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Abstrakty
Chatter is a series of unwanted and extreme vibrations which frequently happens during different machining processes and impose variety of adverse effects on the machine-tool and surface finish. Chatter has two main types namely forced-chatter and self-existed chatter. The forced-chatter has an external cause; however, self-exited chatter has no external stimuli, rather it is created due to the phase difference between the previous and current waves on the surface of the workpiece. Due to the self-generative nature of this type of chatter, its recognition and prevention is much more difficult. For preventing self-exited chatter its model should be available first. The chatter is usually simulated as a one degree of freedom mass-spring-damper model with unknown parameters that they should be determined somehow. In this paper, the parameters of the tool equation of motion i.e. mass, damping, and stiffness coefficients of the system are predicted through a wavelet-based method online, and then based on the achieved parameters, the system is controlled via Model Predictive Control (MPC) approach. For the validation, the algorithm is applied to 25 different experimental tests in which the acceleration of the tool and cutting force are measured via an accelerometer and a dynamometer. By investigation of the SLDs generated by the predicted parameters, the presented system identification method is validated. Also, it is shown that the chatter vibration is completely restrained by means of MPC. For investigation of the MPC performance, MPC algorithm is compared with PID controller and simulations has indicated a much stronger performance of MPC rather than PID controller in terms of vibration attenuation and control effort.
Wydawca
Rocznik
Tom
Strony
217--228
Opis fizyczny
Bibliogr. 15 poz., fig., tab.
Twórcy
autor
- Behbahan Khatam Alanbia University of Technology, Iran
autor
- Behbahan Khatam Alanbia University of Technology, Iran
Bibliografia
- 1. Altintas, Y. and M. Weck, Chatter stability of metal cutting and grinding. CIRP annals, 2004. 53(2): 619-642.
- 2. Lu, K., et al., Model-based chatter stability prediction and detection for the turning of a flexible workpiece. Mechanical Systems and Signal Processing, 2018. 100: 814-826.
- 3. Eynian, M. and Y. Altintas, Chatter stability of general turning operations with process damping. Journal of Manufacturing Science and Engineering, 2009. 131(4): 041005.
- 4. Turkes, E., et al., Linear analysis of chatter vibration and stability for orthogonal cutting in turning. International Journal of Refractory Metals and Hard Materials, 2011. 29(2): 163-169.
- 5. Schmitz, T.-K.S., Machining Dynamics Frequency Response to Improved Productivity Springer Science+ Business Media. 2009, LLC.
- 6. Liu, Y., et al., Chatter reliability prediction of turning process system with uncertainties. Mechanical Systems and Signal Processing, 2016. 66: 232-247.
- 7. Den Hartog, J.P., Mechanical vibrations. 1985: Courier Corporation.
- 8. Lin, S. and M. Hu, Low vibration control system in turning. International Journal of Machine Tools and Manufacture, 1992. 32(5): 629-640.
- 9. Frumusanu, G.R., et al., Development of a stability intelligent control system for turning. The International Journal of Advanced Manufacturing Technology, 2013. 64(5-8): 643-657.
- 10. dos Santos, R.G. and R.T. Coelho, A contribution to improve the accuracy of chatter prediction in machine tools using the stability lobe diagram. Journal of Manufacturing Science and Engineering, 2014. 136(2): 021005.
- 11. Kurata, Y., et al., Chatter stability in turning and milling with in process identified process damping. Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2010. 4(6): 1107-1118.
- 12. Chun-Lin, L., A tutorial of the wavelet transform. NTUEE, Taiwan, 2010.
- 13. Huang, S., G. Qi, and J. Yang. Wavelet for system identification. in Proceedings-Spie The International Society For Optical Engineering. 1994. Spie International Society For Optical.
- 14. Wang, L., Model predictive control system design and implementation using MATLAB®. 2009: Springer Science & Business Media.
- 15. Ning, Y., M. Rahman, and Y. Wong, Investigation of chip formation in high speed end milling. Journal of materials processing technology, 2001. 113(1-3): 360-367.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c63d8559-ab69-4fc2-963b-7668c862f4b8