Identification of Nonlinearity Using Transfer Entropy Combined with Surrogate Data Algorithm
Publication: Journal of Engineering Mechanics
Volume 145, Issue 2
Abstract
A numerical time-delayed transfer entropy method combined with a surrogate data algorithm is proposed to identify the nonlinearities in the vibration data of structures with damages without the use of baseline data. Semianalytical methods based on the Galerkin method are used to precisely predict the linear and nonlinear response of structures. The proposed method can identify nonlinearities in vibration data well. A new nonlinearity index is also proposed. Computation results for different loads indicate that the nonlinearity index increases as load increases. Subsequently, a new discreteness degree index for transfer entropy is additionally proposed. The responses of a plate with different loads are calculated and linear relationships between the discreteness degree index and the nonlinearity index are obtained. Numerical examples with different geometries but similar nonlinearity indexes are also carried out. It is shown that the discreteness degree index for transfer entropy can quantitatively measure nonlinearity degree. As verified, the proposed methodology can be used for structure nonlinearity identification in areas such as civil engineering, mechanical engineering, and ocean engineering.
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Acknowledgments
The authors gratefully acknowledge the financial support provided by the 973 Program of China (No. 2013CB035901), the Fundamental Research Funds for the Central Universities, and the National Natural Science Foundation of China (Nos. 51379185 and 51679214).
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Published In
Journal of Engineering Mechanics
Volume 145 • Issue 2 • February 2019
Copyright
©2018 American Society of Civil Engineers.
History
Received: Sep 13, 2017
Accepted: Aug 17, 2018
Published online: Dec 11, 2018
Published in print: Feb 1, 2019
Discussion open until: May 11, 2019
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