bullet Sensors & Transducers Journal

    (ISSN: 2306-8515, e-ISSN 1726-5479)

205.767

2008 e-Impact Factor

25 Top Downloaded Articles

Best Selling Articles 2012

Journal Subscription 2014

Editorial Calendar

Submit an Article

Editorial Board

Current Issue

S&T journal's cover

Sensors & Transducers Journal 2011

Sensors & Transducers Journal 2010

Sensors & Transducers Journal 2009

Sensors & Transducers Journal 2008

Sensors & Transducers Journal 2007

2000-2002 S&T e-Digest Contents

2003 S&T e-Digest Contents

2004 S&T e-Digest Contents

2005 S&T e-Digest Contents

2006 S&T e-Digest Contents

 

Best Articles 2011

 

 

 

Vol. 165, Issue 2, February 2014, pp. 16-21

 

Bullet

 

Research Application of Support Vector Machine in Fault Diagnosis of Certain Type Engine
 

1, 2 Donghua FENG

1 School of Computer Science and Technology, Wuhan University of Technology, Hubei Wuhan, 430070, China
2 Dept. of Computer and Information Engineering, Nanyang Institute of Technology, Henan Nanyang, 473004, China
1 Tel.: 13733116699

1 E-mail: fengdonghuaedu@163.com

 

Received: 2 December 2013 /Accepted: 28 January 2014 /Published: 28 February 2014

Digital Sensors and Sensor Sysstems

 

Abstract: For the engine fault diagnosis in real problems, the number of samples available are limited, and the progress of research on the theory of the most limited to assume that the data samples, so that the network training data examples, in engineering applications has been slow, in this paper, the application of support vector machine in fault diagnosis of engine, the segmentation of the training sample set, in order to achieve the optimal analysis of the machine, the reasoning ability best. First introduced the two classification method of support vector machine and multi classification method based on two classification methods of the study, and applied to the fault diagnosis of engine, and then the simulation test for this method, and compared with the existing methods, the results show the effectiveness of the classification method, the results of the analysis also can use the tree diagram or table form, simple and intuitive; but also can save the contribution to some extent in time.

 

Keywords: Support vector machine, Multi class classification method, Engine, Fault diagnosis, Fault analysis.

 

Acrobat reader logo Click <here> or title of paper to download the full pages article in pdf format

 

 

Subscribe the full-page Sensors & Transducers journal in print (paper) or pdf formats

(shipping cost by standard mail for paper version is included)

(25 % discount for IFSA Members)

 

 

 

Alternatively we accept a money transfer to our bank account. Please contact for details: sales@sensorsportal.com

 

 

Download <here> the Library Journal Recommendation Form

 

 

 

 

 


1999 - 2014 Copyright , International Frequency Sensor Association (IFSA) Publishing, S.L. All Rights Reserved.


Home - News - Links - Archives - Tools - Voltage-to-Frequency Converters - Standardization - Patents - Marketplace - Projects - Wish List - e-Shop - Sensor Jobs - Membership - Videos - Publishing - Site Map - Subscribe - Search

 Members Area -Sensors Portal -Training Courses - S&T Digest - For advertisers - Bookstore - Forums - Polls - Submit Press Release - Submit White Paper - Testimonies - Twitter - Facebook - LinkedIn