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1.
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
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.
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2.
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
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.
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公开(公告)号:US20220164498A1
公开(公告)日:2022-05-26
申请号:US17429538
申请日:2021-04-19
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor: Xiaohong LU , Yihan LUAN , Zhenyuan JIA , Feixiang RUAN , Han GU
IPC: G06F30/23
Abstract: The present invention belongs to the precise and efficient processing field of micro parts, in particular to a deformation prediction method of micro-milling thin-walled parts. Firstly, based on the finite element simulation software, a finite element simulation model of micro-milling thin-walled parts is established. Johnson-Cook material model and failure criterion are used to describe the material properties and damage criteria of the machined materials, so as to realize the prediction of milling force in the micro-milling process. The accuracy of the model is verified by experiments. Then, based on the birth-death element method, a deformation prediction model of micro-milling thin-walled parts model is established, and the milling force output from the finite element simulation model is loaded into the deformation prediction model. Finally, the deformation prediction of d micro-milling thin-walled parts is realized.
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