风电叶片检测机器人结构设计 及力学分析
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河北工业大学

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TH122

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河北省自然科学基金重点项目(E2018202338)


Wind Turbine Blade Testing Robot Structure Design and Mechanical Analysis
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Hebei University of Technology

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    摘要:

    风力发电已成为必不可少的可再生能源,然而,风力发电机叶片在紫外线辐射、冰、温度变化、污垢等恶劣环境中运行而发生故障。因此,风电叶片需要定期进行检修,针对风电叶片检修困难的问题,对当前风电叶片检修的方式、缺陷进行分析,提出了一种可在风电塔筒爬行并对风电叶片检测的新型机器人机构。该机构采用永磁吸附机构,可稳定吸附在风电塔筒壁面并在壁面移动,可根据风电叶片与塔筒的距离来调节其手臂伸出长度,从而进行对风电叶片检测。利用Solidworks、AnsysMaxwell、Adams等软件对此机器人进行结构建模及吸附机构的仿真、运动的仿真。对此机器人在不同失稳条件下进行受力分析,得到所需的吸附力,将仿真结果与计算结果进行比较。研究结果表明,该爬壁机器人的吸附能力达到吸附要求,可以稳定吸附于风电塔筒并对风电叶片进行检测。

    Abstract:

    Wind power generation has become an indispensable renewable energy source. However, wind turbine blades fail in harsh environments such as ultraviolet radiation, ice, temperature changes, and dirt. Therefore, wind turbine blades need to be regularly repaired. In view of the difficulty of wind turbine blade repair, the current wind turbine blade maintenance methods and defects are analyzed, and a new robot mechanism that can crawl on the wind tower and detect the wind turbine blades is proposed. The mechanism adopts a permanent magnet adsorption mechanism, which can be stably adsorbed on the wall surface of the wind power tower barrel and move on the wall surface, and can adjust the arm extension length according to the distance between the wind power blade and the tower barrel, so as to detect the wind power blade. Using Solidworks, AnsysMaxwell ,Adams and other software to carry out structural modeling of the robot and simulation of the adsorption mechanism, movement simulation. The robot is subjected to force analysis under different instability conditions to obtain the required adsorption force, and the simulation results are compared with the calculation results. The research results show that the wall-climbing robot's adsorption capacity meets the adsorption requirements, and it can be stably adsorbed on the wind power tower and detect the wind power blades.

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引用本文

杨雪健,张小俊. 风电叶片检测机器人结构设计 及力学分析[J]. 科学技术与工程, , ():

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  • 收稿日期:2020-11-02
  • 最后修改日期:2021-01-12
  • 录用日期:2021-01-19
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