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Gaussian mixture model and delay-and-sum based 4D imaging of damage in aircraft composite structures under time-varying conditions

机译：时变条件下飞机复合结构损伤的高斯混合模型和基于延迟和的4D成像

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摘要

In the field of structural health monitoring (SHM) of aircraft composite structures, piezoelectric sensor network and guided wave (GW) based imaging method has proved to be a promising damage monitoring method and has been widely researched. However, the current work has barely considered that aircraft structures are usually subject to random and complex time-varying conditions, which may introduce uncertainties into the acquired GW signals and make it hard to realize reliable damage imaging and localization. Aiming at this issue, this paper proposes a Gaussian mixture model (GMM) and delay-and-sum based 4D imaging method to achieve reliable damage monitoring of aircraft composite structures under time-varying conditions. In this method, the GMM is adopted to suppress the time-varying influence and to construct time-invariant feature signal which is only affected by damage. During the monitoring process, by continuously updating GMM and constructing time-invariant feature signal, the delay-and-sum based 4D imaging can be performed to generate a serial of images with damage gradually emerging, from which the damage can be accurately located. The method is validated on a stiffened carbon fiber composite plate within a temperature range from -20 ℃ to 60 ℃. Validation results indicate that reliable damage imaging and localization under temperature variation is achieved.
机译：在飞机复合结构的结构健康监测（SHM）领域，基于压电传感器网络和导波（GW）的成像方法已被证明是一种有前途的损伤监测方法，并得到了广泛的研究。然而，目前的工作几乎没有考虑到飞机结构通常会受到随机和复杂的时变条件的影响，这可能会给所获取的GW信号带来不确定性，从而难以实现可靠的损害成像和定位。针对这一问题，本文提出了一种基于高斯混合模型（GMM）和基于时延和求和的4D成像方法，以实现在时变条件下飞机复合结构的可靠损伤监测。在这种方法中，采用GMM来抑制时变影响并构造仅受损坏影响的时不变特征信号。在监视过程中，通过连续更新GMM并构造时不变特征信号，可以执行基于延迟和的4D成像，以生成一系列逐渐出现损伤的图像，从中可以准确定位损伤。该方法在温度为-20℃至60℃的碳纤维增强复合板上验证。验证结果表明，在温度变化下可以实现可靠的损伤成像和定位。

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