Open AccessAn Intelligent Fault Diagnosis Scheme Based On PCA-BP Neural Network for the Marine Diesel Engine
Author(s) -
Sibo Wang,
Jin Wang,
Xuewen Ding
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/782/3/032079
Subject(s) - diesel engine , artificial neural network , principal component analysis , diesel fuel , fault (geology) , automotive engineering , computer science , engineering , artificial intelligence , seismology , geology
Using AVL-BOOST to simulate the thermal fault of diesel engine, the principal component analysis method is used to analyze the thermal fault of diesel engine, and the three principal components are selected that can reflect the original variable 99.589% information as the input of BP neural network. The failure mode of the diesel engine is used as an output to construct a three-layer neural network prediction model. The results show that the PCA-BP neural network model can well diagnose the failure mode of diesel engines.