复合材料层板中冲击诱导波的探测和到达时间估算

Lukas Grasboeck, Alexander Humer, A. Benjeddou
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摘要

这项工作通过实验评估了三种选定的方法,用于估算碳纤维增强聚合物板状结构受到冲击时产生的导波的到达时间(TOA)。通过对连续小波变换 (CWT)、修正能量比 (MER) 和阿凯克信息准则 (AIC) 的单独评估来实现这一目标。考虑到层状结构的各向异性,导波在这种薄壁结构中的传播面临着复杂的挑战。利用表面粘结压电陶瓷贴片传感器有助于探测和测量波在板上的传播。实验包括使用冲击锤和冲击枪在不同位置冲击平板,生成一个包含放置在不同位置的传感器捕获的信号的综合数据集。我们的研究表明,经过特定的修改,这些方法可以提供估算 TOA 的有效手段。在 CWT 框架中,引入的频域阈值跨越技术提高了 TOA 估算的精度。为了解决使用 MER 方法估计 TOA 时的轻微延迟问题,我们对该方法进行了改进,识别出第一个超过预定阈值的局部最大值。这一改进大大提高了该方法估计传感器信号 TOA 的能力。在所探讨的方法中,AIC 因其能精确检测初始撞击引起的信号变化而脱颖而出。该方法包括两个连续步骤,其中第二步对其结果有显著影响。通过将方法特定函数中的局部最小值纳入其中,而不是仅仅依赖全局最小值,在一些情况下,估算精度得到了显著提高。尽管如此,我们的修改在某些情况下还是导致了明显不准确的估计结果,表明估计结果明显过早。这些发现为成功的 TOA 估计提供了宝贵的见解,有助于影响定位等潜在应用,并为该领域的进一步研究提供了指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection and time-of-arrival estimation of impact-induced waves in composite laminates
This work assesses experimentally three selected methods for estimating the time of arrival (TOA) of guided waves generated by impacts on a carbon fiber reinforced polymer plate-like structure. This is reached by the individual evaluation of the continuous wavelet transform (CWT), the modified energy ratio (MER), and the Akaike information criterion (AIC). Considering the anisotropic nature of the laminated structure, the propagation of guided waves within such thin-walled structure presents intricate challenges. The utilization of surface-bonded piezoceramic patch sensors aids to detect and measure wave propagation across the plate. The experiments involved impacting the plate at various positions using an impulse hammer and an impact gun, generating a comprehensive dataset encompassing signals captured by sensors placed at different locations. Our investigations have revealed that, with specific modifications, these methods offer effective means of estimating the TOA. In the CWT framework, the introduced frequency domain threshold crossing technique enhances precision in the TOA estimation. To address the slight delays in TOA estimations using the MER method, we refined the method by identifying the first local maximum that exceeds a predefined threshold. This enhancement significantly improves the method’s ability to estimate the TOA of sensor signals. Among the explored methods, the AIC stands out for its precise detection of initial impact-induced signal alterations. This method consists of two sequential steps, with the second step notably influencing its outcome. By incorporating local minima from the method-specific function, instead of relying solely on the global minimum, a significant improvement in estimation accuracy was observed in several cases. Nevertheless, our modification led to notably inaccurate estimates in certain cases, indicating instances where the estimates were significantly too early. These findings offer valuable insights into successful TOA estimation, facilitating potential applications such as impact localization and guiding further research in this domain.
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