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Embedded fiber-optic strain sensors for process monitoring of composites.

机译:嵌入式光纤应变传感器,用于复合材料的过程监控。

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摘要

A new class of mechanical structures, termed "smart" or "adaptive" structures, has been proposed by engineers for use in aerospace, civil, and industrial applications. These structures integrate sensors and actuators directly into the materials from which they are formed, and are envisioned to have the ability to monitor themselves during manufacturing, assess their structural integrity, adapt to changing conditions, and perform self-repair. Two of the key enabling technologies for smart structures are fiber optic sensors and composite materials. Fiber optic sensors are capable of responding to a variety of environmental stimuli, such as temperature and strain. These small sensors can be embedded within polymer-matrix composite materials to form the basic building block of a smart structure.; In the first part of this research, the ability of fiber optic sensors to monitor residual stresses generated during the processing of composites is investigated. A new measurement technique is described--the embedded fiber optic sensor (EFOS) method--in which residual stresses are computed from measurements of internal strain and temperature using a viscoelastic, cure-dependent process model. The EFOS method has the advantage that it is non-destructive and provides information on residual stress development during cure in real-time. Experiments were performed to test the method, and the resulting residual stress measurements compared favorably with prior theoretical predictions and measurements by a destructive technique. The EFOS method was also used to accurately predict the residual-stress induced warpage in a non-symmetric composite sample.; In the second part of this work, the development of a multi-parameter fiber optic sensor is presented which is created by forming two Bragg gratings at widely spaced wavelengths in polarization-maintaining optical fiber. The spectra of the light reflected from this sensor contains four peaks which may be used, in principle, to determine axial strain, two components of transverse strain, and temperature in a single fiber. A theoretical model of the sensor was developed, and several sensors were fabricated and tested to calibrate their performance. Additional experiments were performed to verify the ability for the multi-parameter sensor to simultaneously measure two and three independent components of strain.
机译:工程师已经提出了一种新型的机械结构,称为“智能”或“自适应”结构,用于航空航天,民用和工业应用。这些结构将传感器和执行器直接集成到其形成材料中,并且可以在制造过程中进行自我监控,评估其结构完整性,适应变化的条件并进行自我修复。用于智能结构的两项关键使能技术是光纤传感器和复合材料。光纤传感器能够响应各种环境刺激,例如温度和应变。这些小型传感器可以嵌入聚合物基复合材料中,以形成智能结构的基本构建块。在本研究的第一部分中,研究了光纤传感器监视复合材料加工过程中产生的残余应力的能力。描述了一种新的测量技术-嵌入式光纤传感器(EFOS)方法-使用粘弹性,依赖于固化的过程模型通过内部应变和温度的测量来计算残余应力。 EFOS方法的优势在于它是非破坏性的,并且可以实时提供有关固化过程中残余应力发展的信息。进行了实验以测试该方法,并将所得残余应力测量结果与先前的理论预测和通过破坏性技术的测量结果进行了比较。 EFOS方法还用于精确预测非对称复合材料样品中的残余应力引起的翘曲。在这项工作的第二部分中,提出了一种多参数光纤传感器的开发,该传感器是通过在保偏光纤中形成两个在宽间隔的波长处形成的布拉格光栅来创建的。从该传感器反射的光的光谱包含四个峰值,原则上可用于确定轴向应变,两个横向应变分量和单根光纤中的温度。开发了传感器的理论模型,并制造并测试了多个传感器以校准其性能。进行了其他实验,以验证多参数传感器同时测量应变的两个和三个独立分量的能力。

著录项

  • 作者

    Lawrence, Craig Michael.;

  • 作者单位

    Stanford University.;

  • 授予单位 Stanford University.;
  • 学科 Engineering Mechanical.; Engineering Materials Science.; Physics Optics.
  • 学位 Ph.D.
  • 年度 1997
  • 页码 197 p.
  • 总页数 197
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;工程材料学;光学;
  • 关键词

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