Real-Time Reference-Free Displacement of Railroad Bridges during Train-Crossing Events
Publication: Journal of Bridge Engineering
Volume 22, Issue 10
Abstract
Today, railroads carry 40% of the United States’ freight tonnage, and the demand for this service is expected to double in 20 years. The railroad infrastructure contains more than 100,000 bridges spanning over 225,000 km of tracks. Half of those bridges are over 100 years old. Accordingly, safe and efficient railroad operations depend on the continuous maintenance of this aging bridge network. Recent research has demonstrated that bridge displacements can be utilized as an indication of structural integrity in the prioritization of maintenance, repair, and replacement (MRR) operations. However, existing response-measurement methods either require expensive technological instrumentation or are based on complex structural modeling assumptions. Furthermore, many of them do not accommodate real-time monitoring. This paper proposes a new methodology fusing multimetric measurement data obtained from reference-free sensors, such as accelerometers and tiltmeters, in real time to provide accurate transverse displacement measurements inexpensively. Twenty-four percent of railroad bridges in the United States are timber. Therefore, to study the performance of the proposed method, a realistic train-crossing event was simulated by using a numerical model of a timber pile bent. Timber piles were simplified as free-standing cantilever beams accounting for the soil–structure interaction based on literature and industry input. The model was excited dynamically with real train input loads collected at the site. The analysis reproduced nonsymmetric bridge responses, including pseudostatic displacements observed in the field, which conventional accelerometers cannot measure. The pseudostatic displacements from tiltmeter data were extracted using simple Euler-Bernoulli beam equations that can be estimated for any railroad timber pile bent, requiring only the length of the pile above ground as the input. These pseudostatic responses were combined with dynamic displacements derived from accelerometer data, allowing the estimation of the transverse displacement in the field without the need of a finite-element model. Researchers compared measured responses to displacements estimated by the proposed data-fusion method. The results indicate that transverse bridge displacements can be determined by combining pseudostatic and dynamic responses in real time more precisely compared to previous methods. Consequently, more effective MRR prioritization can be undertaken with accurate response measurement.
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Acknowledgments
The financial support of this research was provided in part by the Department of Civil Engineering at the University of New Mexico and the Center for Teaching and Learning of the University of New Mexico under the Teaching Allocation Grant. The authors thank the Canadian National Railway (CN) for the data collected in the field to inform this model and their feedback in the development of the simplified model and the validation of this methodology. In particular, the insights and relevance of this methodology within the railroad bridge industry provided by Sandro Scola are greatly appreciated. Finally, the authors thank Dr. Bideng Liu for his contribution in the experimental validation of the proposed work. The conclusions of this research solely represent those of the authors.
References
AAR (Association of American Railroads). (2013). “Total annual spending 2013 data.” 〈https://www.aar.org/Fact%20Sheets/Safety/2013-AAR_spending-graphic-fact-sheet.pdf〉 (Aug. 4, 2016).
AAR (Association of American Railroads). (2016). “Freight railroad capacity and investment.” 〈https://www.aar.org/BackgroundPapers/Freight%20Railroad%20Capacity%20and%20Investment.pdf〉 (Aug. 4, 2016).
Agdas, D., Rice, J., Martinez, J., and Lasa, I. (2016). “Comparison of visual inspection and structural-health monitoring as bridge condition assessment methods.” J. Perform. Constr. Facil., 04015049.
AREMA (American Railway Engineering and Maintenance-of-Way Association). (2003). Practical guide to railway engineering, Lanham, MD.
AREMA (American Railway Engineering and Maintenance-of-Way Association). (2010). Manual for railway engineering, Vol. 2, Lanham, MD.
Ashkenazi, V., and Roberts, G. W. (1997). “Experimental monitoring of the Humber Bridge using GPS.” Proc. Inst. Civ. Eng., 120(4), 177–182.
Cambridge Systematics, Inc. (2007). National rail freight infrastructure capacity and investment study, Cambridge, MA.
Chang, S. J., and Kim, N. S. (2012). “Estimation of displacement response from FBG strain sensors using empirical mode decomposition technique.” Exp. Mech., 52(6), 573–589.
Chen, W.-F., and Duan, L. (2014). Bridge engineering handbook: Fundamentals, 2nd Ed., CRC Press, Boca Raton, FL.
Dai, K., Boyajian, D., Liu, W., Chen, S., Scott, J., and Schmieder, M. (2014). “Laser-based field measurement for a bridge finite-element model validation.” J. Perform. Constr. Facil., 04014024.
Davisson, M. T. (1970). “Lateral load capacity of piles.” Highway Research Record No. 333, Highway Research Board, National Academy of Sciences-National Research Council, Washington, DC.
