Dynamic Parameter Characterization for Railway Bridges Using System Identification

  • Pradipta Banerji
  • Sanjay Chikermane


The problem of structural health monitoring of railway bridges is an ongoing research area, and numerous researchers have worked in this domain. The fundamental problem of condition assessment can be addressed by identifying the dynamic parameters like fundamental frequencies and mode shapes of tested structures and validating numerical models using these identified parameters. The entire problem can hence be broken down into two major areas, one of identifying the dynamic parameters in a robust manner from site data and the other of creating updated numerical models which exhibit convergence with these. In the present paper, the first of these areas is addressed. Various system identification techniques are presented along with their results to illustrate the robustness of the various techniques. A novel method is also developed to identify the mode shapes using sparse sensor applications. In this paper the model updation techniques developed elsewhere by the authors is used in conjunction with system identification to as a synthesized approach to identification of mode shapes. All the techniques are illustrated by application on an existing in-service railway bridge to verify these techniques for real structures. In this paper, the concept of global and local modes is introduced where the structural modes involving the movement of the entire structure are termed as global modes, whereas the modes involving only certain elements are termed as local modes. It is shown that a system identification technique is possible which identifies and differentiates these.


Dynamic parameter characterization Railway bridges System identification approaches Structural health monitoring 


  1. Banerji, P., & Chikermane, S. (2009a). Structural parameter estimation of two bridges from site data using an Eigen value realization algorithm. 4th International Conference on Structural Health Monitoring on Intelligent Infrastructure (SHMII-4), Zurich.Google Scholar
  2. Banerji, P., & Chikermane, S. (2009b). Structural parameter estimation of two bridges from site data using Kalman filters and stochastic subspace algorithm. IV ECCOMAS Thematic Conference on smart structures and materials (smart’09), Porto.Google Scholar
  3. Banerji, P., & Chikermane, S. (2011). Structural health monitoring of a steel railway bridge for increased axle loads. Structural Engineering International, 21(2), 210–216.CrossRefGoogle Scholar
  4. Bendat, J. S., & Piersol, A. G. (1980). Engineering applications of correlation and spectral analysis. New York, NY: John Wiley & Sons.Google Scholar
  5. Brincker, R., Zhang, L., & Andersen, P. (2000). Modal identification from ambient responses using frequency domain decomposition. Proc. of the 18th Intl. Modal Analysis Conference (IMAC), San Antonio, Texas.Google Scholar
  6. Doebling, S. W., Farrar, C. R., Prime, M. B., & Shevitz, D. W. (1996). Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: a literature review, Los Alamos National Laboratory Report LA-13070-MS.Google Scholar
  7. Ewins, D. J. (1984). Modal testing: Theory and practice. Taunton: Research Studies Press Ltd..Google Scholar
  8. James III, G. H., Carne, T. G. and Lauffer, J. P. (1993). The Natural Excitation Technique (NExT) for modal parameter extraction from operating wind turbines, Sandia Report, SAND92-1666 UC-261.Google Scholar
  9. Juang, J. N., & Phan, M. Q. (2001). Identification and control of mechanical systems. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  10. Van Overschee, P., & De Moor, B. (1996). Subspace identification for linear systems: theory, implementation, applications. Boston/London/Dordrecht: Kluwer.CrossRefGoogle Scholar
  11. Yanev, B. (1998). The management of bridges in New York City. Engineering Structures, 20(11), 1020–1026.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Pradipta Banerji
    • 1
  • Sanjay Chikermane
    • 2
  1. 1.Department of Civil EngineeringIIT Bombay, PowaiMumbaiIndia
  2. 2.Department of Civil EngineeringIndian Institute of Technology RoorkeeRoorkeeIndia

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