Using Sensors Data and Emissions Information to Diagnose Engine’s Faults

DOI

10.2991/ijcis.11.1.86How to use a DOI?

Keywords

Fault diagnosis; Neural network; Sensors data flow; Emissions information; Engine

Abstract

This paper proposes using engine’s sensors data flow and exhaust emissions information to diagnose engine’s faults, enhancing the accuracy of fault diagnosis. Engine fault diagnosis model is built using both this information and the mature BP neural network and genetic algorithms. In order to verify the method, we build a test platform, which includes South Korea Hyundai fault test vehicle and X-431 diagnosis instrument and AUTO5-1 exhaust gas analyzer and computer. The diagnostic accuracy rate can reach 98.33%, which is higher than using sensors data flow or the exhaust emissions information alone.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

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

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TY  - JOUR
AU  - Chunli XIE
AU  - Yuchao Wang
AU  - John MacIntyre
AU  - Muhammad Sheikh
AU  - Mustafa Elkady
PY  - 2018
DA  - 2018/06/04
TI  - Using Sensors Data and Emissions Information to Diagnose Engine’s Faults
JO  - International Journal of Computational Intelligence Systems
SP  - 1142
EP  - 1152
VL  - 11
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.11.1.86
DO  - 10.2991/ijcis.11.1.86
ID  - XIE2018
ER  -