Magnetic memory testing for early damage of wind turbine tower
-
摘要: 等比例搭建风机塔筒加载试验平台，设计加载试验，对塔筒早期损伤进行了磁记忆检测，分析了载荷、检测角度和特征缺陷对磁记忆信号的影响。结果表明：可以通过磁记忆信号的切向分量、法向分量和法向分量的梯度值来综合判断应力集中区域；对缺陷进行检测时，选择扫查角度与塔筒成90°为最佳；刻槽的应力集中程度高于平底孔的应力集中程度，因此刻槽损伤对塔筒早期损伤的破坏更加明显。Abstract: In this paper, the wind turbine tower loading test platform is built by the ratio, and the magnetic memory detection of the early damage of the tower is carried out through the loading test, and the influence of loads, detection angles and characteristic defects on the magnetic memory signal is analyzed. The results show that the judgment of the stress concentration area can be jointly judged by the gradient values of the tangential component, the normal component and the normal component of the magnetic memory signal. When detecting defects, it is best to choose a scanning angle of 90° with the tower. In addition, the stress concentration of the grooved is higher than that of the flat-bottomed hole, so the damage of the grooved hole to the early damage of the tower is more obvious.
-
Keywords:
- wind turbine tower /
- early damage /
- magnetic memory detection /
- loading test
-
-
[1] 韩帅, 刘立群, 张文超.风力发电并网运行风险评估[J].太原科技大学学报, 2021, 42(2):92-98. [2] 张立翔, 夏倩, 邱汉林, 等.新型风能发电栅栏供电系统[J].科技风, 2021(8):197-198. [3] ZHANG C Y, LU X, REN G, et al.Optimal allocation of onshore wind power in China based on cluster analysis[J].Applied Energy, 2021, 285:116482.
[4] 许金晶, 陈颖楠.风电产业发展待破的难题及应对策略[J].中国经济周刊, 2016(16):80-81. [5] 朱达川, 邓英, 周峰, 等.基于偏航系统的风电机组塔架扭转振动控制研究[J].风能, 2017(11):80-84. [6] 匡晓龙, 钟华兵, 杨庆.风机塔筒焊缝的相控阵超声检测工艺[J].无损检测, 2020, 42(2):52-55, 60. [7] HANG J, ZHANG J Z, CHENG M, et al.An overview of condition monitoring and fault diagnostic for wind energy conversion system[J].电工技术学报, 2013, 28(4):261-271. [8] 刘向军.工程流体力学[M].北京:中国电力出版社, 2013. [9] 张鹏林, 许亚星, 桑远, 等.磁记忆技术在风电塔筒检测中的应用[J].无损检测, 2014, 36(9):67-69. [10] 任吉林, 林俊明, 任文坚, 等.金属磁记忆检测技术研究现状与发展前景[J].无损检测, 2012, 34(4):3-11. [11] 王威, 易术春, 苏三庆, 等.金属磁记忆无损检测的研究现状和关键问题[J].中国公路学报, 2019, 32(9):1-21. [12] 王国庆, 杨理践, 刘斌.基于磁记忆的油气管道应力损伤检测方法研究[J].仪器仪表学报, 2017, 38(2):271-278. [13] ZHAO X R, SU S Q, WANG W, et al.Metal magnetic memory inspection of Q345B steel beam in four point bending fatigue test[J].Journal of Magnetism and Magnetic Materials, 2020, 514:167155.
[14] CHEN H L, WANG C L, ZUO X Z.Research on methods of defect classification based on metal magnetic memory[J].NDT & E International, 2017, 92:82-87.
[15] 陈云程, 陈孝耀.风力机设计与应用[M].上海:上海科学技术出版社, 1990. [16] 冷建成.基于磁记忆技术的铁磁性材料早期损伤诊断方法研究[D].哈尔滨:哈尔滨工业大学, 2012. [17] 孙海磊.风力发电机塔筒受力性能的试验研究[D].包头:内蒙古科技大学, 2012. [18] LENG J C, XU M Q, ZHOU G Q, et al.Effect of initial remanent states on the variation of magnetic memory signals[J].NDT & E International, 2012, 52:23-27.
[19] 郭霞.奥氏体不锈钢磁记忆检测与研究[D].东营:中国石油大学(华东), 2015.
计量
- 文章访问数: 6
- HTML全文浏览量: 0
- PDF下载量: 3
下载:
