煤炭工程 ›› 2025, Vol. 57 ›› Issue (10): 172-178.doi: 10. 11799/ ce202510021

• 研究探讨 • 上一篇    下一篇

基于大模型的综采运维知识图谱云平台建设研究

冯银辉,王咏涛,王博超,西成峰,范成伟   

  1. 1. 北京天玛智控科技股份有限公司,北京 101399

    2. 煤炭无人化开采数智技术全国重点实验室,北京 101320

  • 收稿日期:2024-10-23 修回日期:2025-03-20 出版日期:2025-10-10 发布日期:2025-11-12
  • 通讯作者: 王咏涛 E-mail:peter_y_wang3@163.com

Research and Construction of a Knowledge Graph Cloud Platform for Comprehensive Mining Operations and Maintenance Based on Large Models

  • Received:2024-10-23 Revised:2025-03-20 Online:2025-10-10 Published:2025-11-12

摘要:

为解决煤炭行业缺乏高效实时大数据支撑和AI基础平台导致综采设备故障率高、维护滞后的问题,构建了一个集云原生、边缘计算、大数据与人工智能于一体的工业互联网远程运维平台。平台采用灵活、模块化、高可用的架构,支持多源数据接入与智能分析,重点引入图谱大模型与文档大模型技术,结合BERT-BiLSTM-CRF模型实现知识抽取与知识图谱构建,显著提升了语义理解与知识推理的准确性。基于此构建的AI智能问答系统实现了知识驱动的交互式诊断与决策支持。平台在多个煤矿现场应用后,维护效率明显提升、成本显著下降,为煤炭行业智能化与无人化采煤提供了重要技术支撑。

关键词: 云原生 , 综采工作面 , AR交互式专家系统 , LLM(大语言模型) , 知识图谱

Abstract:

The intelligent mining sector suffers from a lack of big data support, and the application of foundational AI platforms and algorithms is limited. The main reason is the absence of an industrial internet architecture cloud platform tailored for the coal industry, which restricts resource integration. This leads to high failure rates of equipment on comprehensive mining workfaces, along with high maintenance and labor costs. By integrating cloud-native technology, edge computing, big data platforms, and artificial intelligence platforms, a flexible, modular industrial internet architecture remote maintenance platform has been developed to meet these challenges. The platform employs graph and document large model technologies and uses the Bert-BiLSTM-CRF model for knowledge extraction and knowledge graph construction, significantly improving the accuracy of knowledge extraction. The successful development of the platform has narrowed the gap with other energy sectors' industrial internet applications and laid a foundation for the realization of intelligent and unmanned coal mining in the coal industry.

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