舰船推进系统集成管理知识挖掘方法研究

发布时间：2018-05-27 01:19

本文选题：集成管理 + 推进系统　；参考：《舰船科学技术》2016年23期

【摘要】：针对舰船推进系统集成管理中的实船训练仿真建模与机械设备状态评估等高级应用对知识的需求,研究知识管理中所需要的知识内容与形式,探索数据挖掘方法在大数据知识获取中的应用模式。以某型推进装置为对象,研究使用数据挖掘技术获取所需集成管理知识的途径,包括聚类算法在推进系统稳态工况基准模式识别中的应用,以及关联算法在状态特征模式识别中的应用等。本文研究为实现基于知识的舰船推进系统集成管理提供了研究基础。
[Abstract]:Aiming at the requirement of knowledge in advanced applications such as ship training simulation modeling and mechanical equipment condition evaluation in integrated management of ship propulsion system, the knowledge content and form needed in knowledge management are studied. This paper explores the application pattern of data mining method in big data knowledge acquisition. Taking a certain propulsion device as an object, this paper studies the way to acquire the required integrated management knowledge by using data mining technology, including the application of clustering algorithm in the steady condition benchmark pattern recognition of propulsion system. And the application of association algorithm in state feature pattern recognition. This paper provides a research foundation for the integrated management of ship propulsion system based on knowledge.
【作者单位】：海军北海舰队装备部;青岛92001部队司令部;海军工程大学动力工程学院;
【基金】：中国博士后科学基金资助项目(201150M1547) 湖北省自然科学基金资助项目(2013CFB440)
【分类号】：U664.3;TP311.13

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