Analysis of Non Stationary Data Signals Using Hilbert Haung Transform

Abstract

In real world applications, most of the signals are Non-stationary and time-varying. Now a day's analysis of Non stationary and time-varying signals is one of the major concerns in engineering. There are several approaches are present to analyze the various Nonstationary and time-varying signals in that time-frequency analysis methods are more prominent than other approaches like Fourier transform, which can only provide the information entirely either in frequency domain or time domain, while time-frequency approaches gives information in time - frequency plane. In practical applications, the Fourier transform is not best tool, due to most of signals encountered in engineering are Nonstationary and time-varying. In order to study the Non stationary signals, the time-frequency techniques are introduced. In this, study the characteristics of various time-frequency approaches like Wigner-Ville distribution (WVD), Pseudo-WVD (PWVD), Hilbert-Huang transform (HHT). From simulation results, HHT is a good approach for feature extraction in Non stationary signal processing.