Mining Study of Oil Atomic Emission Spectrum Data of Certain Diesel Engine
ZHANG Qiaobin
ZHANG Chunhui
ZHU Aifang
Abstract：Atomic emission spectroscopy is one of the most widely used techniques for oil analysis in the world now .In order to deeply mine the relation between the concentration of wearing elements of diesel engine and its loads ,cylinders'clearances and runtime after renewing oil ,a simulation model and a prediction model of Fe concentration of a type of six cyl‐inder diesel engine are established by applying neural network .The engine set up seven different working conditions and measured concentration of sixty‐nine oil samples .The results show that the relative errors of the simulation value of the 69 samples are within less than 15% .The absolute errors of prediction value of the 19 samples are lower than the acceptable ac‐curacy indices and the relative errors of 84% samples are within 15% .It is proved that Fe concentration can be predicted ef‐fectively by Neural Network algorithm .
Keywords：neural networkatomic emission spectrumdiesel enginewear elements
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 2037-2040 )