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Coupled modelling for machine tool structural optimization

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Effective machine tool design needs to take into account various kinematic configurations and possible combinations of structural parts, which meet the requirements of both the structural properties on one hand and technology and cost limitation on the other hand. Prior to a detailed developing a certain machine tool structure, an expert based decision on the machine tool conception needs to be performed. A high number of design variants should be explored in a short time. Fulfilling those demands leads to developing a machine tool modular models, enabling easy changing the kinematic configuration or various structural parts. In the paper the techniques for effective component coupling and model order reduction using mode truncation or Krylov subspace based technique for creating the machine tool coupled models are introduced. Case studies considering real machine tool structures are given. High quality of Krylov subspace reduction technique in connection with multipoint constraint surface coupling is shown both in terms of dynamic properties of the reduced multibody model and a very low time demands at the same time.
Rocznik
Strony
21--34
Opis fizyczny
Bibliogr. 18 poz., tab., rys.
Twórcy
autor
  • Czech Technical University, Faculty of Mechanical Engineering, RCMT, Prague
autor
  • Czech Technical University, Faculty of Mechanical Engineering, RCMT, Prague
autor
  • Czech Technical University, Faculty of Mechanical Engineering, RCMT, Prague
Bibliografia
  • [1] NEMETH I. et al, 2009, Development of a Machine Tool and Manufacturing System Configurator, 7th International Conference on Manufacturing Research. At Warwich, Semptember.
  • [2] ZATARAIN M. et al, 1998, Modular Synthesis of Machine Tools, CIRP Annals - Manufacturing Technology, 47/1, 333–336.
  • [3] TANI G. et al., 2006, Machining centers for high speed machining: a new design approach, Proceedings of the CIRP-2nd Intenational Conference, High Performance Cutting (HPC), Canada.
  • [4] SMOLÍK J. et al, 2012, Synergetic development of machine tools. MM Science Journal, March, 298-303
  • [5] ITO Y., 2008, Modular design for Machine Tools. The McGraw-Hill Companies, Inc., Japan.
  • [6] BACK N., BURDEKIN M., COWLEY A., 1974, Analysis of Machine Tool Joints by the Finite Element Method, Proceedings of the 14th Int. MTDR Conf., Macmillan, 529–537.
  • [7] T. YANG, S.H. FAN, C.S. LIN, 2003, Joint Stiffness Identification Using FRF Measurements, Comput. Struct, 81, 2549-2556.
  • [8] M. BÖSWALD and M. LINK, 2005, Identification of Non-linear Joint Parameters by Using Frequency Response Residuals, Proc. of the Int. Modal Analysis Conf. IMAC XXIII, Orlando, Florida, USA.
  • [9] WATANABE K., SATO H., 1988, Development of Non-linear Building Block Approach, Jour. of Vibration, Stress, and Reliability in Design, Trans. of ASME; 110: 36-41
  • [10] SCHMITZ B.T., 2003, Receptance coupling for high-speed machining, Proceedings of the 21st Internatinal Modal Analysis Conference, Kissimimee.
  • [11] De KLERK D., RIXEN D., VOORMEEREN S., 2008, General framework for dynamic substructuring: History, review, and classification of techniques, AIAA Journal, 46/5, 1169.
  • [12] QU Z., 2004, Model order reduction techniques: with applications in finite element analysis, Springer, USA.
  • [13] ANTOULAS A C., 2005, Approximation of large-scale dynamical systems, Advances in Design and Control, Philadelphia, PA, USA, Society for Industrial and Applied Mathematics.
  • [14] ANTOULAS A.C., SORENSEN D.C., 2001, Approximation of large-scale dynamical systems: An overview, Int. J. Appl. Math. Comput. Sci, 11, 1093-1121.
  • [15] GUGERCIN S., ANTOULAS A., BEATTIE C., 2008, H2 model reduction for large-scale linear dynamical systems, SIAM Journal on Matrix Analysis and Applications, 30/2, 609-638.
  • [16] ELFADEL I.M., LING D.D., 1997, A block rational Arnoldi algorithm for multipoint passive model-order reduction of multiport RLC networks, Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design, Washington, DC, USA.
  • [17] BAI Z., MEERBERGEN K., SU Y., 2005, Arnoldi methods for structure-preserving dimension reduction of second-order dynamical systems, Dimension Reduction of Large-Scale Systems, P. Benner, D. Sorensen and V. Mehrmann, Eds., Springer Berlin Heidelberg, 45, 173-189.
  • [18] BENNER P., FENG L., RUDNYI E.B., 2008, Using the superposition property for model reduction of linear systems with a large number of inputs, Proceedings of the 18th International Symposium on Mathematical Theory of Networks and Systems, MTNS2008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-08d8c429-7513-4813-8dd8-8003bbbb2ce7
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