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Direct Reference-Free Dynamic Deflection Measurement of Railroad Bridge under Service Load

  • Bideng Liu
  • Ali Ozdagli
  • Fernando Moreu
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

Today, railroads carry 40% of the US freight tonnage and this demand will double in 20 years. North American railroad infrastructure includes approximately 100,000 bridges spanning over 140,000 miles of tracks. Half of those bridges are over 100 years old. Measuring deflection time history of railroad bridges under train load can assist in quantifying the reliability and increasing the safety of railroad operations throughout the network. However, obtaining bridge deflection is often difficult to collect in the field due to the lack of fixed reference points from where to measure. Although reference-free acceleration can be used to estimate the dynamic deflection through double integration, the algorithms are difficult to develop and apply because of the complicated integration constants selected for the data post-processing. This research studies the reference-free dynamic deflection (vertical displacement) acquisition approaches, a sensing system composed of one passive-servo electro-magnetic-induction (PSEMI) velocity sensor and one built-in hardware integrator unit. This research has presented two promising reference-free dynamic deflection acquisition approaches, direct reference-free displacement measurement from a sensing system composed of one passive-servo electro-magnetic-induction (PSEMI) velocity sensor and one built-in hardware integrator unit, and a reference-free displacement estimation from accelerometer by Lee-Method, that can be used for evaluating the performance and safety of railroad bridges under service load. Using the passive-servo feedback electrical control technology, the PSEMI velocity sensor provides a low-frequency direct reference-free measurement performance with its small size and light weight. Using a finite impulse response (FIR) filtering instead of double integrating, the displacement can be estimated from acceleration without the integration errors from unknown integration constants and boundary conditions. Researchers used an ASCE steel truss bridge model and an MTS actuator to quantify the accuracy of the PSEMI sensing system. The actuator replicated various harmonic motions and real bridge vertical displacements under train-crossing events measured in the field. The direct dynamic reference-free displacements measured by PSEMI sensing system and the indirect dynamic reference-free displacements estimated by acceleration using Lee-Method were compared to reference displacements measured by LVDT. The experimental results show that the direct reference-free dynamic displacement sensing system and indirect reference-free displacement estimation method from acceleration are two promising alternatives to railroad bridge deflection under train loading, without the need to a fixed reference frame.

Keywords

Direct reference-free displacement Indirect displacement estimation Railroad bridges Train-crossing load 

Notes

Acknowledgements

The financial support for this research came from the following sources that are gratefully acknowledged: The Center for Teaching and Learning at the University of New Mexico; the National Natural Science Foundation of China (No. 51208107); and the China Scholarship Council Foundation (No. 201604190028). The authors of this paper thank the Canadian National Railway (CN) for the bridge displacement data collected in the field, and Mr. Rahulreddy Chennareddy from the Department of Civil Engineering, University of New Mexico for his support in the configuration of MTS actuator system. The conclusions of this research are solely those of the authors.

