Dynamic parameter identification in nonlinear machining systems

• Autorzy: Nicolescu M. , Archenti A.
• Języki publikacji: EN

Abstrakty

EN

The demand for enhanced performance of production systems in terms of quality, cost and reliability is ever increasing while, at the same time, there is a demand for shorter design cycles, longer operating life, minimisation of inspection and maintenance needs. Experimental testing and system identification in operational conditions still represent an important technique for monitoring, control and optimization. The term identification refers in the present paper to the extraction of information from experimental data and is used to estimate operational dynamic parameters for machining systems. Such an approach opens up the possibility of monitoring the dynamics of machining systems during operational conditions, and can also be used for control and/or predictive purposes The machining system is considered nonlinear and excited by random loads. Parametric and nonparametric techniques are developed for the identification of the nonlinear machining system and their application is demonstrated both by numerical simulations and in actual machining operations. Discrimination between forced and self-excited vibrations is also presented. The ability of the developed methods to estimate operational dynamic parameters ODPs is presented in practical machining operations.

Słowa kluczowe

EN

machining system; dynamic parameters; white noise excitation; self-excited vibration

• Wydawca: Wydawnictwo Wrocławskiej Rady FSNT NOT
• Czasopismo: Journal of Machine Engineering
• Rocznik: 2013
• Tom: Vol. 13, No. 3
• Strony: 91--116
• Opis fizyczny: Bibliograf. 46 poz., rys., fot.

Twórcy

autor

Nicolescu M.

• KTH, Royal Institute of Technology

autor

Archenti A.

