Crystal orientation and deformation state analysis from Kikuchi patterns via pattern reconstruction aided deep Siamese network

作者：Lu, Qi; Cai, Xiaorong; Wu, Jiayi; Zhang, Shiqi; Liu, Shilong^*; Jin, Xuejun^*

来源：MATERIALS & DESIGN, 2023, 230: 111998.

DOI：10.1016/j.matdes.2023.111998

• Pattern reconstruction
• Deep Siamese network
• Crystal orientation
• Deformation gradient tensor
• Kikuchi pattern

Fast and accurate analysis of orientations and deformation states from Kikuchi patterns is vital to understand the crystalline materials' micro- and macro-mechanical behavior. Here, a pattern reconstructionaided Siamese network is developed to extract the crystal orientations and deformation states from Kikuchi patterns. We demonstrate the pattern reconstruction technique is essential for accurate predictions at large-area EBSD scans since the remapping operation enables the Siamese network to consider changes in experimental setup parameters dynamically. Moreover, the reconstruction technique serves as a data augmentation method that expands 342,225 raw patterns to 5,475,600 reconstructed patterns. The resulting Siamese network achieves unprecedented accuracy and robustness over a wide range of experimental setup parameters including pattern center, camera elevation and exposure time. Compared to the cross-correlation based high-resolution EBSD (HR-EBSD) analysis, it shows improved robustness against large rotations and achieves accurate measurements even if the rotation angle is as large as 25 & DEG;. Further investigation also indicates the Siamese network trained on pure aluminum can be generalized at copper, nickel and 316 stainless steel without retraining, suggesting broad and desirable applicability.& COPY; 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

• 单位
  西安交通大学; 河北医科大学; 上海交通大学