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A Contactless Approach to Monitor Rail Vibrations

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Abstract

Background

Continuous welded rails (CWR) are subjected to thermal effects that may lead to buckling or fracture during warm or cold seasons, respectively. The modal characteristics (frequency and mode shapes) of CWR may reveal important information about the thermal stress that can be used to prevent rail failures.

Objective

The primary objective of this study is to prove a contactless method to monitor the vibration and to extract the modal characteristics of rails using a high-speed camera and advanced image processing. This study is the first step towards a general noninvasive monitoring paradigm aimed at measuring axial stress in CWR.

Methods

To prove the principles of the proposed paradigm, a finite element model of an unrestrained rail segment under varying length, boundary conditions, and axial stresses was formulated. The results of the model were then used to interpret the experimental results relative to a 2.4 m-long rail subjected to compressive loading–unloading cycles. During the experiment, the rail was subjected to the impact of an instrumented hammer and the triggered vibration was recorded with a high-speed camera. The videos were then processed using the phase-based displacement extraction, motion magnification, as well as dynamic mode decomposition techniques to extract the modal characteristics of the specimen.

Results

The results show that the frequencies extracted from the images matched well those obtained with two conventional accelerometers bonded to the rail while the mode shapes extracted from the videos matched those predicted numerically. Additionally, the numerical analysis enabled the interpretation of some unexpected experimental results.

Conclusions

The results presented here proved that the proposed method to infer axial stress in CWR requires proper modeling in order to link the modal characteristics of the rails to the axial stress. In the future, the finite element formulation presented here will be expanded to model CWR under given cross-ties and fasteners conditions in order to link the modal characteristics of the rail of interest to its axial stress.

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Source signals and their frequency spectrums of the mode shapes from DMD. a, b and c respectively represents the source signal of the mode shape a, b and c shown in Fig. 14

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References

  1. Kish A, Samavedam G (2005) Improved destressing of continuous welded rail for better management of rail neutral temperature. Transp Res Rec 1916(1):56–65. https://doi.org/10.1177/0361198105191600109

    Article  Google Scholar 

  2. Product Marketing Sheet (2020) VERSE (Vertical Rail Stressing Equipment). http://www.vortok.com/uploads/catalogerfiles/verse/Business_Case.pdf . Accessed 27 March 2020

  3. QinetiQ North America. Intelligent Rail Integrity System (IRIS). https://www.qinetiq-na.com/wp-content/uploads/brochure_iris.pdf .

  4. Wegner A (2007) Prevention of track buckling and rail fracture by non-destructive testing of the neutral temperature in CW-rails. Proceedings International Heavy Haul Conference, Sweden, pp. 557–564

  5. Zhu X, Lanza di Scalea F (2016) Sensitivity to axial stress of electro-mechanical impedance measurements. Exp Mech 56(9):1599–1610

    Article  Google Scholar 

  6. Phillips R, Lanza di Scalea F, Zhu X (2012) The influence of stress on Electro-mechanical impedance measurements in rail steel. Mater Eval 70(10):1213–1218

    Google Scholar 

  7. Hurlebaus S (2011) Determination of longitudinal stress in rails. Safety IDEA Project 15. Trans Res Board 01363276

  8. Nucera C, Lanza di Scalea F (2014a) Nonlinear wave propagation in constrained solids subjected to thermal loads. J Sound Vib 333(2):541–554

    Article  Google Scholar 

  9. Nucera C, Lanza di Scalea F (2014b) Nondestructive measurement of neutral temperature in continuous welded rails by nonlinear ultrasonic guided waves. J Acoust Soc Am 136(5):2561–2574

    Article  Google Scholar 

  10. Nucera C, Phillips R, Lanza di Scalea F, Fateh M, Carr G (2013) RAIL-NT System for the in-situ measurement of neutral temperature in CWR: results from laboratory and field test. J Transp Res Board 01470560(13–3511):13

