Extraction characteristics of pressure signals of oil pulsating flow with different particle concentration based on wavelet analysis

Abstract

The particle concentration in oil has a significant impact on the pressure signal of oil flow; it has multi-layer and multi-scale vibration characteristics. The pressure signal of oil was analyzed using the Morlet wavelet function on its for has 6-layer decomposition, and the corresponding wavelet coefficients of oil samples with different particle concentrations are obtained. The energy density and vibration energy distribution of pressure signals along time series are analyzed. The results show that with the increase of particle concentration in the oil, the number of the extreme value of the wavelet coefficient and its difference range is reduced in the range of 30–64 wavelet decomposition scale of the distributions of the real part of the wavelet coefficient of oil pulsating flow along with the time series, and the degree of cyclical of pressure signal gradually reduce; In the same particle concentration, the periodicity of pulsating flow decreases with the decrease of the wavelet decomposition scale; With the increase of particle concentration, the wavelet decomposition scales corresponding to the first and second main periods gradually increases, and the vibration frequency of the first and second main periods of the oil pulsating flow pressure signal decreases successively.