Underwater acoustic signal feature extraction of mixed flow pump based on empirical wavelet transform

Abstract

The pump converts mechanical energy into potential energy, and a mixed-flow-pump combines the characteristics of an axial flow pump and a centrifugal pump. When the mixed-flow-pump operates at low flow conditions, performance instability in the hump region appears on the performance curve. This study investigates the underwater acoustic signal in this area through experiments, computational fluid dynamics (CFD), and computational aero acoustics (CAA). The hysteresis factor calculated by cross correlation (CC) is utilized to improve the dynamic time warping (DTW) signal comparison verification method. The improved method (CC-DTW) improves the ability of DTW in signal comparison and verification. Compared with the fast Fourier transform (FFT) method, it is more convincing in the comparison of experimental and simulation pressure pulsation signals. After verifying the effectiveness of pressure pulsation signals and underwater acoustic signals, a combined empirical wavelet transform and FFT method is used to analyze underwater acoustic signal in instability regions. The results indicate that the depth of instability aligns with the FFT frequence ratio of the intrinsic mode function. Based on the feature, a criterion for determining instability states in mixed-flow-pumps is proposed.