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New modal identification method under the non-stationary Gaussian ambient excitation

  • Xiu-li Du (杜秀丽)Email author
  • Feng-quan Wang (汪凤泉)
Article

Abstract

Based on the multivariate continuous time autoregressive (CAR) model, this paper presents a new time-domain modal identification method of linear time-invariant system driven by the uniformly modulated Gaussian random excitation. The method can identify the physical parameters of the system from the response data. First, the structural dynamic equation is transformed into a continuous time autoregressive model (CAR) of order 3. Second, based on the assumption that the uniformly modulated function is approximately equal to a constant matrix in a very short period of time and on the property of the strong solution of the stochastic differential equation, the uniformly modulated function is identified piecewise. Two special situations are discussed. Finally, by virtue of the Girsanov theorem, we introduce a likelihood function, which is just a conditional density function. Maximizing the likelihood function gives the exact maximum likelihood estimators of model parameters. Numerical results show that the method has high precision and the computation is efficient.

Key words

modal identification uniformly modulated function continuous time autoregressive model Brownian motion exact maximum likelihood estimator 

Chinese Library Classification

O324 O211.63 TU311.3 

2000 Mathematics Subject Classification

60H10 70J10 70L05 

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Copyright information

© Shanghai University and Springer Berlin Heidelberg 2009

Authors and Affiliations

  • Xiu-li Du (杜秀丽)
    • 1
    Email author
  • Feng-quan Wang (汪凤泉)
    • 2
  1. 1.College of Mathematical SciencesNanjing Normal UniversityNanjingP. R. China
  2. 2.College of Civil EngineeringSoutheast UniversityNanjingP. R. China

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