TY - GEN
T1 - Optimization of robot machining process parameters based on multi-feature signal fusion analysis
AU - Zhang, Beiqing
AU - Jiao, Li
AU - Gao, Yuhang
AU - Ma, Senjie
AU - Qiu, Tianyang
N1 - Publisher Copyright:
© 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2024/11/18
Y1 - 2024/11/18
N2 - Industrial robots have the advantages of good flexibility, low manufacturing cost, high processing efficiency, high level of automation, compared with the traditional machine tool processing, there are better prospects for application in the holistic processing of mass and sophisticated components. But, given the weak structural stiffness performance of the robot, resulting in poor milling accuracy, it is difficult to meet the actual processing quality requirements. For this reason, this paper takes the aerospace module bracket as the research object, proposes the machining quality control method based on the optimization of process parameters, carries out the orthogonal test of robotic milling, researches the impact of process parameters on cutting force, cutting vibration, and surface quality, and adopts the gray correlation method to optimize the milling process parameters, and finally realizes the quality control of robotic machining.
AB - Industrial robots have the advantages of good flexibility, low manufacturing cost, high processing efficiency, high level of automation, compared with the traditional machine tool processing, there are better prospects for application in the holistic processing of mass and sophisticated components. But, given the weak structural stiffness performance of the robot, resulting in poor milling accuracy, it is difficult to meet the actual processing quality requirements. For this reason, this paper takes the aerospace module bracket as the research object, proposes the machining quality control method based on the optimization of process parameters, carries out the orthogonal test of robotic milling, researches the impact of process parameters on cutting force, cutting vibration, and surface quality, and adopts the gray correlation method to optimize the milling process parameters, and finally realizes the quality control of robotic machining.
KW - Grey relation analysis
KW - Orthogonal analysis
KW - Robotic milling
UR - https://www.scopus.com/pages/publications/85212824087
U2 - 10.1145/3687488.3687489
DO - 10.1145/3687488.3687489
M3 - Conference contribution
AN - SCOPUS:85212824087
T3 - ACM International Conference Proceeding Series
SP - 1
EP - 7
BT - Proceedings of 2024 4th International Conference on Control and Intelligent Robotics, ICCIR 2024
PB - Association for Computing Machinery
T2 - 4th International Conference on Control and Intelligent Robotics, ICCIR 2024
Y2 - 21 June 2024 through 23 June 2024
ER -