摘要
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。
For quantitative description of turbulence wind field and solving the blindness and inaccuracy of turbulent wind spectrum model,the wind speed fluctuation curve is generated based on different turbulent wind spectrum modelsand considering turbulence intensity,the influence of surface roughness and space height. Based on the technology of image recognition and box-counting dimension,the fractal dimension of time series curve is calculated. The results show that the different turbulence wind spectrum model have different fractal characteristics. Turbulent wind is affected by turbulence intensity and surface roughness. Under the same physiognomy and climate conditions,the wind speed time series data of different height have different fractal dimensions.
出处
《热能动力工程》
CAS
CSCD
北大核心
2017年第5期118-124,共7页
Journal of Engineering for Thermal Energy and Power
基金
国家自然科学基金资助项目(51676131
51176129)
上海市科学技术委员会项目资助(13DZ2260900)
关键词
湍流风谱
图像识别
计盒维数法
分形维数
turbulent wind spectrum
image identification
box-counting dimension method
fractal dimension