This work presents a scientific study on Short-Time Frequency Transforms (STFT) with different windows, also called Windowed Fourier Transforms, applied to power quality signals. Additionally, it deals with S transforms, with its frequency-dependent window. The disturbances related to energy quality have non-stationary nature, in which the spectral content varies over time. So, the Fourier Transform is not appropriate for such analysis, because it doesn’t show time locations, only information about existing frequencies in the signal. Therefore, the spectral analysis by windowed transforms helps to identify and detect a series of defects associated to these power signals. The motivation behind this document is to verify which window will provide a more precise identification of the characteristics of the disturbances in time-frequency domain. For this work, synthetic signals were generated for some of these disturbances, and their spectra were compared considering Gaussian, Hann and Blackman windows, as well as the S transform. Based on the obtained results, it was verified that each transform presents different behaviours acording to the input signal, except for the ones with Hann and Blackman windows, that showed similar spectra. For all of them, there is always a tradeoff between time and frequency resolutions. Therefore, the choice of the window must be done according to the desired outputs. The Dev-C ++ ® IDE was used for C ++ programming, and the Gnuplot ® program for graphics generation.
Dictionary learning sparse-sampling reconstruction method for in-vivo 3D photoacoustic computed tomography
