Abstract
Vibration testing is a crucial approach for identifying modal properties of a structure, e.g. natural frequencies, mode shapes and damping ratios. Based on these model properties, optimization methods can be employed to detect, locate damage and assess the status of structures. These are important goals of Structural Health Monitoring (SHM) in formulating nondestructive assessment tools. The paper focuses on system identification of a simply supported steel I-beam and its modal parameters, under forced excitation. Therefore, output-only system identification methods for instance: nonparametric PSD+ estimation, data-driven and covariance-driven stochastic subspace identification, will be introduced in the paper. Then modal analysis techniques using peak picking and stabilization diagram, are applied. Moreover, measurement results are verified with those obtained from Finite Element (FE) model using ANSYS. The discrepancy of outcomes with regard to eigenfrequencies, mode shapes between measurements and simulations is compared and interpreted.
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MACEC is a MATLAB toolbox and developed by many authors at the Civil Engineering department of K.U. Leuven University, Belgium. Many identification algorithms are introduced into MACEC to deal with every step in the modal analysis procedure [9].
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The theory of the Kalman filter states is not explained in this paper, please consult ref. [4] for more information.
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Please consult [4] for details of the stochastic state-space model.
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Acknowledgements
The authors acknowledge the financial support of VLIR-OUS TEAM Project, VN2018TEA479A103, ‘Damage assessment tools for Structural Health Monitoring of Vietnamese infrastructures’, funded by the Flemish Government.
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Ho, V.L., Tran, N., De Roeck, G., Bui, T., Abdel Wahab, M. (2019). System Identification Based on Vibration Testing of a Steel I-Beam. In: Abdel Wahab, M. (eds) Proceedings of the 1st International Conference on Numerical Modelling in Engineering . NME 2018. Lecture Notes in Civil Engineering , vol 20. Springer, Singapore. https://doi.org/10.1007/978-981-13-2405-5_21
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DOI: https://doi.org/10.1007/978-981-13-2405-5_21
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