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郭艳珍,张磊安,隋文涛,等. 风电叶片全尺度静力试验加载力布置优化[J]. 科学技术与工程, 2019, 19(28): 147-151.
GUO Yan-zhen,et al.Optimization of loading force arrangement for full-scale static test of wind turbine blades[J].Science Technology and Engineering,2019,19(28):147-151.
风电叶片全尺度静力试验加载力布置优化
Optimization of loading force arrangement for full-scale static test of wind turbine blades
投稿时间:2019-03-22  修订日期:2019-05-01
DOI:
中文关键词:  风电叶片 静力试验 加载力布置 粒子群优化 软件开发
英文关键词:wind turbine blade static test loading force arrangement particle swarm optimization software development
基金项目:山东省重点研发计划,2018GGX100304;第11批中国博士后科学基金特别资助,2018T110704;第62批中国博士后科学基金一等资助,2017M620291
              
作者单位
郭艳珍 山东理工大学机械工程学院
张磊安 山东理工大学机械工程学院
隋文涛 山东理工大学机械工程学院
王景华 山东理工大学机械工程学院
黄雪梅 山东理工大学机械工程学院
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中文摘要:
      静力试验是风电叶片全尺度检测的必备环节,为了提高试验中弯矩分布精度,基于引入叶片自重的弯矩计算模型,本文提出了一种用于加载力布置的变参型粒子群优化算法。首先,研究了不同加载点数加载力布置的弯矩分布特性,结果表明弯矩分布精度与加载点数正相关,且对加载位置极其敏感。其次,通过动态更新学习因子和惯性权重,并引入概率0.2的粒子变异,改进了粒子群算法,提高了算法收敛性和搜索平衡性,尤其提高了叶片叶根和过渡区的弯矩分布精度。最后,基于上述理论开发了一套静力试验加载力布置软件,取得了很好的工程应用效果。
英文摘要:
      Static test is an essential part for full-scale detection of wind turbine blade. In order to improve the accuracy of bending moment distribution in test, an improved particle swarm optimization algorithm for loading force arrangement was proposed based on the model of moment calculation introduced blade weight. Firstly, the moment distribution characteristics of different loading points were studied. The results show that the bending moment distribution accuracy is positively correlated with loading point and sensitive to loading position. Secondly, the convergence and the search balance of particle swarm optimization algorithm was improved by dynamically updating the learning factor and inertia weight, and introducing the particle variation with probability of 0.2, especially the bending moment distribution accuracy of the blade root and transition zone are improved. Based on the above theory, a set of loading force layout software for static test is developed, which achieve good engineering application results.
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