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New Paradigm in Control of Machining Systems Dynamics

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The increasing demands for precision and efficiency in machining call for effective control strategies based on the identification of static and dynamic characteristics under operational conditions. The capability of a machining system is significantly determined by its static and dynamic stiffness. The aim of this paper is to introduce novel concepts and methods regarding identification and control of a machining system’s dynamics. After discussing the limitations in current methods and technologies of machining systems’ identification and control, the paper introduces a new paradigm for controlling the machining system dynamics based on design of controllable structural Joint Interface Modules, JIMs, whose interface characteristics can be tuned using embedded actuators. Results from the laboratory and industrial implementation demonstrate the effectiveness of the control strategy with a high degree of repeatability.
Rocznik
Strony
117--137
Opis fizyczny
Bibliogr. 36 poz., tab., rys.
Twórcy
autor
  • KTH, Royal Institute of Technology, Stockholm, Sweden
  • KTH, Royal Institute of Technology, Stockholm, Sweden
autor
  • KTH, Royal Institute of Technology, Stockholm, Sweden
autor
  • KTH, Royal Institute of Technology, Stockholm, Sweden
autor
  • KTH, Royal Institute of Technology, Stockholm, Sweden
Bibliografia
  • [1] NICOLESCU C.M., 1996, On-line Identification and Control of Dynamic Characteristics of Slender Workpieces in Turning, Journal of Materials Processing Technology, 58/4, 374–378.
  • [2] FRANGOUDIS C., 2014, Controlling the Dynamic Characteristics of Machining Systems through Consciously Designed Joint Interfaces, Licentiate Thesis, KTH Royal Institute of Technology. Department of Production Engineering, Stockholm.
  • [3] KURATA Y., MERDOL S.D., ALTINTAS Y., SUZUKI N., SHAMOTO E., 2010, Chatter Stability in Turning and Milling with Process Identified Process Damping, Journal of Advanced Mechanical Design, Systems and Manufacturing, 4/6.
  • [4] BUDAK E., TUNC L.T., ALAN S., ÖZGÜVEN H.N., 2012, Prediction of Workpiece Dynamics and its Effects on Chatter Stability in Milling, CIRP Annals - Manufacturing Technology, 61/1, 339−342.
  • [5] BUDAK E., COMAK A., OZTURK E., 2013, Stability and High Performance Machining Conditions in Simultaneous Milling, CIRP Annals - Manufacturing Technology, 62/1, 403−406.
  • [6] TLUSTY J., 1978, Analysis of the State of Research in Cutting Dynamics, CIRP Annals, 27/2.
  • [7] TLUSTY J., ZATON W., ISMAIL F., 1983, Stability Lobes in Milling, Annals of the CIRP, 1, 32/1, 309−313.
  • [8] WECK M., VERHAAG E., GATHIER M., 1975, Adaptive Control for Face Milling Operations with Strategies for Avoiding Chatter Vibrations and Automatic Cut Distribution, Annals of the CIRP, 24/1, 405−409.
  • [9] ALTINTAS Y., WECK M., 2004, Chatter Stability of Metal Cutting and Grinding, CIRP Annals - Manufacturing Technology, 53/2, 619−642.
  • [10] ITO Y., 2013, Position Paper – Fundamental Issues in Self-Excited Chatter in Turning, Journal of Machine Engineering, 13/3, 7−25.
  • [11] POWAŁKA B., JEMIELNIAK K., 2015, Stability Analysis in Milling of Flexible Parts based on Operational Modal Analysis, CIRP Journal of Manufacturing Science and Technology, 9, 125−135.
  • [12] ZAGHBANI I., SONGMENE Y., 2009, Estimation of Machine-Tool Dynamic Parameters during Machining Operation through Operational Modal Analysis, International Journal of Machine Tools & Manufacture, 49, 947–957.
  • [13] AKAY M., 1994, The Autoregressive Moving Average (ARMA) Method, Biomedical Signal Processing, 252−280.
  • [14] POZNYAK A.S., 2009, Parametric Identification, Advanced Mathematical Tools for Automatic Control Engineers, Stochastic Techniques, 357−416.
  • [15] CADZOW A., 1987, Spectral Analysis, Handbook of Digital Signal Processing, 701−740.
