Smart Structures and Systems

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Health monitoring of multistoreyed shear building using parametric state space modeling

  • Medhi, Manab (Department of Civil Engineering, Indian Institute of Technology Guwahati) ;
  • Dutta, Anjan (Department of Civil Engineering, Indian Institute of Technology Guwahati) ;
  • Deb, S.K. (Department of Civil Engineering, Indian Institute of Technology Guwahati)
  • Received : 2006.03.16
  • Accepted : 2007.03.06
  • Published : 2008.01.25
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Abstract

The present work utilizes system identification technique for health monitoring of shear building, wherein Parametric State Space modeling has been adopted. The method requires input excitation to the structure and also output acceleration responses of both undamaged and damaged structure obtained from numerically simulated model. Modal parameters like eigen frequencies and eigen vectors have been extracted from the State Space model after introducing appropriate transformation. Least square technique has been utilized for the evaluation of the stiffness matrix after having obtained the modal matrix for the entire structure. Highly accurate values of stiffness of the structure could be evaluated corresponding to both the undamaged as well as damaged state of a structure, while considering noise in the simulated output response analogous to real time scenario. The damaged floor could also be located very conveniently and accurately by this adopted strategy. This method of damage detection can be applied in case of output acceleration responses recorded by sensors from the actual structure. Further, in case of even limited availability of sensors along the height of a multi-storeyed building, the methodology could yield very accurate information related to structural stiffness.

Keywords

References

  1. Barroso, L. R. and Rodriguez, R. (2004), "Damage detection utilizing the damage index method to a benchmark structure", J. Eng. Mech., ASCE, 130(2), 142-51. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:2(142)
  2. Bernal, D. and Gunes, B. (2004), "Flexibility based approach for damage characterization: benchmark application", J. Eng. Mech., ASCE, 130 (1), 61-70. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(61)
  3. Caicedo, J. M., Dyke, S. J. and Johnson, E. A. (2004), "Natural excitation technique and eigensystem realization algorithm for Phase I of the IASC-ASCE benchmark problem: simulated data", J. Eng. Mech., ASCE, 130(1), 49-60. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(49)
  4. Chakraverty, S. (2005), "Identification of structural parameters of multistorey shear buildings from modal data", Earthq. Eng. Struct. Dyn., 34, 543-554. https://doi.org/10.1002/eqe.431
  5. Doebling, S. W., Farrar, C. R. and Prime, M. B. (1998), "A summary review of vibration-based damage identification methods", Shock Vib. Dig., 30(2), 91-105. https://doi.org/10.1177/058310249803000201
  6. Doebling, S. W., Farrar, C. R., Prime, M. B., and 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, Rep. No. LA-13070- MS, Los Alamos N.M.
  7. Fasel, T. R., Sohn, H., Park, G. and Farrar, C. R. (2005), "Active sensing using impedance-based ARX models and extreme value statistics for damage detection", Earthq. Eng. Struct. Dyn., 34(7), 763-785. https://doi.org/10.1002/eqe.454
  8. Juang, J. N. (1994), Applied System Identification, Prentice-Hall.
  9. Lam, H. F., Katafygiotis, L. S. and Mickleborough, N. C. (2004), "Application of a statistical model updating approach on Phase I of the IASC-ASCE structural health monitoring benchmark study", J. Eng. Mech., ASCE, 130(1), 34-48. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(34)
  10. Ljung, L. (1987), System Identification: Theory for the User, Prentice-Hall.
  11. Lynch, J. P. (2004) "Linear classification of system poles for structural damage detection using piezoelectric active sensors", Proceedings of SPIE 11th Annual International Symposium on Smart Structures and Materials, San Diego, CA, USA, March.
  12. Overschee, P. V., Moor, B. D. (1993) "N4SID: numerical algorithms for state space system identification", Proceedings of the World Congress of the International Federation of Automatic control, IFAC, Sydney, Australia.
  13. Yang, J. N., Lei, Y., Lin, S. and Huang, N. (2004), "Hilbert-huang based approach for structural damage detection", J. Eng. Mech., ASCE, 130(1), 85-95. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(85)
  14. Yuan, P., Wu, Z. and Ma, X. (1998), "Estimated mass and stiffness matrices of shear building from model test data", Earthq. Eng. Struct. Dyn., 27, 415-421. https://doi.org/10.1002/(SICI)1096-9845(199805)27:5<415::AID-EQE706>3.0.CO;2-7
  15. Yuen, K., Au, S. K. and Beck, J. L. (2004), "Two-stage structural health monitoring approach for phase i benchmark studies", J. Eng. Mech., ASCE, 130(1), 16-33. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(16)

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