Title :
Design of intelligent fault diagnosis system based on naval vessel´s cooling system of diesel engine
Author :
Xianglong, Zhou ; Feng, Gao ; Jingbo, Zhao
Author_Institution :
Naval Submarine Acad., China
Abstract :
Aimed at the defect of low veracity and inefficient tradition fault diagnosis, an intelligent fault diagnosis system of a naval vessel´s cooling system for diesel engine is designed. Based on improved Back Propagation neural network algorithm and realized by Visual Basic loading Dynamic Link Library which by C++. Application results show that it has the more strong ability of self learning and self adaptation.
Keywords :
C++ language; Visual BASIC; backpropagation; cooling; diesel engines; fault diagnosis; naval engineering computing; neural nets; ships; software libraries; C++ language; Visual Basic loading Dynamic Link Library; back propagation neural network; cooling system; diesel engine; intelligent fault diagnosis system; naval vessel; self adaptation; self learning; Artificial intelligence; Artificial neural networks; Diesel engines; Fault diagnosis; Heuristic algorithms; Libraries; Visual BASIC; Visual Basic &C++ mixed programming; cooling system of diesel engine; improved Back Propagation algorithm; intelligent fault diagnosis;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554776
