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MUSIC CORROSION MONITORING METHOD VIA EXCITATION BEAM FORMING AND WEIGHTED IMAGE FUSING

机译:激励梁成形和加权图像融合的音乐腐蚀监测方法

摘要

The present invention discloses a Multiple Signal Classification (MUSIC) corrosion monitoring method via excitation beam forming and weighted image fusing. Because damage-related scattering signals are weak and precision of the MUSIC algorithm is affected, the present invention first introduces excitation beam forming and two arrays into the MUSIC method, to enhance scattering signals of corrosive damage and improve their signal-to-noise ratios. Then, the two arrays serve as an excitation array or a sensor array in turn, by assigning weight to fused corrosive damage images of the two arrays, monitoring of corrosive damage in blind zones of the one-dimensional linear arrays is realized. Finally, factors related to the corrosive damage are calculated based on eigenvalues of covariance matrixes of array signals, to determine the depth of the corrosive damage. The present invention improves the positioning precision in the MUSIC corrosion monitoring, widens a monitoring range of the conventional one-dimensional linear array, and realizes evaluation of the depth of the corrosive damage, thus has wide application prospects in actual monitoring of corrosive damage in an aviation structure.
机译:本发明公开了一种通过激励束形成和加权图像融合的多信号分类腐蚀监测方法。由于与损伤有关的散射信号较弱并且影响了MUSIC算法的精度,因此本发明首先将激发束形成和两个阵列引入MUSIC方法中,以增强腐蚀性损伤的散射信号并提高其信噪比。然后,将两个阵列依次用作激励阵列或传感器阵列,通过将权重分配给两个阵列的融合腐蚀损伤图像,实现对一维线性阵列的盲区中腐蚀损伤的监视。最后,基于阵列信号的协方差矩阵的特征值,计算与腐蚀破坏有关的因素,以确定腐蚀破坏的深度。本发明提高了MUSIC腐蚀监测中的定位精度,拓宽了传统的一维线性阵列的监测范围,实现了对腐蚀损伤深度的评价,因此在实际监测腐蚀损伤中具有广阔的应用前景。航空结构。

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