Characterizing nonstationary wind speed using empirical mode decomposition
Characterizing nonstationary wind speed using empirical mode decomposition
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DOI：
10.1061/(asce)0733-9445(2004)130:6(912
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发表时间：
2004-06-01
影响因子：
4.1
通讯作者：
Chen, J
中科院分区：
文献类型：
--
作者：
Xu, YL;Chen, J
本文探讨了如何表征非平稳风速，可以建模为一个确定性的时变平均风速分量加上一个平稳的随机过程的脉动风速分量。采用经验模态分解（EMD）方法，从非平稳风场数据中自然提取时变平均风速。利用台风维克托期间安装在青马悬索桥上的风速计记录的风场数据，计算了风场的时变平均风速、脉动风速的概率分布、风谱、湍流强度和阵风因子。所得的风特性进行了比较与传统的方法的基础上得到的一个固定的风模型。研究发现，大多数非平稳风数据可以分解成一个时变的平均风速加上一个良好的行为脉动风速承认作为一个平稳的随机过程与高斯分布。经验模态分解在指定频率下识别的时变平均风速比传统的时均平均风速更自然。所提出的方法也可以适用于固定的风速与传统的方法获得相同的输出。它的结论是，所提出的方法是更合适的比传统的方法来表征风速。
This paper explores how to characterize nonstationary wind speed that can be modeled as a deterministic time-varying mean wind speed component plus a stationary random process for the fluctuating wind speed component. The time-varying mean wind speed is naturally extracted from the nonstationary wind data using the empirical mode decomposition (EMD). The proposed approach is then applied to the wind data recorded by the anemometers installed in the Tsing Ma suspension Bridge during Typhoon Victor to find its time-varying mean wind speed, probability distribution of fluctuating wind speed, wind spectrum, turbulence intensity, and gust factor. The resulting wind characteristics are compared with those obtained by the traditional approach based on a stationary wind model. It is found that most of nonstationary wind data can be decomposed into a time-varying mean wind speed plus a well-behaved fluctuating wind speed admitted as a stationary random process with a Gaussian distribution. The time-varying mean wind speed identified by EMD at a designated intermittency frequency level is more natural than the traditional time-averaged mean wind speed over the certain time interval. The proposed approach can also be applied to stationary wind speed with the same output as obtained by the traditional approach. It is concluded that the proposed approach is more appropriate than the traditional approach for characterizing wind speed.