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An improved two-dimensional multiple signal classification approach for impact localization on a composite structure

机译:一种用于复合结构碰撞定位的改进的二维多信号分类方法

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Efficient impact monitoring techniques are important to be researched to ensure the safety of in-service composite structures. Multiple signal classification-based method is a new promising method. This method uses small aperture sensor array arrangement instead of sparse sensor arrangement. It has the advantage of easy sensor array arrangement. By processing the whole sensor array outputs using the multiple signal classification algorithm, transfer function and material property of the structure are not needed. Although some researches have shown the potential of this new method, most of the current researches have been performed based on the far-field assumption on aluminum structures. In engineering applications, composite structures are the main structures which need impact monitoring. Deep research needs to be addressed. Aiming at these problems, an improved two-dimensional near-field multiple signal classification processing algorithm is presented for impact localization on composite structure in this article. The proposed method can simultaneously estimate the impact occurring direction and distance. A uniform carbon fiber composite plate and a real aircraft oil tank made of carbon composite structure with varied thickness are adopted to evaluate the presented method. To deal with the anisotropy performance of the complex composite, the two-dimensional multiple signal classification processing algorithm is also improved by taking into account the existing anisotropy performance.
机译:有效的冲击监测技术对于确保在役复合结构的安全性至关重要。基于多信号分类的方法是一种有前途的新方法。该方法使用小孔径传感器阵列布置代替稀疏传感器布置。它具有容易排列传感器阵列的优点。通过使用多重信号分类算法处理整个传感器阵列的输出,不需要传递函数和结构的材料特性。尽管一些研究表明了这种新方法的潜力,但目前的大多数研究都是基于铝结构的远场假设进行的。在工程应用中,复合结构是需要影响监测的主要结构。深度研究需要解决。针对这些问题,本文提出了一种改进的二维近场多信号分类处理算法,对复合结构进行冲击定位。所提出的方法可以同时估计碰撞发生的方向和距离。采用均匀的碳纤维复合材料板和由厚度变化的碳复合结构制成的真实飞机油箱来评价该方法。为了处理复杂复合材料的各向异性性能,还考虑到了现有的各向异性性能,对二维多信号分类处理算法进行了改进。

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