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首页> 外文期刊>Journal of Alloys and Compounds: An Interdisciplinary Journal of Materials Science and Solid-state Chemistry and Physics >Detection of crack development with Al/SiCp using tensile with online acoustic emission
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Detection of crack development with Al/SiCp using tensile with online acoustic emission

机译：使用抗拉塞与在线声发射的抗拉塞裂纹裂纹发育检测

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摘要

It is important to find an easy and efficient way of finding the tensile strength of the alloys by detecting the crack development in alloys. In the present project by having used fourteen samples of Al-SiC composite pieces the energy discharge during the cracks were found out. The Acoustic Emission technique was used in this experiment. The tensile testing was achieved by tensile loading on a 100 kN universal testing machine. The values obtained using the parameters such as hits; Felicity Ratio and Rise Angle were fed into the Artificial Neural Network. The network could foresee the errors at the rate of 3.125%, - 3.515% and -2.73% of hits, felicity ratio and rise angle respectively. Among these the value -2.73% seems to be the best while using Acoustic Emission technique. Though all the three have demonstrated significantly the value obtained using the Rise Angle can be taken as the best, since it is closer to the ideal error value 'zero'. (C) 2018 Elsevier BY. All rights reserved.
机译：重要的是通过检测合金中的裂纹发育来寻找一种简单而有效的方法来找到合金的拉伸强度。 在本项目中，通过使用14个样品的Al-SiC复合物件，发现裂缝期间的能量放电。 在该实验中使用声学发射技术。 通过拉伸载荷在100KN通用试验机上实现拉伸测试。 使用诸如命中的参数获得的值; 富集比和上升角度进入人工神经网络。 该网络可以以3.125％的速率预见误差，分别为3.125％，3.515％和-2.73％的命中，富集比和上升角度。 其中，在使用声发射技术的同时是最好的。 虽然所有三个都明显展示了使用上升角度获得的值可以是最好的，因为它更接近理想的误差值'零'。 （c）2018 Elsevier。 版权所有。

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