Recurrence Characteristics Analysis of Near-Surface Wind Speed Signal with Different Sampling Frequencies

Abstract:

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.

• Periodical: Applied Mechanics and Materials (Volumes 599-601)
• Pages: 1605-1609
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.599-601.1605
• Online since: August 2014
• Authors: Ming Zeng*, Zhan Xie Wu, Qing Hao Meng, Jing Hai Li, Shu Gen Ma
• Keywords: Near-Surface Wind Speed, Recurrence Plot (RP), Recurrence Quantification Analysis (RQA), Sampling Frequency, Time Series

References

[1] J. Atema. Eddy Chemotaxis and Odor Landscapes: Exploration of Nature with Animal Sensors. Biological Bulletin, 1996, 191(1): 129~138.

DOI: 10.2307/1543074

[2] H. Ishida. Study of Autonomous Mobile Sensing System for Localization of Odor Source Using Gas Sensors and Anemometric Sensors. Sensors and Actuators A, 1994, 45(2): 153~157.

DOI: 10.1016/0924-4247(94)00829-9

[3] J.P. Echmann, S.O. Kamphorst. Recurrence Plots of Dynamical Systems. Europhysics Letter, 1987, 4(9): 973~977.

[4] J.P. Zbilut. Embeddings and Delays as Derived from Quantification of Recurrence Plots. Physical Letter A, 1992, 171(3-4): 199~203.

DOI: 10.1016/0375-9601(92)90426-m

[5] Y.B. Liu, H. Li, Z.Y. Ma and W.D. Xin. The Nonlinear Characteristics Analysis of Wind Speed Time Series. Journal of North China Electric Power University, 2008, 35(6): 99~102.

[6] M. Zeng, H.Y. Jia and Q.H. Meng. Nonlinear Analysis of the Near-surface Wind Speed Time Series. International Congress on Image and Signal Processing, 2012, 2469~2473.

DOI: 10.1109/cisp.2012.6470023

[7] T.P. Chang, H.H. Ko and F.J. Liu. Fractal Dimension of Wind Speed Time Series. Applied Energy, 2012, 93, 742~749.

DOI: 10.1016/j.apenergy.2011.08.014

[8] F. Takens. Detecting Strange Attractors in Fluid Turbulence. Dynamical Systems and Turbulence, 1981, 898, 366~381.

DOI: 10.1007/bfb0091924

[9] J.B. Gao. Recurrence Time Statistic for Chaotic Systems and Their Application. Physical Review Letter, 1999, 83(16), 3178~3181.