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Mechatronics in Vibration Monitoring and Control

  • Tadeusz Uhl
Chapter
  • 389 Downloads
Part of the Computational Methods in Applied Sciences book series (COMPUTMETHODS, volume 1)

Summary

This chapter deals with methods of vibration monitoring and control based on mechatronic solutions. An innovative, new approach of design and implementation of mechatronic systems is applied to design of smart sensor for operational load measurements. New idea of smart sensors and their application for health monitoring and diagnostics of structures is described. Test of performance of designed and implemented smart sensor is shown. The main advantage of its application is automation of design process focused on virtual and fast prototyping. The second example of application of mechatronic design method is active balancing system for rotating shaft which is carefully discussed. The concept, control algorithms, and prototyping system implementation are shown.

Keywords

Virtual Prototype Vibration Level Mechatronic System Smart Sensor Vibration Monitoring 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Caccavale F, Villani L (Eds.) (2003) Fault diagnosis and fault tolerance for mechatronic systems. Springer, BerlinzbMATHGoogle Scholar
  2. 2.
    Isermann R (2003) Mechatronic Systems. Springer, LondonGoogle Scholar
  3. 3.
    Uhl T (Ed.) (1999) Selected problems in mechatronic design. Robotics and Machine Dynamics Department Press, University of Science and Technology AGH, KrakowGoogle Scholar
  4. 4.
    Uhl T, Barszcz T, Hanc A (2003) Mechatronics in design of Monitoring and Diagnostic Systems. Key Engineering Materials 245–246: 381–390CrossRefGoogle Scholar
  5. 5.
    Petko M (2003) Fast prototyping in development of diagnostics and monitoring systems. Exploitation Problems of Machines 38 (3): 95–114Google Scholar
  6. 6.
    Harpel H-J, Glesner M (1998) Rapid prototyping of real-time information processing units for mechatronic systems. Real-Time Systems 14: 269–291CrossRefGoogle Scholar
  7. 7.
    Rowson A (1994) Hardware/software co-simulation, Proc. Of the 31st Design Automation Conference, San Diego, USA, pp 129–134.Google Scholar
  8. 8.
    Glesner M, Kirshbaum A, Renner FM, Voss B (2002) State of the art in rapid prototyping for mechatronic systems. Mechatronics 12: 987–998CrossRefGoogle Scholar
  9. 9.
    Damic V, Montgomery J (2003) Mechatronics by Bond Graphs. Springer, BerlinGoogle Scholar
  10. 10.
    Uhl T, Rod J (1999) Modeling and simulation of Mechatronic systems, In: Selected problems in mechatronic design, T. Uhl (ed.), Robotics and Machine Dynamics Department Press, University of Science and Technology AGH (in Polish)Google Scholar
  11. 11.
    Mrozek Z (2002) Computer assisted design of mechatronic systems. Sci. Bul. Cracow Univ. Tech., 1Google Scholar
  12. 12.
    Uhl T (1999) Trends and progress in monitoring and diagnostic systems. PAK 4, (in Polish)Google Scholar
  13. 13.
    Giergiel J, Uhl T (1989) Identification of the input impact type forces in mechanical systems. The Archives of Transport 1 (1)Google Scholar
  14. 14.
    Uhl T (2001) Identification of loading forces in mechanical systems using genetic algorithms, Proc. of AIMECH 01, GliwiceGoogle Scholar
  15. 15.
    Haas DJ, Milano J, Flitter L (1995) Prediction of Helicopter Component Loads Using Neural Networks. J. American Helicopter Society vol. 1Google Scholar
  16. 16.
    Zion L (1994) Predicting fatigue loads using regression diagnostics, Proc. American Helicopter Society Annual Formu, Washington D.C.Google Scholar
  17. 17.
