Modal parameter identification for non-linear systems using the time-domain fourier filter output method

1997 ◽  
Author(s):  
Dong-ling Tao
Keyword(s):  
Parameter Identification ◽  
Linear Systems ◽  
Time Domain ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Filter Output ◽  
Non Linear ◽  
Non Linear Systems ◽  
The Time Domain

Study of Time-Domain Techniques for Modal Parameter Identification of a Long Suspension Bridge with Dense Sensor Arrays

2009 ◽  
Vol 135 (7) ◽  
pp. 669-683 ◽  
Author(s):  
Reza D. Nayeri ◽  
Farzad Tasbihgoo ◽  
Mazen Wahbeh ◽  
John P. Caffrey ◽  
Sami F. Masri ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Time Domain ◽  
Sensor Arrays ◽  
Suspension Bridge ◽  
Modal Parameter ◽  
Modal Parameter Identification

scholarly journals On the Use of Weighted Least Squares for Time Domain Modal Parameter Identification

2004 ◽  
Vol 11 (3-4) ◽  
pp. 457-465 ◽  
Author(s):  
Jonathan E. Cooper
Keyword(s):  
Parameter Identification ◽  
Least Squares ◽  
Time Domain ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Computational Effort ◽  
High Signal ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Wide Range

An approach for the use of the Weighted Least Squares method for time domain modal parameter identification is introduced. The approach enables standard identification methods to be employed in the usual manner, except that sections of the time records with high signal-noise ratios are given a greater emphasis in the identification process. It is shown how it is possible to apply the method to a wide range of applications, including the analysis of impulse response, input-output and time varying data. A number of different weighting schemes are explored, based upon exponential weighting and the envelope of the measured data. A series of simulated tests demonstrate how the performance of conventional time domain algorithms can be improved significantly with little extra computational effort though the use of a Weighted Least Squares scheme.

Frequency Domain Modal Parameter Identification of High Order Systems in a Numerically Stable Way

1997 ◽  
Vol 119 (2) ◽  
pp. 265-270 ◽  
Author(s):  
K. Q. Xu
Keyword(s):  
Parameter Identification ◽  
Frequency Domain ◽  
Narrow Band ◽  
Wide Frequency Range ◽  
Frequency Range ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Identification Methods ◽  
The Time Domain ◽  
Experimental Data Analysis

Frequency domain modal parameter identification methods have several attractive properties as compared with the time domain methods except for the limitation of low-order-and-narrow-band per analysis. As rule of thumb, a limit of less than ten modes has been observed for several popular frequency domain algorithms. However, this paper will show, that with a proper and thorough use of the orthogonal polynomials in the frequency domain, the number of modes per analysis can be increased to as high as 75 in a comparatively wide frequency range of interest while still retaining numerical stability. Both numerical example (75 modes in 5–1000 Hz) and experimental data analysis (56 modes in 50–5000 Hz) are presented to demonstrate the effectiveness of this innovative approach.

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