Feng, D., Feng, M. Q., Ozer, E., and Fukuda, Y. (2015a). “A vision-based sensor for noncontact structural displacement measurement.” Sensors, 15(7), 16557–16575.
Feng, M., Fukuda, Y., Feng, D., and Mizuta, M. (2015b). “Nontarget vision sensor for remote measurement of bridge dynamic response.” J. Bridge Eng., 04015023.
FRA (Federal Railroad Administration). (2008). “Railroad bridge working group report to the railroad safety advisory committee.” Railroad Bridge Working Group Final Rep., Washington, DC 〈https://rsac.fra.dot.gov/document.php?type=meeting&date=20080910&name=RR+Bridge+WG+ReportFinal.pdf〉 (Feb. 4, 2017).
FRA (Federal Railroad Administration). (2014). “Track and rail and infrastructure integrity compliance manual: Volume II—Chapter 1—Track safety standards—Classes 1 through 5.” 〈https://www.fra.dot.gov/eLib/details/L18604〉 (Jul. 23, 2017).
FRA (Federal Railroad Administration). (2016). “Freight rail today.” 〈https://www.fra.dot.gov/Page/P0362〉 (Aug. 4, 2016).
Fukuda, Y., Feng, M. Q., and Shinozuka, M. (2010). “Cost-effective vision-based system for monitoring dynamic response of civil engineering structures.” Struct. Control Health Monit., 17(8), 918–936.
Gavin, H. P., Rodrigo, M., and Kathryn, R. (1998). “Drift-free integrators.” Rev. Sci. Instrum., 69(5), 2171–2175.
Helmi, K., Taylor, T., Zarafshan, A., and Ansari, F. (2015). “Reference free method for real time monitoring of bridge deflections.” Eng. Struct., 103,116–124.
Hou, X., Yang, X., and Huang, Q. (2005). “Using inclinometers to measure bridge deflection.” J. Bridge Eng., 564–569.
IBISWorld. (2016). “Rail transportation in the US: Market research report.” 〈http://www.ibisworld.com/industry/default.aspx?indid=1133〉 (Aug. 4, 2016).
Kim, K., and Sohn, H. (2017). “Dynamic displacement estimation by fusing LDV and LiDAR measurements via smoothing based Kalman filtering.” Mech. Syst. Sig. Process., 82, 339–355.
Kim, N. S., and Cho, N. S. (2004). “Estimating deflection of a simple beam model using fiber optic Bragg-grating sensors.” Exp. Mech., 44(4), 433–439.
Kogan, M. G., Kim, W. Y., Bock, Y., and Smyth, A. W. (2008). “Load response on a large suspension bridge during the NYC Marathon revealed by GPS and accelerometers.” Seismol. Res. Lett., 79(1), 12–19.
Lai, Y. C. (2008). Increasing railway efficiency and capacity through improved operations, control and planning, Univ. of Illinois at Urbana–Champaign, Champaign, IL.
Lee, H. S., Hong, Y. H., and Park, H. W. (2010). “Design of a FIR filter for the displacement reconstruction using measured acceleration in low-frequency dominant structures.” Int. J. Numer. Methods Eng., 82(4), 403–434.
Lee, J. J., and Shinozuka, M. (2006a). “A vision-based system for remote sensing of bridge displacement.” NDT E Int., 39(5), 425–431.
Lee, J. J., and Shinozuka, M. (2006b). “Real-time displacement measurement of a flexible bridge using digital image processing techniques.” Exp. Mech., 46(1), 105–114.
Mazzoni, S., McKenna, F., Scott, M. H., and Fenves, G. L. (2006). OpenSees command language manual, Pacific Earthquake Engineering Research (PEER) Center, Berkeley, CA.
Meng, X., Dodson, A. H., and Roberts, G. W. (2007). “Detecting bridge dynamics with GPS and triaxial accelerometers.” Eng. Struct., 29(11), 3178–3184.
Moreu, F., et al. (2015). “Dynamic assessment of timber railroad bridges using displacements.” J. Bridge Eng, 04014114.
Moreu, F., et al. (2016). “Reference-free displacements for condition assessment of timber railroad bridges.” J. Bridge Eng., 04015052.
Moreu, F., Kim, R. E., and Spencer, B. F. Jr. (2017a). “Railroad bridge monitoring using wireless smart sensors.” Struct. Control Health Monit., 24, e1863.
Moreu, F., and LaFave, J. M. (2012). Current research topics: Railroad bridges and structural engineering, Newmark Structural Engineering Laboratory, Univ. of Illinois at Urbana–Champaign, Champaign, IL.
Moreu, F., Spencer, B. F., Jr, Foutch, D. A., and Scola, S. (2017b). “Consequence-based management of railroad bridge networks.” Struct. Infrastruct. Eng., 13(2), 273–286.
