Technical Papers
Apr 10, 2024

Wear Detection of Bridge Sliding Bearing Based on Temporal Variation of Thermally Induced Daily Displacement Amplitude

Publication: Journal of Bridge Engineering
Volume 29, Issue 6

Abstract

Sliding bearings are a vulnerable component of bridges. Bearing wear will affect the free expansion of the bridge structure and produce greater temperature stress, resulting in damage to the main girder and other components of the bridge. In the process of bridge operation, the timely detection of bearing wear is very important for ensuring structural safety. Therefore, this paper proposes a wear detection method for bridge sliding bearings based on displacement amplitude by eliminating the effects of daily temperature variations. First, the bearing mechanical behavior under temperature effects and the correlation between temperature and bearing friction force are analyzed. The bearing displacement hysteresis model under temperature effects is established, and the variation in thermally induced bearing displacement after wear is obtained. Then, the correlation between temperature and thermally induced bearing displacement is analyzed and, based on the particle swarm optimization (PSO) algorithm and long short-term memory (LSTM) neural network, a multivariate temperature–displacement correlation model is established to achieve the accurate prediction of thermally induced bearing displacement and the elimination of temperature effects. According to the variation in the thermally induced displacement of the bearing after wear, the indicator of thermally induced displacement amplitude errors (TDAE) is proposed, and the cumulative sum (CUSUM) control chart is used to detect the bearing anomaly. Finally, a long-span bridge is analyzed as an example. The results show that the proposed TDAE detection indicator can effectively reflect the sliding friction force of the bridge bearing, and the proposed detection method can accurately detect the sliding bearing wear, which can provide effective information for the bridge caretakers to monitor the occurrence of bearing wear and replace the bearing slide plate in a timely manner.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

All data, models, or codes that support the findings of this study are available from the corresponding author upon request.

Acknowledgments

This research work was jointly supported by the National Natural Science Foundation of China (Grant Nos. 52078102, 52322807, and 52250011) and the Key Laboratory of Performance Evolution and Control for Engineering Structures in Tongji University, Ministry of Education (Grant No. 2022KF-1).

