基于知识图谱的盾构掘进机智能维修

Hao Qin, Jiong Jin
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引用次数: 2

摘要

盾构掘进机是深埋地下作业的大型工程设备,其维护对保证盾构掘进机的连续运行具有重要意义。然而,传统的由工程师进行定期维护需要耗费大量的人力和时间。在这种情况下,需要更智能的维护方法。为了填补这一空白,本文提出了一种基于知识图的智能维修方法,该方法对维修过程中产生的知识进行捕获和重用,从而智能地推荐维修任务的解决方案。该方法包括创建知识表示模型、构建知识图谱、开发协同知识管理系统并实施三个阶段。以某盾构掘进机为例,验证了该方法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Maintenance of Shield Tunelling Machine based on Knowledge Graph
Shield tunnelling machine is a giant engineering equipment working deep under the ground, whose maintenance is significant in ensuring the continually operation of the machine. However, the traditional regular maintenance by engineers takes long time and plenty of people. In this case, a more intelligent maintenance method is required. To fill this gap, this paper proposes an intelligent maintenance method based on knowledge graph, which captures and reuse the knowledge generated during maintenance process in order to intelligently recommend solutions for maintenance tasks. This method includes three stages, creating knowledge representation model, building knowledge graph, developing collaborative knowledge management system for implementation. A case study on a specific shield tunnelling machine is demonstrated in this paper, with results showing the feasibility and effectiveness of this method.
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