DOI QR코드

DOI QR Code

Structural health monitoring system for Sutong Cable-stayed Bridge

  • Wang, Hao (Key Laboratory of C&PC Structures of Ministry of Education, Southeast University) ;
  • Tao, Tianyou (Key Laboratory of C&PC Structures of Ministry of Education, Southeast University) ;
  • Li, Aiqun (Key Laboratory of C&PC Structures of Ministry of Education, Southeast University) ;
  • Zhang, Yufeng (Jiangsu Transportation Institute)
  • Received : 2015.08.06
  • Accepted : 2016.06.17
  • Published : 2016.08.25

Abstract

Structural Health Monitoring System (SHMS) works as an efficient platform for monitoring the health status and performance deterioration of engineering structures during long-term service periods. The objective of its installation is to provide reasonable suggestions for structural maintenance and management, and therefore ensure the structural safety based on the information extracted from the real-time measured data. In this paper, the SHMS implemented on a world-famous kilometer-level cable-stayed bridge, named as Sutong Cable-stayed Bridge (SCB), is introduced in detail. The composition and core functions of the SHMS on SCB are elaborately presented. The system consists of four main subsystems including sensory subsystem, data acquisition and transmission subsystem, data management and control subsystem and structural health evaluation subsystem. All of the four parts are decomposed to separately describe their own constitutions and connected to illustrate the systematic functions. Accordingly, the main techniques and strategies adopted in the SHMS establishment are presented and some extension researches based on structural health monitoring are discussed. The introduction of the SHMS on SCB is expected to provide references for the establishment of SHMSs on long-span bridges with similar features as well as the implementation of potential researches based on structural health monitoring.

Keywords

Acknowledgement

Supported by : National Science Foundation of China, Fok Ying-Tong Education Foundation, Ministry of Education of China, Jiangsu Higher Education Institutions

