A comparative study on the identification of the dynamical model of multi-mass electrical drives using wavelet transforms

Development of neural­network and fuzzy models of multimass electromechanical systems

“…These models do not take into consideration all factors that influence the dynamic processes in multimass systems. Studies [4][5][6][7][8][9][10][11][12][13][14] tackle the issues of improving accuracy of identification of parameters of multimass system models. A method for identifying parameters of the mechanical component of the electromechanical system with many masses and elastic connections and viscous friction between them is given in [4].…”

“…However, the presented methods have been applied in parametric identification of a linear system with delays. Paper [9] reports a study into the expediency and usefulness of employing continuous wavelet transformation for estimation of model parameters, such as attenuation factors and eigenfrequencies of two-mass and three-mass electromechanical systems. Identification using a continuous wavelet transform is compared with the Gilbert-Huang transform technique and is evaluated in terms of accuracy and ability to evaluate system parameters.…”

Parameter Identification for Structural Health Monitoring with Extended Kalman Filter Considering Integration and Noise Effect

“…In particular, the time-domain analyses have been used extensively, such as the least-squares method [1,2], Monte Carlo method [3][4][5], and filtering methods [6][7][8]. Besides, the methods of wavelet analysis [9][10][11] and Hilbert-Huang transform [12][13][14], in which the vibration signals are decomposed into the frequency/time-domain signals, have also received much attention.…”