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Embedded Shape Memory Alloy Particles for the Self-Sensing of Fatigue Crack Growth in an Aluminum Alloy.

机译:嵌入式形状记忆合金颗粒,用于铝合金中疲劳裂纹扩展的自感知。

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摘要

Future aerospace vehicles will be built using novel materials for mission conditions that are difficult to replicate in a laboratory. Structural health monitoring and condition-based maintenance will be critical to ensure the reliability of such vehicles. A multi-functional aluminum alloy containing embedded shape memory alloy (SMA) particles to detect fatigue crack growth is proposed. The regions of intensified strain near the tip of a growing fatigue crack cause the SMA particles to undergo a solid-to-solid phase transformation from austenite to martensite, releasing a detectable and identifiable acoustic emission (AE) signal that can be used to locate the crack in the affected component.;This study investigates the AE response of two SMA systems, Ni-Ti, and Co-Ni-Al. Tensile (Ni-Ti) and compressive (Co-Ni-Al) tests were conducted to study the strain-induced transformation response in both of the alloy systems. It was found that the critical stress for transformation in both SMA systems was easily identified by a burst of AE activity during both transformation and reverse transformation. AE signals from these experiments were collected for use as training data for a Bayesian classifier to be used to identify transformation signals in a Al7050 matrix with embedded SMA particles.;The Al/SMA composite was made by vacuum hot pressing SMA powder between aluminum plates. The effect of hot pressing temperature and subsequent heat treatments (solutionizing and peak aging) on the SMA particles was studied. It was found that, at the temperatures required, Co-Ni-Al developed a second phase that restricted the transformation from austenite to martensite, thus rendering it ineffective as a candidate for the embedded particles. Conversely, Ni-Ti did survive the embedding process and it was found that the solutionizing heat treatment applied after hot pressing was the main driver in determining the final transformation temperatures for the Ni-Ti particles. The effect of hot pressing on the transformation temperatures was negated upon solutionizing and peak aging occurred at a sufficiently low temperature to as not affect the properties of the Ni-Ti.;Strain-induced transformation was confirmed in the Ni-Ti particles by digital image correlation (DIC) using an environmental scanning electron microscope (ESEM). Specimens were fatigue pre-cracked until a crack was produced and observed to be approaching a particle that could be monitored on the surface, at which point it was put into the ESEM for DIC under tensile loading. Acoustic emission activity was observed during this experiment. In order to distinguish AE signals arising due to phase transformation in the particles from those due to crack extension in the matrix, a Bayesian classifier was constructed based on frequency parameters calculated using the Hilbert-Huang transform (HHT). Using this classifier, AE signals consistent with those arising from phase transformation in bulk Ni-Ti were identified during phase transformation in the particles as observed with DIC.;In addition to tensile crack growth in the ESEM, a fatigue crack was grown through a specimen with particles interspersed along the specimen center line. Several low amplitude AE events were observed as the crack grew through the aluminum. As the fatigue crack passed through the line of particles AE events increased dramatically in rate of occurance and amplitude. Amplitudes were 6-10 times higher as the crack passed near the particles. These AE events were also shown to be consistent with Ni-Ti phase transformation.;A successful proof-of-concept was demonstrated for an aluminum alloy with embedded particles that emit an identifiable and repeatable AE signal in the presence of a fatigue crack, allowing for quick diagnosis of fatigue crack damage in this material.
机译:未来的航空航天飞行器将使用新颖的材料制造,以适应难以在实验室复制的任务条件。结构健康监测和基于状况的维护对于确保此类车辆的可靠性至关重要。提出了一种包含嵌入形状记忆合金(SMA)颗粒的多功能铝合金,以检测疲劳裂纹扩展。疲劳裂纹不断扩展的尖端附近的应变增加区域使SMA颗粒经历了从奥氏体到马氏体的固-固相变,释放出可检测和可识别的声发射(AE)信号,可用于定位本研究调查了两种SMA系统Ni-Ti和Co-Ni-Al的AE响应。进行了拉伸(Ni-Ti)和压缩(Co-Ni-Al)测试,以研究两种合金体系中应变诱导的相变响应。已经发现,通过在转化和反向转化期间的AE活性的爆发,很容易识别出两个SMA系统中转化的临界应力。收集来自这些实验的AE信号作为贝叶斯分类器的训练数据,以用于识别带有嵌入SMA颗粒的Al7050基质中的转化信号。Al / SMA复合材料是通过真空热压SMA粉末在铝板之间制成的。研究了热压温度和后续热处理(固溶和峰值时效)对SMA颗粒的影响。发现在所需温度下,Co-Ni-Al形成了第二相,该第二相限制了从奥氏体到马氏体的转变,因此使其无法用作嵌入粒子的候选者。相反,Ni-Ti确实能经受住包埋过程,并且发现热压后进行的固溶化热处理是确定Ni-Ti颗粒最终转变温度的主要驱动力。固溶时热压对相变温度的影响被消除,并且在足够低的温度下发生峰值时效以至于不影响Ni-Ti的性能。;通过数字图像在Ni-Ti颗粒中证实了应变诱导的相变使用环境扫描电子显微镜(ESEM)进行关联(DIC)。将样品疲劳预开裂,直到产生裂纹为止,并观察到接近了可以在表面上监测的颗粒,然后将其放入拉力载荷下的EIC中进行DIC。在该实验期间观察到声发射活性。为了区分由于粒子中的相变而产生的AE信号与由于基质中的裂纹扩展而产生的AE信号,基于使用希尔伯特-黄(Hilbert-Huang)变换(HHT)计算的频率参数,构造了贝叶斯分类器。使用该分类器,通过DIC观察到,在颗粒的相变过程中识别出与整体Ni-Ti的相变相一致的AE信号;除了ESEM中的拉伸裂纹扩展之外,还通过试样生长了疲劳裂纹颗粒沿着样品中心线散布。当裂纹通过铝扩展时,观察到一些低振幅的AE事件。随着疲劳裂纹穿过粒子线,AE事件的发生率和幅度急剧增加。当裂纹通过颗粒附近时,振幅要高6-10倍。这些AE事件也被证明与Ni-Ti相变是一致的;;对于具有嵌入颗粒的铝合金,在疲劳裂纹的存在下发射出可识别且可重复的AE信号的成功概念验证得到了证实,用于快速诊断这种材料的疲劳裂纹损伤。

著录项

  • 作者

    Leser, William Paul.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Engineering Aerospace.;Engineering Mechanical.;Engineering Materials Science.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 143 p.
  • 总页数 143
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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