碩士 / 國立成功大學 / 航空太空工程學系 / 107 / Offshore wind energy is one of the popular power resources to solve the global energy crisis. Wind turbine blades are strongly influenced by turbulence structure and small scale turbulence fluctuation is the main cause of structure damage. This enhances the importance of understanding the characteristics of wind turbulence to prevent wind turbines from damages. In this study, wind data was collected from the meteorological mast located at offshore of Changhua, Taiwan, at a sampling rate of 1 Hz. Data set was collected from two periods of Aug. 16, 2016 to June 22, 2017 and Dec. 1, 2017 to Nov. 30, 2018 while monsoons and typhoons extreme conditions occurred.
HHT uses the empirical mode decomposition (EMD) and adds white noises to become the ensemble empirical mode decomposition (EEMD), which has the ability to analyse the non-linear and unsteady data, e.g. atmospheric turbulence. During this process, the signal is decomposed into a series called intrinsic mode function (IMF). In this study, trend and low frequency IMF are not considered in this study and the rest is analysed by Probability Density Function (PDF) and Fast Fourier Transform (FFT) in order to find the characteristic of ideal turbulence.
| Identifer | oai:union.ndltd.org:TW/107NCKU5295042 |
| Date | January 2019 |
| Creators | Weng-HanLin, 林翁瀚 |
| Contributors | Jiun-Jih Miau, 苗君易 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 91 |
Page generated in 0.0022 seconds