Cart (Loading....) | Create Account
Close category search window
 

An Expert System for Fault Diagnosis in Diesel Engine Based on Wavelet Packet Analysis and Hybrid PSO-DV Based Neural Network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Bo Liu ; Sch. of Mech. Eng. & Autom., North Univ. of China, Taiyuan, China ; Hongxia Pan ; Xiuling Li

In the present study, an expert system is developed to identify and classify fault condition for diesel engine. Vibration signals are collected on a diesel engine test platform. Wavelet packet analysis (WPA) coefficients of vibration signals are used for evaluating their Shannon entropy and treated as the features to identify the fault conditions of diesel engine in the preprocessing. A back-propagation neural network (BPNN) is used to classify the fault condition. To improve the convergence of BPNN, a hybrid particle swarm optimization (PSO) with a differential operator named PSO-DV is used to adjust the weights and threshold of BPNN in fault diagnosis of diesel engine. To verify the proposed PSO-DV hybrid method has the better convergence, a classical PSO based BPNN is compared with a PSO-DV based BPNN in fault classification of diesel engine. The experimental results showed the proposed hybrid intelligent PSO-DV method not only achieved classification for diesel engine, but also can escape from local optima, so has better convergence than classical PSO.

Published in:

Intelligent Computing and Cognitive Informatics (ICICCI), 2010 International Conference on

Date of Conference:

22-23 June 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.