Abstract In a previous paper, we had evidenced that the memory effect of the resistance of embedded quantum resistive strain sensors (sQRS) could be used to quantitatively assess the damage accumulation in glass fibre reinforced polymers (GFRP). In this work, to comfort this finding and to better understand the mechanisms making sQRS able to monitor the composite's damage, three techniques have been combined to look for correlations during incremental cyclic tensile tests. Experiments were performed on composite samples of different typologies, all instrumented with sQRS in their core. The strain profile measured in the vicinity of defects such as a hole or a notch by digital image correlation ( DIC), has been used to determine the strain profile to which the percolated carbon nanotube network based resistive sensors (sQRS) were exposed. Further on, acoustic emission (AE) counts were used to identify the strain level over which damages were recorded to interpret the events detected on the piezo-resistive trace of sQRS, i.e., matrix fracture, interface decohesion, fibres breakage. It is found that sQRS, through the variation of their apparent gauge factor GF, are able to detect strain concentration in their surroundings and to identify damage events in the composite, provided that the fracture behaviour has been previously analysed by AE. Finally, sQRS can keep the memory of the damage accumulated in the composite as their initial resistance shift monitors the non-reversible events associated to damage. Their implementation in composite structures should offer interesting prospects to secure their use by helping to locate stress/strain singularities and potentially anticipate the complete failure.

中文翻译：

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具有嵌入式量子电阻应变传感器 (sQRS)、声发射 (AE) 和数字图像相关 (DIC) 的复合材料损伤的交叉研究

摘要 在之前的一篇论文中，我们已经证明嵌入式量子电阻应变传感器 (sQRS) 电阻的记忆效应可用于定量评估玻璃纤维增​​强聚合物 (GFRP) 中的损伤累积。在这项工作中，为了安慰这一发现并更好地理解使 sQRS 能够监测复合材料损坏的机制，已结合三种技术来寻找增量循环拉伸试验期间的相关性。实验是在不同类型的复合样本上进行的，所有样本都在其核心中配备了 sQRS。通过数字图像相关 (DIC) 在孔或凹口等缺陷附近测量的应变分布已用于确定基于渗滤碳纳米管网络的电阻传感器 (sQRS) 所暴露的应变分布。此外，声发射 (AE) 计数用于识别记录损坏的应变水平，以解释在 sQRS 的压阻迹线上检测到的事件，即基质破裂、界面脱聚、纤维断裂。发现 sQRS 通过其表观应变系数 GF 的变化能够检测其周围的应变集中并识别复合材料中的损伤事件，前提是先前已通过 AE 分析了断裂行为。最后，sQRS 可以保持对复合材料中累积损伤的记忆，因为它们的初始电阻变化监测与损伤相关的不可逆事件。