面向船舶电力系统故障诊断的数据仓库与数据挖掘技术  

Data Warehouse and Data Mining Technology for Fault Diagnosis of Ship Power System

作　　者：陈鸣妤 CHEN Mingyu(Warship Automatic System Division,Shanghai Ship and Shipping Research Institute Co.,Ltd.,Shanghai 200135,China)

机构地区：[1]上海船舶运输科学研究所有限公司舰船自动化系统事业部,上海200135

出　　处：《上海船舶运输科学研究所学报》2022年第3期44-50,62,共8页Journal of Shanghai Ship and Shipping Research Institute

摘　　要：为适应大型船舶电力系统的数字化和信息化发展需求,建立一个以数据仓库技术为基础,以数据挖掘技术为手段的故障诊断决策系统,实现对船舶电力系统故障的分析和预测。融合数据仓库技术和数据挖掘技术,设计船舶电力系统故障信息数据仓库系统架构,并对数据挖掘技术的主要应用方法和数据挖掘算法的性能进行分析,在此基础上提出基于Prism算法的电力监控信息数据挖掘方法,并通过仿真试验验证该方法的有效性。试验结果表明,该方法能为船舶电力系统故障诊断提供辅助决策,进而合理安排检修计划,提高船舶电力系统的安全性和稳定性。With the continuous expansion of the power system of modern large ships,the fault information and data system will accumulate massive digital information in the long operation process.The fault diagnosis and decision-making system based on data warehouse technology and data mining technology can be established.This paper briefly introduces the data warehouse technology and data mining technology,designs the system architecture of the ship power system fault information data warehouse,and studies the main methods of the data mining used in the system architecture and the evaluation of the mining algorithms based on prism.

关 键 词：船舶电力系统 故障诊断 数据仓库 挖掘算法评估 

分 类 号：U672[交通运输工程—船舶及航道工程] TP311.13[交通运输工程—船舶与海洋工程]