以保障船舶通信系统联络通畅为目的，提出基于大数据挖掘的船舶通信系统关键设备状态分析方法。该方法使用北向接口和通信关键设备直连相结合方式，采集船舶通信系统关键设备运行信息后，利用大数据挖掘技术中的自组织映射神经网络，挖掘船舶通信系统关键设备状态信息随时间变化规律，得到时间变化序列。以关键设备状态信息时间变化序列为基础，使用大数据挖掘技术中区间集聚类分析方法，经过划分关键设备状态信息时间变化序列区间集、计算区间集子序列相似度和子序列异常值评分等步骤，分析得到船舶通信系统关键设备运行时的异常状态。实验结果表明：该方法采集船舶通信系统关键设备状态信息能力较好，可有效分析关键设备当前运行状态，应用效果较为显著。
In order to ensure the smooth communication of the ship communication system, the state analysis method of the key equipment of the ship communication system based on big data mining is studied. This method uses the combination of northbound interface and direct connection of key communication equipment to collect the operation information of the key equipment of the ship communication system, and uses the self-organizing mapping neural network in big data mining technology to mine the rule of the state information of the key equipment of the ship communication system changing with time to obtain the time change sequence, which is based on the time change sequence of the state information of the key equipment, Using the cluster analysis method of inter-area set in big data mining technology, the abnormal state of the key equipment of the ship communication system during operation is analyzed by dividing the interval set of the time change sequence of the key equipment status information, calculating the similarity of the interval set subsequence and scoring the outlier of the subsequence. The experimental results show that this method has a good ability to collect the status information of the key equipment of the ship communication system, and can effectively analyze the current operation status of the key equipment, the application effect is significant.
2023,45(5): 136-139 收稿日期：2022-11-10
DOI：10.3404/j.issn.1672-7649.2023.05.025
分类号：F127
基金项目：河南省重点研发与推广专项支持项目（202400410148）；河南省驻马店职业技术学院校级教改项目（2019YBJG01）
作者简介：杨青(1981-),女,讲师,主要从事物联网大数据技术研究