    Lisowski W, Mendrok K, Uhl T (2001) Identification of loads basing on output signal measurement, Proceedings of V Conf. on Experimental Methods in Machine Design, Wrocaw- Szklarska Porçba, (in Polish)Google Scholar
  18. 18.
    Busby HR, Trujillo DM, Solution of an invesrse dynamics problem using an eigenvalue reduction technique. Computer ampStructures 25(1)Google Scholar
  19. Simonian SS (1981) Inverse problems in structural dynamics. Int. J. Num. Meth. Engng. 17: 357–365MathSciNetzbMATHCrossRefGoogle Scholar
  20. 20.
    Trujillo DM (1987) Application of Dynamic programming to the general inverse problem. Int. J. Num. Meth. Engng. 23: 613–624zbMATHGoogle Scholar
  21. 21.
    Uhl T, Pieczara J (2003) Identification of operational loading forces for mechanical structures. Archives of Transport 16 (2)Google Scholar
  22. 22.
    SIMULINK User’s Guide (1999) The MathWorks Inc., Natic.Google Scholar
  23. 23.
  24. 24.
  25. 25.
  26. 26.
    Frank R (2000) Understanding Smart Sensors. Artech House, NorwoodGoogle Scholar
  27. 27.
    Uhl T, Petko M (2002) Smart Sensor for Operational Load Measurements. J. Theor. Appl. Mech. 40 (3): 797–815Google Scholar
  28. 28.
    Petko M (1999) Mechatronics product realization (in Polish), In: Mechatronics design ( T. Uhl (Ed.), KRiDM AGH, KrakowGoogle Scholar
  29. 29.
    Petko M (2001) Implementation of control algorithms in ASIC/FPGA. Mecatronics. Proceedings 5th Franco-Japanese Congress & 3“ European-Asian Congress of Mechatronics pp. 70–74, BesanconGoogle Scholar
  30. 30.
    Petko M, Uhl T (2001), Embedded controller desing-mechatronic approach Proc. Second International Workshop on Robot Motion and Control RoMoCo’Ol, Politechnika Poznanska, Bukowy Dworek, pp. 195–200Google Scholar
  31. 31.
    Uhl T, Mrozek Z, Petko M (2000) Rapid control prototyping for flexible arm. 1-st IFAC Conference on Mechatronic Systems, Preprint, 2:489–494, DarmstadtGoogle Scholar
  32. 32.
    Jang J-SR, Sun C-T, Mizutani E (1997) Neuro-Fuzzy and Soft Computing: A computational approach to learning and machine intelligence. Prentice Hall, Upper Saddle RiverGoogle Scholar
  33. 33.
    Perry DL (1998) VHDL, McGraw-HillGoogle Scholar
  34. 34.
    FPGA Compiler II/FPGA Express VHDL Reference Manual (1999) Synopsys, Inc.Google Scholar
  35. 35.
    Neural Network Toolbox User’s Guide (1999) The MathWorks Inc., NaticGoogle Scholar
  36. 36.
    Fixed-Point Blockset User’s Guide (1999) The MathWorks Inc., NaticGoogle Scholar
  37. 37.
    Nonlinear Control Design Blockset User’s Guide (1997) The MathWorks Inc., NaticGoogle Scholar
  38. 38.
    ART Library User’s & Reference Manual (2000) Frontier Design Inc., DanvilleGoogle Scholar
  39. 39.
    ART Builder User’s and Reference Documentation (2000) Frontier Design Inc., DanvilleGoogle Scholar
  40. 40.
    APEX 20K Programmable Logic Device Family (1999) Altera Corp.Google Scholar
  41. 41.
    Manka M, Felis J, Petko M, Uhl T (2003) The new method of automatic balancing during operation. Bull. Univ. Sci. Tech. AGH, 22 (3): 347–354Google Scholar
  42. 42.
    Furman BJ (1982) A new theramly controlled, non contact rotor balancing method. J. Mechanical Design 116: 823–832CrossRefGoogle Scholar
  43. 43.
    Van den Vegte J (1981) Balancing of flexible rotors during operation. J. Mech. Engng. Sci., vol. 23 (3): 257–261CrossRefGoogle Scholar
  44. 44.
    Hanselmaan H (1993) Hardware in the loop simulation as a standard approach for development, customization and production test. SEA Paper no. 930207Google Scholar
  45. 45.
    Uhl T (1996) Fast prototyping — a new tool for xnechatronic system development. PAK, 4: 34–41Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Tadeusz Uhl
    • 1
  1. 1.University of Science and Technology AGHKrakówPoland

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