Microtexture regions (MTRs) are collections of grains with similar crystallographic orientation. Because their presence in titanium alloys can significantly impact aerospace component life, a nondestructive method to detect and characterize MTR is needed. In this work, we propose to use data from two nondestructive evaluation methods, eddy current testing (ECT) and scanning acoustic microscopy (SAM), in order to recover the boundary and dominant crystallographic orientation of each MTR in a specimen. ECT is an electromagnetic method that is sensitive to changes in crystallographic orientation associated with MTR; however, its low resolution prevents it from resolving MTR boundaries well. In contrast, SAM is a high frequency ultrasound method that is able to resolve MTR boundaries but is not sensitive to orientation. This paper proposes an algorithm to characterize MTR that makes use of a method known as covariance generalized matching component analysis. This method is used to build a surrogate linear forward model that relates MTR boundaries and orientation to ECT data. The model is inverted using the SAM data as a structural prior. We demonstrate this technique using simulated ECT and experimental SAM data from a large grain titanium specimen.

中文翻译：

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使用结构先验对涡流测试数据进行微观纹理区域分割

微观纹理区域（MTR）是具有相似晶体取向的晶粒的集合。由于它们在钛合金中的存在会显着影响航空航天部件的寿命，因此需要一种无损方法来检测和表征 MTR。在这项工作中，我们建议使用两种无损评估方法（涡流测试（ECT）和扫描声学显微镜（SAM））的数据，以恢复样本中每个 MTR 的边界和主要晶体取向。 ECT 是一种电磁方法，对与 MTR 相关的晶体取向变化敏感；然而，其低分辨率使其无法很好地解析 MTR 边界。相比之下，SAM 是一种高频超声方法，能够解析 MTR 边界，但对方向不敏感。本文提出了一种表征 MTR 的算法，该算法利用协方差广义匹配分量分析的方法。该方法用于构建将 MTR 边界和方向与 ECT 数据相关联的替代线性正演模型。使用 SAM 数据作为结构先验来反转模型。我们使用来自大颗粒钛样品的模拟 ECT 和实验 SAM 数据演示了该技术。