Study on Fault Classification of Power-Shift Steering Transmission Based on v-Support Vector Machine

Yuan Zhu (), Ying-feng Zhang and Ai-yong Du
Additional contact information
Yuan Zhu: Academy Military Transportation
Ying-feng Zhang: Academy Military Transportation
Ai-yong Du: Academy Military Transportation

Chapter Chapter 70 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 647-654 from Springer

Abstract: Abstract This paper focused on the condition monitoring problem of the Power-Shift Steering Transmission (PSST). Spectrometric oil analysis is an important way to study the running state of PSST. Because of complicated nonlinear relationship in oil analysis data, a model of PSST’ fault classification based on v- Support Vector Machine (v-SVM) is proposed. The fundamental of v-SVM is researched. The influence of model parameters for performance of v-SVM is analyzed. Experimental results show that, comparing with C-support vector machine and BP neural network, the v-support vector machine has good properties in research of fault classification of PSST.

Keywords: Fault classification; v-support vector machine; Power-shift steering transmission (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-38433-2_70

Ordering information: This item can be ordered from
http://www.springer.com/9783642384332

DOI: 10.1007/978-3-642-38433-2_70

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().