The identification of the load causing partial yielding on the basis of the dynamic characteristics
Abstract
Possible yielding of the cross-section of a structure, which may arise as a result of external actions or the (micro)defects, might significantly decrease the safety margin of the considered structure [2] . Since the cross-section yielding affects the structure stiffness, the dynamic characteristics (eigenvalues and eigenvectors) might be significantly different then the ones of the original structure. The measurement of the changes of the dynamic parameters may provide the information necessary to identify the load causing the yielding of the cross-section and further the yielding index (which may be calculated when the load causing the yielding is know) enables the evaluation of the structure safety margin. This paper presents the application of Artificial Neural Networks (ANN) [4, 9] in the identification of the load casing partial yielding of simply-supported beam and one- or two-column frames.
Keywords
finite element method, identification, dynamics, artificial neural networks,References
[1] W.F. Chen, D.J. Han. Plasticity for Structural Engineers. Springer-Verlag, New York/ Berlin/Heidelberg, 1988.[2] W.F. Chen, H. Zhang. Structural Plasticity: Theory, Problems and CAE Software. Springer-Verlag, New York/ Berlin/ Heidelberg, 1991.
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[4] S. Haykin. Neural Networks. A Comprehensive Foundation. Prentice-Hall, Upper Saddle River, 2nd ed., 1999.
[5] B. Miller, G. Piątkowski, L. Ziemiański. Beam yielding load identification by neural networks. Comput. Assisted Mech. Engrg. Sci., 6(3-4): 449- 467, 1999.
