Conference article

Model Based System Identification for Hydraulic Deep Drawing Presses

Tobias Schulze
Institute of Fluid Power, TU Dresden, Germany

Jürgen Weber
Institute of Fluid Power, TU Dresden, Germany

Download articlehttp://dx.doi.org/10.3384/ecp1714469

Published in: Proceedings of 15:th Scandinavian International Conference on Fluid Power, June 7-9, 2017, Linköping, Sweden

Linköping Electronic Conference Proceedings 144:7, p. 69-79

Show more +

Published: 2017-12-20

ISBN: 978-91-7685-369-6

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

The paper describes the development of an automated system identification algorithm for the die cushion drive in hydraulic deep drawing presses. The algorithm could successfully be implemented on the drive controller to automatically identify the system parameters of the drive. Main aspect of the paper is the application driven development of an appropriate system model and identification algorithm with its implementation on the drive controller. It could be verified with experiments on a 2500 kN hydraulic deep drawing press. This thorough knowledge of the system model with its parameters shows a high potential to be further evaluated for system diagnosis and could also be used for system simulation and controller design.

Key points are the limited processing power of the drive controller and the occurring signal noise. A grey-box system model was chosen and its parameters were identified by means of a recursive least square algorithm. The implementation on the drive controller required adaptions due to restricted cycle time and additional signal processing to reduce noise that will also be discussed in the paper.

Keywords

Industrial hydraulics, hydraulic deep drawing press, system identification, system simulation, grey box model, valve control, parameter estimation, orthogonal correlation, moving average filter, symmetrical derivative

References

[1] Lohse, Harald; Helduser, Siegfried; Marthiens, Olaf; Matthias, Thorsten; Behrens, Bernd-Arno (2010): Reglerauslegung für hydraulische Tiefziehpressen Unterstützt durch ganzheitliche Simulation. In: O+P Ölhydraulik und Pneumatik 2010 (3), S. 68.

[2] Helduser, Siegfried (2006): Elektrisch-hydraulische Systemtechnik. Entwicklungsschwerpunkte in der Stationärhydraulik. In: O+P Ölhydraulik und Pneumatik 2006 (1), S. 16–23.

[3] Schoppel, Georg (2003): Beiträge zur automatischen Inbetriebsetzung und Regelung hydraulischer Zylinderantriebe. Aachen: Shaker.

[4] Isermann, Rolf (2011): Identification of Dynamic Systems, Springer.

[5] Keesmann, K. J. (2011): System identification an introduction, Advanced textbooks in control and signal processing, Springer.

[6] Ljung, L. (2009): System Identification. Theory for the user, Prentice Hall.

[7] Jelali, M.; Kroll, A. (2004): Hydraulic servo-systems. Modelling, identification and control. Springer London Ltd.

[8] Orfanidis, S. J. (1996): Introduction to signal processing, Prentice Hall signal processing series. Prentice Hall

[9] Schulze, T.; Weber, J.; Penter, L.; Großmann, K. (2014): Modelling and Simulation of the die cushion in a hydraulic deep drawing press. 16th ITI Symposium, Dresden

[10] Schulze, T.; Weber, J.; Großmann, K.; Penter, L.; Schenke, C. (2015): Hydraulic die cushions in deep drawing presses – analysis and optimization using coupled simulation. ASME/BATH 2015 Symposium on Fluid Power and Motion Control, Chicago

[11] Smith, S. W. (1999): The scientist and engineer`s guide to digital signal processing. California Technical Publication

[12] Helmke, M.; Majer, H.; Thanassakis, A. (2016): Improvement of hydraulic control quality for deep drawing presses through retrofit. 10th IFK 2016, Dresden,

Citations in Crossref