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Rotor blade operational data analysis methods and applications for health monitoring of wind turbines using integrated blade sensing.

机译:转子叶片运行数据分析方法和应用程序,通过集成叶片传感技术对风力发电机组进行健康监测。

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摘要

Wind energy is one of the fastest growing sources of power production in the world today. In order to extract the maximum potential amount of energy from the wind, a wind turbine's reliability must be a top priority. As utility scale wind turbines increase in size and initial capital investment cost, there also comes an increasing need to monitor the health of the turbine. Currently, most wind turbines do not incorporate blade mounted inertial sensing in addition to blade strain measurements. This approach has the potential to detect inevitable blade damage types early on so that a maintenance schedule can be optimized and the damage does not propagate to the point of blade failure or even damage to the drivetrain components.;In this thesis, the wind turbine blade's structural dynamic response is simulated and analyzed with the goal of characterizing the presence and severity of a shear web disbond. Computer models of a five megawatt (MW) offshore utility scale wind turbine were created to develop effective algorithms for detecting such damage. It was shown through data analysis that with the use of blade measurements, a shear web disbond could be quantified according to its length. An aerodynamic sensitivity study was conducted to ensure robustness of the developed detection algorithms. In all analyses, the measurements of the blade's flap-wise acceleration and root pitch- ing moment were the clearest indicators of the presence and severity of a shear web disbond. In fact, the RMS flap-wise blade tip acceleration decreased as much as 35% in the presence of a shear web disbond. These results were correlated to extracted stiffness properties of the damaged blades showing that the torsional and flap-wise stiffnesses were most sensitive to the disbond. Based on the results of the sensitiv- ity study, the damage detection strategy was refined in order to encompass several different wind loading conditions. In addition, a maintenance action strategy was included. A combination of blade and non-blade measurements were formulated into a final algorithm for the detection and quantification of the disbond.
机译:风能是当今世界上增长最快的电力生产来源之一。为了从风中提取最大的潜在能量,必须将风力涡轮机的可靠性放在首位。随着公用事业规模的风力涡轮机的尺寸增加和初始资本投资成本的增加,对监视涡轮机的健康状况的需求也日益增加。当前,除了叶片应变测量之外,大多数风力涡轮机不包括叶片安装惯性感测。这种方法有可能尽早发现不可避免的叶片损坏类型,从而可以优化维护计划,并且损坏不会蔓延到叶片故障甚至不会损坏动力传动系统组件的位置。模拟和分析结构动力响应,以表征剪切腹板剥离的存在和严重性。创建了5兆瓦(MW)的海上公用事业规模风力涡轮机的计算机模型,以开发用于检测此类损坏的有效算法。通过数据分析表明,通过使用刮刀测量,可以根据其长度来量化抗剪腹板的剥离。进行了空气动力学灵敏度研究,以确保开发的检测算法的鲁棒性。在所有分析中,对叶片的襟翼方向加速度和根部俯仰力矩的测量是剪切幅剥离的存在和严重程度的最清晰指标。实际上,在存在抗剪腹板的情况下,RMS襟翼方向的叶尖加速度降低了35%。这些结果与受损叶片的刚度特性相关,表明扭转刚度和襟翼刚度对脱胶最敏感。根据敏感性研究的结果,完善了损伤检测策略,以涵盖几种不同的风荷载条件。此外,还包括一项维护行动策略。将刀片和非刀片测量的组合制定为最终算法,用于检测和量化胶结。

著录项

  • 作者

    Myrent, Noah J.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Mechanical engineering.
  • 学位 M.S.M.E.
  • 年度 2013
  • 页码 89 p.
  • 总页数 89
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:41:17

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