无人系统故障知识图谱的构建方法及应用

Construction and Application of Unmanned System Fault Knowledge Graph

摘要:

无人系统产生的海量数据存储分散且缺乏联系,信息共享困难,难以满足复杂度和集成度越来越高的无人系统的维修保障需求。知识图谱技术能够将复杂数据信息抽取成结构化知识,建立数据间的联系,增强知识间的语义信息。本文以无人系统的故障数据为研究对象,利用知识图谱技术进行知识抽取、知识融合以及知识加工,形成一系列相互关联的知识,为构建无人系统领域故障知识图谱提供一种可行的方法。知识图谱技术利用无人系统各种传感器集成的海量数据建立的知识库,可有效整合无人系统领域分散的数据,以此提高无人系统领域知识的利用率,帮助维修保障人员快速精确查找故障知识,对无人系统的维修保障具有重要的军事应用前景。

Abstract:

The massive data generated by unmanned systems is scattered and lacks in connection, and information sharing is difficult. It is difficult to meet the maintenance support requirements of unmanned systems with increasing complexity and integration. Knowledge graph technology can extract complex data information into structured knowledge, establish connections between data, and enhance semantic information between knowledge. This paper takes the fault data as the research object, and uses knowledge graph technology to accomplish knowledge extraction, knowledge fusion and knowledge processing, and form a series of interrelated knowledge, which provides a feasible way to construct fault knowledge graph in unmanned system domain. The knowledge graph technology uses massive data integrated by various sensors of the unmanned system to build a knowledge base, which can effectively integrate the scattered data in the unmanned system field, thereby improving the utilization rate of the knowledge of the unmanned system field, and helping maintenance support personnel to quickly and accurately find fault knowledge. It has important military application prospects for the maintenance and support of unmanned systems.