风电叶片玻璃纤维布铺层装备的运动学分析
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摘要
针对风电叶片玻璃纤维布铺层过程的多自由度特性,开发一套自动化铺层装备。对布辊回转单元构建基于双坐标系的位姿变换矩阵,得到布辊的运动学模型,并获得影响铺层路径及速度的因素,可视化得到玻璃纤维布的铺层曲面轨迹。采用该装备进行现场铺布试验表明,叶片模具的实际曲面,仿真与试验的铺层路径轨迹误差不超过20 mm,速度误差小于1.5 mm/s,机构的试验误差符合玻璃纤维布铺层的技术要求,可为后续铺层控制算法开发奠定了理论依据。
Director of the multidimensional characteristics of wind turbine blade laying process,a set of automated equipment of laying for fiberglass fabric was designed. The pose transformation matrix based on the two-coordinate system was constructed for the cloth roller rotating head,and the kinematic model of the cloth roller was obtained. The factors affecting the track and speed of the laying were obtained,and the pavement surface track of the fiberglass fabric was obtained visually. The on-site paving test showed that the paving track error,which based on the actual curved surface of the blade mold,between simulation and test was within 20 mm,at the same time,speed error was within 1.5 mm/s. The test error of the mechanism could meet the requirements of the fiberglass fabric laying technology and provided subsequent layer control algorithm with the theoretical basis.
Director of the multidimensional characteristics of wind turbine blade laying process,a set of automated equipment of laying for fiberglass fabric was designed. The pose transformation matrix based on the two-coordinate system was constructed for the cloth roller rotating head,and the kinematic model of the cloth roller was obtained. The factors affecting the track and speed of the laying were obtained,and the pavement surface track of the fiberglass fabric was obtained visually. The on-site paving test showed that the paving track error,which based on the actual curved surface of the blade mold,between simulation and test was within 20 mm,at the same time,speed error was within 1.5 mm/s. The test error of the mechanism could meet the requirements of the fiberglass fabric laying technology and provided subsequent layer control algorithm with the theoretical basis.
引文
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[2] Chen Xiao,Zhao Wei,Zhao Xiaolu,et al. Failure test and finite element simulation of a large wind turbine composite blade under static loading[J]. Energy,2014,7:2274—2297.
[3] Hayashi D,Huenteler J,Lewis J I. Gone with the wind:A learning curve analysis of China′s wind power industry[J]. Energy Policy,2018,120:38—51.
[4] Zhao Pan,Shirinzadeh Bijan,Shi Yaoyao,et al. Multipass layup process for thermoplastic composites using robotic fiber placement[J]. Robotics and Computer Integrated Manufacturing,2018,49:277—284.
[5] Shirinzadeh B,Cassidy G,Oetomo D,et al. Trajectory generation for open-contoured structures in robotic fiber placement[J]. Robotics and Computer-Integrated Manufacturing,2007,23:380—394.
[6] Blom A W,Abdalla M M,Gürdal Z. Optimization of courselocations in fiber-placed panels for general fiber angledistributions[J]. Composites Science and Technology,2010,70(4):564—570.
[7]宋清华,肖军,文立伟,等.热塑性复合材料自动纤维铺放装备技术[J].复合材料学报,2016,33(6):1214—1222.[7] Song Qinghua,Xiao Jun,Wen Liwei,et al. Automated fiber placement system technology for thermoplastic composites[J]. Acta Materiae Compositae Sinica,2016,33(6):1214—1222.
[8]刘哲,金达锋,范志瑞.基于密度分布曲线法的复合材料变刚度铺层优化[J].复合材料学报,2015,32(6):1737—1744.[8] Liu Zhe,Jin Dafeng,Fan Zhirui. Ply optimization of variable stiffness for composite based on density distribution curve method[J]. Acta Materiae Compositae Sinica,2015,32(6):1737—1744.
[9]孙鹏文,侯战华,岳彩宾,等.基于遗传算法的风力机叶片结构铺层厚度优化[J].太阳能学报,2016,37(6):1566—1572.[9] Sun Pengwen,Hou Zhanhua,Yue Caibin,et al. Ply thickness optimization of wind turbine blade based on genetic algorithm[J]. Acta Energiae Solaris Sinica,2016,37(6):1566—1572.