References

  1. 1.
    Federal Railroad Administration (FRA): Freight Rail Today (2016) https://www.fra.dot.gov/Page/P0362 (11 Oct 2016)
  2. 2.
    Moreu, F., Li, J., Jo, H., Kim, R., Scola, S., Spencer Jr., B., LaFave, J.M.: Reference-free displacements for condition assessment of timber railroad bridges. J. Bridg. Eng. 04015052 (2015).  https://doi.org/10.1061/(ASCE)BE.1943-5592.0000805
  3. 3.
    Moreu, F., LaFave, J.M.: Current Research Topics: Railroad Bridges and Structural Engineering. Newmark Structural Engineering Laboratory. University of Illinois at Urbana-Champaign, Champaign (2012)Google Scholar
  4. 4.
    Wipf, T.J., Ritter, M.A., Wood, D.L.: Evaluation and field load testing of Timber Railroad Bridge. In: Fifth International Bridge Engineering Conference, TRR Number 1696, Paper No. 5B0112, pp. 323–333, Washington, DC (2000)CrossRefGoogle Scholar
  5. 5.
    Moreu, F., Jo, H., Li, J., Kim, R.E., Cho, S., Kimmle, A., Scola, S., Le, H., Spencer Jr., B.F., LaFave, J.M.: Dynamic assessment of timber railroad bridges using displacements. J. Bridg. Eng. 20(10), NSEL-032 04014114, Urbana, IL, USA (2014)CrossRefGoogle Scholar
  6. 6.
    Hou, X., Yang, X., Huang, Q.: Using inclinometers to measure bridge deflection. J. Bridg. Eng. 10(5), 564–569 (2005)CrossRefGoogle Scholar
  7. 7.
    Yu, Y., Liu, H., Li, D., Mao, X., Ou, J.: Bridge deflection measurement using wireless mems inclination sensor systems. Int. J. Smart Sens. Intell. Syst. 6(1), (2013)CrossRefGoogle Scholar
  8. 8.
    Zhang, W., Sun, L.M., Sun, S.W.: Bridge-deflection estimation through inclinometer data considering structural damages. J. Bridg. Eng. 22(2), 04016117 (2016)CrossRefGoogle Scholar
  9. 9.
    Fukuda, Y., Feng, M.Q., Shinozuka, M.: Cost-506 effective vision-based system for monitoring dynamic response of civil engineering structures. Struct. Control. Health Monit. 17, 918–936 (2010).  https://doi.org/10.1002/stc.360 CrossRefGoogle Scholar
  10. 10.
    Feng, M., Fukuda, Y., Feng, D., Mizuta, M.: Nontarget vision sensor for remote measurement of bridge dynamic response. J. Bridg. Eng. 04015023 (2015).  https://doi.org/10.1061/(ASCE)BE.1943-5592.0000747
  11. 11.
    Rice, J.A., Changzhi, L., Changzhan, G., Hernandez, J.C.: A wireless multifunctional radar-based displacement sensor for structural health monitoring. Sensors and smart structures Technologies for Civil, Mechanical, and Aerospace Systems 2011. Edited by Tomizuka, Masayoshi. Proceedings of the SPIE. 7981, 79810K-79810K-11 (2011).  https://doi.org/10.1117/12.879243 CrossRefGoogle Scholar
  12. 12.
    Zhao, X., Liu, H., Yu, Y., Xu, X., Hu, W., Li, M., Jingping, O.: Bridge displacement monitoring method based on laser projection-sensing technology. Sensors. 15(4), 8444–8463 (2015)CrossRefGoogle Scholar
  13. 13.
    Psimoulis, P., Stiros, S.: Measuring deflections of a short-span railway bridge using a Robotic Total Station (RTS). J. Bridg. Eng. 18(2), 182–185 (2013)CrossRefGoogle Scholar
  14. 14.
    Watson, C., Watson, T., Coleman, R.: Structural monitoring of cable-stayed bridge: analysis of GPS versus modeled deflections. J. Surv. Eng. 133(1), 23–28 (2007)CrossRefGoogle Scholar
  15. 15.
    Boore, D.M.: Analog-to-digital conversion as a source of drifts in displacements derived from digital recordings of ground acceleration. Bull.Seismol. Soc. Am. 93(5), 2017–2024 (2003)CrossRefGoogle Scholar
  16. 16.
    Gindy, M., Vaccaro, R., Nassif, H., Velde, J.: A state-space approach for deriving bridge displacement from acceleration. Comput. Aided. Civ. Inf. Eng. 23(4), 281–290 (2008)CrossRefGoogle Scholar
  17. 17.
    Hester, D., Brownjohn, J., Bocian, M., Xu, Y.: Low cost bridge load test: calculating bridge displacement from acceleration for load assessment calculations. Eng. Struct. 143, 358–374 (2017)CrossRefGoogle Scholar
  18. 18.
    Park, K.-T., Kim, S.-H., Park, H.-S., Lee, K.-W.: The determination of bridge displacement using measured acceleration. Eng. Struct. 27(3), 371–378 (2005)CrossRefGoogle Scholar
  19. 19.
    Cho, S., Park, J.W., Palanisamy, R.P., Sim, S.H.: Reference-free displacement estimation of bridges using Kalman filter-based multimetric data fusion. J. Sens. 2016 (2016)Google Scholar
  20. 20.
    Gomez, J.A., Ozdagli, A.I. and Moreu, F. (2016). Application of Low-Cost Sensors for Estimation of Reference-Free Displacements Under Dynamic Loading for Railroad Bridges Safety. In ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (pp. V001T05A021-V001T05A021). American Society of Mechanical EngineersGoogle Scholar
  21. 21.
    Lee, H.S., Hong, Y.H., Park, H.W.: Design of an FIR filter for the displacement reconstruction using measured acceleration in low-frequency dominant structures. Int. J. Numer. Methods Eng. 82(4), 403–434 (2010)zbMATHGoogle Scholar
  22. 22.
    Ozdagli, A.I., Gomez, J.A., Moreu, F.: Real-time reference-free displacement of railroad bridges during train-crossing events. J. Bridg. Eng. 22(10), 04017073 (2017)CrossRefGoogle Scholar
  23. 23.
    Clinton, J.F., Heaton, T.H.: Potential advantages of a strong-motion velocity meter over a strong-motion accelerometer. Seismol. Res. Lett. 73(3), 332–342 (2002)CrossRefGoogle Scholar
  24. 24.
    Shuanglan, C., Jun, L., Hongyuan, Y., et al.: Low frequency expansion technologies applied in deep seismic exploration geophones. Prog. Geophys. 27(5), 1904–1911 (2012)Google Scholar
  25. 25.
    Yang, X., Gao, F., Xingmin, H.: Low-frequency characteristics extension for vibration sensors. Earthq. Eng. Eng. Vib. 3(1), 139–146 (2004)CrossRefGoogle Scholar
  26. 26.
    Qinglei, C., Wei, H., Xianlong, H.: A vibration-measuring system based on passive servo vibration pickups. J. Vib. Shock. 4, 039, 153--156, 167 (2009)Google Scholar
  27. 27.
    Qinglei, C., Yang, X., Shuaiku, S.: Passive servo feedback multi output low frequency vibration sensor. Chin. J. Sci. Instrum. 38(1), 105–111 (2017)Google Scholar
  28. 28.
    Debao, L., Lu, Q.: Analysis of Experiments of Engineering Vibration. Tsinghua University Press, Beijing, China (2004)Google Scholar

Copyright information

© The Society for Experimental Mechanics, Inc. 2019

Authors and Affiliations

  • Bideng Liu
    • 1
  • Ali Ozdagli
    • 2
  • Fernando Moreu
    • 2
  1. 1.Beijing Municipal Institute of Labour ProtectionBeijingP.R. China
  2. 2.Department of Civil EngineeringUniversity of New MexicoAlbuquerqueUSA

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