风力机叶片覆冰影响因素灰色关联分析  

Grey correlation analysis on influencing factors of wind turbine blade icing

作　　者：陈彩凤 成斌[1] 李西洋[1] 杨杰[1] 莫杰 王犇 CHEN Caifeng;CHENG Bin;LI Xiyang;YANG Jie;MO Jie;WANG Ben(College of Mechanical and Electrical Engineering,Shihezi University,Shihezi,Xinjiang 832000,China)

机构地区：[1]石河子大学机械电气工程学院,新疆石河子832000

出　　处：《中国科技论文》2018年第16期1931-1936,共6页China Sciencepaper

基　　金：国家自然科学基金资助项目(51665052)

摘　　要：针对影响风力机叶片覆冰的各因素(温度、湿度、风速和水滴直径)与覆冰形态之间关系复杂、覆冰形态与覆冰原因之间存在重叠交叉等问题而不易预测风力机叶片覆冰状况,提出基于灰色关联分析预测风力机叶片的覆冰模型。首先通过正交试验,得到常规预测模型,然后将试验数据采用灰色关联分析方法进行处理,得到温度、湿度、风速和水滴直径与覆冰形态之间的关联度,将灰色关联分析的值与常规预测进行对比发现,所得结论一致。因此,得到的结论为覆冰最严重的位置是距离叶根3/4处的叶前缘,影响风力机叶片覆冰厚度因素的重要程度依次为湿度、水滴直径、风速、温度。With the problems like complicated relationship between various influencing factors （such as temperature, humidity, wind speed and diameter of water droplets） on wind turbine blade icing and the morphology of ice coating and the overlap between the ice coating and the cause of its formation, a model to predict the wind turbine blade icing was proposed based on the grey correlation analysis. Firstly, the conventional prediction model was obtained through orthogonal experiments. Then the experimental data were processed by the grey correlation analysis method to obtain the correlation between temperature, humidity, wind speed, diameter of the water droplets and the ice coating morphology. The comparison between the values of the grey correlation analysis and the conventional prediction indicates that the conclusions are consistent. Therefore, it is concluded that the most serious icing position locates in leaf front edge, three-quarters of the blade root. The influencing factors on the ice thickness of the wind turbine blades are sequentially humidity, water droplet diameter, wind speed and temperature.

关 键 词：机械与材料 风力机叶片 灰色关联 模型预测 

分 类 号：TK83[动力工程及工程热物理—流体机械及工程]