Hilbert - Huang Transform Power Harmonic Analysis In Applied Research

There are some limitations in traditional methods of time-frequency analysis while deal with complex fault signals, and it is unable to meet with the real-time signal analysis in large power system disturbances and power failure. Hilbert-Huang Transform (HHT) is a new non-stationary signal processing technology, including the Empirical Mode Decomposition (EMD) and Hilbert spectral analysis. In this method, arbitrary non-stationary signals was divided into a series data sequence with different characteristic scales after the first EMD treatment, each sequence is called an intrinsic mode function (IMF), and then each IMF component gained corresponding the Hilbert spectrum though Hilbert spectrum analysis, a summary of all Hilbert spectrum assembled to the spectra of the original signal. In essence, this method is a stable processing for non-stationary signal, which decomposed the different fluctuations or trends in the signal in turn, and represented the frequency content of the original signal using the final instantaneous frequency and energy.In this paper, Hilbert-Huang Transform (HHT) was used to analysis the harmonics signal in power system, simulation analysis the high frequency components of fault phase voltage in fault transmission line. The results show that, HHT method can quickly extract the signal high-frequency components, significantly reduce the time to select a suitable time window compared to wavelet analysis method , resolve the problem of time-scale and analysis time. In this paper, Hilbert-Huang Transform (HHT) was used to analysis the harmonics signal in power system, simulation analysis the high frequency components of fault phase voltage in fault transmission line. The results show that, HHT method can quickly extract the signal high-frequency components, significantly reduce the time to select a suitable time window compared to wavelet analysis method , resolve the problem of time-scale and analysis time. Though the HHT analysis of harmonic distortion in current and voltage caused by the nonlinear, we found much higher accuracy in the signal parameters than the FFT method and fuzzy analysis. We harmonic analyzed the monitor signal of the insulation of electrical equipment using HTT, decomposed the original signal though EMD, and then calculated dielectric loss angle through the sine wave parameter method. This method extracts the fundamental component, with high accuracy and good filtering effect, while without problem in wavelet and decomposition level selection. This method can effectively suppress the influence of high-order harmonic and random interference on the measurement results, and the simulation results show that the method achieve high-precision measurement of dielectric loss angle 8 in the noise background.