References

Adamov, A. A., and АА Kamenskikh. 2019. “Comparative analysis of the contact deformation of the spherical sliding Layer of the bearing with and without taking into account the grooves with lubricant.” IOP Conf. Ser.: Mater. Sci. Eng. 581 (1): 012031. https://doi.org/10.1088/1757-899X/581/1/012031.
Ala, N., E. H. Power, and A. Azizinamini. 2016. “Experimental evaluation of high-performance sliding surfaces for bridge bearings.” J. Bridge Eng. 21 (2): 04015034. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000708.
Al-Anany, Y. M., and M. J. Tait. 2017. “Experimental assessment of utilizing fiber reinforced elastomeric isolators as bearings for bridge applications.” Composites, Part B 114: 373–385. https://doi.org/10.1016/j.compositesb.2017.01.060.
Aria, M., and R. Akbari. 2013. “Inspection, condition evaluation and replacement of elastomeric bearings in road bridges.” Struct. Infrastruct. Eng. 9 (9): 918–934. https://doi.org/10.1080/15732479.2011.638171.
Crivellari, A., and E. Beinat. 2020. “Forecasting spatially-distributed urban traffic volumes via multi-target LSTM-based neural network regressor.” Mathematics 8 (12): 2233. https://doi.org/10.3390/math8122233.
Dorafshan, S., K. R. Johnson, M. Maguire, M. W. Halling, P. J. Barr, and M. Culmo. 2019. “Friction coefficients for slide-in bridge construction using PTFE and steel sliding bearings.” J. Bridge Eng. 24 (6): 04019045. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001417.
Du, Y.-L., T.-H. Yi, X.-J. Li, X.-L. Rong, L.-J. Dong, D.-W. Wang, G. Yang, and Z. Leng. 2023. “Advances in intellectualization of transportation infrastructures.” Engineering 24 (4): 239. https://doi.org/10.1016/j.eng.2023.01.011.
Freire, L. M. R., J. De Brito, and J. R. Correia. 2015. “Inspection survey of support bearings in road bridges.” J. Perform. Constr. Facil. 29 (4): 04014098. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000569.
Fu, Y., and J. T. DeWolf. 2001. “Monitoring and analysis of a bridge with partially restrained bearings.” J. Bridge Eng. 6 (1): 23–29. https://doi.org/10.1061/(ASCE)1084-0702(2001)6:1(23).
Guo, T., J. Liu, and L. Huang. 2016. “Investigation and control of excessive cumulative girder movements of long-span steel suspension bridges.” Eng. Struct. 125: 217–226. https://doi.org/10.1016/j.engstruct.2016.07.003.
Han, Q., Q. Ma, J. Xu, and M. Liu. 2021. “Structural health monitoring research under varying temperature condition: A review.” J. Civ. Struct. Health Monit. 11 (1): 149–173. https://doi.org/10.1007/s13349-020-00444-x.
Huang, H.-B., T.-H. Yi, H.-N. Li, and H. Liu. 2022. “Sparse Bayesian identification of temperature‒displacement model for performance assessment and early warning of bridge bearings.” J. Struct. Eng. 148 (6): 04022052. https://doi.org/10.1061/(ASCE)ST.1943-541X.0003354.
Kim, S.-H., H.-S. Mha, and S.-W. Lee. 2006. “Effects of bearing damage upon seismic behaviors of a multi-span girder bridge.” Eng. Struct. 28 (7): 1071–1080. https://doi.org/10.1016/j.engstruct.2005.11.015.
Li, B., Y. Li, X. Liu, X. Liu, S. Zhu, and L. Ke. 2023. “Section optimization design of UHPC beam bridges based on improved particle swarm optimization.” Front. Mater. 10: 1276118. https://doi.org/10.3389/fmats.2023.1276118.
Liang, Y.-X., Q.-S. Feng, M.-Z. Fu, B.-T. Wu, J.-F. Lu, and G.-X. Tang. 2022. “Prediction and monitoring of the construction vibration effect on an adjacent old long span double-convex arch bridge.” KSCE J. Civ. Eng. 26 (5): 2183–2201. https://doi.org/10.1007/s12205-022-2170-2.
Ma, F., X. Cheng, X. Zhu, G. Wu, D.-C. Feng, S. Hou, and X. Kang. 2022. “Safety monitoring of bearing replacement for a concrete high-speed railway bridge based on acoustic emission.” J. Perform. Constr. Facil 36 (3): 04022014. https://doi.org/10.1061/(ASCE)CF.1943-5509.0001719.
Mahboubi, S., and M. R. Shiravand. 2019. “Seismic evaluation of bridge bearings based on damage index.” Bull. Earthquake Eng. 17 (7): 4269–4297. https://doi.org/10.1007/s10518-019-00614-3.
Miao, P., H. Yokota, and Y. Zhang. 2023. “Deterioration prediction of existing concrete bridges using a LSTM recurrent neural network.” Struct. Infrastruct. Eng. 19 (4): 475–489. https://doi.org/10.1080/15732479.2021.1951778.
Niu, S., X. Ouyang, and Y. Liu. 2021. “Experimental study on the influence of temperature on the wear performance of polymer sliding plate materials for bridge bearings.” IOP Conf. Ser.: Earth Environ. Sci. 638 (1): 012095. https://doi.org/10.1088/1755-1315/638/1/012095.
Siringoringo, D. M., and Y. Fujino. 2008. “System identification of suspension bridge from ambient vibration response.” Eng. Struct. 30 (2): 462–477. https://doi.org/10.1016/j.engstruct.2007.03.004.
Steelman, J. S., L. A. Fahnestock, J. F. Hajjar, and J. M. LaFave. 2016. “Performance of nonseismic PTFE sliding bearings when subjected to seismic demands.” J. Bridge Eng. 21 (1): 04015028. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000777.
Ülker-Kaustell, M., and R. Karoumi. 2013. “Influence of rate-independent hysteresis on the dynamic response of a railway bridge.” Int. J. Rail Transp. 1 (4): 237–257. https://doi.org/10.1080/23248378.2013.835129.
Wang, G., Y. Ding, H. Guo, and X. Zhao. 2018. “Safety evaluation of the wear life of high-speed railway bridge bearings by monitoring train-induced dynamic displacements.” Shock Vib. 2018: 6479480. https://doi.org/10.1155/2018/6479480.
Wu, G.-M., T.-H. Yi, D.-H. Yang, H.-N. Li, and H. Liu. 2021. “Early warning method for bearing displacement of long-span bridges using a proposed time-varying temperature‒displacement model.” J. Bridge Eng. 26 (9): 04021068. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001763.
Yue, Z., Y. Ding, H. Zhao, and Z. Wang. 2022. “Ultra-high precise Stack-LSTM-CNN model of temperature-induced deflection of a cable-stayed bridge for detecting bridge state driven by monitoring data.” Structures 45: 110–125. https://doi.org/10.1016/j.istruc.2022.09.011.
Zeng, L., Y. Liu, G. Zhang, L. Tang, Z. Jiang, and Z. Liu. 2018. “Analysis of structural responses of bridges based on long-term structural health monitoring.” Mech. Adv. Mater. Struct. 25 (1): 79–86. https://doi.org/10.1080/15376494.2016.1243283.
Zhou, H. F., Y. Q. Ni, and J. M. Ko. 2010. “Constructing input to neural networks for modeling temperature-caused modal variability: Mean temperatures, effective temperatures, and principal components of temperatures.” Eng. Struct. 32 (6): 1747–1759. https://doi.org/10.1016/j.engstruct.2010.02.026.

Information & Authors

Information

Published In

Go to Journal of Bridge Engineering
Journal of Bridge Engineering
Volume 29Issue 6June 2024

History

Received: Aug 20, 2023
Accepted: Feb 1, 2024
Published online: Apr 10, 2024
Published in print: Jun 1, 2024
Discussion open until: Sep 10, 2024

Permissions

Request permissions for this article.

ASCE Technical Topics:

Authors

Affiliations

Dong-Hui Yang, M.ASCE [email protected]
Professor, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China. Email: [email protected]
Jia-Zheng Sun, S.M.ASCE [email protected]
Master's Candidate, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China. Email: [email protected]
Ting-Hua Yi, M.ASCE [email protected]
Professor, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China (corresponding author). Email: [email protected]
Hong-Nan Li, F.ASCE [email protected]
Professor, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China. Email: [email protected]
Hua Liu, Ph.D. [email protected]
Chief Engineer, China Railway Bridge and Tunnel Technologies Co., Ltd., Nanjing 210061, China. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share