Abstract
On the basis of illustration of attribute hybrid computing network model, the paper gives the improving methods of training and learning of the model and applies it to fault diagnosis of the main engine water cooling system. The final results of simulation test verify the feasibility of methods.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Chen, Y., Shu, S., Weng, Z.: General Comments on Failure Diagnosis Methods of Dynamic System. Chemical Automation and Instruments 28(3), 1–14 (2001)
Zhang, J., Feng, J.: Attribute Petri Net Modeling and Its Application. Computer Engineering 32(17) (2006)
Wu, G., Ren, X.: Dynamic modeling and simulation of cylinder jacker water cooling system for main marine diesel engine. Journal of Harbin Engineering University 24(4) (2003)
Feng, J.: Qualitative Mapping Orthogonal System Induced by Subdivision Transformation of Qualitative Criterion and Biomimetic Pattern Recognition. Chinese Journal of Electronics, Special Issue on Biomimetic Pattern Recognition 85(6A), 850–856 (2006)
Feng, J., Xu, G.: Study on Mixed Input Attribute Computing Network Model and Boundary Study Algorithm. Computational Intelligence in Decision and Control
Zhou, D., Ye, Y.: Modern Fault Diagnosis and Fault-tolerance Control, vol. 20. Qinghua University Press, Beijing
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nianzu, L., Guanglin, X., Yongchang, L. (2011). Fault Diagnosis Model of Main Engine Water Cooling System Based on Attribute Hybrid Computing Network. In: Zeng, D. (eds) Applied Informatics and Communication. ICAIC 2011. Communications in Computer and Information Science, vol 225. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23220-6_42
Download citation
DOI: https://doi.org/10.1007/978-3-642-23220-6_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23219-0
Online ISBN: 978-3-642-23220-6
eBook Packages: Computer ScienceComputer Science (R0)