Detection of Fibre Waviness Using Ultrasonic Array Scattering Data

Detection of Fibre Waviness Using Ultrasonic Array Scattering Data
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DOI:
10.1007/s10921-013-0174-z
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发表时间:
2013-09-01
影响因子:
2.8
通讯作者:
Drinkwater, Bruce W.
Drinkwater, Bruce W.
中科院分区:
材料科学2区
文献类型:
--
作者:
Pain, Damien;Drinkwater, Bruce W.

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复合材料的成功归功于在特定方向上有利于机械性能的能力,同时最大限度地减少组件的重量。虽然复合材料的制造工艺已经逐步改进,但纤维波纹等细微缺陷仍然很常见。已知层片与所需铺叠方向的任何局部偏离都会对强度产生不利影响。因此,制造商和最终用户有兴趣在检测缺陷,如纤维波纹在不同阶段的原型和制造过程的一部分。在本文中,超声阵列是用来既形象的复合材料和提取信息的散射的内部结构的特点。散射信息被编码在散射矩阵中:定义为作为入射角和散射角的函数的来自缺陷的散射信号的远场幅度。本文提出了一种从空间局部化区域上的实验阵列数据中提取散射矩阵的方法。最终,这可能导致能够映射复合材料内散射行为的分布。该方法被证明对复合样品含有不同程度的波纹。它还表明,使用的散射矩阵的差异可以提供的可能性,以统计上区分不同的性质和严重程度的波。
Composite materials owe their success to the ability to favour mechanical properties in specific directions whilst minimising the weight of components. Although the composite manufacturing process has been progressively improved, subtle defects such as fibre waviness are still commonplace. Any localised departure of a ply from the desired lay-up direction is known to adversely affect strength. Therefore, manufacturers and end users are interested in detecting defects such as fibre waviness at various stages during prototyping and as part of the manufacturing process.In this paper, an ultrasonic array is used to both image the composite and extract information that characterises the scattering of the interior structure. The scattering information is encoded in the scattering matrix: defined as the far field amplitude of scattered signals from a defect as a function of the incident and scattering angles. A method for extracting the scattering matrix from experimental array data over a spatially localised region is presented. Ultimately this could lead to the ability to map the distribution of scattering behaviour within the composite. The method is demonstrated on composite samples containing various levels of waviness. It is also shown that use of the differences in the scattering matrices can offer the possibility to statistically differentiate wavinesses of different nature and severity.