Fault diagnosis of diesel engine based on energy spectrum analysis

Author

Hongxia Pan ; Jifang Men

Author_Institution

Sch. of Mech. Eng. & Autom., North Univ. of China, Taiyuan, China

fYear

2012

fDate

3-5 Sept. 2012

Firstpage

697

Lastpage

701

Abstract

This paper has studied the application of wavelet package energy spectrum and frequency energy spectrum analysis in the diesel engine fault diagnosis. Extracting the fault features by wavelet package energy spectrum and frequency energy spectrum analysis of the fault angle of fuel supply decreased 2.5° and plug of air filter, then making those as the input character of neural networks and implementing the fault diagnosis. It is concluded that frequency energy spectrum analysis is more strongly of the practicability than wavelet package energy spectrum analysis by comparing the test results.

Keywords

air cleaners; diesel engines; fault diagnosis; feature extraction; fuel systems; mechanical engineering computing; neural nets; air filter plug; diesel engine fault diagnosis; fault angle; fault feature extraction; frequency energy spectrum analysis; fuel supply; neural networks; wavelet package energy spectrum analysis; Biological neural networks; Fault diagnosis; Spectral analysis; Training; Wavelet analysis; Wavelet packets; energy spectrum; fault diagnosis; neural networks; wavelet packet;

fLanguage

English

Publisher

ieee

Conference_Titel

Control (CONTROL), 2012 UKACC International Conference on

Conference_Location

Cardiff

Print_ISBN

978-1-4673-1559-3

Electronic_ISBN

978-1-4673-1558-6

Type

conf

DOI

10.1109/CONTROL.2012.6334714

Filename

6334714