大数据分析下海洋通信网络故障识别方法  

Fault identification method of marine communication network based on big data analysis

作　　者：孟晓莉[1] 张娟[1] MENG Xiao-li;ZHANG Juan(Jiangsu Maritime Institute College of Information Engineering,Nanjing 211100,China)

机构地区：[1]江苏海事职业技术学院信息工程学院,江苏南京211100

出　　处：《舰船科学技术》2020年第4期115-117,共3页Ship Science and Technology

摘　　要：为了提高海洋通信网络故障识别效果,针对当前海洋通信网络故障识别成功率低、建模时间长等缺陷,提出大数据分析下的海洋通信网络故障识别方法。首先,分析海洋通信网络故障识别原理,指出当前各种海洋通信网络故障识别方法的弊端。然后,引入大数据分析技术对海洋通信网络故障识别进行建模,并对建模过程一些问题进行相应解决。最后,采用具体海洋通信网络故障数据对本文方法的性能进行验证。本文方法可以对大规模海洋通信网络故障进行短时间识别,识别正确率完全可以保证海洋通信网络正常通信要求,同时海洋通信网络故障识别综合性能要优于当前其它经典方法,对比结果表明了本文方法用于海洋通信网络故障识别的优越性。In order to improve the effect of fault identification of marine communication network,aiming at the defects of low success rate of fault identification and long modeling time of current marine communication network,a fault identification method of marine communication network based on big data analysis is proposed.Firstly,this paper analyzes the principle of fault identification of marine communication network,points out the disadvantages of various fault identification methods of marine communication network,then introduces big data analysis technology to model the fault identification of marine communication network,and solves some problems in the modeling process,and finally uses specific fault data of marine communication network to verify the performance of this method It can identify the fault of large-scale marine communication network in a short time,and the recognition accuracy can fully guarantee the normal communication requirements of marine communication network.At the same time,the comprehensive performance of fault recognition of marine communication network is better than other current classical methods.The comparison results show that the method in this paper is superior to the fault recognition of marine communication network.

关 键 词：海洋通信网络 大数据分析技术 故障识别 识别效率 性能测试 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]