Title :
Fault diagnosis of diesel engine combustion system based on neural networks
Author :
Yan, Gen-ting ; Ma, Guang-Fu
Author_Institution :
Dept. of Control Sci. & Eng., Harbin Inst. of Technol., China
Abstract :
We have developed a neural-network based on fault diagnostic system for diesel engine combustion system. Grounded on the presented evolutionary algorithm, neural networks automatically adjust the network parameters (connection weights and bias terms). Computer simulation experimental results confirm that the proposed method has high diagnostically accuracy.
Keywords :
diesel engines; digital simulation; evolutionary computation; fault diagnosis; neural nets; bias term parameter; computer simulation; connection weight parameter; diesel engine combustion system; evolutionary algorithm; fault diagnostic system; network parameters; neural networks; Artificial neural networks; Combustion; Computer simulation; Control systems; Diesel engines; Electronic mail; Evolutionary computation; Fault diagnosis; Neural networks; Pattern recognition;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1378568
