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Symbolic dynamics time series analysis for assessment of barely visible indentation damage in composite sandwich structures based on guided waves

机译:基于导波的复合夹层结构中几乎可见凹痕损伤的象征性动力学时间序列分析

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摘要

This study addresses the detection and localization of barely visible indentation damage in composite sandwich structures using ultrasonic guided waves. A quasi-static loading was gradually applied on a specimen of carbon fiber reinforced epoxy with honeycomb core, with the resulting dent size varying between 0.2 and 2.7mm. The fundamental symmetric (S-0) Lamb wave mode was excited to interrogate the structure. An anomaly measure was established based on symbolic time series analysis; it was defined as the ratio between the norms of probability vectors obtained from the symbol sequence vectors before and after damage has occurred. The symbolic time series analysis method transforms time series data into symbol sequences according to a pre-constructed symbol space using a set number of partitions. The number of partitions selected was determined based on the maximum Shannon's entropy approach. An imaging algorithm was adopted in order to localize the damage. The effects of the excitation frequency and the number of partitions on the precision of prediction were investigated. The adopted approach showed high sensitivity to a very small change of 0.2mm on the surface panel after a quasi-static loading of 2-mm indentation. Furthermore, the ability of the method to detect progressive damage was demonstrated. The results obtained demonstrate that symbolic time series analysis has excellent potential for use in detecting small defects such as barely visible indentation damage.
机译:本研究解决了使用超声波引导波的复合夹层结构中几乎可见凹口损伤的检测和定位。逐渐施加对碳纤维增强环氧树脂样品的准静电载荷,其凹痕尺寸在0.2和2.7mm之间变化。对称对称(S-0)兰姆波模式令人兴奋以询问该结构。基于象征时间序列分析建立了异常措施;它被定义为从损坏之前和之后从符号序列向量获得的概率向量之间的比率。符号时间序列分析方法根据使用设定的分区的预构造的符号空间将时间序列数据转换为符号序列。选择的分区数是基于最大Shannon的熵方法确定的。采用了成像算法以便本地化损坏。研究了激发频率和对预测精度的分区数量的影响。采用的方法在2mm压痕的准静态负载后,在表面面板上对表面面板的0.2mm的较高敏感性高。此外,证明了方法检测渐进损伤的能力。所获得的结果表明,符号时间序列分析具有出色的潜力,用于检测诸如几乎可见的压痕损伤的小缺陷。

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