Title :
A fault diagnosis method for diesel engine based on Adaptive Network-based Fuzzy Inference System
Author :
Duan Wei-Wu ; Song Yi-Bin
Author_Institution :
Sch. of Comput. Sci. & Technol., Yantai Univ., Yantai, China
Abstract :
Combines fuzzy logic inference system with Neural Network, a fault diagnosis method for diesel engine based on Adaptive Network-based Fuzzy Inference System (ANFIS) is studied. The theory and arithmetic and structure of this system are introduced, and a fault model for the fuel injection system of a diesel engine is built with the help of Matlab Fuzzy Toolbox. Simulation results demonstrate that the proposed approach can efficiently diagnose the faults and is better than the fault diagnosis method based on BP neural network.
Keywords :
backpropagation; diesel engines; fault diagnosis; fuel systems; fuzzy set theory; inference mechanisms; mechanical engineering computing; neural nets; BP neural network; Matlab Fuzzy Toolbox; adaptive network-based fuzzy inference system; diesel engine; fault diagnosis method; fuel injection system; fuzzy logic inference system; neural network; Adaptation model; Adaptive systems; Artificial neural networks; Decision making; Diesel engines; Fault diagnosis; MATLAB; ANFIS; Diesel Engine; Fault Diagnosis;
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
