Fault Diagnosis of Vehicle Engine Based on Analytic Hierarchy Process and Neural Network

DOI

10.2991/mecae-18.2018.32How to use a DOI?

Keywords

analytic hierarchy process (AHP); neural network; vehicle launching; fault diagnosis; simulation experiment

Abstract

Due to the nonlinear relationship between vehicle engine fault characteristics, traditional methods can not accurately describe the correlation characteristics between different features, it is very difficult to achieve accurate diagnosis of vehicle engine fault. In order to improve the accuracy of vehicle engine fault diagnosis, a new fault diagnosis method for vehicle engine AHP and neural network based on extracted characteristics of the vehicle engine fault diagnosis, then use AHP to determine the weight value of the vehicle engine fault diagnosis, the fault diagnosis of vehicle engine features as the input of neural network, the establishment of classification engine fault diagnosis of the vehicle, the vehicle engine fault diagnosis simulation experiment, the results show that this method improves the accuracy of engine fault diagnosis, fault diagnosis and accelerate the speed of the vehicle engine, has important practical significance.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chuanxiang Du
AU  - Xiuling Wei
PY  - 2018/03
DA  - 2018/03
TI  - Fault Diagnosis of Vehicle Engine Based on Analytic Hierarchy Process and Neural Network
BT  - Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-18.2018.32
DO  - 10.2991/mecae-18.2018.32
ID  - Du2018/03
ER  -