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A quantitative acoustic emission study on fracture processes in ceramics based on wavelet packet decomposition

机译:基于小波包分解的陶瓷断裂过程声发射定量研究

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摘要

We base a quantitative acoustic emission (AE) study on fracture processes in alumina ceramics on wavelet packet decomposition and AE source location. According to the frequency characteristics, as well as energy and ringdown counts of AE, the fracture process is divided into four stages: crack closure, nucleation, development, and critical failure. Each of the AE signals is decomposed by a 2-level wavelet package decomposition into four different (from-low-to-high) frequency bands (AA_2, AD_2, DA_2, and DD_2). The energy eigenvalues P_0, P_1, P_2, and P_3 corresponding to these four frequency bands are calculated. By analyzing changes in P_0 and P_3 in the four stages, we determine the inverse relationship between AE frequency and the crack source size during ceramic fracture. AE signals with regard to crack nucleation can be expressed when P_0 is less than 5 and P_3 more than 60; whereas AE signals with regard to dangerous crack propagation can be expressed when more than 92% of P_0 is greater than 4, and more than 95% of P_3 is less than 45. Geiger location algorithm is used to locate AE sources and cracks in the sample. The results of this location algorithm are consistent with the positions of fractures in the sample when observed under a scanning electronic microscope; thus the locations of fractures located with Geiger's method can reflect the fracture process. The stage division by location results is in a good agreement with the division based on AE frequency characteristics. We find that both wavelet package decomposition and Geiger's AE source locations are suitable for the identification of the evolutionary process of cracks in alumina ceramics.
机译:我们基于小波包分解和AE源位置对氧化铝陶瓷断裂过程的定量声发射(AE)研究。根据AE的频率特性以及能量和振铃次数,将断裂过程分为四个阶段:裂纹闭合,成核,发展和临界破坏。每个AE信号通过2级小波包分解分解为四个不同的(从低到高)频带(AA_2,AD_2,DA_2和DD_2)。计算与这四个频带相对应的能量本征值P_0,P_1,P_2和P_3。通过分析四个阶段中P_0和P_3的变化,我们确定了陶瓷破裂过程中AE频率与裂纹源尺寸之间的反比关系。当P_0小于5且P_3大于60时,可以表示与裂纹成核有关的AE信号。当P_0的92%大于4,P_3的95%大于45时,可以表示与危险裂纹扩展有关的AE信号。使用Geiger定位算法定位样品中的AE源和裂纹。当在扫描电子显微镜下观察时,该定位算法的结果与样品中裂缝的位置一致;因此,用盖革方法确定的裂缝位置可以反映裂缝过程。舞台按位置划分的结果与基于AE频率特性的划分有很好的一致性。我们发现小波包分解和盖革的声发射源位置都适合于确定氧化铝陶瓷中裂纹的演化过程。

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  • 来源
    《Journal of Applied Physics》 |2014年第8期|084901.1-084901.8|共8页
  • 作者

    J. G. Ning; L. Chu; H. L. Ren;

  • 作者单位

    State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, China;

    State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, China;

    State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
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