Frequency-domain TLS and GTLS algorithms for modal analysis applications

This contribution focuses on the area of modal analysis and studies the applicability of Total Least Squares algorithms for the estimation of modal parameters in the frequency domain from Input-Output Fourier data. These algorithms provide an alternative for the frequency response function based estimators, especially in the case that the measurement data is characterized by low signal-to-noise ratios, short data sequences and leakage. In this paper it is shown how frequency-domain TLS and GTLS estimators can be numerically optimized to handle large amounts of modal data. Using an errors-in-variables noise model, a linear approximation is necessary in order to obtain a fast implementation of the GTLS algorithm. The validity of this approximation is a function of the signal-to-noise ratio of the input Fourier data and is evaluated by means of Monte Carlo simulations and experimental data.