Abstract
Robot milling has become an important means of machining large structural parts, and the dynamic compliance of the robot end is the key factor affecting machining quality and efficiency. The dynamic characteristics of the milling robot end are different in movement state and static state and have significant pose dependence. In order to effectively evaluate the dynamic compliance of the robot end in the workspace under the movement state, the operational impact excitation method for robot joint relative frequency response function (FRF) identification based on operational modal analysis (OMA) used in machine tool is established, the inertial force generated by the joint acceleration and deceleration movements is used as the excitation force, the robot end relative dynamic compliance index (RERDCI) is proposed to evaluate the dynamic compliance of robot end in different poses, and verified by cutting experiments. Based on RERDCI, the effect of the robot pose on end dynamic compliance is analyzed, and some theoretical guidance for improvement of dynamic performance to resist vibration in milling is given.
Issue Section:
Technical Brief
References
1.
Zhu
, Z. R.
, Tang
, X. W.
, Chen
, C.
, Peng
, F. Y.
, Yan
, R.
, Zhou
, L.
, Li
, Z. P.
, and Wu
, J. W.
, 2022
, “High Precision and Efficiency Robotic Milling of Complex Parts: Challenges, Approaches and Trends
,” Chin. J. Aeronaut.
, 35
(2
), pp. 22
–46
. 2.
Mohammadi
, Y.
, and Ahmadi
, K.
, 2021
, “Single Degree-of-Freedom Modeling of the Nonlinear Vibration Response of a Machining Robot
,” ASME J. Manuf. Sci. Eng.
, 143
(5
), p. 051003
. 3.
Cen
, L.
, Melkote
, S.
, Castle
, J.
, and Appelman
, H.
, 2018
, “A Method for Mode Coupling Chatter Detection and Suppression in Robotic Milling
,” ASME J. Manuf. Sci. Eng.
, 140
(8
), p. 081015
. 4.
Vu
, V.-H.
, Liu
, Z.
, Thomas
, M.
, Li
, W.
, and Hazel
, B.
, 2016
, “Output-Only Identification of Modal Shape Coupling in a Flexible Robot by Vector Autoregressive Modeling
,” Mech. Mach. Theory
, 97
, pp. 141
–154
. 5.
Yan
, R.
, Tang
, X. W.
, Peng
, F. Y.
, Li
, Y. T.
, and Li
, H.
, 2017
, “RCSA-Based Method for Tool Frequency Response Function Identification Under Operational Conditions Without Using Noncontact Sensor
,” ASME J. Manuf. Sci. Eng.
, 139
(6
), p. 061009
. 6.
Li
, B.
, Li
, L. J.
, He
, H. B.
, Mao
, X. Y.
, Jiang
, X. C.
, and Peng
, Y. L.
, 2019
, “Research on Modal Analysis Method of CNC Machine Tool Based on Operational Impact Excitation
,” Int. J. Adv. Manuf. Technol.
, 103
(1–4
), pp. 1155
–1174
. 7.
Verl
, A.
, Valente
, A.
, Melkote
, S.
, Brecher
, C.
, Ozturk
, E.
, and Tunc
, L. T.
, 2019
, “Robots in Machining
,” CIRP Ann.
, 68
(2
), pp. 799
–822
. 8.
Ji
, W.
, and Wang
, L. H.
, 2019
, “Industrial Robotic Machining: A Review
,” Int. J. Adv. Manuf. Technol.
, 103
(1–4
), pp. 1239
–1255
. 9.
Sun
, J. B.
, Zhang
, W. M.
, and Dong
, X. F.
, 2020
, “Natural Frequency Prediction Method for 6R Machining Industrial Robot
,” Appl. Sci.
, 10
(22
), p. 8138
. 10.
Nguyen
, V.
, Cvitanic
, T.
, and Melkote
, S.
, 2019
, “Data-Driven Modeling of the Modal Properties of a Six-Degrees-of-Freedom Industrial Robot and Its Application to Robotic Milling
,” ASME J. Manuf. Sci. Eng.
, 141
(12
), p. 121006
. 11.
Nguyen
, V.
, Johnson
, J.
, and Melkote
, S.
, 2020
, “Active Vibration Suppression in Robotic Milling Using Optimal Control
,” Int. J. Mach. Tools Manuf.
, 152
, p. 103541
. 12.
He
, F. X.
, Liu
, Y.
, and Liu
, K.
, 2018
, “A Chatter-Free Path Optimization Algorithm Based on Stiffness Orientation Method for Robotic Milling
,” Int. J. Adv. Manuf. Technol.
, 101
(9–12
), pp. 2739
–50
.13.
