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Simultaneous Identification of Vehicle Load and Structural Damage on Renyihe Bridge

Guo-Mu Ji

Beijing Texida Transportation Facilities, Consultants Co., Ltd., Beijing, P. R. China

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Xiao-Chen Liu

Beijing Texida Transportation Facilities, Consultants Co., Ltd., Beijing, P. R. China

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Yuan Yuan

Beijing Texida Transportation Facilities, Consultants Co., Ltd., Beijing, P. R. China

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Ya-Xin Guo

Beijing Texida Transportation Facilities, Consultants Co., Ltd., Beijing, P. R. China

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Jin-Qiao Chen

DongQu Intelligent Transportation Infrastructure, Technology (Jiangsu) Co., Ltd., Nanjing, P. R. China

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Hao-Ran Hu

DongQu Intelligent Transportation Infrastructure, Technology (Jiangsu) Co., Ltd., Nanjing, P. R. China

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Wei-Jie Yang

DongQu Intelligent Transportation Infrastructure, Technology (Jiangsu) Co., Ltd., Nanjing, P. R. China

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Guang-Dong Liu

Fujian Expressway Maintenance Engineering Co., Fuzhou, P. R. China

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Xiao Fan

China Railway Construction Suzhou Design & Research Institute Co., Suzhou, P. R. China

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Xiao-Xiang Cheng

School of Civil Engineering, Southeast University, Nanjing 211189, P. R. China

National and Local Joint Engineering Research Center for Intelligent Construction and Maintenance, Southeast University, Nanjing, P. R. China

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, and

Shi-Tong Hou

https://orcid.org/0009-0004-0125-2223

School of Civil Engineering, Southeast University, Nanjing 211189, P. R. China

National and Local Joint Engineering Research Center for Intelligent Construction and Maintenance, Southeast University, Nanjing, P. R. China

E-mail Address: shitonghou@seu.edu.cn

Corresponding author.

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https://doi.org/10.1142/S0219455425500750Cited by:1 (Source: Crossref)

Abstract

Simultaneous identification of vehicle load and structural damage is an issue of practical significance in structural health monitoring and maintenance of in-service concrete bridges. However, most methods proposed in history to deal with this engineering issue are solely based on data from a single source of structural vibration response measurement, which are subjected to problems such as incomplete understanding of the structural health, the computational inefficiency and the easy failure of the monitoring system. To this end, this paper proposes a new method of synthesizing data generated from two different types of sensors (the strain gauges and the accelerometers) to simultaneously identify the vehicle load and the structural damage which is established on the theories of weigh-in-motion method based on the strain influence line. The new method, which is supposed to be able to well solve the problems with the traditional approaches disseminated to the profession, is formulated in a flowchart for use, and applied to the actual Renyihe Bridge (a concrete rigid-frame continuous highway bridge with spans of 80 m + 4 × 145 m + 80 m) to validate its effectiveness. The results suggest that the new method is of high accuracy in use in low vehicle speed scenarios and superior to the traditional simultaneous identification approach based on unitary structural acceleration sensing.

