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A singular value decomposition-based guided wave array signal processing approach for weak signals with low signal-to-noise ratios

机译：基于奇异值分解的低信噪比弱信号导波阵列信号处理方法

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摘要

This paper presents a novel singular value decomposition (SVD)-based guided wave array signal processing approach for relatively weak signals, which are usually encountered in long-range inspections. Because the scattered signals from a damaged area received by each element of a receiver array are from the same source, the damage information can be extracted from the covariance matrix of the array signals. By performing SVD of the covariance matrix of each part of the original array signals chosen by different time windows, the time of flight (ToF) of the damage-scattered signal corresponding to the largest singular value will be obtained. The effectiveness of the proposed SVD-based array signal processing method is then verified by a numerical analysis. Subsequently, experimental investigations are carried out on an orthotropic steel deck plate in an actual cable-stayed bridge and an 84-m-long steel pipe to verify the practicability of the SVD-based method. The results indicate that the proposed method is highly effective for array signal processing, especially for the signals with low signal-to-noise ratios (SNRs).
机译：本文提出了一种新颖的基于奇异值分解（SVD）的导波阵列信号处理方法，用于较弱的信号，这在远程检查中通常会遇到。因为由接收器阵列的每个元素接收的来自受损区域的散射信号来自同一源，所以可以从阵列信号的协方差矩阵中提取损害信息。通过执行由不同时间窗选择的原始阵列信号的每个部分的协方差矩阵的SVD，将获得与最大奇异值相对应的损伤分散信号的飞行时间（ToF）。然后通过数值分析验证了所提出的基于SVD的阵列信号处理方法的有效性。随后，在实际的斜拉桥和84米长的钢管中的正交异性钢桥面板上进行了实验研究，以验证基于SVD的方法的实用性。结果表明，该方法对阵列信号处理特别是信噪比（SNR）低的信号非常有效。

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