Open AccessResearch on Wear Status of Diesel Engine Cylinder Based on BP Neural Network and Instantaneous Speed
Author(s) -
Xinqi Qiao,
Cheng Gu
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1237/5/052011
Subject(s) - cylinder , artificial neural network , diesel engine , dimensionless quantity , automotive engineering , fault (geology) , signal (programming language) , diesel fuel , engineering , state (computer science) , main bearing , mechanical engineering , control theory (sociology) , computer science , mechanics , crankshaft , algorithm , artificial intelligence , geology , physics , control (management) , seismology , programming language
The instantaneous speed contains a large amount of diesel engine operating state information. This paper establishes the diesel engine dynamics model to obtain the instantaneous speed curve under different cylinder wear states, and extracts its four dimensionless parameters, then establishes the cylinder wear state model based on BP neural network using the simulated fault signal, and the actual vehicle test data is used to verify. The results show that the cylinder wear analysis model based on BP neural network can accurately determine the cylinder wear state.