References

  1. Aktan, A.E., Catbas F.N., Grimmelsman, K.A. et al. (2000), "Issues in infrastructure health monitoring for management", J. Eng. Mech.- ASCE, 126(7), 711-724. https://doi.org/10.1061/(ASCE)0733-9399(2000)126:7(711)
  2. Chang, P.C., Flatau, A. and Liu, S.C. (2003), "Review paper: health monitoring of civil infrastructure", Struct. Health Monit., 2(3), 257-267. https://doi.org/10.1177/1475921703036169
  3. Cho, S., Jang, S.A., Jo, H. et al. (2010), "Structural health monitoring system of a cable-stayed bridge using a dense array of scalable smart sensor network", In Proc. of SPIE, 7647, 7-19.
  4. Galiana-Merino, J.J., Rosa-Herranz, J., Giner, J. et al. (2003), "De-noising of short-period seismograms by wavelet packet transform", B. Seismol. Soc. Am., 93(6), 2554-2562. https://doi.org/10.1785/0120010133
  5. Gimsing, N.J. (1983), Cable Supported Bridge: Concept and Design, John Wiley and Sons, New York, NY, USA.
  6. Jang, S., Jo, H., Cho, S. et al. (2010), "Structural health monitoring of a cable-stayed bridge using smart sensor technology: deployment and evaluation", Smart Struct. Syst., 6(5-6), 439-459. https://doi.org/10.12989/sss.2010.6.5_6.439
  7. Kopsinis, Y. and McLaughlin, S. (2009), "Development of EMD-based denoising methods inspired by wavelet thresholding", IEEE T. Signal Proces., 57(4), 1351-1362. https://doi.org/10.1109/TSP.2009.2013885
  8. Li, A.Q., Ding, Y.L., Wang, H. et al. (2012), "Analysis and assessment of bridge health monitoring mass data-progress in research/development of Structural Health Monitoring", Sci. China Technol. Sci., 55(8), 2212-2224. https://doi.org/10.1007/s11431-012-4818-5
  9. Li, H., Ou, J.P., Zhang, X.G. et al. (2015), "Research and practice of health monitoring for long-span bridges in the mainland of China", Smart Struct. Syst., 15(3), 555-576. https://doi.org/10.12989/sss.2015.15.3.555
  10. Li, H., Ou, J.P., Zhao, X.F. et al. (2006), "Structural health monitoring system for the Shandong Binzhou Yellow River Highway Bridge", Comput - Aided. Civ. Inf., 21, 306-317. https://doi.org/10.1111/j.1467-8667.2006.00437.x
  11. Lynch, J.P. and Loh, K.J. (2006), "A summary review of wireless sensors and sensor networks for structural health monitoring", Shock Vib. Digest, 38(2), 91-130. https://doi.org/10.1177/0583102406061499
  12. Ministry of Communications of PRC. (2004), Wind-resistant Design Specification for Highway Bridges. China Communications Press, Beijing, China. (in Chinese)
  13. Miyataa, T., Yamadaa, H., Katsuchia, H. et al. (2002), "Full-scale measurement of Akashi-Kaikyo Bridge during typhoon", J. Wind Eng. Ind. Aerod., 90, 1517-1527. https://doi.org/10.1016/S0167-6105(02)00267-2
  14. Ni, Y.Q., Hua, X.G., Wong, K.Y. et al. (2007), "Assessment of bridge expansion joints using long-term and temperature measurement", J. Perform. Constr. Fac., 21(2), 143-151. https://doi.org/10.1061/(ASCE)0887-3828(2007)21:2(143)
  15. Ni, Y.Q., Ye, X.W. and Ko, J.M. (2010), "Monitoring-based fatigue reliability assessment of steel bridges: analytical model and application", J. Struct. Eng.- ASCE, 136(12), 1563-1573. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000250
  16. Ou, J.P. and Li, H. (2010), "Structural health monitoring in mainland China: Review and future trends", Struct. Health Monit., 9(3), 219-231. https://doi.org/10.1177/1475921710365269
  17. Schallhorn, C. and Rahmatalla, S. (2015), "Crack detection and health monitoring of highway steel-girder bridges", Struct. Health Monit., 14(3), 281-299. https://doi.org/10.1177/1475921714568404
  18. Soyoz, S. and Feng, M.Q. (2009), "Long-term monitoring and identification of bridge structural parameters", Comput - Aided. Civ. Inf., 24, 82-92. https://doi.org/10.1111/j.1467-8667.2008.00572.x
  19. Spencer, B.F. and Cho, S. (2011), "Wireless smart sensor technology for monitoring civil infrastructure: technological developments and full-scale applications", Proceedings of the World Cong. on ASEM.
  20. Spencer, B.F., Ruiz-Sandoval, M.E. and Kurata, N. (2004), "Smart sensing technology: opportunities and challenges", Struct. Control Health Monit., 11, 349-368. https://doi.org/10.1002/stc.48
  21. Wang, H., Li, A.Q., Guo, T. et al. (2014), "Establishment and application of the wind and structural health monitoring system for the Runyang Yangtze River Bridge", J. Shock Vib., 2014, 1-15.
  22. Wang, H., Li, A.Q., Niu, J. et al. (2013), "Long-term monitoring of wind characteristics at Sutong Bridge site", J. Wind Eng. Ind. Aerod., 115, 39-47. https://doi.org/10.1016/j.jweia.2013.01.006
  23. Wang, H., Tao, T. Y., Wu, T. et al. (2015), "Joint distribution of wind speed and direction in the context of field measurement", Wind Struct., 20(5), 701-718. https://doi.org/10.12989/was.2015.20.5.701
  24. Wang, H., Tao, T.Y., Guo, T. et al. (2014), "Full-scale measurements and system identification on Sutong Cable-Stayed Bridge during Typhoon Fung-Wong", Sci. World J., 2014, 1-13.
  25. Xu, Y.L., Zhang, X.H., Zhan, S. et al. (2012), "Testbed for structural health monitoring of long-span suspension bridges", J. Bridge Eng.- ASCE, 17(6), 896-906. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000349
  26. Yarnold, M.T. and Moon, F.L. (2015), "Temperature-based structural health monitoring baseline for long-span bridges", Eng. Struct., 86, 157-167. https://doi.org/10.1016/j.engstruct.2014.12.042

