A Time-Domain Modal Parameter Identification for CNC Machine Tools Using Singular Spectrum Analysis (SSA)

2009 ◽  
Author(s):  
F. J. Alonso ◽  
D. R. Salgado ◽  
I. Cambero ◽  
Vicente Jesus Segui
Keyword(s):  
Parameter Identification ◽  
Time Domain ◽  
Spectrum Analysis ◽  
Machine Tools ◽  
Singular Spectrum Analysis ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Singular Spectrum

Time domain load extrapolation method for CNC machine tools based on GRA-POT model

2019 ◽  
Vol 103 (9-12) ◽  
pp. 3799-3812 ◽  
Author(s):  
Jialong He ◽  
Xinyue Zhao ◽  
Guofa Li ◽  
Chuanhai Chen ◽  
Zhaojun Yang ◽  
...  
Keyword(s):  
Time Domain ◽  
Machine Tools ◽  
Extrapolation Method ◽  
Cnc Machine Tools ◽  
Cnc Machine

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.

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