Effect of embedded printed circuit board (PCB) sensors on the mechanical behavior of glass fiber-reinforced polymer (GFRP) structures
Effect of embedded printed circuit board (PCB) sensors on the mechanical behavior of glass fiber-reinforced polymer (GFRP) structures
复制标题
嵌入式印刷电路板 (PCB) 传感器对玻璃纤维增强聚合物 (GFRP) 结构机械性能的影响
DOI：
10.1088/0964-1726/25/6/065016
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发表时间：
2016
影响因子：
4.1
通讯作者：
G. Ziegmann
中科院分区：
文献类型：
--
作者：
M. Javdanitehran;R. Hoffmann;J. Groh;M. Vossiek;G. Ziegmann
将用于固化监测的介电无芯片传感器嵌入到纤维增强热固性材料中，可以监测和控制固化过程，从而提高生产质量。嵌入式传感器在处理之后保留在结构中。这局部地影响复合结构的完整性。为了研究这些因素对玻璃纤维增强聚合物（GFRP）力学性能的影响，采用真空辅助树脂传递模塑（VARTM）方法将制作在特殊低损耗基板上的传感器集成到具有不同铺层和厚度的层压板中。在参数研究中，改变传感器的尺寸，以观察其对层压板的强度和刚度的影响，根据其铺层和厚度。传感器附近的树脂丰富的区域的大小和方向，以及作为引入的传感器的后果在承载区域中的变形与结构的强度一起进行了研究。作者提出了一个经验模型，它涉及到前面提到的因素，并作为一个快速的工具，用于预测的弯曲和拉伸强度的变化与嵌入式传感器的简单结构。在这项工作中提出的方法模型的校准以及验证模型对不同的铺层和厚度的不同层压板的实验数据。拉伸和弯曲载荷下的机械测试表明，由于传感器集成的结构的强度的降低可以归因于丰富的树脂区的大小和方向，并取决于以上的扭曲的承载区域的大小。根据传感器的弹性模量，结构的刚度可以通过引入传感器而变化。
The embedding of dielectric chipless sensors for cure monitoring into fiber-reinforced thermosets allows for monitoring and controlling the curing process and consequently higher quality in production. The embedded sensors remain after the processing in the structure. This affects the integrity of the composite structure locally. In order to investigate these effects on the mechanical behavior of the glass fiber-reinforced polymer (GFRP), sensors made on special low loss substrates are integrated into laminates with different lay-ups and thicknesses using vacuum assisted resin transfer molding (VARTM) method. In a parametric study the size of the sensor is varied to observe its influence on the strength and the stiffness of the laminates according to its lay-up and thickness. The size and orientation of the resin rich areas near sensors as well as the distortion in load bearing area as the consequences of the introduction of the sensors are investigated in conjunction with the strength of the structure. An empirical model is proposed by the authors which involves the previously mentioned factors and is used as a rapid tool for the prediction of the changes in bending and tensile strength of simple structures with embedded sensors. The methodology for model's calibration as well as the validation of the model against the experimental data of different laminates with distinct lay-ups and thicknesses are presented in this work. Mechanical tests under tensile and bending loading indicate that the reduction of the structure's strength due to sensor integration can be attributed to the size and the orientation of rich resin zones and depends over and above on the size of distorted load bearing area. Depending on the sensor's elastic modulus the stiffness of the structure may vary through the introduction of a sensor.
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DOI：
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发表时间：
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DOI：
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