Smart Structures and Systems

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Bridge safety monitoring based-GPS technique: case study Zhujiang Huangpu Bridge

  • Kaloop, Mosbeh R. (Public Works and Civil Engineering Department, Faculty of Engineering, Mansoura University)
  • Received : 2010.11.06
  • Accepted : 2012.05.17
  • Published : 2012.06.25
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Abstract

GPS has become an established technique in structural health monitoring. This paper presents the application of an on-line GPS RTK system on the Zhujiang Huangpu Bridge (China) for monitoring bridge deck and towers movements. In this study, both the form and functions of movements of the deck and towers of the bridge under affecting loads were monitored in lateral, longitudinal and vertical directions. Such movements were described in time and frequency domains by determining the trend, torsion, periodical of the series using probability density function (PDF). The results of the time series GPS data are practical and useful to bridge health monitoring.

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References

  1. Ai, X.Q. and Li, J. (2004), "Stochastic response research of buried pipeline under earthquake load", Proceedngs of the 3rd international conference on earthquake engineering, 19-20 October 2004, Nanjing, China.
  2. Brownjohn, J., Dumanoglu, A. and Blakeborough, A. (1988), Ambient vibration survey of the Bosporus suspension bridge, Report No.UBCE-EE-88-1.
  3. Casciati, F. and Fuggini, C. (2011), "Monitoring a steel building using GPS sensors", Smart Struct. Syst., 7(5), 349-363. https://doi.org/10.12989/sss.2011.7.5.349
  4. Chmielewski, T., Breuer, P., Gorski, P. and Konopka, E. (2009), "Monitoring of tall slender structures by GPS measurements", Wind Struct., 12(5), 401-412. https://doi.org/10.12989/was.2009.12.5.401
  5. Chatfield, C. (1996), The analysis time series, Chapman&Hall/CRC.
  6. Dodson, A., Meng, X., Roberts, G. and Emily,C. (2003), "Integrated approach of GPS and pseudolites for bridge deformation monitoring", http://citeseerx.ist.psu. edu/viewdoc/summary, Doi=10.1.1.68.3120.
  7. Kaloop, M. and Li, H. (2009a), "Tower bridge movement analysis with GPS and accelerometer techniques: case study Yonghe tower bridge", J. Inf. Technol., 8(8), 1213-1220. https://doi.org/10.3923/itj.2009.1213.1220
  8. Kaloop, M. and Li, H. (2009b), "Monitoring of bridges deformation using GPS technique", KSCE J. Civil Eng., 13(6), 423-431. https://doi.org/10.1007/s12205-009-0423-y
  9. Kaloop, M. and Li, H. (2011), "Sensitivity and analysis GPS signals based bridge damage using GPS observations and wavelet transform", Measurement, 44(5), 927-937. https://doi.org/10.1016/j.measurement.2011.02.008
  10. Kuhlman, K. (2001), "Importance of autocorrelation for parameter estimation in regression models, theory and deformation analysis", Proceedngs of the 10th International Symposium on Deformation Measurements, California.
  11. Li, X., Peng, G., Rizo, C., Ge, L., Tamura, Y. and Yoshida, A. (2004), "Integration of GPS, accelerometer and optical fiber sensors for structural deformation monitoring", ION GNSS 17th International Technical Meeting of the Satellite Division, pp.21-24, http://citeseerx.ist.psu.edu/viewdoc/summary?, Doi=10.1.1.66.3180.
  12. Li, J. and Chen, J. (2003), "Probability density evaluation method for dynamic response analysis of stochastic structures", Proceedngs of the 5th international conference on stochastic structural dynamics-SSD03, Hangzhou, China, 309-316.
  13. Li, J. (1996), Stochastic structure system: analyzing & modeling building, Science publication company, China.
  14. Li, J. and Chen, J. (2006), "The probability density evolution method for dynamic response analysis of nonlinear stochastic structures", Int. J. Numer. Meth. Eng., 65(6), 882-903. https://doi.org/10.1002/nme.1479
  15. Li, J. and Chen, J. (2004), "Probability density evolution method for dynamic response of structures with uncertain parameters", Comput. Mech., 34(5), 400-409. https://doi.org/10.1007/s00466-004-0583-8
  16. Liu, Z.J. and Li, J. (2008), "Probabilistic response and reliability evaluation of nonlinear structures under earthquake", Proceedings of the 14th World Conference on Earthquake Engineering, October 12-17, 2008, Beijing, China.
  17. Martin, H. (2007), Matlab recipes for earth sciences, 2th Ed., Springer Berlin Heidelberg New York.
  18. Mascarenas, D,. Flynn, E., Todd, M., Overly, T., Farinholt, K., Park,G. and Farrar, C. (2009), "Development of capacitance-based and impedance-based wireless sensors and sensor nodes for structural health monitoring applications", J. Sound Vib., 329(12), 2410-2420.
  19. Mathworks. Matlab (2008), Release 12, The Mathworks, Inc.
  20. Meng, X., Dodson, A.H. and Roberts, G.W. (2007), "Detecting bridge dynamics with GPS and triaxial accelerometers", J. Struct. Eng. - ASCE, 29(11), 3178-3184. https://doi.org/10.1016/j.engstruct.2007.03.012
  21. Ogaja, C., Rizos, C., Wang, J. and Brownjohn, J. (2001), "A dynamic GPS system for on-line structural monitoring", http://citeseerx.ist.psu.edu/viewdoc/summary?, Doi=10.1.1.15.2643.
  22. Park, H.S., Sohn, H.G., Kimi, I.S. and Park, J.H. (2008), "Application of GPS to monitoring of wind-induced responses of high-rise building", Struct. Des. Tall Spec., 17(1), 117-132. https://doi.org/10.1002/tal.335
  23. Ramin, S.A. and Helmi, Z.M. (2009), "Mass structure deformation monitoring using low cost differential global positioning system device", Am. J. Appl. Sci., 6(1), 152-156. https://doi.org/10.3844/ajassp.2009.152.156
  24. Wu, B.J. (2008), Multiscale analyses of structural health monitoring data for condition assessment, Dissertation for the Degree of Master of Engineering, Southeast University, Nanjing.

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