公开(公告)号：US20240264002A1

公开(公告)日：2024-08-08

申请号：US18021904

申请日：2022-09-26

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Xiaohong LU ,  Chong MA ,  Zhenyuan JIA ,  Shixuan SUN ,  Yihan LUAN ,  Le TENG

IPC: G01J5/00 ,  B23K20/12

CPC classification number: G01J5/0018 ,  B23K20/1235 ,  G01J2005/0077

Abstract: The invention belongs to the field of friction stir welding (FSW) quality prediction and relates to an intelligent prediction method for the tensile strength of FSW joints considering welding temperature and axial force. The invention uses a combination of experiment and theory. FSW experiment is carried out, the infrared thermal imager and force sensor are used to obtain the temperature of the feature points on the advancing side and retreating side of the outside of the shoulder of the weldment surface and the axial force during FSW process. The obtained data is used to train and test the one-dimensional convolutional neural network. The tensile strength prediction of friction stir welding is realized, which provided a reference for welding process control.