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Methods for Expanding Rotary Wing Aircraft Health and Usage Monitoring Systems to the Rotating Frame through Real-time Rotor Blade Kinematics Estimation.

机译:通过实时转子叶片运动学估计将旋转翼飞机健康和使用情况监视系统扩展到旋转框架的方法。

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摘要

Since the advent of Health and Usage Monitoring Systems (HUMS) in the early 1990's, there has been a steady decrease in the number of component failure related helicopter accidents. Additionally, measurable cost benefits due to improved maintenance practices based on HUMS data has led to a desire to expand HUMS from its traditional area of helicopter drive train monitoring.;One of the areas of greatest interest for this expansion of HUMS is monitoring of the helicopter rotor head loads. Studies of rotor head load and blade motions have primarily focused on wind tunnel testing with technology which would not be applicable for production helicopter HUMS deployment, or measuring bending along the blade, rather than where it is attached to the rotor head and the location through which all the helicopter loads pass.;This dissertation details research into finding methods for real time methods of estimating rotor blade motion which could be applied across helicopter fleets as an expansion of current HUMS technology. First, there is a brief exploration of supporting technologies which will be crucial in enabling the expansion of HUMS from the fuselage of helicopters to the rotor head: wireless data transmission and energy harvesting. A brief overview of the commercially available low power wireless technology selected for this research is presented. The development of a relatively high-powered energy harvester specific to the motion of helicopter rotor blades is presented and two different prototypes of the device are shown.;Following the overview of supporting technologies, two novel methods of monitoring rotor blade motion in real time are developed. The first method employs linear displacement sensors embedded in the elastomer layers of a high-capacity laminate bearing of the type commonly used in fully articulated rotors throughout the helicopter industry. The configuration of these displacement sensors allows modeling of the sensing system as a robotic parallel mechanism, similar to a Stewart Platform. A calibration method for this device is developed and the improved orientation estimation results are shown. The second method is not specific to the fully articulated rotor head mounting geometry of the first method. Rather, it utilizes micro-electromechanical (MEMS) accelerometers and gyroscopes configured to measure the centrifugal acceleration and rotation rate induced through rotor head rotation differentially. By measuring these quantities differentially, other accelerations from the fuselage reference frame are removed from the measurement, resulting in acceleration and rate quantities that are impacted only by the angle of the sensors relative to the plane of rotation. By mounting these sensors strategically and symmetrically about the rotor blade root center of rotation, the orientation of the rotor blade can be estimated in real time.
机译:自1990年代初期健康和使用情况监视系统(HUMS)出现以来,与组件故障有关的直升机事故数量一直在稳步下降。此外,由于基于HUMS数据的改进维护实践而产生的可衡量的成本优势,导致人们希望将HUMS从其传统的直升机传动系统监控领域进行扩展。; HUMS扩展最令人感兴趣的领域之一是直升机的监控转子头负荷。转子头负载和叶片运动的研究主要集中在风洞测试上,该技术不适用于生产型直升机HUMS部署,也不适用于测量沿叶片的弯曲,而不是将其固定在转子头上的位置以及安装位置。本论文详细研究了实时估算转子叶片运动的实时方法的寻找方法,该方法可作为当前HUMS技术的扩展而应用于直升机机队。首先,对支持技术进行了简短的探索,这对于使HUMS从直升机的机身扩展到旋翼机头至关重要:无线数据传输和能量收集。简要概述了为此研究选择的商用低功耗无线技术。介绍了针对直升机旋翼桨叶运动的功率相对较高的能量采集器的开发,并显示了该设备的两个不同原型。;在支持技术概述之后,有两种实时监测旋翼桨叶运动的新颖方法:发达。第一种方法是将线性位移传感器嵌入到高容量层压轴承的弹性体层中,该高弹性层压轴承通常在整个直升机行业中的全铰接旋翼中使用。这些位移传感器的配置允许将传感系统建模为类似于Stewart平台的机器人并联机构。开发了该设备的校准方法,并显示了改进的方向估计结果。第二种方法并不特定于第一种方法的完全铰接的转子头安装几何形状。相反,它利用微机电(MEMS)加速度计和陀螺仪来配置,以测量通过转子头旋转产生的离心加速度和旋转速率。通过差异地测量这些量,来自机身参考系的其他加速度也从测量中移除,从而导致加速度和速率量仅受传感器相对于旋转平面的角度的影响。通过围绕转子叶片根部旋转中心策略性且对称地安装这些传感器,可以实时估算转子叶片的方向。

著录项

  • 作者

    Allred, Charles Jefferson.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Mechanical engineering.;Aerospace engineering.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 155 p.
  • 总页数 155
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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