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A non-contacting approach for full field dynamic strain monitoring of rotating structures using the photogrammetry, finite element, and modal expansion techniques.

机译:使用摄影测量法,有限元和模态扩展技术对旋转结构进行全场动态应变监测的非接触方法。

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摘要

Health monitoring of rotating structures such as wind turbines and helicopter rotors is generally performed using conventional sensors that provide a limited set of data at discrete locations near or on the hub. These sensors usually provide no data on the blades or interior locations where failures may occur. Within this work, an unique expansion algorithm was extended and combined with finite element (FE) modeling and an optical measurement technique to identify the dynamic strain in rotating structures. The merit of the approach is shown by using the approach to predict the dynamic strain on a small non-rotating and rotating wind turbine. A three-bladed wind turbine having 2.3-meter long blades was placed in a semi-built-in boundary condition using a hub, a machining chuck, and a steel block. A finite element model of the three wind turbine blades assembled to the hub was created and used to extract resonant frequencies and mode shapes. The FE model was validated and updated using experimental modal tests. For the non-rotating optical test, the turbine was excited using a sinusoidal excitation, a pluck test, arbitrary impacts on three blades, and random force excitations with a mechanical shaker. The response of the structure to the excitations was measured using three-dimensional point tracking. A pair of high-speed cameras was used to measure the displacement of optical targets on the structure when the blades were vibrating. The measured displacements at discrete locations were expanded and applied to the finite element model of the structure to extract the full-field dynamic strain. The results of the work show an excellent correlation between the strain predicted using the proposed approach and the strain measured with strain-gages for all of the three loading conditions. Similar to the non-rotating case, optical measurements were also preformed on a rotating wind turbine. The point tracking technique measured both rigid body displacement and flexible deformation of the blades at target locations. The measured displacements were expanded and applied to the finite element model of the turbine to extract full-field dynamic strain on the structure. In order to validate the results for the rotating turbine, the predicted strain was compared to strain measured at four locations on the spinning blades using a wireless strain-gage system. The approach used in this work to predict the strain showed higher accuracy than measurements obtainable by using the digital image correlation technique. The new expansion approach is able to extract dynamic strain all over the entire structure, even inside the structure beyond the line of sight of the measurement system. Because the method is based on a non-contacting measurement approach, it can be readily applied to a variety of structures having different boundary and operating conditions, including rotating blades.
机译:通常使用常规传感器对旋转结构(例如风力涡轮机和直升机旋翼)进行健康监控,该常规传感器在轮毂附近或轮毂上的离散位置提供有限的数据集。这些传感器通常不会在可能发生故障的刀片或内部位置上提供任何数据。在这项工作中,扩展了独特的扩展算法,并将其与有限元(FE)建模和光学测量技术相结合,以识别旋转结构中的动态应变。通过使用该方法预测小型非旋转和旋转风力涡轮机上的动态应变,可以显示该方法的优点。使用轮毂,机加工卡盘和钢块,将具有2.3米长叶片的三叶片风力涡轮机置于半内置边界条件下。创建了组装到轮毂的三个风力涡轮机叶片的有限元模型,并将其用于提取共振频率和振型。使用实验模态测试验证并更新了有限元模型。对于非旋转光学测试,使用正弦波激励,弹力测试,对三个叶片的任意冲击以及机械振动器的随机力激励来激励涡轮。使用三维点跟踪测量了结构对激发的响应。当叶片振动时,使用一对高速相机测量光学目标在结构上的位移。扩展了在离散位置处测得的位移,并将其应用于结构的有限元模型,以提取全场动态应变。工作结果表明,在所有三种载荷条件下,使用该方法预测的应变与使用应变计测得的应变之间都具有极好的相关性。与不旋转的情况类似,光学测量也在旋转的风力涡轮机上进行。点跟踪技术可测量目标位置处叶片的刚体位移和弹性变形。扩展测得的位移并将其应用于涡轮机的有限元模型,以提取结构上的全场动态应变。为了验证旋转涡轮机的结果,将预测的应变与使用无线应变仪系统在旋转叶片上四个位置处测得的应变进行了比较。与通过使用数字图像相关技术获得的测量结果相比,在这项工作中用于预测应变的方法显示出更高的精度。新的扩展方法能够提取整个结构的动态应变,甚至是超出测量系统视线的结构内部。由于该方法基于非接触式测量方法,因此可以轻松地应用于具有不同边界和操作条件的各种结构,包括旋转叶片。

著录项

  • 作者

    Baqersad, Javad.;

  • 作者单位

    University of Massachusetts Lowell.;

  • 授予单位 University of Massachusetts Lowell.;
  • 学科 Mechanical engineering.;Civil engineering.;Aerospace engineering.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 130 p.
  • 总页数 130
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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