Abstract
The nonlinear behavior is the primary attribute of the dynamic system stability. In this study, the time-delayed transfer entropy method is proposed to identify the nonlinear dynamic behavior of hydropower house and civil construction, including the transport directionality of information, cracked damage location, and degree of dynamic nonlinearity. Differing from the objects investigated in currently available literature, large-scale civil engineering structures such as hydropower house are more complex and larger size, which stimulate the demand for special identification techniques. Due to the fact that nonlinearity of hydropower house can be induced by many types of interactions between structure and mechanism, a simple similarity model of a multistory building, including damaged contact nonlinearity is studied first following by a discussion of the method for identifying information transmission directionality of the linear or nonlinear structure. The method for identifying the source and degrees of structural nonlinearity vibration is described. Furthermore, the procedure for identification of nonlinearity dynamic behavior in the hydropower house structure based on transfer entropy is studied based on a prototype field experiment under various load cases. Rather than the traditional linear signal processing tools and identification methods, the advantage of this proposed method is to identify the nonlinearity dynamic characteristics of hydropower house structure. This study provides a valuable reference for identifying the damage-induced nonlinearities in civil engineering structures as well as studying the nonlinear dynamic characteristics of hydropower house.
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Acknowledgement
This work was supported by “the Fundamental Research Funds for the Central Universities” (10MG33), and by Open Research Fund Program of State key Laboratory of Hydroscience and Engineering, Tsinghua University (sklhse-2010-C-01).
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Sun, WQ., Yan, DM. Identification of the nonlinear vibration characteristics in hydropower house using transfer entropy. Nonlinear Dyn 75, 673–691 (2014). https://doi.org/10.1007/s11071-013-1094-2
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DOI: https://doi.org/10.1007/s11071-013-1094-2