Journals / İTÜ Dergisi Seri D: Mühendislik / 2002 / Cilt: 1 - Sayı: 1

Experimental modelling for piston dynamics of a pneumatic system

Pnömatik bir sistemin piston dinamiğinin deneysel modellenmesi

Pages
75–83
Publication Date
2022-10-19
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

And through watching the change of the system parameters by time, fault estimation can be performed and, ease of maintenance can be provided.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, modelling and parameter identification f or parameters of the piston dynamics are experimentally carried out on a pneumatic system, which consists of a magnetically coupled rodless cylinder with high precision guide, and electropneumatic proportional servovalves, magnetic linear scale, pressure sensors, analog anti-aliasing filters and interface circuits, through applying PRBS signals and acquiring the system responses as chamber pressures and piston position.
📊
Key Findings & Data:Later the data are digitally processed to create input-output data for the identification model.
💡
Conclusion & Impact:And through watching the change of the system parameters by time, fault estimation can be performed and, ease of maintenance can be provided.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, modelling and parameter identification f or parameters of the piston dynamics are experimentally carried out on a pneumatic system, which consists of a magnetically coupled rodless cylinder with high precision guide, and electropneumatic proportional servovalves, magnetic linear scale, pressure sensors, analog anti-aliasing filters and interface circuits, through applying PRBS signals and acquiring the system responses as chamber pressures and piston position. Later the data are digitally processed to create input-output data for the identification model. First order linear velocity model of piston dynamics is obtained by using extended least squares method, parameter adaptation algorithm with decreasing gain for identification. The parametric model obtained is first convened into discrete-time state-space model. Then, the dis-crete state-space model is also convened into continuous-time state-space model. By comparing this model with mathematical motion equations of the system, viscous friction coefficients and mass quantity for the system are identified. Considering difficulties, even impossibilities, of determination of viscous friction coefficients by another way, the importance of the identification is obvious. In the simulation studies, realistic results can be obtained by using actual system parameters instead of assumed ones. And through watching the change of the system parameters by time, fault estimation can be performed and, ease of maintenance can be provided.

Özet

Bu çalışmada; pnömatik bir sistemin piston dinamiği parametrelerinin, PRBS sinyalleri uygulanarak ve sistemin bu sinyallere silindir basınçları ve piston konumu olarak verdiği cevapları kullanarak, deneysel modelleme yapılarak tanılanması gerçekleştirilmektedir. Genişletilmiş en küçük kareler yöntemi azalan kazançlı parametre uyum algoritmasıyla kullanılarak birinci mertebe lineer piston hız modeli tanılanmıştır. Elde edilen ayrık zamanlı modelin sürekli zamanlı modele dönüştürülmesi ve matematiksel hareket denklemleriyle kıyaslanmasıyla sisteme ait kütle miktarı ve başka bir yöntemle bulunması güç olan viskoz sürtünme katsayısı bulunmuştur. Simülasyon çalışmalarında, sistem parametrelerinin belirli kabuller yerine gerçek değerlerinin kullanılmasıyla daha gerçekçi sonuçlar elde edilebilir. Yine parametre değerlerinin zamana göre değişimi incelenerek sistemde arıza tahmini yapılabilir, bakım kolaylıkları sağlanabilir.

🔖

Cite This Article

ZORLU, A., ÖZSOY, C. (2022). Experimental modelling for piston dynamics of a pneumatic system. İTÜ Dergisi Seri D: Mühendislik, Cilt: 1 - Sayı: 1, 75–83. https://ajindex.com/articles/541890

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (9)

  1. Antoniou, A., (1993). Digital filters, analysis, design and applications, McGraw Hill, Newyork. Cihan, S., (1999).
  2. Pnömatik konum kontrolu, Yüksek Lisans Tezi, İ.T.Ü. Fen Bilimleri Enstitüsü, İstanbul.
  3. Deniz, U., (2001).
  4. Pnömatik kuvvet kontrolu, Bitirme Çalışması, İ.T.Ü. Makina Fakültesi, İstanbul.
  5. Isermann, R., (1981).
  6. Digital control systems, Springer-Verlag Berlin, Newyork. Koç, İ. M., (1998). Hassas ve katı pnömatik konum kontrolu, Yüksek Lisans Tezi, İ.T.Ü. Fen Bilimleri Enstitüsü, İstanbul.
  7. Lin, X., Spettel, F., Scavarda, S., (1996). Modelling and test of an electropneumatic servovalve controlled long rodless actuator, Transactions of the ASME, Journal of Dynamic Systems, Measurement, and Control, 118, 457-462.
  8. Pandian, S. R., Hayakawa, Y., Kanazawa, Y., Kamayama, Y., Kawamura, S., (1997). Practical design of a sliding mode controller for pneumatic actuators, Transactions of the ASME, Journal of Dynamic Systems, Measurement, and Control, 119, 666-674.
  9. Zeimer, R. E., Tranter, W. H., Fannin, D. R., (1993). Signals and systems: continuous and discrete, Macmillan, Newyork.