Journal article
Automotive Internal-Combustion-Engine Fault Detection and Classification Using Artificial Neural Network Techniques
Abstract
In this paper, an engine fault detection and classification technique using vibration data in the crank angle domain is presented. These data are used in conjunction with artificial neural networks (ANNs), which are applied to detect faults in a four-stroke gasoline engine built for experimentation. A comparative study is provided between the popular backpropagation (BP) method, the LevenbergMarquardt (LM) method, the quasi-Newton (QN) method, …
Authors
Ahmed R; Sayed ME; Gadsden SA; Tjong J; Habibi S
Journal
IEEE Transactions on Vehicular Technology, Vol. 64, No. 1, pp. 21–33
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
January 1, 2015
DOI
10.1109/tvt.2014.2317736
ISSN
0018-9545