Title :
Information fusion application for engine in condition measurement and fault diagnose
Author :
Liang, Guihang ; Wang, Jian ; Yu, Jingnuo ; Song, Jingui
Author_Institution :
Sch. of Traffic, Ludong Univ., Yantai, China
Abstract :
According to a variety of engine malfunctions, a method for fault diagnoses of engine based on the fuzzy logic theory and neural net work is put forward. Applying fuzzy membership functions to depict the fault extent, the system has the characteristic of fast inference speed. The model of engine fault diagnoses is set up by using the state parameter as learning samples. The data that engine state is identified are sample for the model. The results after tested show that it has a great improvement in convenient operation, facilitates to use. This method has more accurately for diagnosis faults of engine. It can improve the veracity for diagnose the fault of engine. And it can also develop the optimal control of engine.
Keywords :
automobiles; condition monitoring; engines; fuzzy set theory; mechanical engineering computing; neural nets; automobile engines; condition measurement; engine fault diagnosis model; engine malfunctions; fuzzy logic theory; fuzzy membership functions; information fusion; neural network; optimal control; state parameter; Engines; Fault diagnosis; Fuzzy neural networks; Mathematical model; Sensor systems; Temperature sensors; engine; fault diagnosis; fuzzy neural network; information fusion;
Conference_Titel :
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4673-0198-5
DOI :
10.1109/ICSAI.2012.6223294
