Title :
OBTS-oriented research on warship main power system hybrid model
Author :
Xie, Kuan ; Wu, Liechang ; Guo, Chaoyou
Author_Institution :
Dept. of Mech. Eng., Naval Univ. of Eng., Wuhan, China
Abstract :
This paper puts forward a warship main power on board training system hybrid modeling method based on neural network and integrates the method of mechanism modeling and Identification Modeling, uses neural network to compensate the error from the mechanism model. It improves the model precision, and suit the behavior changing of main power system. Taking warship diesel as an example, the developing method of hybrid model of diesel rotating speed was studied, and the feasibility of hybrid modeling method proposed was testified.
Keywords :
computer based training; marine power systems; neural nets; power engineering computing; ships; OBTS-oriented research; diesel rotating speed was; identification modeling; mechanism modeling; model precision; neural network; warship diesel; warship main power on board training system hybrid modeling method; warship main power system hybrid model; Accuracy; Analytical models; Predictive models; hybrid modeling; main power system; neural network; on board training system;
Conference_Titel :
Electrical & Electronics Engineering (EEESYM), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2363-5
DOI :
10.1109/EEESym.2012.6258685