华北水利水电大学学报（自然科学版）2026，Vol.47Issue(3)：112-122,140,12.DOI:10.19760/j.ncwu.zk.2026044
融合知识图谱与DeepSeek的抽蓄电站设备运维问答系统研究
Research on a Question-Answering System for Equipment Operation and Maintenance in Pumped Storage Power Stations Based on Integration of Knowledge Graph and DeepSeek
摘要
Abstract
[Objective]This study develops an intelligent question-answering system that integrates a large language model with a domain-specific knowledge graph to address challenges such as inefficient domain knowledge retrieval,weak decision support,and insufficient professional accuracy of large language models.This system provides operation and maintenance per-sonnel with real-time,precise,and scientifically standardized auxiliary decision support.[Methods]First,a knowledge graph applicable to the operation and maintenance of pumped storage power station equipment was constructed,enabling a systematic representation of equipment operation and maintenance knowledge for the power station.Second,a two-stage knowledge retrieval method was innovatively proposed,deeply integrating the knowledge graph with the DeepSeek large lan-guage model to design and implement the KG-DS QAS,a question-answering system for pumped storage power station equip-ment operation and maintenance.[Results](1)KG-DS QAS achieved precision,recall,and F1 scores of 0.85,0.87,and 0.86,respectively,on the BERTScore evaluation indicator,demonstrating outstanding stability and accuracy.(2)The aver-age score in the expert subjective evaluation was 4.65,and the overall performance significantly outperformed benchmark models(Model Q,Model D,Model L)of the same parameter scale(7B).(3)In timeliness verification,the system's aver-age processing time was 12 seconds,meeting the real-time requirements for on-site operation and maintenance.[Conclusions]KG-DS QAS achieves precise adaptation and application in the field of equipment operation and maintenance for pumped stor-age power stations,providing insights and demonstration for the application of knowledge graph technology and large language models in this domain.Future development can extend from equipment operation and maintenance to full-lifecycle manage-ment of power stations,covering planning,construction,and operation,to build a multidimensional and multimodal integrat-ed intelligent management system.关键词
抽水蓄能电站/设备运维/知识图谱/DeepSeek模型/问答系统Key words
pumped storage power station/equipment operation and maintenance/knowledge graph/DeepSeek model/ques-tion-answering system分类
建筑与水利引用本文复制引用
胡昊,张兴奎,崔争艳,张浩宇,许昭一..融合知识图谱与DeepSeek的抽蓄电站设备运维问答系统研究[J].华北水利水电大学学报（自然科学版）,2026,47(3):112-122,140,12.基金项目
国家自然科学基金项目(52079053) （52079053）
河南省重点研发专项(241111210300) （241111210300）
中央引导地方科技发展资金项目(Z20241471035) （Z20241471035）
河南省科技攻关项目(252102210061) （252102210061）
河南省自然科学基金项目(252300420056) （252300420056）
河南省高等教育研究项目(2025SXHLX084). （2025SXHLX084）
