Title :
Fuzzy neural network in condition maintenance for marine electric propulsion system
Author :
Shutian Liang ; Junfei Yang ; Yanan Wang ; Menglian Wang
Author_Institution :
Wuhan Inst. of Marine Electr. Propulsion, Wuhan, China
fDate :
Aug. 31 2014-Sept. 3 2014
Abstract :
Since marine electric propulsion system is composed of numerous equipments with complicated yet interconnected structure it should apply condition maintenance to solve maintenance not on time or over-maintenance. Applied condition maintenance could improve the usage of equipments so as to improve operational efficiency and maintenance ability of ship. Recognizing the shortcomings of non-intelligence of fuzzy theory as well as slow convergence of intelligent neural-network, the fuzzy neural network (FNN) method of condition maintenance of marine electric propulsion system is applied in the paper. It represented the superiority of FNN method and using FNN to set up the progress and implement steps of condition maintenance of marine electric propulsion system. Using the certain ship´s measurement data we obtained a model of condition maintenance model with FNN. Simulation using MATLAB shows that it can provide high precision and is suitable for project application.
Keywords :
fuzzy neural nets; maintenance engineering; marine propulsion; power engineering computing; MATLAB simulation; condition maintenance model; fuzzy neural network; intelligent neural network; marine electric propulsion system; operational efficiency; Artificial neural networks; Fuzzy neural networks; Maintenance engineering; Propulsion; Training; Windings; Condition maintenance; Electric propulsion system; Fuzzy neural network; Marine;
Conference_Titel :
Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-4240-4
DOI :
10.1109/ITEC-AP.2014.6941252