Study on two mode-mixing resistant empirical Mode Decomposition methods

Abstract

Empirical Mode Decomposition (EMD) is an adaptive decomposition method developed in non-stationary signal processing. But one of the main drawbacks of the EMD is the appearance of mode-mixing when high frequency components in a signal contain intermittence in time domain. The paper discusses two new mode-mixing resistant methods: frequency heterodyne EMD method and masking signal EMD method. The principle and the operating steps of these methods are studied in detail, as well as their comparison. The simulation and application in a backlash nonlinearity system shows that both of them can successfully solve the mode-mixing problem in normal EMD method.