大型风电机组塔筒应力监测点的选取与预警
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  • 英文篇名:Selection and Early Warning of Monitoring Points of the Tower of the LargeSized Wind Turbine Unit
  • 作者:尹少平 ; 冯沫 ; 王灵梅 ; 郭跃年
  • 英文作者:YIN Shaoping;FENG Mo;WANG Lingmei;GUO Yuenian;College of Control Theory and Control Engineering,Shanxi University;China Power Investment Shanxi New Energy Co.,Ltd.;
  • 关键词:塔筒 ; 模态分析 ; 受力分析 ; person相关系数 ; 灰色神经网络 ; 应力预警
  • 英文关键词:tower;;modal analysis;;force analysis;;person correlation coefficient;;gray neural network;;stress warning
  • 中文刊名:SXFD
  • 英文刊名:Power System and Clean Energy
  • 机构:山西大学控制理论与控制工程学院;国家电投集团山西新能源有限公司;
  • 出版日期:2018-10-25
  • 出版单位:电网与清洁能源
  • 年:2018
  • 期:v.34;No.231
  • 基金:2014年度山西省煤基重点科技攻关项目(MD2014-06)~~
  • 语种:中文;
  • 页:SXFD201810012
  • 页数:7
  • CN:10
  • ISSN:61-1474/TK
  • 分类号:80-86
摘要
针对大型风电机组塔筒应力监测缺失的情况,提出基于ANSYS软件应力点的选取和person相关系数法与灰色神经网络相结合的塔筒应力预警方法。通过软件分析和现场实验,研究风电数据和塔筒应力的关系并进行塔筒预测,并首次应用到风电机组塔筒监测中。通过实例分析验证,结果表明,该方法能够有效地进行塔筒应力监测,为风电机组塔筒的检测提供依据。
        Aiming at lack of stress monitoring of the largescale wind turbine tower,a method of tower stress monitoring based on combination of ANSYS software stress point selection and Person correlation coefficient method and gray neural network is proposed. The relationship between the wind power data and the tower stress is studied through the software analysis and field experiment, and the tower stress condition is predicted,which is applied to the monitoring of the wind turbine tower. The result of the example analysis shows that the method can effectively monitor the stress of the tower and provide a basis for detection of the wind turbine tower.
引文
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