A time-domain model-based method for the identification of multi-frequency signal parameters

2014 ◽  
Vol 9 (06) ◽  
pp. P06019-P06019
Author(s):  
Y Guo ◽  
J Tan
Keyword(s):  
Time Domain ◽  
Domain Model ◽  
Frequency Signal ◽  
Model Based ◽  
Signal Parameters

MESFET large-signal model based on small-signal measurements for time-domain CAD

1988 ◽  
Vol 24 (15) ◽  
pp. 973 ◽  
Author(s):  
A. Ouslimani ◽  
G. Vernet ◽  
J.C. Henaux ◽  
P. Crozat ◽  
R. Adde
Keyword(s):  
Time Domain ◽  
Small Signal ◽  
Large Signal ◽  
Signal Model ◽  
Model Based

scholarly journals Prediction of deepwater riser VIV with an improved time domain model including non-linear structural behavior

2021 ◽  
Vol 236 ◽  
pp. 109508
Author(s):  
Sang Woo Kim ◽  
Svein Sævik ◽  
Jie Wu ◽  
Bernt Johan Leira
Keyword(s):  
Time Domain ◽  
Domain Model ◽  
Structural Behavior ◽  
Non Linear ◽  
Deepwater Riser

scholarly journals Time domain model for calculation of pure in-line vortex-induced vibrations

2017 ◽  
Vol 68 ◽  
pp. 158-173 ◽  
Author(s):  
J.V. Ulveseter ◽  
S. Sævik ◽  
C.M. Larsen
Keyword(s):  
Time Domain ◽  
Domain Model ◽  
Line Vortex ◽  
Vortex Induced Vibrations

mparison of model-based identification methods for reserve-capacity assessment of existing bridges

2018 ◽  
Author(s):  
Marco Proverbio ◽  
François-Xavier Favre ◽  
Ian F. C. Smith
Keyword(s):  
Parameter Identification ◽  
Structural Identification ◽  
Domain Model ◽  
Reserve Capacity ◽  
Steel Bridge ◽  
Model Based ◽  
Wrong Identification ◽  
Alternative Methodology ◽  
Existing Bridges ◽  
Residual Minimization

The goal of model-based structural identification is to find suitable values of parameters that affect structure behaviour. To this end, measurements are often compared with predictions of finiteelement models. Although residual minimization (RM) is a prominent methodology for structural identification, it provides wrong parameter identification when flawed model classes are adopted. Error-domain model falsification (EDMF) is an alternative methodology that helps identify candidate models – models that are compatible with behaviour measurements – among an initial model population. This study focuses on the comparison between RM and EDMF for the structural identification of a steel bridge in Exeter (UK). Advantages and limitations of both methodologies are discussed with reference to parameter identification and prognosis tasks such as quantification of reserve capacity. Results show that the employment of RM may lead to wrong identification and unsafe estimations of reserve capacity.

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