Publicação: Harmonics filtering and detection of disturbances using wavelets
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Traditional mathematical tools, like Fourier Analysis, have proven to be efficient when analyzing steady-state distortions; however, the growing utilization of electronically controlled loads and the generation of a new dynamics in industrial environments signals have suggested the need of a powerful tool to perform the analysis of non-stationary distortions, overcoming limitations of frequency techniques. Wavelet Theory provides a new approach to harmonic analysis, focusing the decomposition of a signal into non-sinusoidal components, which are translated and scaled in time, generating a time-frequency basis. The correct choice of the waveshape to be used in decomposition is very important and discussed in this work. A brief theoretical introduction on Wavelet Transform is presented and some cases (practical and simulated) are discussed. Distortions commonly found in industrial environments, such as the current waveform of a Switched-Mode Power Supply and the input phase voltage waveform of motor fed by inverter are analyzed using Wavelet Theory. Applications such as extracting the fundamental frequency of a non-sinusoidal current signal, or using the ability of compact representation to detect non-repetitive disturbances are presented.
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Electric waveforms, Harmonic analysis, Set theory, Signal filtering and prediction, Signal theory, Waveform analysis, Wavelet transforms, Current waveforms, Disturbance detection, Harmonics filtering, Nonsinusoidal current signal, Wavelet theory, Waveshape, Signal distortion
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Inglês
Como citar
IEEE International Symposium on Industrial Electronics, v. 3, p. 1168-1173.
