کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6961408 1452101 2018 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Incremental digital volume correlation method with nearest subvolume offset: An accurate and simple approach for large deformation measurement
ترجمه فارسی عنوان
روش همبستگی حجمی دیجیتال با نزدیکترین مقادیر کم حجم: رویکرد دقیق و ساده برای اندازه گیری تغییر شکل بزرگ
کلمات کلیدی
همبستگی حجم دیجیتال، تغییر شکل بزرگ، نزدیکترین مقادیر جبران شده،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزار
چکیده انگلیسی
Digital volume correlation (DVC) has been widely accepted as an effective experimental technique for quantifying full-field internal 3D deformation of solid materials and structures under external loading. However, conventional DVC using a fixed reference volume image generally fails when serious decorrelation occurs in deformed volume images due to large deformation or other reasons. In this work, an accurate and simple incremental DVC method with nearest subvolume offset is proposed for large deformation measurement. Specifically, the reference subvolumes in the updated reference volume images are translated to nearest integer-voxel positions, rather than being interpolated at subvoxel locations. The translated reference subvolumes, within which all correlation points locate at integer-voxel positions, are then tracked in the rest deformed volume images to retrieve incremental displacement fields. The obtained incremental displacement fields are then accumulated to previously obtained displacement fields to determine the overall displacements. By using the simple nearest subvolume offset approach, subvoxel intensity interpolation for the updated reference subvolumes is entirely avoided, thus not only eliminating the bias error associated with imperfect subvoxel intensity interpolation, but also increasing the computational efficiency of incremental DVC calculation by approximately 2.5 times. The accuracy, efficiency and practicality of the presented incremental DVC are demonstrated by analyzing two sets of volume images with large deformation generated in numerically simulated and real-world experiments.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Engineering Software - Volume 116, February 2018, Pages 80-88
نویسندگان
, ,