摘要
综合利用Hadoop的分布式计算、负载均载均衡能力好、易于扩展、适合海量数据存储等特点,开展大数据环境下船舶轴承状态监测系统研究。通过分析监测系统的技术需求,提出船舶轴承健康状态监测系统总体框架;从功能设计、业务流程等方面进行系统设计。在此基础上,研制了船舶轴承健康状态监测系统,并开展案例验证。研究结果表明,提出的船舶轴承健康状态监测系统适用于大数据环境下的海量监测数据分布式存储和分析。
The comprehensive utilization of Hadoop’s distributed computing,load equalization and easy to expand,and it is suitable for mass data storage.Research on the ship bearing condition monitoring system in the big data environment was carried out.By analyzing the technical requirements of the monitoring system,the overall framework of the ship bearing health monitoring system was proposed.Then,the system design was carried out from the aspects of functional design and business process.On this basis,the ship bearing health status monitoring system was developed and case verification was carried out.The research results show that the proposed ship bearing condition monitoring system is suitable for distributed storage and analysis of massive monitoring data in big data environment.
作者
吴军
陈作懿
严喆
王吉
胡奎
WU Jun;CHEN Zuoyi;YAN Zhe;WANG Ji;HU Kui(School of Naval Architecture&Ocean Engineering(Huazhong University of Science and Technology,Wuhan 430074,China)
出处
《兵器装备工程学报》
CAS
北大核心
2020年第1期140-144,共5页
Journal of Ordnance Equipment Engineering
基金
国家自然科学基金项目(51875225)
国家重点研发计划项目(2018YFB1702302)
甲板机械质量品牌专项经费项目.
