Minimum variance guided wave imaging in a quasi-isotropic composite plate
Minimum variance guided wave imaging in a quasi-isotropic composite plate
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DOI：
10.1088/0964-1726/20/2/025013
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发表时间：
2011-02-01
影响因子：
4.1
通讯作者：
Berthelot, Yves H.
中科院分区：
文献类型：
--
作者：
Hall, James S.;McKeon, Peter;Berthelot, Yves H.
超声导波能够快速询问大型板状结构，用于无损评估和结构健康监测（SHM）应用。廉价的压电换能器的分布式稀疏阵列提供了一种具有成本效益的方式来自动化询问过程。然而，阵列的稀疏性质限制了可用于执行损伤检测和定位的信息量。最小方差技术已被纳入导波成像，以减少成像伪影的幅度，并提高稀疏阵列SHM应用的成像性能。这些技术提高成像性能的能力与先验模型假设的准确性有关，例如散射特性和色散。本文报告了应用程序的最小方差成像下稍不准确的模型假设，如预期在现实环境中。具体地，成像算法假设各向同性、非色散、单模传播环境，其中散射场与入射角和频率无关。实际上，这里考虑的复合材料不仅是轻微的各向异性和色散，而且还支持多个传播模式，此外，散射场取决于入射角，散射角和频率。在成像之前通过校准来估计各向同性传播速度，以实现非色散模型假设。成像性能在这些不准确的假设下，以证明最小方差成像的鲁棒性，常见的成像伪影的来源。
Ultrasonic guided waves are capable of rapidly interrogating large, plate-like structures for both nondestructive evaluation and structural health monitoring (SHM) applications. Distributed sparse arrays of inexpensive piezoelectric transducers offer a cost-effective way to automate the interrogation process. However, the sparse nature of the array limits the amount of information available for performing damage detection and localization. Minimum variance techniques have been incorporated into guided wave imaging to reduce the magnitude of imaging artifacts and improve the imaging performance for sparse array SHM applications. The ability of these techniques to improve imaging performance is related to the accuracy of a priori model assumptions, such as scattering characteristics and dispersion. This paper reports the application of minimum variance imaging under slightly inaccurate model assumptions, such as are expected in realistic environments. Specifically, the imaging algorithm assumes an isotropic, non-dispersive, single mode propagating environment with a scattering field independent of incident angle and frequency. In actuality, the composite material considered here is not only slightly anisotropic and dispersive but also supports multiple propagating modes, and additionally, the scattering field is dependent on the incident angle, scattered angle, and frequency. An isotropic propagation velocity is estimated via calibration prior to imaging to implement the non-dispersive model assumption. Imaging performance is presented under these inaccurate assumptions to demonstrate the robustness of minimum variance imaging to common sources of imaging artifacts.