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References

1. X. Q. Zhu and S. S. Law, Moving loads identification through regularization, J. Eng. Mech.-ASCE 128(9) (2002) 989–1000. Google Scholar
2. S. Q. Wu and S. S. Law, Statistical moving load identification including uncertainty, Probab. Eng. Mech. 29 (2012) 70–78. Crossref, Web of Science, Google Scholar
3. S. S. Law, J. Q. Bu, X. Q. Zhu and S. L. Chan, Vehicle axle loads identification using finite element method, Eng. Struct. 26 (2004) 1143–1153. Web of Science, Google Scholar
4. C. Q. Yang, D. Yang, Y. He, Z. S. Wu, Y. F. Xia and Y. F. Zhang, Moving load identification of small and medium-sized bridges based on distributed optical fiber sensing, Int. J. Struct. Stab. Dyn. 16(4) (2016) 1640021. Web of Science, Google Scholar
5. P. Asnachinda, T. Pinkaew and J. A. Laman, Multiple vehicle axle load identification from continuous bridge bending moment response, Eng. Struct. 30 (2008) 2800–2817. Web of Science, Google Scholar
6. K. Lee et al., Damage-detection approach for bridges with multi-vehicle loads using convolutional autoencoder, Sensors 1839 (2022) 19. Google Scholar
7. R. Ono, T. M. Ha and S. Fukada, Analytical study on damage detection method using displacement influence lines of road bridge slab, J. Civil Struct. Health Monitor. 9 (2019) 565–577. Web of Science, Google Scholar
8. Y. Zhang and K. V. Yuen, Review of artificial intelligence-based bridge damage detection, Adv. Mech. Eng. 14(9) (2022) 1–21, https://doi.org/10.1177/16878132221122770. Google Scholar
9. J. H. Fan, Z. H. Xiao and X. X. Cheng, Numerical simulations of modal tests on Yingzhou bridge using a passing vehicle as the excitation, Exp. Tech. 46 (2022) 529–541. Web of Science, Google Scholar
10. Y. Oshima, Y. Kobayashi, T. Yamaguchi and K. Sugiura, Eigenfrequency estimation for bridges using the response of a passing vehicle with excitation system, in Bridge Maintenance, Safety, Management, Health Monitoring and Informatics-Proc. 4th Int. Conf. Bridge Maintenance, Safety and Management (CRC Press, 2008). Google Scholar
11. X. X. Cheng and Y. C. Liao, Structural safety assessment oriented modal experiments on Renyihe bridge using vehicle excitations, Structures 56 (2023) 105016. Web of Science, Google Scholar
12. L. Dai et al., Effects of vehicle speed on vehicle-induced dynamic behaviors of a concrete bridge with smooth and rough road surfaces, Appl. Sci. 13 (2023) 9460. Crossref, Google Scholar
13. S. Pourzeynali et al., Simultaneous identification of bridge structural damage and moving loads using the explicit form of newmark- $β$ method: Numerical and experimental studies, Remote Sens. 14 (2022) 119. Google Scholar
14. H. Zhu et al., Structural damage and force identification under moving load, Struct. Eng. Mech. 53(2) (2015) 261–276. Web of Science, Google Scholar
15. Z. R. Lu and J. K. Liu, Identification of both structural damages in bridge deck and vehicular parameters using measured dynamic responses, Comput. Struct. 89 (2011) 1397–1405. Crossref, Web of Science, Google Scholar
16. D. Feng, H. Sun and M. Q. Feng, Simultaneous identification of bridge structural parameters and vehicle loads, Comput. Struct. 157 (2015) 76–88. Crossref, Web of Science, Google Scholar
17. L. Zhang et al., Synchronous identification of damage and vehicle load on simply supported bridges based on long-Gauge fiber Bragg grating sensors, J. Perform. Construct. Facil. ASCE 34(1) (2020) 04019097. Web of Science, Google Scholar
18. F. Moses, Weigh-in-motion system using instrumented bridges, Transp. Eng. J. 105(3) (1979) 233–249. Google Scholar
19. Y. He, Study on load identification technology of small and medium bridges based on influence line, MSc Dissertation, Southeast University, Nanjing, China (2015) (in Chinese). Google Scholar
20. Shanxi Provincial Transportation Construction Engineering Quality Testing Center, Bridge Technical Condition Inspection Report for Renyihe Bridge, Report QS1-2020-1189, Taiyuan, China (2020) (in Chinese). Google Scholar
21. X. X. Cheng, J. H. Fan and Z. H. Xiao, Finite element model updating for the Tsing Ma Bridge tower based on surrogate models, J. Low Frequen. Noise, Vib. Active Control 41(2) (2022) 500–518. Crossref, Web of Science, Google Scholar
22. X. L. Liu et al., Comprehensive evaluation method of cable-stayed bridges with multi-index evidence fusion, J. Harbin Inst. Technol. 49(3) (2017) 74–79 (in Chinese). Google Scholar
23. S. Cho et al., Reference-free displacement estimation of bridges using Kalman filter-based multimetric data fusion, J. Sens. 9 (2016) 3791856. Google Scholar
24. M. Ahmed, O. Moselhi and A. Bhowmick, Two-tier data fusion method for bridge condition assessment, Canad. J. Civil Eng. 45(3) (2018) 197–214. Web of Science, Google Scholar
25. X. X. Cheng et al., Structural health monitoring-oriented finite-element model for a large transmission tower, Int. J. Civil Eng. 16(1) (2018) 79–92. Crossref, Google Scholar
26. A. P. Adewuyi, Z. Wu and N. H. M. K. Serker, Assessment of vibration-based damage identification methods using displacement and distributed strain measurements, Struct. Health Monitor. 8(6) (2009) 443–461. Web of Science, Google Scholar
27. Y. Xu, J. M. W. Brownjohn, D. Hester and K. Y. Koo, Long-span bridges: Enhanced data fusion of GPS displacement and deck accelerations, Eng. Struct. 147 (2017) 639–651. Web of Science, Google Scholar
28. R. Ferrari et al., Fusion of wireless and non-contact technologies for the dynamic testing of a historic RC bridge, Measur. Sci. Technol. 27 (2016) 124014. Web of Science, Google Scholar
29. Y. Xu, J. M. W. Brownjohn and F. Huseynov, Accurate deformation monitoring on bridge structures using a cost-effective sensing system combined with a camera and accelerometers: Case study, J. Bridge Eng. ASCE 24(1) (2019) 05018014. Web of Science, Google Scholar
30. Y. Chen, J. Zhang, Y. Li and J. Li, Analysis of bridge health detection based on data fusion, Adv. Civil Eng. 2022 (2022) 6893160. Web of Science, Google Scholar
31. X. H. Wang, J. M. Xia and M. Z. Bao, Ship fire detection based on fuzzy neural network and genetic algorithm, Chin. J. Sci. Instrum. 22(3) (2001) 312–314 (in Chinese). Google Scholar