Application of Nonlinear Autoregressive with Exogenous Input Model to Estimate the Linear and Nonlinear Characteristic Parameters of Structural Systems

碩士 === 國立臺灣大學 === 工程科學及海洋工程學研究所 === 99 === During the past decade, although the linear structural system identification had been well developed, the nonlinear response was often taken as noise or neglected throughout the linear system identification procedure. Therefore, in this thesis, using the NA...

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Bibliographic Details
Main Authors: Chi-Hsueh Wu, 吳季學
Other Authors: 柯文俊
Format: Others
Language:zh-TW
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/09580707115133272663
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Summary:碩士 === 國立臺灣大學 === 工程科學及海洋工程學研究所 === 99 === During the past decade, although the linear structural system identification had been well developed, the nonlinear response was often taken as noise or neglected throughout the linear system identification procedure. Therefore, in this thesis, using the NARX (Nonlinear AutoRegressive with eXogenous input) model, a nonlinear characteristic parameters identification formula was derived. And combining with state-space system identification theorem, the linear and nonlinear characteristic parameters were estimated successfully. Furthermore, the differences between linear and nonlinear characteristics were discussed. Using Volterra series, the GFRF (generalized frequency response function) was derived; and basing on the GFRF, the nonlinear characteristics of nonlinear structural systems were examined. In the end, the nonlinear system identification procedure was applied on computer simulations, including free and forced vibrations in single-degree-of-freedom and three-degree-of-freedom structural systems. The procedure was then further applied on two real structural system identification cases, one is the impact test of a vertical cantilever steel beam structure, and the other one is the earthquake shaking test of a Bench-Mark-Model, which was conducted by National Center for Research on Earthquake Engineering of R.O.C. All the results of identifications are represented completely.