    Google Scholar 

  11. Lanza di Scalea F, Nucera C, (2018) Nonlinear ultrasonic testing for non-destructive measurement of longitudinal thermal stresses in solids. US Patents, No. US20150377836A1

  12. Bagheri A, La Malfa RE, Rizzo P, Al-Nazer L, Giambanco G (2015) On the use of l-shaped granular chains for the assessment of thermal stress in slender structures. Exp Mech 55(3):543–558

    Article  Google Scholar 

  13. Bagheri A, La Malfa RE, Rizzo P, Al-Nazer L (2016) On the coupling dynamics between thermally stressed beams and granular chains. Arch of Appl Mech 86(3):541–556

    Article  Google Scholar 

  14. Bagheri A, Rizzo P, Al-Nazer L (2016) A numerical study on the optimization of a granular medium to infer the axial stress in slender structures. Mech Adv Mater Struct 23(10):1131–1143

    Article  Google Scholar 

  15. Nasrollahi A, Rizzo P (2018) Axial stress determination using highly nonlinear solitary waves. J Acoust Soc Am 144(4):2201–2212

    Article  Google Scholar 

  16. Nasrollahi A, Rizzo P (2019) Numerical analysis and experimental validation of an nondestructive evaluation method to measure stress in rails. ASME J Nondestruct Eval Diagn Progn Eng Syst 2(3):031002. https://doi.org/10.1115/1.4043949

    Article  Google Scholar 

  17. Feng D, Feng MQ (2016) Vision-based multipoint displacement measurement for structural health monitoring. Struct Control Health 23(5):876–890

    Article  Google Scholar 

  18. Ribeiro D, Calçada R, Ferreira J, Martins T (2014) Non-contact measurement of the dynamic displacement of railway bridges using an advanced video-based system. Eng Struct 75:164–180

    Article  Google Scholar 

  19. Feng D, Feng MQ (2017) Experimental validation of cost-effective vision-based structural health monitoring. Mech Syst Signal Process 88:199–211

    Article  Google Scholar 

  20. Chen JG, Wadhwa N, Cha YJ, Durand F, Freeman WT, Büyüköztürk O (2015) Modal identification of simple structures with high-speed video using motion magnification. J Sound Vib 345(9):58–71

    Article  Google Scholar 

  21. Wadhwa N, Rubinstein M, Durand F, Freeman WT (2013) Phase-based video motion processing. ACM Trans Graph 32(4):1–10

    Article  Google Scholar 

  22. Chen JG, Davis A, Wadhwa N, Durand F, Freeman WT, Büyüköztürk O (2017) Video camera–based vibration measurement for civil infrastructure applications. J Infrastruct Syst 23(3):B4016013

    Article  Google Scholar 

  23. Chen JG, Adams TM, Sun H, Bell ES, Büyüköztürk O (2018) Camera-based vibration measurement of the World War I memorial bridge in Portsmouth New Hampshire. J Struct Eng 144(11):04018207

    Article  Google Scholar 

  24. Sarrafi A, Zhu Mao CN, Poozesh P (2018) Vibration-based damage detection in wind turbine blades using phase-based motion estimation and motion magnification. J Sound Vib 421:300–318

    Article  Google Scholar 

  25. Sefa Orak M, Nasrollahi A, Ozturk T, Mas D, Ferrer B, Rizzo P (2018) Non-contact smartphone-based monitoring of thermally stressed structures. Sens J. https://doi.org/10.3390/s1804125

    Article  Google Scholar 

  26. Wu HY, Rubinstein M, Shih E, Guttag J, Durand F, Freeman W (2012) Eulerian Video Magnification for Revealing Subtle Changes in the World. ACM Trans Graph 31(4):1–8

    Article  Google Scholar 

  27. Simoncelli E P, Freeman W T (1995) The steerable pyramid: a flexible architecture for multi scale derivative computation, Proceedings of the1995 International Conference on Image Processing (ICIP 95), Vol.3, IEEE Comput Soc, Washington DC, pp 444–447

