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基于文本挖掘的电力行业触电人身伤亡事故致因分析研究

栗婧 叶栩辛 张毓珈 艾旭婷 敦煜煊

矿业科学学报2026,Vol.11Issue(1):194-205,12.
矿业科学学报2026,Vol.11Issue(1):194-205,12.DOI:10.19606/j.cnki.jmst.2025069

基于文本挖掘的电力行业触电人身伤亡事故致因分析研究

Research on the cause analysis of electric shock personal injury and death accidents in electric power industry based on text mining

栗婧 1叶栩辛 1张毓珈 2艾旭婷 1敦煜煊1

作者信息

  • 1. 中国矿业大学(北京)应急管理与安全工程学院,北京 100083
  • 2. 中国电力工程顾问集团东北电力设计院有限公司,吉林 长春 130000
  • 折叠

摘要

Abstract

Electric shock accident is the most common type of accident in the construction process of the power industry except for high fall.Identifying the influencing factors leading to electric shock acci-dents is the premise of taking targeted safety management measures.Based on text mining technology and R language,word segmentation and word frequency analysis were carried out on 80 reports of elec-tric shock casualties in power industry construction.By constructing social network and semantic net-work analysis diagrams and conducting centrality analysis,58 influencing factors were divided into four levels:key factors,important factors,secondary factors and general factors.The extracted factors were sentenced according to the related conjunctions,and the influencing factors with similar main contents were merged and summarized or deleted,so as to obtain the electric shock accident cause factor library in power industry.By combining the cause factor database of electric shock accidents with the results of centrality analysis,the most critical factors of electric shock accidents are obtained,which are unautho-rised work(A3),inadequate or unimplemented occupational safety and health responsibility(D1)and defective protective devices and facilities(B1),should be highly valued and focused on control.

关键词

触电事故/影响因素/文本挖掘/共现分析/语义网络分析

Key words

electric shock accident/influencing factors/text mining/co-occurrence analysis/semantic web analytics

分类

信息技术与安全科学

引用本文复制引用

栗婧,叶栩辛,张毓珈,艾旭婷,敦煜煊..基于文本挖掘的电力行业触电人身伤亡事故致因分析研究[J].矿业科学学报,2026,11(1):194-205,12.

基金项目

应急管理部重点科技计划(2024EMST121202) (2024EMST121202)

国家重点研发计划(2024YFC3306900) (2024YFC3306900)

矿业科学学报

2096-2193

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