Bai Long, Liu Minkang, Liu Nanxin, Su Xin, Lai Fuyao, Xu Jianfeng
State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Southwest Institution of Electronic Technology, Chengdu 610036, China.
Ultrasonics. 2022 Feb;119:106625. doi: 10.1016/j.ultras.2021.106625. Epub 2021 Oct 22.
Ultrasonic arrays are increasingly used for inspection of the structural components in non-destructive testing (NDT) applications. The ultrasonic array data can be processed to form high-resolution images for detection and localization of defects. Alternatively, the scattering matrix can be extracted from the full matrix of array data and used for defect characterization if the defect size is small (i.e., comparable to an ultrasonic wavelength). This paper studies the dimensionality reduction problem of scattering matrix databases. In particular, we focus on accurate characterization of inclined defects for which previous approaches based on principal component analysis (PCA) yielded high characterization uncertainty. We propose a supervised approach based on locality preserving projection (LPP) and introduce noise constraints to the objective function of LPP. In simulation, the proposed approach is shown to produce a well-resolved defect manifold for 45°ellipses. Characterization results obtained using the simulated noisy measurements of four 60°ellipses confirm the performance improvement of LPP over PCA. In experiments, three 60°ellipses and two surface-breaking cracks have been characterized. On average, the root-mean-square (RMS) sizing error given by the LPP approach is 39.0% lower compared to PCA for the ellipses and 11.1% lower for the surface-breaking cracks.
超声阵列在无损检测（NDT）应用中越来越多地用于结构部件的检测。超声阵列数据可以进行处理，以形成用于缺陷检测和定位的高分辨率图像。或者，如果缺陷尺寸较小（即与超声波长相当），则可以从阵列数据的全矩阵中提取散射矩阵并用于缺陷表征。本文研究了散射矩阵数据库的降维问题。特别是，我们专注于对倾斜缺陷进行准确表征，而基于主成分分析（PCA）的先前方法在这方面产生了较高的表征不确定性。我们提出了一种基于局部保留投影（LPP）的监督方法，并在LPP的目标函数中引入了噪声约束。在模拟中，所提出的方法被证明能够为45°椭圆生成分辨率良好的缺陷流形。使用四个60°椭圆的模拟噪声测量获得的表征结果证实了LPP相对于PCA的性能提升。在实验中，对三个60°椭圆和两个表面开口裂纹进行了表征。平均而言，对于椭圆，LPP方法给出的均方根（RMS）尺寸误差比PCA低39.0%，对于表面开口裂纹低11.1%。
