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Experimental scenarios. (a) This scenario only includes the presence of uncorrelated independent noise at the inputs and outputs; (b) This scenario includes the presence of uncorrelated independent noise at the inputs and outputs and presence of unknown forces acting on the system.
In modal identification, the value of the model parameters and the associated uncertainty depends on the quality of the measurements. The maximum likelihood estimator (mle) is a consistent and efficient estimator. This means that the value of the parameters trends asymptotically close to the true value, while the variance of such parameters is the...
Context in source publication
... different estimators mle, Dmle, D o mle and D ? mle are compared in a system under two scenarios: The first scenario presents uncorrelated independent noise added at the inputs and outputs of the system with levels that reach signal to noise ratios (SNR) of 70, 50, 40, 30, 20, 15 and 10 dB. The second scenario covers the conditions of the first one, but includes the presence of an unknown excitation. The unknown excitation reach attenuations (regarding the known excitation) of ?50 and ?10 dB. Table 1 summarizes the employed levels while the Figure 1 illustrates the experimented scenarios. The different estimators will be assessed by mean of the general variance (GV) of the parameters of the system (the GV can be seen as a scalar measure of the overall multidimensional scatter of the analyzed data. Lower the GV value is, lower variance in the parameters) and the computational execution time. Table 1. SNR and attenuation levels used for the input, output and unknown excitation. ...