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The purpose of this paper is to compare the accuracy of tracking the amplitude and frequency changes of non‐stationary electric signals.

Short‐time fourier transform (STFT) and S‐transform algorithms were applied to analyze non‐stationary signals originating from switching of capacitor banks in a power system.

The S‐transform showed possibilities of sharp localization of the basic component, and allowed improvement of tracking dynamism the transient components in comparison to STFT.

S‐transform is a better tool for the analysis of non‐stationary waveforms in power systems and its properties can be used for diagnostic and power quality applications.

The dynamic tracking of the changes in time and frequency of real‐like signals originating from a power system are investigated in this paper.

Classical techniques to estimate the spectrum of the multi‐component signal are based on Fourier‐based transformations. The frequency estimates obtained from their spectral peaks are affected by the window length and phase of signal component, thus presenting a large variance even in the absence of noise. The spectrum of the signals is estimated with the help of the Wigner‐Ville distribution and its time‐frequency representation is obtained. For the same purpose, the min‐norm method (subspace method) is used. The accuracy of the tested methods was investigated and compared with the parameters of the frequency estimation via FFT. The proposed methods were also tested with non‐stationary multiple‐component signals occurring during the fault operation of inverter‐fed drives and transmission lines.