On-line chatter detection in milling using drive motor current commands extracted from CNC

Abstract This paper presents an on-line chatter detection method in milling using drive motor current commands supplied by the CNC system in real-time. The methodology is described by using the spindle drive motor current command although it has been applied to the feed drives as well which is demonstrated in the results section. The transfer function of spindle velocity controller is constructed by reading the control law parameters and measuring the Frequency Response Function (FRF) of the system automatically using an external computer communicating with the CNC in real time. By subtracting the rigid body based FRF from the measured FRF of the velocity controller that includes the flexibilities, the structural modes of the spindle drive are identified. The closed loop transfer function between the cutting torque at the tool and corresponding noise free digital current commanded by the CNC is formed. The effects of structural dynamic modes of the spindle are compensated via a proposed observer. The bandwidth of the compensated FRF of the current command over cutting torque disturbance has been increased to 2.5 kHz with 10 kHz communication speed limit of the CNC with external PC. After removing the forced vibration components, the frequency and presence of chatter are detected from the Fourier Spectrum of the current commands supplied by CNC in real time. The proposed system is experimentally validated in milling tests.

[1]  Yusuf Altintas,et al.  Prediction of Cutting Forces in Five-Axis Milling Using Feed Drive Current Measurements , 2018, IEEE/ASME Transactions on Mechatronics.

[2]  Yusuf Altintas,et al.  Integration of virtual and on-line machining process control and monitoring , 2017 .

[3]  Yusuf Altintas,et al.  Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design , 2000 .

[4]  Yang Fu,et al.  Timely online chatter detection in end milling process , 2016 .

[5]  Yasuhiro Kakinuma,et al.  Detection of chatter vibration in end milling applying disturbance observer , 2011 .

[6]  Gábor Stépán,et al.  Multiple chatter frequencies in milling processes , 2003 .

[7]  Gurbachan S. Sekhon Monitoring and control of machining operations , 2013 .

[8]  Won Tae Kwon,et al.  Estimation of the cutting torque without a speed sensor during CNC turning , 2005 .

[9]  Philip K. Chan,et al.  In-process detection and suppression of chatter in milling , 1992 .

[10]  Erhan Budak,et al.  In-process tool point FRF identification under operational conditions using inverse stability solution , 2015 .

[11]  Fathy Ismail,et al.  Chatter detection by monitoring spindle drive current , 1997 .

[12]  S. A. Tobias Machine-tool vibration , 1965 .

[13]  Kouhei Ohnishi,et al.  Disturbance Observer–Based In-process Detection and Suppression of Chatter Vibration , 2012 .

[14]  Richard A. Brown,et al.  Introduction to random signals and applied kalman filtering (3rd ed , 2012 .

[15]  Jianguang Li,et al.  Development and testing of an integrated smart tool holder for four-component cutting force measurement , 2017 .

[16]  Yusuf Altintas,et al.  High speed tooltip FRF predictions of arbitrary tool-holder combinations based on operational spindle identification , 2018, International Journal of Machine Tools and Manufacture.

[17]  Won Tae Kwon,et al.  Drilling torque control using spindle motor current and its effect on tool wear , 2004 .

[18]  Elso Kuljanić,et al.  Multisensor approaches for chatter detection in milling , 2008 .

[19]  Yusuf Altintas,et al.  Dynamic Compensation of Spindle Integrated Force Sensors With Kalman Filter , 2004 .

[20]  Yusuf Altintas,et al.  Analytical Prediction of Stability Lobes in Milling , 1995 .

[21]  Shin'ichi Warisawa,et al.  Development of an Intelligent High-Speed Machining Center , 2001 .

[22]  Alexander Verl,et al.  Estimation of stability lobe diagrams in milling with continuous learning algorithms , 2017 .

[23]  Hiroshi Fujimoto,et al.  External sensorless adaptive chatter avoidance in NC machining by applying disturbance observer using high resolution linear encoder , 2017, 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).

[24]  Lida Zhu,et al.  Chatter detection in milling process based on VMD and energy entropy , 2018 .

[25]  F. Fairman Introduction to dynamic systems: Theory, models and applications , 1979, Proceedings of the IEEE.

[26]  Scott D. Sudhoff,et al.  Analysis of Electric Machinery and Drive Systems , 1995 .

[27]  Yusuf Altintas,et al.  Multi frequency solution of chatter stability for low immersion milling , 2004 .