  28. Schmid PJ (2010) Dynamic mode decomposition of numerical and experimental data. J Fluid Mech 656:5–28

    Article  MathSciNet  Google Scholar 

  29. Tu JH, Rowley CW, Luchtenburg DM, Brunton SL, Kutz JN (2014) On dynamic mode decomposition: Theory and applications. J Comput Dyn 1(2):391–421

    Article  MathSciNet  Google Scholar 

  30. Kerr AD (1978a) Analysis of thermal track buckling in the lateral plane. Acta Mech 30(1–2):17–50

    Article  Google Scholar 

  31. Donley MG, Kerr AD (1987) Thermal buckling of curved railroad tracks. Int J Non-Linear Mech 22(3):175–192

    Article  Google Scholar 

  32. Kerr AD (1978b) Lateral buckling of railroad tracks due to constrained thermal expansions—a critical survey. Elsevier, Railr Track Mech Technol, pp 141–169

    Google Scholar 

  33. Lim NH, Park NH, Kang YJ (2003a) Stability of continuous welded rail track. Compu Struct 81(22–23):2219–2236

    Article  Google Scholar 

  34. Kerr AD (1980) An improved analysis for thermal track buckling. Int J Non-Linear Mech 15(2):99–114

    Article  Google Scholar 

  35. Kish A (2011) On the fundamentals of track lateral resistance. American Railway Engineering and Maintenance of Way Association (AREMA)

  36. Martínez IN, Sanchis IV, Fernández PM, Franco RI (2015) Analytical model for predicting the buckling load of continuous welded rail tracks. Proceedings of the Institution of Mechanical Engineers, Part F, J Rail Rapid Transit 229(5):542–552

    Article  Google Scholar 

  37. Lim NH, Park NH, Kang YJ (2003b) Stability of continuous welded rail track. Comput Struct 81(22–23):2219–2236

    Article  Google Scholar 

  38. Kostovasilis D, Thompson DJ, Hussein MFM (2017) A semi-analytical beam model for the vibration of railway tracks. J Sound Vib 393:321–337

    Article  Google Scholar 

  39. Livingston T, Beliveau JG, Huston DR (1995) Estimation of axial load in prismatic members using flexural vibrations. J Sound Vib 5:899–908

    Article  Google Scholar 

  40. Kish A, Samavedam G (2013) Track Buckling Prevention: Theory, Safety Concepts, and Applications. Final Report, DOT/ FRA/ORD-13/16

  41. Bayon A, Gascon F, Medina R, Nieves FJ, Salazar FJ (2012) On the flexural vibration of cylinders under axial loads: Numerical and experimental stusty. J Sound Vib 331:2315–2333

    Article  Google Scholar 

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Acknowledgements

The authors would like to acknowledge the sponsorship and support of the Federal Railroad Administration’s Office of Research, Development and Technology under contract FR19RPD3100000022. The purchase of the high-speed camera was possible thanks to a small grant from AAR-TTCI University Program.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Pittsburgh, PA, Pittsburgh, 15261, USA

    A. Enshaeian, M. Belding & P. Rizzo

  2. Department of Civil and Environmental Engineering, Northeastern University, Boston, MA, 02115, USA

    L. Luan & H. Sun

  3. Department of Civil and Environmental Engineering, MIT, Cambridge, MA, 02139, USA

    H. Sun

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  1. A. Enshaeian
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  2. L. Luan
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  3. M. Belding
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  4. H. Sun
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  5. P. Rizzo
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Correspondence to P. Rizzo.

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Enshaeian, A., Luan, L., Belding, M. et al. A Contactless Approach to Monitor Rail Vibrations. Exp Mech 61, 705–718 (2021). https://doi.org/10.1007/s11340-021-00691-z

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