Multifractal analysis of short-term wind speed time series with different sampling frequencies

Characterizing the fluctuations properties in wind speed signals is a significant problem in the field of nonlinear dynamics and aerodynamics. In this paper, firstly, to fully capture the details of the wind field fluctuation, a 3D ultrasonic anemometer is selected to measure the wind speed data in a short-term wind field experiment. Then, we employ the multifractal detrended fluctuation analysis (MF-DFA) to reveal the fluctuations characteristics of the short-term wind speed time series. We find that short-term wind speed data exhibit obvious multifractal dynamic behaviors, mainly due to the different long-range correlations. In particular, this multifractality is related to the nonlinear features of the wind speed time series. Furthermore, the effects of sampling frequency on multifractal features of wind speed time series are investigated. The results suggest that when the sampling frequency is higher or lower than 5Hz, there exist different power law relations between the sampling frequency and the singularity value at the peak of multifractal spectrums.