Title :
Prediction on turbine supercharger speed of diesel engines based on projection pursuit regression
Author :
Dong, Yucai ; Zhang, Ling ; Yi, Lianghai ; Lin, Min ; Fan, Gehua
Author_Institution :
Inst. of Nonlinear Sci., Acad. of Armored Force Eng., Beijing, China
Abstract :
In the plateau environment with low pressure, turbine supercharger speed is an important parameter to supervise working condition of diesel engines. In view of the problems of installation difficulty and low measurement accuracy in measurement of turbine supercharger speed in vehicles, this paper sets up a projection pursuit regression (PPR) model to predict turbine supercharger speed. The calculation result indicates that the fitting effect of this model is obviously superior to that of any other regression models, which has great significance to prediction on turbine supercharger speed of diesel engines in a low pressure environment.
Keywords :
diesel engines; fuel systems; regression analysis; turbines; velocity measurement; diesel engines working condition; projection pursuit regression; speed measurement; turbine supercharger speed; Diesel engines; Fitting; Kernel; Pollution measurement; Predictive models; Turbines; Vehicles; Diesel Engines; Projection Pursuit Regression; Turbine Supercharger Speed;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
DOI :
10.1109/ICCSNT.2011.6182102