Moschas, F., Psimoulis, P. A., and Stiros, S. C. (2013). “GPS/RTS data fusion to overcome signal deficiencies in certain bridge dynamic monitoring projects.” Smart Struct. Syst., 12(3–4), 251–269.
Moschas, F., and Stiros, S. (2011). “Measurement of the dynamic displacements and of the modal frequencies of a short-span pedestrian bridge using GPS and an accelerometer.” Eng. Struct., 33(1), 10–17.
Nakamura, S. (2000). “GPS measurement of wind-induced suspension bridge girder displacements.” J. Struct. Eng., 1413–1419.
Nassif, H. H., Gindy, M., and Davis, J. (2005). “Comparison of laser Doppler vibrometer with contact sensors for monitoring bridge deflection and vibration.” NDT E Int., 38(3), 213–218.
Olaszek, P. (1999). “Investigation of the dynamic characteristic of bridge structures using a computer vision method.” Measurement, 25(3), 227–236.
OpenSees [Computer software]. University of California, Berkeley, CA.
Park, J.-W., Sim, S.-H., and Jung, H.-J. (2014). “Wireless displacement sensing system for bridges using multi-sensor fusion.” Smart Mater. Struct., 23(4), 045022.
Psimoulis, P. A., and Stiros, S. C. (2007). “Measurement of deflections and of oscillation frequencies of engineering structures using robotic theodolites (RTS).” Eng. Struct., 29(12), 3312–3324.
Psimoulis, P., and Stiros, S. (2013). “Measuring deflections of a short-span railway bridge using a robotic total station.” J. Bridge Eng., 182–185.
Puente, I., Solla, M., González-Jorge, H., and Arias, P. (2015). “NDT documentation and evaluation of the Roman Bridge of Lugo using GPR and mobile and static LiDAR.” J. Perform. Constr. Facil., 06014004.
Ribeiro, D., Calçada, R., Ferreira, J., and Martins, T. (2014). “Non-contact measurement of the dynamic displacement of railway bridges using an advanced video-based system.” Eng. Struct., 75, 164–180.
Sanli, A., Uzgider, E., Caglayan, O., Ozakgul, K., and Bien, J. (2000). “Testing bridges by using tiltmeter measurements.” Transp. Res. Rec., 1696, 111–117.
Simulink Real-Time Toolbox [Computer Software]. MathWorks, Natick, MA.
Smyth, A., and Wu, M. (2007). “Multi-rate Kalman filtering for the data fusion of displacement and acceleration response measurements in dynamic system monitoring.” Mech. Syst. Sig. Process., 21(2), 706–723.
Soyoz, S., and Feng, M. Q. (2009). “Long-term monitoring and identification of bridge structural parameters.” Comput.-Aided Civ. Infrastruct. Eng., 24(2), 82–92.
Stiros, S. C., and Psimoulis, P. A. (2012). “Response of a historical short-span railway bridge to passing trains: 3-D deflections and dominant frequencies derived from robotic total station (RTS) measurements.” Eng. Struct., 45, 362–371.
Surface Transportation Board. (2016). “FAQs.” 〈https://www.stb.gov/stb/faqs.html〉 (Aug. 4, 2016).
TRB (Transportation Research Board). (2006). “Maintenance and operations of transportation facilities.” Transportation Research Circular E-C092, Washington, DC.
Wahbeh, A. M., Caffrey, J. P., and Masri, S. F. (2003). “A vision-based approach for the direct measurement of displacements in vibrating systems.” Smart Mater. Struct., 12(5), 785–794.
Watson, C., Watson, T., and Coleman, R. (2007). “Structural monitoring of cable-stayed bridge: Analysis of GPS versus modeled deflections.” J. Surv. Eng., 23–28.
Wipf, T., Ritter, M., and Wood, D. (2000). “Evaluation and field load testing of timber railroad bridge.” Transp. Res. Rec., 1696, 323–333.
Wong, K.-Y. (2004). “Instrumentation and health monitoring of cable-supported bridges.” Struct. Contr. Health Monit., 11(2), 91–124.
Wong, K. Y., Man, K. L., and Chan, W. Y. (2001). “Real-time kinematic spans the gap.” GPS World, 12(7), 10–19.
Yi, T.-H., Li, H.-N., and Gu, M. (2013). “Experimental assessment of high-rate GPS receivers for deformation monitoring of bridge.” Measurement, 46(1), 420–432.
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Published In
Journal of Bridge Engineering
Volume 22 • Issue 10 • October 2017
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© 2017 American Society of Civil Engineers.
History
Received: Oct 28, 2016
Accepted: May 4, 2017
Published online: Aug 2, 2017
Published in print: Oct 1, 2017
Discussion open until: Jan 2, 2018
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