A Fault Diagnostic Method for EFI Engine Based on MATLAB Software Package

Author

Du Danfeng ; Guo Xiurong ; Guan Qiang

Author_Institution

Northeast Forestry Univ., Harbin

Volume

2

fYear

2008

fDate

20-22 Oct. 2008

Firstpage

870

Lastpage

874

Abstract

At present, the diagnostic instruments used widely here and abroad is not entire, which can not diagnose the mechanical fault without fault code. In order to solve this problem, this paper presents a method for fault diagnosis of electronic fuel injection (EFI) engine using radial basis function (RBF) neural network. By connecting MATLAB software package and ACCESS database, a fault diagnosis program is set up and a fault without code can be found. Meanwhile, the comparison has been done between RBF network and back propagation (BP) network. The simulation experimental results show that the RBF model is more feasible and successful than BP model and makes fault diagnosis easier.

Keywords

backpropagation; engines; fault diagnosis; fuel systems; mechanical engineering computing; radial basis function networks; software packages; ACCESS database; EFI engine; MATLAB software package; RBF network; back propagation network; electronic fuel injection engine; fault diagnostic method; radial basis function neural network; Databases; Engines; Fault diagnosis; Fuels; Instruments; Joining processes; MATLAB; Mathematical model; Neural networks; Software packages; electronic fuel injection (EFI) engine; fault diagnosis; radial basis function (RBF) neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on

Conference_Location

Hunan

Print_ISBN

978-0-7695-3357-5

Type

conf

DOI

10.1109/ICICTA.2008.97

Filename

4659886