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.

公开(公告)号：US20230384161A1

公开(公告)日：2023-11-30

申请号：US18108966

申请日：2023-02-13

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Xiaohong LU ,  Guochuan SUI ,  Zhenyuan JIA ,  Shixuan SUN ,  Le TENG

IPC: G01J5/00 ,  G01J5/48 ,  G06F30/27

CPC classification number: G01J5/0003 ,  G01J5/485 ,  G06F30/27 ,  G01J2005/0077 ,  G06F2111/10

Abstract: The present invention belongs to the field of friction stir welding (FSW) temperature detection, and relates to a temperature characterization method of FSW weld zone based on infrared thermal imager. The invention combines theory with experiment. A temperature field simulation model of FSW is established based on DEFORM. The data sets of temperature of surface feature points, the maximum and minimum temperatures in weld zone are obtained according to the simulation model result. Then, Support Vector Regression (SVR) is used to establish a temperature characterization model, which represents the correlation between the temperature of surface feature points and the maximum and minimum temperatures in weld zone. In the actual welding process, an infrared camera is used to measure the temperature of the surface feature point in real-time. Combined with the built temperature characterization model, the characterization of the maximum and minimum temperatures in weld zone is achieved.