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为定量描述湍流风场和解决湍流风谱模型选择时存在盲目性和不准确性等问题,基于多种湍流风谱模型并考虑湍流强度、地表粗糙度及空间高度的影响,生成不同程度的风速时间序列曲线。基于图像识别技术和计盒维数法对各条件下风速曲线分形维数进行计算。结果表明:不同湍流风谱模型具有不同的分形特性;湍流风分形特性受湍流强度和地表粗糙度影响;相同地貌特征和气候条件下,不同高度处风速时间序列数据具有不同的分形维数。
In order to quantitatively describe the turbulence wind field and solve the blindness and inaccuracy in the selection of the turbulent wind spectrum model, various degrees of wind speed are generated based on a variety of turbulence wind spectrum models and considering the effects of turbulence intensity, surface roughness and space height Time series curve. The fractal dimension of the wind speed curve under each condition was calculated based on the image recognition technology and the box-counting dimension method. The results show that different turbulence models have different fractal characteristics. The fractal characteristics of turbulent wind are affected by turbulence intensity and surface roughness. Under the same landform and climatic conditions, the wind speed time-series data have different fractal dimensions at different altitudes.