| Solar and wind power and other new energy applied in small vessels are more and more commonly used.Especially on the condition of sustainable development of tourism in recent years,people put efforts to develop and strengthen the resort facilities,scenic lakes and river etc.In order to protect water resource and improve traveling quality,the sightseeing ships which equipped with a solar powered energy are more and more commonly used.However,due to the lack of technical experience and complicated technique,the limited numbers of staffs on board often have a problem in the ship fault monitoring,diagnosis and maintenance and so on,which leads to difficulties in finding the problems in actual use,or it’s difficult for them to find out the fault sources and give timely maintenance.It’s impractical to arrange a specialist responsible for troubleshooting and repair.So for solving this problem,considering on the aspect of ship reliability,maintainability and economy,the establishment of appropriate fault diagnosis system on the sightseeing ships can be effectively solve this problem.Firstly,considering of the development and research of fault diagnosis technology both at home and abroad,we make a comparison of the characteristics of the current common diagnostic methods.Regarding the fault diagnosis of power lithium batteries of solar ship as the research object,combining characteristics of lithium batteries,we analyze failure modes and performance characteristics of the power lithium batteries of the ship which aim to propose a method to do fault diagnosis based on fuzzy neural network theory.Secondly,we do research on the fault diagnosis model of the lithium batteries.We establish the model adaptive neural network fault diagnosis fuzzy model with the help of MATLAB tools,and do the model training through the sample data,and finally use testing data to verify the accuracy of fault diagnosis model.Then,according to the study and use of the environment,this paper proposes a fault diagnosis system design of power lithium battery of solar ship,and it also uses Delphi and SQL Server software,which targeted in completing the software interface design of the fault diagnosis system,relevant development capabilities and the establishment of a database of the lithium batteries fault diagnosis system.Finally,experiment the testing results of the solar ship lithium batteries fault diagnosis system,and test the correctness of the proposed model once again through the diagnostics oflithium batteries of real ship in proving that the solar ship lithium batteries fault diagnosis which based on fuzzy neural network fault diagnostic methods is an effective diagnostic method and it also proves the fault diagnosis system can diagnose the fault efficiently.It has some reference value for a solar ship fault diagnosis of lithium batteries. |