Mousavi
, S.
, Gagnol
, V.
, Bouzgarrou
, B. C.
, and Ray
, P.
, 2017
, “Dynamic Modeling and Stability Prediction in Robotic Machining
,” Int. J. Adv. Manuf. Technol.
, 88
(9–12
), pp. 3053
–3065
. 14.
Mousavi
, S.
, Gagnol
, V.
, Bouzgarrou
, B. C.
, and Ray
, P.
, 2018
, “Stability Optimization in Robotic Milling Through the Control of Functional Redundancies
,” Rob. Comput. Integr. Manuf.
, 50
, pp. 181
–192
. 15.
Chen
, C.
, Peng
, F. Y.
, Yan
, R.
, Tang
, X. W.
, Li
, Y. T.
, and Fan
, Z.
, 2020
, “Rapid Prediction of Posture-Dependent FRF of the Tool Tip in Robotic Milling
,” Rob. Comput. Integr. Manuf.
, 64
, p. 101906
. 16.
Mohamed
, R. P.
, Xi
, F. J.
, and Chen
, T.
, 2017
, “A Pose-Based Structural Dynamic Model Updating Method for Serial Modular Robots
,” Mech. Syst. Sig. Process.
, 85
, pp. 530
–555
. 17.
Maamar
, A.
, Gagvol
, V.
, Le
, T.-P.
, and Sabourin
, L.
, 2020
, “Pose-Dependent Modal Behavior of a Milling Robot in Service
,” Int. J. Adv. Manuf. Technol.
, 107
(1–2
), pp. 527
–533
. 18.
Vu
, V.-H.
, Liu
, Z. H.
, Marc
, T.
, Amir
, T. M.
, and Bruce
, H.
, 2016
, “Identification of Frequency Response Functions of a Flexible Robot as Tool-Holder for Robotic Grinding Process
,” IECON 2016—42nd Annual Conference of the IEEE Industrial Electronics Society
, Florence, Italy
, Oct. 24–27
, pp. 6347
–6352
.19.
Li
, W. C.
, Vu
, V.-H.
, Liu
, Z. H.
, Thomas
, M.
, and Hazel
, B.
, 2017
, “Application of Adaptable Functional Series Vector Time-Dependent Autoregressive Model for Extraction of Real Modal Parameters for Identification of Time-Varying Systems
,” Measurement
, 103
, pp. 143
–156
. 20.
Modak
, S. V.
, Rawal
, C.
, and Kundra
, T. K.
, 2010
, “Harmonics Elimination Algorithm for Operational Modal Analysis Using Random Decrement Technique
,” Mech. Syst. Sig. Process.
, 24
(4
), pp. 922
–944
. 21.
Li
, B.
, Luo
, B.
, Mao
, X. Y.
, Cai
, H.
, Peng
, F. Y.
, and Liu
, H. Q.
, 2013
, “A New Approach to Identifying the Dynamic Behavior of CNC Machine Tools With Respect to Different Worktable Feed Speeds
,” Int. J. Mach. Tools Manuf.
, 72
, pp. 73
–84
. 22.
Saupe
, F.
, and Knoblach
, A.
, 2015
, “Experimental Determination of Frequency Response Function Estimates for Flexible Joint Industrial Manipulators With Serial Kinematics
,” Mech. Syst. Sig. Process.
, 52–53
, pp. 60
–72
. 23.
Huynh
, H. N.
, Assadi
, H.
, Rivière-Lorphèvre
, E.
, Verlinden
, O.
, and Ahmadi
, K.
, 2020
, “Modelling the Dynamics of Industrial Robots for Milling Operations
,” Rob. Comput. Integr. Manuf.
, 61
, p. 101852
. 24.
Yu
, J. J.
, Liu
, X. J.
, and Ding
, X. L.
, 2016
, Mathematic Foundation of Mechanisms and Robotics
, China Machine Press
, Beijing
, pp. 82
–92
.25.
Tang
, X. W.
, Zhu
, Z. R.
, Yan
, Y.
, Chen
, C.
, Peng
, F. Y.
, Zhang
, M. K.
, and Li
, Y. T.
, 2018
, “Stability Prediction Based Effect Analysis of Tool Orientation on Machining Efficiency for Five-Axis Bull-Nose End Milling
,” ASME J. Manuf. Sci. Eng.
, 140
(12
), p. 121015
. 26.
Cordes
, M.
, and Hintze
, W.
, 2017
, “Offline Simulation of Path Deviation Due to Joint Compliance and Hysteresis for Robot Machining
,” Int. J. Adv. Manuf. Technol.
, 90
(1–4
), pp. 1075
–1083
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