Cited by

  1. An improved frequency-domain regression method for structural damage detection in wireless sensor network vol.8, pp.10, 2016, https://doi.org/10.1177/1687814016673805
  2. Reference-Free Displacement Estimation of Bridges Using Kalman Filter-Based Multimetric Data Fusion vol.2016, 2016, https://doi.org/10.1155/2016/3791856
  3. Structural health monitoring system of the long-span bridges in Turkey 2017, https://doi.org/10.1080/15732479.2017.1360365
  4. Health Monitoring and Evaluation of Long-Span Bridges Based on Sensing and Data Analysis: A Survey vol.17, pp.3, 2017, https://doi.org/10.3390/s17030603
  5. Deployment of a Smart Structural Health Monitoring System for Long-Span Arch Bridges: A Review and a Case Study vol.17, pp.9, 2017, https://doi.org/10.3390/s17092151
  6. Design and Implementation of a New System for Large Bridge Monitoring—GeoSHM vol.18, pp.3, 2018, https://doi.org/10.3390/s18030775
  7. Self-Sensing CFRP Fabric for Structural Strengthening and Damage Detection of Reinforced Concrete Structures vol.18, pp.12, 2018, https://doi.org/10.3390/s18124137
  8. Computing continuous load rating factors for bridges using structural health monitoring data vol.8, pp.5, 2018, https://doi.org/10.1007/s13349-018-0313-4
  9. Investigation of dynamic properties of long-span cable-stayed bridges based on one-year monitoring data under normal operating condition vol.25, pp.5, 2018, https://doi.org/10.1002/stc.2146
  10. Measurement of Wind Effects on a Kilometer-Level Cable-Stayed Bridge during Typhoon Haikui vol.144, pp.9, 2018, https://doi.org/10.1061/(ASCE)ST.1943-541X.0002138
  11. Dynamic Performance of Typical Steel Truss–Railway Bridges under the Action of Moving Trains vol.32, pp.4, 2018, https://doi.org/10.1061/(ASCE)CF.1943-5509.0001200
  12. Fatigue Reliability Assessment of a Long-Span Cable-Stayed Bridge Based on One-Year Monitoring Strain Data vol.24, pp.1, 2019, https://doi.org/10.1061/(ASCE)BE.1943-5592.0001337
  13. An integrated structural health monitoring system for the Xijiang high-speed railway arch bridge vol.21, pp.5, 2016, https://doi.org/10.12989/sss.2018.21.5.611
  14. Localisation of embedded water drop in glass composite using THz spectroscopy vol.21, pp.6, 2018, https://doi.org/10.12989/sss.2018.21.6.751
  15. Modal flexibility based damage detection for suspension bridge hangers: A numerical and experimental investigation vol.23, pp.1, 2016, https://doi.org/10.12989/sss.2019.23.1.015
  16. Modeling and forecasting of temperature-induced strain of a long-span bridge using an improved Bayesian dynamic linear model vol.192, pp.None, 2016, https://doi.org/10.1016/j.engstruct.2019.05.006
  17. A low-cost IoT-based wireless sensor system for bridge displacement monitoring vol.28, pp.8, 2019, https://doi.org/10.1088/1361-665x/ab2a31
  18. Application of GeoSHM System in Monitoring Extreme Wind Events at the Forth Road Bridge vol.11, pp.23, 2016, https://doi.org/10.3390/rs11232799
  19. Automatic Management and Monitoring of Bridge Lifting: A Method of Changing Engineering in Real-Time vol.19, pp.23, 2016, https://doi.org/10.3390/s19235293
  20. Main Girder Deflection Variations in Cable-Stayed Bridge with Temperature over Various Time Scales vol.2020, pp.None, 2016, https://doi.org/10.1155/2020/4316921
  21. Long-Term Dynamic Monitoring of Medieval Masonry Towers vol.6, pp.None, 2020, https://doi.org/10.3389/fbuil.2020.00009
  22. Long term structural health monitoring for old deteriorated bridges: a copula-ARMA approach vol.25, pp.3, 2020, https://doi.org/10.12989/sss.2020.25.3.285
  23. Temperature distribution analysis of steel box-girder based on long-term monitoring data vol.25, pp.5, 2016, https://doi.org/10.12989/sss.2020.25.5.593
  24. A computer-vision based vibration transducer scheme for structural health monitoring applications vol.29, pp.8, 2016, https://doi.org/10.1088/1361-665x/ab9062
  25. Numerical simulation of unsteady galloping of two-dimensional iced transmission line with comparison to conventional quasi-steady analysis vol.75, pp.4, 2016, https://doi.org/10.12989/sem.2020.75.4.487
  26. Investigation of Temperature Effects on Steel-Truss Bridge Based on Long-Term Monitoring Data: Case Study vol.25, pp.9, 2020, https://doi.org/10.1061/(asce)be.1943-5592.0001593
  27. Smart properties of carbon nanotube-epoxy composites vol.234, pp.11, 2020, https://doi.org/10.1177/1464420720942934
  28. Deformation monitoring and analysis of a long-span cable-stayed bridge during strong typhoons vol.1, pp.1, 2020, https://doi.org/10.1186/s43251-020-00008-5
  29. Modal identification of the first Bosporus bridge during hanger replacement vol.16, pp.12, 2016, https://doi.org/10.1080/15732479.2020.1717551
  30. Smart self-sensing fiber-reinforced polymer sheet with woven carbon fiber line sensor for structural health monitoring vol.24, pp.1, 2016, https://doi.org/10.1177/1369433220944507
  31. Probabilistic Framework with Bayesian Optimization for Predicting Typhoon-Induced Dynamic Responses of a Long-Span Bridge vol.147, pp.1, 2016, https://doi.org/10.1061/(asce)st.1943-541x.0002881
  32. Toward data anomaly detection for automated structural health monitoring: Exploiting generative adversarial nets and autoencoders vol.20, pp.4, 2016, https://doi.org/10.1177/1475921720924601
  33. Dynamic performance investigation of a long-span suspension bridge using a Bayesian approach vol.168, pp.None, 2022, https://doi.org/10.1016/j.ymssp.2021.108700