公开(公告)号：US20240075568A1

公开(公告)日：2024-03-07

申请号：US17785657

申请日：2021-11-17

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Haibo LIU ,  Chengxin WANG ,  Yongqing WANG ,  Xu LI ,  Kuo LIU ,  Xiaofei MA ,  Dongming GUO

IPC: B23Q3/08 ,  B23Q3/06

CPC classification number: B23Q3/086 ,  B23Q3/065 ,  B23Q2703/10

Abstract: The present invention proposes an in-situ freezing machining method for an integrated thin-walled array structure. In the method, the area among cups is cut off first; then, the outer walls of a cup array are machined; and finally, water filling and freezing are carried out, and in-situ freezing machining of the inner walls of the cup array is carried out. Then, hoisting and turning over are carried out, and the area among cavities is cut off; then, the outer walls of a cavity array are machined; and finally, water filling and freezing are carried out, and in-situ freezing machining of the inner walls of the cavity array is carried out. The method realizes in-situ freezing clamping of workpieces, avoids error accumulation caused by repeated installation of a fixture, and can refrigerate efficiently, suppress ambient and cutting thermal interference, and ensure the stability of freezing fixture.

公开(公告)号：US20230092694A1

公开(公告)日：2023-03-23

申请号：US17758285

申请日：2020-01-21

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Hui NIU ,  Shiqi XIE ,  Shuhui LIU ,  Zongke HE ,  Zhuo BAO ,  Liying LIU ,  Zhe HUA ,  Aihui WANG ,  Wenjing YIN ,  Jing WANG ,  Xu LI ,  Shuang SUN

IPC: C08K5/3417 ,  C08K5/151 ,  C08K5/54 ,  C08K5/14 ,  C08F110/06 ,  B29C48/00 ,  B29C48/40

Abstract: A vulcanizing agent is added during the processing of a polymer, and can form a crosslinking structure network in the polymer, thereby improving the mechanical properties of the material. Furthermore, the crosslinking agent can also de-crosslink the polymer material at a high temperature, and after being cooled, same can be crosslinked again to produce a network structure, thus endowing the polymer material with thermoplasticity for repeated processing.

公开(公告)号：US20200249130A1

公开(公告)日：2020-08-06

申请号：US16470925

申请日：2019-02-21

Applicant: Dalian University of Technology

Inventor： Kuo LIU ,  Yongqing WANG ,  Haibo LIU ,  Xu LI ,  Mingrui SHEN ,  Mengmeng NIU ,  Ziyou BAN

IPC: G01M99/00 ,  F16C25/06

Abstract: A method for determining the preload value of the screw based on thermal error and temperature rise weighting. Firstly, thermal behavior test of the feed shaft under typical working conditions is carried out to obtain the maximum thermal error and the temperature rise at the key measuring points in each preloaded state. Then, a mathematical model of the preload value of the screw and the maximum thermal error is established; meanwhile, another mathematical model of the preload value of the screw and the temperature rise at the key measuring points is also established. Finally, the optimal preload value of the screw is obtained. The thermal error of the feed shaft and the temperature rise of the moving components are comprehensively considered, improving the processing accuracy and accuracy stability of the machine tool, and ensuring the service life of the moving components such as bearings.

公开(公告)号：US20210048793A1

公开(公告)日：2021-02-18

申请号：US16636556

申请日：2019-02-21

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Kuo LIU ,  Bo QIN ,  Xu LI ,  Yongquan GAN ,  Wei HAN ,  Renjie HUANG ,  Yongqing WANG

IPC: G05B19/4155

Abstract: A spindle thermal error compensation method which is insensitive to the disturbance of the cooling system is provided, belonging to the technical field of error compensation in numerical control machine tools. First, the spindle model coefficient identification test, based on multi-state speed variable, is performed; after which, based on the correlation analysis between temperature and thermal error, the temperature measurement point, significantly correlated with the axial thermal error of the spindle, is determined. Next, a spindle thermal error model is established, which is insensitive to the cooling system disturbance. In addition, the coefficients in the model are identified under constraint condition, according to the nonlinear quadratic programming algorithm. Finally, based on the OPC UA communication protocol, the compensation value, as calculated by the model, is input to the numerical control system, in order to realize the compensation of the spindle thermal error.

公开(公告)号：US20230191521A1

公开(公告)日：2023-06-22

申请号：US17981126

申请日：2022-11-04

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Te LI ,  Tian LAN ,  Haibo LIU ,  Yuhang GE ,  Qile BO ,  Kuo LIU ,  Xingjian LIU ,  Xu LI ,  Yongqing WANG

IPC: B23K9/028

CPC classification number: B23K9/0284

Abstract: The present invention relates to a process method for conformal processing of a cylindrical shell inner weld seam by a special mobile robot, a laser scanner is used to scan a cylindrical shell inner weld seam to obtain point cloud data of a contour of a weld seam area first. Weld seam feature identification is carried out to each generatrix, and misidentified generatrices are filtered out to obtain weld seam left and right boundaries. An ideal weld seam processing contour is generated conformally according to the appearance of the weld seam area, weld seam coarse grinding is carried out after correction and compensation, and weld seam contour information after coarse grinding is obtained by scanning after the coarse grinding is completed. Process parameters of the grinding are controlled according to an actual weld seam contour, and weld seam fine grinding is carried out to obtain a smooth weld seam contour.

公开(公告)号：US20210064988A1

公开(公告)日：2021-03-04

申请号：US16636258

申请日：2019-02-26

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Kuo LIU ,  Yongqing WANG ,  Xu LI ,  Bo QIN ,  Yongquan GAN ,  Dawei LI ,  Haining LIU

IPC: G06N3/08 ,  G06N3/04 ,  G06F17/10 ,  G05B19/4065

Abstract: A method for calculating the reliability of the thermal error model of a machine tool based on deep neural network (DNN) and the Monte Carlo method, which belongs to the field of the thermal error compensation of computer numerical control (CNC) machine tools. Firstly, according to the probability distribution of the thermal parameters and thermal error model, a set of data for training the DNN is generated. Next, the DNN is constructed based on the deep belief networks (DBNs) and trained with the training data. Then, a group of random sampling data is obtained according to the probability distribution of the thermal characteristic parameters of the machine tool, and the group of random sampling is taken as the input and the output is obtained by the trained depth neural network. Finally, the reliability of the thermal error model is calculated based on the Monte Carlo method.