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The analysis of offshore islands wind characteristics in Taiwan by Hilbert–Huang transform
Abstract In this study, the Hilbert–Huang transform (HHT) with empirical mode decomposition was applied to analyze the wind characteristics of offshore islands in Taiwan. The daily wind data for 40 years of three weather stations at Pengjia Islet, Dongji Islet and Penghu were investigated. The wind speed series signals were decomposed into the intrinsic mode functions and discussed in the Hilbert spectrum. The results of rolling average analysis, Fast Fourier transform (FFT) and HHT analysis are presented to show the wind characteristics under various time-scale variations. The rolling average statistics analysis shows that the wind data have significantly non-stationary features. Fourier spectrum analysis results identified various frequency peaks. And HHT analysis indicated that Pengjia Islet has a peak of 3 cycle-per-year. Mean frequency and percentage power of the intrinsic mode functions showed that Dongji Islet has strong annual variation, and Pengjia Islet has the strong variation of the 3–7 day period.
Highlights ► 47 years daily wind speed data of offshore islands are analyzed by HHT. ► Rolling average statistics analysis shows the significantly non-stationary features. ► Fourier spectrum analysis identified various frequency peaks. ► The values of IMFs table resolve climate characteristics for various scales.
The analysis of offshore islands wind characteristics in Taiwan by Hilbert–Huang transform
Abstract In this study, the Hilbert–Huang transform (HHT) with empirical mode decomposition was applied to analyze the wind characteristics of offshore islands in Taiwan. The daily wind data for 40 years of three weather stations at Pengjia Islet, Dongji Islet and Penghu were investigated. The wind speed series signals were decomposed into the intrinsic mode functions and discussed in the Hilbert spectrum. The results of rolling average analysis, Fast Fourier transform (FFT) and HHT analysis are presented to show the wind characteristics under various time-scale variations. The rolling average statistics analysis shows that the wind data have significantly non-stationary features. Fourier spectrum analysis results identified various frequency peaks. And HHT analysis indicated that Pengjia Islet has a peak of 3 cycle-per-year. Mean frequency and percentage power of the intrinsic mode functions showed that Dongji Islet has strong annual variation, and Pengjia Islet has the strong variation of the 3–7 day period.
Highlights ► 47 years daily wind speed data of offshore islands are analyzed by HHT. ► Rolling average statistics analysis shows the significantly non-stationary features. ► Fourier spectrum analysis identified various frequency peaks. ► The values of IMFs table resolve climate characteristics for various scales.
The analysis of offshore islands wind characteristics in Taiwan by Hilbert–Huang transform
Hsieh, Cheng-Han (author) / Dai, Chi-Fu (author)
Journal of Wind Engineering and Industrial Aerodynamics ; 107-108 ; 160-168
2012-04-14
9 pages
Article (Journal)
Electronic Resource
English
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