摘要
针对传统的火力发电企业设备缺陷管理方法存在的诸多问题,如处理效率低、准确性差、历史经验及数据未得到有效利用等,本文提出一种基于知识图谱技术的系统化解决方案。通过构建一种基于知识图谱的设备全寿命周期管理系统,可以在设备缺陷闭环管理中,有效实现设备维修辅助决策,通过设备维修历史、缺陷记录的自动分析,为运维人员提供优化的检修策略。本文首先简介了背景及整体技术方案,接着对系统的整体设计架构和功能进行了阐述,然后对系统的实现进行了详细说明,最后总结并讨论了存在的问题及未来的优化方向。本文对国内火电企业建设类似系统具有一定的参考价值。
This paper proposes a systematic solution based on knowledge graph technology to address the many problems of traditional equipment defect management methods in thermal power enterprises,such as low processing efficiency,poor accuracy,and ineffective use of historical experience and data.By constructing a knowledge graph-based equipment full life cycle management system,it can effectively realize equipment maintenance auxiliary decision-making in equipment defect closed-loop management,provide optimized maintenance strategies for operation and maintenance personnel through automatic analysis of equipment maintenance history and defect records.This paper first introduces the background and overall technical scheme,then elaborates on the overall design architecture and functions of the system,followed by a detailed description of the system's implementation.Finally,it summarizes and discusses the existing problems and future optimization directions.This paper has certain reference value for the construction of similar systems in domestic thermal power enterprises.
作者
张诚
金峰
奚英涛
何文凯
ZHANG Cheng;JIN Feng;XI Yingtao;HE Wenkai(Shanghai Waigaoqiao No.3 Power Generation Co.,Ltd.,Shanghai 200137,China;Shenergy Co.,Ltd.,Shanghai 201103,China)
出处
《电力大数据》
2023年第12期54-61,共8页
Power Systems and Big Data
关键词
缺陷管理
知识图谱
维修决策
Defect management
knowledge graph
maintenance decision