| Autor: |
Qi Lu, Xiaorong Cai, Jiayi Wu, Shiqi Zhang, Shilong Liu, Xuejun Jin |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Materials & Design, Vol 230, Iss , Pp 111998- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
0264-1275 |
| DOI: |
10.1016/j.matdes.2023.111998 |
| Popis: |
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 reconstruction-aided 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°. 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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