Study On Data Monitoring And Transmission Simulation System Of Shipboard Ship’s Engine Room

In recent years,the updating and development of computer,communication,network,big data,artificial intelligence and so on technology accelerates the development of ship intelligent and makes green,safety,high efficiency and unmanned intelligent ship implementation to be possible.Intelligent ship completes ship to shore’s convection mainly by ship and shore collected and integrated processing information between each other,and then achieves the ultimate goal of the sailing ship safety,economy and environmental protection.At present,our country’s development of intelligent ship still at the primary stage,the development of intelligent ship system needs strong technical supports,the intelligent system control and wireless communication technology is not enough to support the development of intelligent ship from individual to system integration technology.Based on the concept of "intelligent ship",this paper proposes a data monitoring and transmission simulation system for ship-shore bases on ship engine room,which bases on shore data communication and ship status monitoring system.Through the analysis of the architecture of B/S and C/S,the data management platform is developed based on the architecture of C/S,and the data and information interaction between ships and shore are realized by wireless network.In addition,design a shore-based ship power equipment fault diagnosis system based on B/S architecture,which embed in the Webaccess configuration software,realizes sharing dynamic monitoring interface in LAN;the improved G(1,1)grey model and expert diagnosis model based on fuzzy neural network are applied to the system of fault diagnosis criterion,realizes the high accuracy of ship power equipment health forecast,provides a good solution for the development of "smart ship".Base on ship power equipment fault diagnosis system,the expert diagnosis model based on fuzzy neural network is applied to B/S structure of shore-based ship power equipment fault diagnosis system,and use the BP algorithm training examples verify the accuracy of the model.The results show that the system is stable and reliable,and the fault diagnosis accuracy is high enough.Base on ship power equipment fault prediction method,in order to improve the predictive accuracy,for the purpose of improved grey model based on the general G(1,1)grey model of correlation analysis,to modify its structure parameters,build the improved based on the metabolism of G(1,1)dynamic prediction model.In addition,uses part of the thermal parameters of diesel engine to establish a prediction model,and make analysis of the each model’s accuracy,the results show that ultimately improved the metabolism of G(1,1)forecasting model is more general G(1,1)grey model has higher accuracy,meet the application requirements.