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A Novel Detection of Defects in Al–SiC Composite by Active Pulsed Infrared Thermography Using Data and Image Processing
Transactions of the Indian Institute of Metals ( IF 1.6 ) Pub Date : 2020-09-11 , DOI: 10.1007/s12666-020-02074-9
R. Ruban Blessed Singh , T. Sasikumar , S. Suresh , G. Ramanan

This paper presents detection of defects on the tensile specimen of Al6061/SiC composite using active pulsed infrared thermography technique (APIRT) by data and image processing. APIRT is a powerful nondestructive evaluation tool for online monitoring of the real defects of composite which gives an accurate region of defects with respect to temperature variations. Al/SiC composites have high strength, high resistance to wear and low weight properties which increases their demand in many industrial applications. Thirty numbers of Al6061/SiC composite specimens were prepared by stir casting technique, out of which 20 specimens are defect-free with different compositions and the remaining with induced defect and cut, as per ASTM standard B577M-14. The APIRT experimental result shows that the Al/SiC composite tensile surface region with defect reveals higher temperature than region without defect and also cooling process proceeds longer in the region having defect. APIRT clearly shows that internal and external surface defects, defect areas with high thermal concentration, accurate defect area with high revolution, prediction of first failure location in specific region of specimen, coverage with large detection areas, size, depth of defect and material loss percentage of defect area are found with digital image processing.



中文翻译:

利用数据和图像处理的主动脉冲红外热成像技术检测Al-SiC复合材料中的缺陷

通过数据和图像处理,提出了利用主动脉冲红外热成像技术(APIRT)检测Al6061 / SiC复合材料拉伸试样中的缺陷的方法。APIRT是功能强大的非破坏性评估工具,用于在线监控复合材料的实际缺陷,从而针对温度变化提供准确的缺陷区域。Al / SiC复合材料具有高强度,高耐磨性和低重量特性,这增加了它们在许多工业应用中的需求。通过搅拌铸造技术制备了30个Al6061 / SiC复合材料样品,其中20个样品按照组成ASTM B577M-14的规定,无缺陷且具有不同的成分,其余的样品具有诱发的缺陷和切痕。APIRT实验结果表明,具有缺陷的Al / SiC复合拉伸表面区域比没有缺陷的区域具有更高的温度,并且在具有缺陷的区域中冷却过程进行得更长。APIRT清楚地显示出内部和外部表面缺陷,具有高热浓度的缺陷区域,具有高旋转度的准确缺陷区域,预测样品特定区域中的首次失效位置,具有较大检测区域的覆盖率,缺陷的大小,深度和材料损失百分比数字图像处理可以发现缺陷区域的数量。

更新日期:2020-09-11
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