Application for diesel engine in fault diagnose based on fuzzy neural network and information fusion

Author

Guihang, Liang ; Qiang, Wang ; Jian, Wang ; Jingui, Song

Author_Institution

Sch. of Traffic, Ludong Univ., Yantai, China

fYear

2011

fDate

27-29 May 2011

Firstpage

102

Lastpage

105

Abstract

According to a variety of diesel engine malfunctions, a method for fault diagnoses of diesel engine based on neural net work and information fusion is put forward. The model has the characteristic of fast inference speed applying fuzzy membership functions to depict the fault extent. The model of fault diagnoses is set up by using the state parameter of diesel engine as learning samples. The data from diesel engine state is identified are sample. It is verified the validity of the model of fuzzy neural network after experiments. The results show that it has a great improvement in convenient operation and facilitates to use. This method for diagnosis faults of diesel engine has more accurately. It can improve the veracity for diagnose the fault. It can also develop the optimal control of diesel engine.

Keywords

automotive engineering; diesel engines; fault diagnosis; fuzzy neural nets; fuzzy reasoning; mechanical engineering computing; sensor fusion; diesel engine malfunction; fault diagnosis; fuzzy membership function; fuzzy neural network; information fusion; learning sample; optimal control; Computers; Engines; diesel engine; fault diagnosis; fuzzy neural network; information fusion;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-61284-485-5

Type

conf

DOI

10.1109/ICCSN.2011.6014398

Filename

6014398