• KTH, Royal Institute of Technology

Bibliografia

• [1] BUDAK E., TUNC L T., 2009, A new method for identification and modeling of process damping in machining, Journal of Manufacturing Science and Engineering October, 131.
• [2] TUNC L. T., BUDAK E., 2012 Effect of cutting conditions and tool geometry on process damping in machining, International Journal of Machine Tools & Manufacture, 57, 10–19.
• [3] TYLER C. T., SCHMITZ,T.L., 2013, Analytical process damping stability prediction, Journal of Manufacturing Processes, 15, 69–76.
• [4] ARCHENTI A., 2011, A computational framework for control of machining system capability, Doctoral Thesis, KTH, Royal Institute of Technology.
• [5] KURATA Y., MERDOL D., ALTINTAS Y., SUZUKI N., SHAMOTO E., 2010, Chatter stability in turning and milling with in process identified process damping, Journal of Advanced Mechanical Design, Systems, and Manufacturing, 10.
• [6] AHMADI K., ISMAIL F., 2011, Analytical stability lobes including nonlinear process damping effect on machining chatter, International Journal of Machine Tools & Manufacture 51, 296–308.
• [7] ELBESTAWI M. A., ISMAIL F., DU R., ULLAGADI B.C., 1994, Modeling machining dynamics including damping in the tool-workpiece interface, ASME J. Eng. Ind., 116, 435–439.
• [8] SHAWKY A. M., ELBESTAWI M.A., 1997, An enhanced dynamic model in turning including the effect of ploughing forces, ASME J. Manuf. Sci. Eng., 119, 10–20.
• [9] ALTINTAS Y., EYNIAN M., ONOZUKA H., 2008, Identification of dynamic cutting force coefficients and chatter stability with process damping, CIRP Annals - Manufacturing Technology, 57, 371–374.
• [10] LÓPEZ L.N., LACALLE D., A. LAMIKIZ A., 2009, Machine tool performance and precision, in machine Tools for high performance machining, Springer-Verlag.
• [11] TLUSTY J., ISMAIL F., 1981, Basic nonlinearity in machining chatter, CIRP Annals - Manufacturing Technology, 30/1, 21–25.
• [12] ITO Y., 2008, Design for machine tools, McGraw-Hill.
• [13] TLUSTY J., ISMAIL,F., 1983, Special aspects of chatter in milling, ASME J. of Eng. for Industry, 105, 24-32.
• [14] LEE B.Y., TARNG Y.S., MA S.C., 1995, Modeling of the process damping force in chatter vibration, Int. J. Mach Tools Manufacturing, 35/7, 951-962.
• [15] SELLMEIER V., DENKENA B., 2012, High speed process damping in milling, CIRP Journal of Manufacturing Science and Technology, 5/1, 8–19.
• [16] RIVIN E.I., 2000, Tooling structure: Interface between cutting edge and machine tool, CIRP Annals - Manufacturing Technology, 49/2.
• [17] WENTZEL H., OLSSON M. Numerical prediction of damping in structures with frictional joints, Int. Journal of Vehicle Noise and Vibration, (in press).
• [18] WU D.W., 1988, Application of a comprehensive dynamic cutting force model to orthogonal wave-generating processes, Int. J. Mech. Sci. 30/8, 581-600.
• [19] ROBERTS J.B., SPANOST P.D., 1986, Stochastic averaging: An approximate method of solving random vibration problems, Int. J. Nonlinear. Mechanics 21/2, 111-134.
• [20] KRENK S., ROBERTS J.B., 1999, Local similarity in nonlinear random vibration, J. Appl. Mech. 6/1, 225-235.
• [21] RÜDING F., KRENK S., 2001, Non-parametric system identification from nonlinear stochastic response, Probabilistic Engineering Mechanics, 16, 233-243.
• [22] RISKEN H., 1995, The Fokker-Plank equation, Springer Verlag.
• [23] CAUGHEY T.K., 1986, On the response of nonlinear oscillators to stochastic excitation, Probabilistic Engineering Mechanics, 1/1.
• [24] CAI G.Q., LIN Y.K., 1988, A New approximate solution technique for randomly excited nonlinear oscillators, Int. J. Nonlinear Mechanics, 2/5.
• [25] ROBERTS J.B., 1978, The energy envelope of a randomly excited nonlinear oscillator, Journal of Sound and Vibration, 60/2.
• [26] ROBERTS J.B., DUNNE J.F., DEBONS A., 1994, Stochastic estimation methods for nonlinear ship roll motion, Probabilistic Engineering Mechanics, 9.
• [27] CHIRIACESCU S.T., 1990, Stability in the dynamics of metal cutting, Elsevier.
• [28] GRADISEK J., FRIEDRICH R., GOVEKAR E., GRABEC, E., 2002, Analysis of data from periodically forced stochastic processes, Physics Letters, 294, 234–238.
• [29] ZHANG W., ZHANG H., 1994, Modelling and analysis of nonlinear damping mechanism in vibrating systems, Int. J. Mech. Sci., 36/9.
• [30] NAPRSTEK J., 1998, Nonlinear self-excited random vibrations and stability of an SDOF system with parametric noises, Meccanica, 33, 267–277.
• [31] SHERIF H.A., OMAR T.M., 2004, Mechanism of energy dissipation in mechanical systems with dry contact, Tribology International, 37/3, 235-244.
• [32] SHERIF H.A., OMAR T.M., 2001, Interface properties due to microslip from vibration measurement, ASME Journal of Tribology, 123, 230-233.
• [33] AL-BENDER F., LAMPERT V., SWEVERS J., 2004, Modeling of dry sliding friction dynamics: From heuristic models to physically motivated models and back. Chaos, An Interdisciplinary Journal of Nonlinear Science, 14/2, 446–460.
• [34] WANG J.Q., ZHU X.J., CHENG Q., 1998, Study on friction chatter mechanism of power ultrasonic vibration honing based on Stribeck effect, Applied Mechanics and Materials, 328, 531-535.
• [35] QUINTANA G., CIURANA J., 2011, Chatter in machining processes: A review, International Journal of Machine Tools & Manufacture, 51, 363–376.
• [36] STEPAN G., 2001, Modelling nonlinear regenerative effects in metal cutting, Philosophical Transactions of the Royal Society of London, A 359, 739–757.
• [37] MANN B.P., INSPERGER T., BAYLEY P.V., STEPAN G., 2003, Stability of up-milling and down-milling, Part 2: Experimental Verification. International Journal of Machine Tools & Manufacture 43, 35–40.
• [38] ARCHENTI A., OSTERLIND T., NICOLESCU C.M., 2011, Evaluation and representation of machine tool deformations, Journal of Machine Engineering, 11/4, 105–117.
• [39] IOURTCHENKO D.V., DIMENTBERG M.F., 2002, In-service identification of nonlinear damping from measured random vibration, Journal of Sound and Vibration, 255/3, 549-554.
• [40] LJUNG T., 1999, System identification—theory for the user, Prentice-Hall.
• [41] ARCHENTI A., NICOLESCU C.M., 2010, Recursive estimation of operational dynamic parameters in milling using acoustic signal, CIRP 2nd International Conference on Process Machine Interactions, 1, Vancouver, BC, Canada.
• [42] SÖDERSTROM T., STOICA P., 2001, System identification, Uppsala.
• [43] BOX G.E.P., JENKINS G.M., 1970, Time series analysis.
• [44] PANDIT S.M., WU S.M., 1983, Time series and system analysis with application, WILEY.
• [45] ARCHENTI A., NICOLESCU C.M., 2008, Model-Based identification of dynamic stability of machining systems, Process Machine Interaction (PMI), Hannover, Germany, 41-52.
• [46] BERGLUND A., 2011, Milling of CGI, Doctoral thesis, KTH, Stockholm, Sweden.