  • [16] NEUMAN D., 1992, Fault Diagnosis of Machine-Tools by Estimation of Signal Spectra, Fault Detection, Supervision and Safety for Technical Processes, 147−152.
  • [17] CHEN H.F., 2009, Recursive System Identification, Acta Mathematica Scientia, 29/3, May, 650−672.
  • [18] LE T.P., PAULTRE P., 2013, Modal Identification Based on the Time–Frequency Domain Decomposition of Unknown-Input Dynamic Tests, International Journal of Mechanical Sciences, 71, 41–50.
  • [19] ARCHENTI A., 2008, Model‐Based Investigation of Machining Systems Characteristics, Licentiate Thesis, KTH Royal Institute of Technology.
  • [20] PRIESTLEY M.B., 1988, Current Developments in Time Series Modelling, Journal of Econometrics, 37/1, 67−86.
  • [21] LJUNG L., 1981, Analysis of a General Recursive Prediction Error Identification Algorithm, Automatica, 17/1.
  • [22] STOICA P., SŐDERSTRŐM T., 1981, Analysis of an output error identification Algorithm, Automatica, 17/6, 861−863.
  • [23] ARCHENTI A., DAGHINI L., NICOLESCU C.M., 2010, Recursive Estimation of Machine Tool Structure Dynamic Properties, CIRP International Conference on High Performance Cutting, / [ed] Tojiro Aoyama, Yoshimi Takeuchi, Gifu, 365−370.
  • [24] ARCHENTI A., NICOLESCU C.M., 2010, Recursive Estimation of Operational Dynamic Parameters in Milling Using Acoustic Signal, International Conference on Process Machine Interactions / [ed] Y. Altintas, Vancouver.
  • [25] ARCHENTI A., 2011, A Computational Framework for Control of Machining System Capability: From Formulation to Implementation, Doktorsavhandling, KTH, Skolan för industriell teknik och management (ITM), Industriell produktion, Maskin- och processteknologi.
  • [26] NICOLESCU C.M., ARCHENTI A., 2013, Dynamic Parameter Identification in Nonlinear Machining Systems, Journal of Machine Engineering, 13/3, 91−116.
  • [27] TUNC L.T., BUDAK E., 2012, Effect of Cutting Conditions and Tool Geometry on Process Damping in Machining, International Journal of Machine Tools and Manufacture, 57, 10−19.
  • [28] BRECHER C., BAUMLER S., BROCKMANN B., 2013, Avoiding Chatter by means of Active Damping Systems for Machine Tools, Journal of Machine Engineering, 13/3, 117−128.
  • [29] JEMIELNIAK K., WIDOTA A., 1984, Suppression of Self Excited Vibration by the Spindle Speed Variation Method, Int. J. Machine Tools and Manufacture, 23/3, 207−214.
  • [30] ITO Y., 2008, Modular Design for Machine Tools, McGraw-Hill.
  • [31] SMITH S., TLUSTY J., 1992, Stabilizing Chatter by Automatic Spindle Speed Regulation, Annals of the CIRP, 41/1, 433−436.
  • [32] RIVIN E.I., 1999, Stiffness and Damping in Mechanical Design, CRC Press.
  • [33] RIVIN E.I., 2001, Interrelation of Stiffness and Damping in Machine Tool Dynamics, in Transactions of the North American Manufacturing Research Institution of SME, 137−143.
  • [34] SAKAI Y., TSUTSUMI M., 2013, Dynamic Characteristics of Linear Rolling Bearings for Machine Tools, Journal of Machine Engineering, 13/3, 129−142.
  • [35] JEDRZEJEWSKI J., KWASNY W., J. MILEJSKI D., SZAFARCZYK M., 1985, Selected Diagnostic Methods for Machine Tools Acceptance Tests, CIRP Annals - Manufacturing Technology, 34/1, 343−346.
  • [36] KRAS A., BOURGAIN F., CLAEYSSEN F., 2014, Amplified Piezo Actuator APA with Viscoelastic Material for Machine Tool Semi-Active Damping System, Journal of Machine Engineering 14/3, 83–96.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7d0cda5b-3514-4a0b-b742-a0bd98403d58
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