Study on Diesel Engine Status Analysis and Fault Diagnosis Based on SAE J1939 Protocol

DOI

10.2991/eame-15.2015.72How to use a DOI?

Keywords

SAE J1939; diesel engine; fault diagnosis; PSO-RBF neural network

Abstract

SAE J1939 is one of the most widely used application layer protocols in automotive industry based on CAN bus. SAE J1939 defines vehicle application layer to make us read the status of the vehicle easily. We propose an improved RBF neural network fault classification algorithm to classify diesel engine fault. Also we analyse the state of the vehicle from vehicle CAN bus and use MATLAB to write a program so that we can analyse the CAN bus data. According to CAN data obtained from a diesel engine, we got diesel engine fault data and use they to train PSO-RBF neural network, the resulting effect is better than PSO neural network and we can use it to do a diesel engine fault diagnosis.

Copyright

© 2015, 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  - L.H. Cao
AU  - J.N. Li
AU  - X.L. Liu
AU  - J.L. Yu
AU  - Z.M. Wu
AU  - F.G. Chen
PY  - 2015/07
DA  - 2015/07
TI  - Study on Diesel Engine Status Analysis and Fault Diagnosis Based on SAE J1939 Protocol
BT  - Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering
PB  - Atlantis Press
SP  - 263
EP  - 266
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-15.2015.72
DO  - 10.2991/eame-15.2015.72
ID  - Cao2015/07
ER  -