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Mitigating the Effect of Incomplete Measurement in Sensitivity-Based FE Model Updating by Enhanced Transfer Function

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Iranian Journal of Science and Technology, Transactions of Civil Engineering Aims and scope Submit manuscript

Abstract

Finite-element method is widely used for estimation of the structural behavior at various states. The finite-element (FE) models are not, however, a perfect representation of the real-life structures. In order to find a perfect FE model of the structure as well as monitoring of structural parameter changes, the FE model must be updated to match with real-life model. The curse of incomplete measurement is a major challenge for an updating method, especially in frequency domain. This paper proposes and investigates the replacement of the unmeasured degrees of freedom (DOFs) by experimentally enhanced decomposed transfer function (EDTF), in a FRF-based sensitivity equation to mitigate the adverse effects of data incompleteness. The enhanced transfer function is reached by a truncated set of experimentally measured natural frequencies and damping loss factors of real model. To highlight the merits of the EDTF in mitigating the effect of incomplete measurement, it is compared with the dynamic expansion of measured mode shapes. The results of the numerical investigations show that proposed approach is more efficient than dynamic expansion in the presence of high measurement error, large damages (parameter changes) and fewer measured DOFs. Besides, EDTF eliminates the need for modal data measurement up to a frequency much higher than the highest excitation frequency, which is necessary in dynamic expansion method. In this study, linear least-square method bounded with impartial side constraints is used for solving the sensitivity-based error minimization problem needed for model updating. Furthermore, fifty sets of numerically simulated error-contaminated FRF data are adopted to conduct Monte-Carlo analysis of the robustness of model updating results against error. The mean and coefficient of variation of estimated parameters are utilized for results indication and illustration purpose.

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Authors and Affiliations

  1. Department of Maritime Engineering, Amirkabir University of Technology, 424 Hafez Avenue, P.O. Box 15875-4413, Tehran, Iran

    Masoud Pedram & Akbar Esfandiari

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  1. Masoud Pedram
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  2. Akbar Esfandiari
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Correspondence to Masoud Pedram.

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Pedram, M., Esfandiari, A. Mitigating the Effect of Incomplete Measurement in Sensitivity-Based FE Model Updating by Enhanced Transfer Function. Iran J Sci Technol Trans Civ Eng 43 (Suppl 1), 467–486 (2019). https://doi.org/10.1007/s40996-018-0180-6

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  • DOI: https://doi.org/10.1007/s40996-018-0180-6

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