Zhang Zhen, Cao Andong, Li Qian, Yang Weidong, Li Yan
School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai 200092, China.
Materials (Basel). 2023 May 17;16(10):3786. doi: 10.3390/ma16103786.
Fiber waviness and voids may be produced in thick composites due to improper manufacturing conditions and consequently pose a risk of structural failure. A proof-of-concept solution for imaging fiber waviness in thick porous composites was proposed from both numerical and experimental studies, via calculating ultrasound non-reciprocity along different wave paths in a sensing network constructed by two phased array probes. Time-frequency analyses were conducted to reveal the cause of ultrasound non-reciprocity in wavy composites. Subsequently, the number of elements in the probes and excitation voltages was determined for fiber waviness imaging using the ultrasound non-reciprocity with a probability-based diagnostic algorithm. The fiber angle gradient was observed to cause ultrasound non-reciprocity and fiber waviness in the thick wavy composites were successfully imaged regardless of presence of voids. This study proposes a new feature for the ultrasonic imaging of fiber waviness and is expected to contribute to processing improvement in thick composites without prior knowledge of material anisotropy.
由于制造条件不当,厚复合材料中可能会产生纤维波纹和孔隙,从而带来结构失效的风险。通过计算由两个相控阵探头构建的传感网络中沿不同波路径的超声非互易性,从数值和实验研究两方面提出了一种用于对厚多孔复合材料中的纤维波纹进行成像的概念验证解决方案。进行了时频分析以揭示波纹复合材料中超声非互易性的原因。随后,使用基于概率的诊断算法,通过超声非互易性确定用于纤维波纹成像的探头中的元件数量和激励电压。观察到纤维角度梯度会导致超声非互易性,并且无论是否存在孔隙,厚波纹复合材料中的纤维波纹都成功成像。本研究提出了一种用于纤维波纹超声成像的新特征,有望在无需材料各向异性先验知识的情况下促进厚复合材料加工工艺的改进。