Abstract
Development and implementation of new and innovative damage detecting techniques is at the forefront of civil engineering advancements. One such technique, presented herein, is formulated to identify damage in steel frames. This study utilizes modal analysis and Bayesian inference model calibration techniques to detect connection damage in steel frames, and is illustrated on a two-bay, two-story scaled steel model. Rotational stiffness coefficients for the connections of the finite element model of the undamaged frame are calibrated through the comparison of model predictions with experimental data. Damage in the form of the removal of bolts at the base connection of one column is then introduced into the experimental frame and features are extracted through dynamic testing. Modal features are used to identify damage, and the calibration of connection spring stiffnesses is used to identify the location of the damage. The shift in natural frequencies of the first four modes indicates damage (i.e. loss of stiffness). The reduction in the calibrated rotational stiffness parameters for the base connection indicates that the damage is present in the base connections of the structure.
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References
Park S, Yun C-B, Roh Y, Lee J-J (2006) PZT-based active damage detection techniques for steel bridge components. Smart Mater Struct 15:957–966
Carr GE, Chapetti MD (2010) On the detection threshold for fatigue cracks in welded steel beams using vibration analysis. Int J Fatigue 33:642–648
Wahab AMM, De Roeck G (1999) Damage detection in bridges using modal curvatures: application to a real damage scenario. J Sound Vib 226(2):217–235
Dutta A, Talukdar S (2004) Damage detection in bridges using accurate modal parameters. Finite Elem Anal Des 40:287–304
Vestroni F (2008) Structural identification and damage detection. In: Morassi A, Vestroni F (eds) Dynamic methods for damage detection in structures. Springer, Austria, pp 111–135
Friswelli MI (2008) Damage identification using inverse methods. In: Morassi A, Vestroni F (eds) Dynamic methods for damage detection in structures. Springer, Austria, pp 13–66
Hemez FM (2008) Convergence. In a course on the validation and verification of computational models, Lecture 10
Kennedy M, O’Hagan A (2000) Predicting the output from a complex computer code when fast approximations are available. Biometrika 87:1–13
Higdon D, Gattiker J, Williams B, Rightley M (2008) Computer model calibration using high-dimensional output. JAm Stat Assoc 103(482):570–583
Higdon D, Nakhleh C, Gattiker J, Williams B (2008) A Bayesian calibration approach to the thermal problem. Comput Meth Appl Mech 197:2431–2441
Acknowledgments
The authors would like to acknowledge Danny Metz for all of his hard work in construction of the test frame.
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© 2012 The Society for Experimental Mechanics, Inc.
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Hegenderfer, J., Atamturktur, S., Gillen, A. (2012). Damage Detection in Steel Structures Using Bayesian Calibration Techniques. In: Allemang, R., De Clerck, J., Niezrecki, C., Blough, J. (eds) Topics in Modal Analysis II, Volume 6. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-2419-2_16
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DOI: https://doi.org/10.1007/978-1-4614-2419-2_16
Publisher Name: Springer, New York, NY
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