H. Full scale strain monitoring of a suspension bridge using high performance distributed fiber optic sensors[J]. Measurement Science and Technology, 2016, 27(12): 124017.

[8]
Wei, S.Y., Zhang, Z.H., Li, S.L., et al. Strain features and condition assessment of orthotropic steel deck cable-supported bridges subjected to vehicle loads by using dense FBG strain sensors[J]. Smart Materials and Structures, 2017, 26(10):
[9]

Li, C.X., Li, Y., Chen, Z.Y., et al. Fatigue characteristics of steel box girder diaphragm based on measured traffic flow[J]. Journal of Chang’an University (Natural Science Edition), 2019, 39(5): 48–58.

[10]

Belmokhtar, M., Schmidt, F., Chevalier, C., et al. Vibration-Based Method for Structural Health Monitoring of a Bridge Pier Subjected to Environmental Loads[J]. Experimental Vibration Analysis for Civil Engineering Structures, 2022, 224: 73–82.

[11]

Shi, X.W., Wang, K.M., Jiang, J., et al. Study on loading efficiency of bridge load test based on old and new design codes[J]. GongluJiaoTongKeJI, 2012, 8(9): 263–266.

[12]

Saroufim, A., Issa, M.A., Issa, M.A. Optimized finite element analysis and strengthening assessment of the I-39 Kishwaukee bridge utilizing proof load testing[J]. Journal of Civil Structural Health Monitoring, 2024, 14(3): 545–574.

[13]

Nugroho, U., Wardani, S.P.R., Setiadji, B.H. Rigid pavement acceleration-velocity dynamic behavior induced by traffic load[J]. Civil Engineering and Architecture, 2024, 12(3): 1386–1394.

[14]

Zhang, K.X., Qi, T.Y., Li, D.C., et al. Health Monitoring-Based Assessment of Reinforcement with Prestressed Steel Strand for Cable-Stayed Bridge[J]. Structural Durability & Health Monitoring, 2022, 16(1): 53–80.

[15]
Mohammad, A., Antonio, N., Nafiseh, K., et al. Bridge load testing and damage evaluation using model updating method[J]. Engineering Structures, 2022, 252.
[16]

Wang, G.H., Hu, L.H. Study on damage identification of bridge structure based on the method of element modal strain energy[J]. Journal of the China Railway Society, 2006, 28(3): 83–86.

[17]

He, M.L., Song, J., Lin, H.L., et al. Multi-lane vehicle load and deflection response characteristics of long-span highway bridge[J]. Journal of Highway and Transportation Research and Development, 2022, 39(S2): 76–81,141.

[18]

Cherid, D., Bourahla, N., Laghoub, S.M., et al. Sensor number and placement optimization for detection and localization of damage in a suspension bridge using a hybrid ANN-PCA reduced FRF method[J]. International Journal of Structural Integrity, 2021, 13(1): 133–149.

[19]

Fu, W., Liu, B. Analysis of the Application of Static Load Test in Bridge Bearing Capacity Testing[J]. Journal of Architectural Research and Development, 2024, 8(3): 36–41.

[20]

Győző, K., László, Á.S., István, P., et al. Different conical angle connection of implant and abutment behavior: A static and dynamic load test and finite element analysis study[J]. Materials, 2023, 16(5): 1988–1988.

[21]

Wang, H.Q., Nagayama, T. Response spectrum model of vehicle dynamic load for the prediction of bridge vibration level due to single vehicle-passage[J]. Engineering Structures, 2022, 260: 114180-.

[22]

Yang, Z.K., Yang, Y.X., Yu, H.B. Study on optimal sensor arrangement on bridge structure based on sensitivity and effective independence method[J]. Journal of Highway and Transportation Research and Development, 2022, 39(4): 83–92.

[23]

Huang, G.P., Hu, J.H., Cui, J.F., et al. Study on girder end displacement characteristics of steel truss suspension bridge based on measurement data[J]. Journal of Highway and Transportation Research and Development, 2022, 39(5): 65–73.

[24]
Alessandra, A.D., Rosaria, M.P. Model assessment of a bridge by load and dynamic tests[J]. Engineering Structures, 2023, 275(PA):
Journal of Highway and Transportation Research and Development (English Edition)
Pages 90-102
Cite this article:
Zhou F, Cui Z. Status assessment and management strategy of a large bridge based on massive real time data. Journal of Highway and Transportation Research and Development (English Edition), 2024, 18(4): 90-102. https://doi.org/10.26599/HTRD.2024.9480038

287

Views

16

Downloads

0

Crossref

Altmetrics

Received: 16 August 2024
Revised: 10 October 2024
Accepted: 30 October 2024
Published: 31 December 2024
© The Author(s) 2024.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, http://creativecommons.org/licenses/by/4.0/).

Return