Advertisement

Simulation of the Behavior of Disc-Spring Valve Systems with the Fuzzy Inference Systems and Artificial Neural Networks

  • Grzegorz Wszołek
  • Piotr Czop
  • Antoni Skrobol
  • Damian Sławik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7268)

Abstract

This paper proposes an analytical tool that supports the design process of a hydraulic damper valve system. The analytical tool combines Artificial Neural Networks (ANNs) and Fuzzy Inference Systems (FIS) into one tool called, in the paper, the Approximation Tool. The proposed Approximation Tool obtains a key design characteristic of a valve, which is the flow rate, and the corresponding maximum stress level in the valve components, as a function of a pressure load. The cases required to prepare the Approximation Tool were produced by a first-principle model using a finite element approach. The model was calibrated based on experimental results to provide accurate results in the entire range of input parameters. The paper describes the proposal, implementation, validation and an example of applying the Approximation Tool that allows the replacement of complex high- fidelity Finite Element analyses. As an approximator the Feed Forward Neural Network and FIS were taken.

Keywords

Fuzzy Inference System Shock Absorber Valve System Approximation Tool Maximum Stress Level 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Burczynski, T., Orantek, P., Skrobol, A.: Fuzzy-neural and evolutionary computation in identification of defect. Journal of Theoretical and Applied Mechanics 42(3), 445–460 (2004)Google Scholar
  2. 2.
    Burczynski, T., Skrobol, A.: Coupled evolutionary algorithm and artificial neural network in defects identification. In: Bathe, K.J. (ed.) Third MIT Conf. on Computational Fluid and Solid Mechanics, pp. 122–1226 (2005)Google Scholar
  3. 3.
    Czop, P., Slawik, D., Sliwa, P., Wszolek, G.: Circular plater theory applied to modeling of intake valves used in shock absorbers. Journal of Achievements in Materials and Manufacturing Engineering 33(2), 173–180 (2009)Google Scholar
  4. 4.
    Czop, P., Slawik, D., Sliwa, P.: Static validation of a model of a disc valve system used in shock absorbers. International Journal of Vehicle Design 53(4), 317–342 (2010)CrossRefGoogle Scholar
  5. 5.
    Dassault Systemes: Isight 3.5. Getting started guide (2009), http://www.simulia.com
  6. 6.
    Dixon, J.C.: The shock absorber handbook. Wiley, England (2007)CrossRefGoogle Scholar
  7. 7.
    Kosinski, W., Weigl, M.: Fuzzy-neural systems for multivariate approximation problems. In: Proceeding of 6rd Zittau Fuzzy Colloquium, Zittau, pp. 141–146 (1998)Google Scholar
  8. 8.
    Math-Works Inc.: Matlab-Simulink documentation (2011), http://www.mathworks.com/help
  9. 9.
    Piatkowski, G., Ziemianski, L.: Neural network identification of a circular hole in the rectangular plate. In: Rutkowski, L., Kacprzyk, J. (eds.) Neural Networks and Soft Computing, pp. 778–783. Physica-Verlag Springer, Heidelberg (2003)Google Scholar
  10. 10.
    Rutkowska, D.: Computational intelligent systems. Akademicka Oficyna Wydawnicza PLJ, Warszawa (1997)Google Scholar
  11. 11.
    Segel, L., Lang, H.H.: The mechanics of automotive hydraulic dampers at high stroking frequencies. Vehicle System Dynamics 10(2–3), 82–85 (1981)CrossRefGoogle Scholar
  12. 12.
    Van der Velden, A., Koch, P.: Isight design optimisation methodologies (2009), http://www.simulia.com
  13. 13.
    Van Kasteel, R., et al.: A new shock absorber model with an application in vehicle dynamics studies. In: 2003 SAE International Truck and Bus Meeting and Exhibition, Fort Worth, Texas (2003)Google Scholar
  14. 14.
    Young, W.C.: Roark’s formulas for stress and strain. McGraw-Hill, New York (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Grzegorz Wszołek
    • 1
  • Piotr Czop
    • 1
  • Antoni Skrobol
    • 1
  • Damian Sławik
    • 1
  1. 1.Silesian University of TechnologyGliwicePoland

Personalised recommendations