新翼型风力机叶片综合性能的实验研究

以自制新翼型风力机风轮为研究对象,在B1/K2直流式低速风洞完成自制新翼型风力机的功率特性测试实验,采用丹麦B＆K公司结构动态测试系统完成风轮结构动态特性实验,并与国内某公司同型号传统翼型的风力机进行气动特性、结构动态特性的对比分析,为下一步系统研究新翼型的气动特性和设计综合性能较优的风轮奠定了理论和实验基础.     

风力机叶片大挠度挥舞振动特性分析

分析了风力机叶片大挠度挥舞振动特性.基于Hamilton原理,建立了叶片大挠度挥舞振动控制方程,其中非稳态气动力由Greenberg公式得出.使用瑞利-利兹法求解振动特征问题,得到振动的频率和无阻尼模态函数.基于得出的模态函数,使用Galerkin方法将控制偏微分方程离散,得到模态坐标方程.将振动位移分解为静态位移和动态位移,得到了静态位移和动态位移方程,考查了入流速度比对静态位移和气动阻尼的影响,并对大挠度挥舞振动动态响应进行了分析,得到如下结论：大挠度挥舞振动静态位移沿叶片展向随入流速度比的增大而增大,叶尖处位移最大；当入流速度比较小时,振动为小振幅的周期运动,入流速度比较大时,振动为大振幅的拟周期运动.     

Design of low noise airfoil with high aerodynamic performance for use on small wind turbines

Wind power is one of the most reliable renewable energy sources and internationally installed capacity is increasing radically every year.Although wind power has been favored by the public in general,the problem with the impact of wind turbine noise on people living in the vicinity of the turbines has been increased.Low noise wind turbine design is becoming more and more important as noise is spreading more adverse effect of wind turbine to public.This paper demonstrates the design of 10 kW class wind turbi...     

基于轻量型YOLOv5的风机桨叶检测与空间定位

应用无人机对风力发电机进行自主巡检时,需对其桨叶叶尖进行精准定位,同时因机载计算板的计算能力有限,常规目标检测算法检测效率低下。为此提出了一种基于轻量型YOLOv5的风机桨叶检测与空间定位方法,首先对YOLOv5目标检测算法进行轻量化改进,将ShuffleNetv2作为特征提取主干网络;然后利用该算法对风机全景图像中的风机轮毂和桨叶进行检测,以得到轮毂和桨叶叶尖的像素坐标;最后利用无人机位姿信息和空间平面的几何关系,对风机桨叶进行精准定位。实验表明,所改进的目标检测算法以1.536×10⁶的参数量在大疆MANIFOLD2-C上的检测速度提升47%,可达29.4 f/s,所设计的定位方法可对风机桨叶叶尖进行精准定位,水平和高度定位误差均为±5 cm,三维整体定位误差为±10 cm。     

An experimental research study on the effect of pictorial icons on a user-learner’s performance

This experimental counterbalanced repeated measures study on the effect of three types of icons (abstract, pictorial and drawing) on the learning and performance of two types of learners (abstract and concrete) was conducted during the Spring 2000–Spring 2001 semesters at the University of Central Florida. The counterbalanced lesson followed by a counterbalanced and completely randomized quiz on three levels was field tested in the Spring–Summer 2000 on 37 UCF graduate students and final tested in the Fall 2000–Spring 2001 on 53 UCF graduate student subjects. A general linear model repeated measures ANOVA revealed that icon type had a significant effect on the learning and performance of both types of learners. Pictorial icons resulted in best scores. No significant interaction was found between icon type and learner type even though on a matched condition, abstract learners with abstract icon resulted in better scores than when concrete learners were matched with concrete (pictorial and drawing) icons. Implications for future research are drawn as well as practical applications identified in the field of teaching, learning, training and performance.