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Modal Parameter Uncertainty Estimates as a Tool for Automated Operational Modal Analysis: Applications to a Smart Building

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Dynamics of Civil Structures, Volume 2

Abstract

The knowledge of modal parameter uncertainties derived from operational modal analysis (OMA) can greatly improve automated decisions by providing information about the quality of the modal identification. Yet so far, this information has been largely ignored in continuous monitoring studies on civil infrastructure, especially with respect to buildings. In this paper, we implement an automated version of Covariance Based Stochastic Subspace Identification on a highly instrumented smart building. An expansion of the technique estimates uncertainty bounds for all modal parameters. Through a series of full scale experiments, we demonstrate how uncertainties are valuable tools in various contexts of automation. These include the identification and removal of badly-fitted modes, the identification of periods of high signal-to-noise ratio, and the validation of reference sensors selection.

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References

  1. Brincker, R., Andersen, P., Jacobsen, N.-J.: Automated frequency domain decomposition for operational modal analysis. In: Proceedings of the 13th SEM International Modal Analysis Conference, Nashville, pp. 661–667 (1995)

    Google Scholar 

  2. Rainieri, C., Fabbrocino, G.: Automated output-only dynamic identification of civil engineering structures. Mech. Syst. Signal Process. 24(3), 678–695 (2010)

    Article  Google Scholar 

  3. Reynders, E., Houbrechts, J., De Roeck, G.: Fully automated (operational) modal analysis. Mech. Syst. Signal Process. 29, 228–250 (2012)

    Article  Google Scholar 

  4. Cabboi, A., Magalhães, F., Gentile, C., Cunha, Á.: Automated modal identification and tracking: application to an iron arch bridge. Struct. Control Health Monit. 24(1), e1854 (2017)

    Article  Google Scholar 

  5. Cross, E.J., Koo, K.Y., Brownjohn, J.M.W., Worden, K.: Long-term monitoring and data analysis of the Tamar Bridge. Mech. Syst. Signal Process. 35, 16–34 (2012)

    Article  Google Scholar 

  6. Peeters, B., De Roeck, G.: One-year monitoring of the Z 24-Bridge: environmental effects versus damage events. Earthq. Eng. Struct. Dyn. 30(2), 149–171 (2001)

    Article  Google Scholar 

  7. Siringoringo, D., Fujino, Y.: System identification of suspension bridge from ambient vibration response. Eng. Struct. 30(2), 462–477 (2008)

    Article  Google Scholar 

  8. Magalhães, F., Cunha, Á., Caetano, E.: Online automatic identification of the modal parameters of a long span arch bridge. Mech. Syst. Signal Process. 23(2), 316–329 (2009)

    Article  Google Scholar 

  9. Zhang, Q.W., Fan, L.C., Yuan, W.C.: Traffic-induced variability in dynamic properties of cable-stayed bridge. Earthq. Eng. Struct. Dyn. 31, 2015–2021 (2002)

    Article  Google Scholar 

  10. Hu, W.-H., Moutinho, C., Caetano, E., Magalhães, F., Cunha, Á.: Continuous dynamic monitoring of a lively footbridge for serviceability assessment and damage detection. Mech. Syst. Signal Process. 33, 38–55 (2012)

    Article  Google Scholar 

  11. Döhler, M., Mevel, L., Andersen, P.: Efficient uncertainty computation for modal parameters in stochastic subspace identification. In: Proceedings of the International Cnference on Uncertainty in Structural Dynamics, pp. 4793–4805 (2012)

    Google Scholar 

  12. Reynders, E., Pintelon, R., De Roeck, G.: Uncertainty bounds on modal parameters obtained from stochastic subspace identification. Mech. Syst. Signal Process. 22(4), 948–969 (2008)

    Article  Google Scholar 

  13. Reynders, E., Maes, K., Lombaert, G., De Roeck, G.: Uncertainty quantification in operational modal analysis with stochastic subspace identification: validation and applications. Mech. Syst. Signal Process. 66–67, 13–30 (2016)

    Article  Google Scholar 

  14. Verboven, P., Parloo, E., Guillaume, P., Van Overmeire, M.: Autonomous structural health monitoring–part I: modal parameter estimation and tracking. Mech. Syst. Signal Process. 16(4), 637–657 (2002)

    Article  Google Scholar 

  15. Sarlo, R., Tarazaga, P., Kasarda, M.: Operational modal analysis of a steel-frame, low-rise building with L-shaped construction. In: Proceedings of SPIE – The International Society for Optical Engineering, vol. 10168 (2017)

    Google Scholar 

  16. Van Overschee, P., De Moor, B.: Subspace Identification for Linear System: Theory – Implementation – Applications, 1st edn. Kluwer Academic Publishers, Boston (1996)

    Book  Google Scholar 

  17. Peeters, B., De Roeck, G.: Reference-based stochastic subspace identification for output-only modal analysis. Mech. Syst. Signal Process. 13(6), 855–878 (1999)

    Article  Google Scholar 

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Acknowledgements

The authors acknowledge the support as well as the collaborative efforts provided by our sponsors, VTI Instruments, PCB Piezotronics, Inc.; Dytran Instruments, Inc.; and Oregano Systems. The authors are particularly appreciative for the support provided by the College of Engineering at Virginia Tech through Dean Richard Benson and Associate Dean Ed Nelson as well as VT Capital Project Manager, Todd Shelton, and VT University Building Official, William Hinson. The authors would also like to acknowledge Gilbane, Inc. and in particular, David Childress and Eric Hotek. We are especially thankful to the Student Engineering Council (SEC) at Virginia Tech and their financial commitment to this project. Dr. Tarazaga is also thankful for the support provided by the John R. Jones III Fellowship. The work was conducted under the patronage of the Virginia Tech Smart Infrastructure Laboratory and its members.

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Correspondence to Rodrigo Sarlo .

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Sarlo, R., Tarazaga, P.A. (2019). Modal Parameter Uncertainty Estimates as a Tool for Automated Operational Modal Analysis: Applications to a Smart Building. In: Pakzad, S. (eds) Dynamics of Civil Structures, Volume 2. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-74421-6_23

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  • DOI: https://doi.org/10.1007/978-3-319-74421-6_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74420-9

  • Online ISBN: 978-3-319-74421-6

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