Effects of the number of pulse repetitions and noise on the velocity data from the ultrasonic pulsed Doppler method with different algorithms

Abstract

The ultrasonic pulsed Doppler technique known as the ultrasonic velocity profile (UVP) method has been widely used in many engineering fields. The analysis algorithms of the UVP, the number of pulse repetitions (Npulse), noise and reflector conditions, etc. all affect the measurement accuracy. Npulse is related to the temporal resolution, thus to improve this resolution it must be set as low as possible. However, it is known that the measurement accuracy of the instantaneous velocity becomes worse with decreasing values of Npulse. In this study, UVP analysis algorithms including the fast Fourier transform (FFT), autocorrelation, and the wavelet transform (WT) were compared via simulations and experiments using varying values of Npulse and the signal-to-noise ratio (SNR). We show that there is an appropriate Npulse for each algorithm that depends on the SNR; specifically, the value of Npulse increases with decreasing SNR. The difference between the algorithms for the velocity data was small under low noise conditions. However, a FFT with a Gaussian interpolation produced the best result under noisy conditions. In contrast the WT was relatively unaffected by noise. Therefore, a WT is the preferred choice for measuring velocity distributions if high sampling measurement is not required.