Study on the Control System of Grinding the Nozzle of Twin Flapper-Nozzle Valve

Article Preview

Abstract:

In this paper, neural network and grey fuzzy control technology are applied in Abrasive Flow Machining (AFM) to grind the mico-hole in th nozzle of the twin flapper-nozzle valve. An intelligent control system with fine tuning working pressure is established that can predict the process parameters automatically before machining and forcast the flow to adjust the working pressure in machining.The result of experiment indicates that this system has high level of intelligent and can get very high machining accuracy.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

62-66

Citation:

Online since:

September 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] D.I. Mu, C.C. Liand M. Sun, Nonlinear simulation and linearization of twin flapper-nozzle servo valve, Journal of Mechanical Engineering, vol. 48(2012), p.193.

DOI: 10.3901/jme.2012.02.193

Google Scholar

[2] Z.F. Peng C.G. Sun R.B. Yuan, The CFD Analysis of Main Valve Flow Field and Structural Optimization for Double-nozzle Flapper Servo Valve, Procedia Engineering, vol. 31(2012), p.115.

DOI: 10.1016/j.proeng.2012.01.1000

Google Scholar

[3] Y.D. Tian, Technology of Electro Hydraulic Servo Valves, Aviation Industry Press, BeiJing, (2008).

Google Scholar

[4] H.Y. Li, S.M. Wang, Analysis and Research on Mechanic Parts Quality and Value Characteristics for Nozzle Flapper Hydroelectric Servo Valve, Chinese Hydraulics & Pneumatics, In Chinese, vol. 10(2013), p.110.

Google Scholar

[5] Y.C. Lin, H.M. Chow and B.H. Yan, Effects of Finishing in Abrasive Fluid Machining on Microholes Fabricated by EDM, Int J Adv Manuf Technol, vol. 33(2007), p.489.

DOI: 10.1007/s00170-006-0485-7

Google Scholar

[6] V.K. Jain and S.G. Adsul , Experimental investigations into abrasive flow machining (AFM), Int J Machine Tools and Manufacture , vol. 40(2000), p.1003.

DOI: 10.1016/s0890-6955(99)00114-5

Google Scholar

[7] D. Jung, W.L. Wang, A. Knafl, Experimental investigation of abrasive flow machining effects on injector nozzle geometries, engine performance, and emissions in a di diesel engine, International Journal of Automotive Technology, Vol. 9(2008), p.9.

DOI: 10.1007/s12239-008-0002-0

Google Scholar

[8] V.K. Gorana, V.K. Jain and G.K. Lal. Prediction of surface roughness during abrasive flow machining, Int J Adv Manuf tech, vol. 31(2006), p.258.

DOI: 10.1007/s00170-005-0197-4

Google Scholar

[9] Sandhya Samarasinghe, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition, Auerbach Publications, New York, (2006).

Google Scholar

[10] D.H. Liu Y.G. Dang and X.M. Li, Improvement and Application of GM (1, 1) Model, Proceed of the IEEE International Grey Systems and Intelligent Services, 2009, p.344.

Google Scholar