An extended time series algorithm for modal identification from nonstationary ambient response data only

Chang Sheng Lin, Dar Yun Chiang, Tse Chuan Tseng

研究成果: Article同行評審

3 引文 斯高帕斯(Scopus)

摘要

Modal Identification is considered from response data of structural systems under nonstationary ambient vibration. The conventional autoregressive moving average (ARMA) algorithm is applicable to perform modal identification, however, only for stationary-process vibration. The ergodicity postulate which has been conventionally employed for stationary processes is no longer valid in the case of nonstationary analysis. The objective of this paper is therefore to develop modal-identification techniques based on the nonstationary time series for linear systems subjected to nonstationary ambient excitation. Nonstationary ARMA model with time-varying parameters is considered because of its capability of resolving general nonstationary problems. The parameters of moving averaging (MA) model in the nonstationary time-series algorithm are treated as functions of time and may be represented by a linear combination of base functions and therefore can be used to solve the identification problem of time-varying parameters. Numerical simulations confirm the validity of the proposed modal-identification method from nonstationary ambient response data.

原文English
文章編號391815
期刊Mathematical Problems in Engineering
2014
DOIs
出版狀態Published - 2014 一月 1

All Science Journal Classification (ASJC) codes

  • Mathematics(all)
  • Engineering(all)

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