基于文本挖掘的叉车事故致因因素分析
刘宇 1邓代军 1李军1
作者信息
- 1. 湖北特种设备检验检测研究院宜昌分院 宜昌 443005
- 折叠
摘要
为了更加科学地分析叉车事故致因因素的相互关系,揭示叉车事故的演变机理,有效预防叉车事故发生.文中以近 5a官方通报的 118 起叉车事故报告为依据,提取了人员、设备、环境、管理 4 个方面的 16 项事故致因因素,并应用Apriori算法挖掘叉车事故致因的关联规则;然后基于共现矩阵构建事故致因网络图,通过度中心性、紧密中心性、介数中心性分析,明确了叉车事故的关键致因项.结果表明:违章作业、安全意识淡薄、安全隐患排查不到位、安全管理制度缺失、安全教育培训不到位是叉车事故关键致因因素.
Abstract
To more scientifically analyze the relationship between the causative factors of forklift accidents,reveal the evolution mechanism of accidents and effectively prevent accidents,based on 118 forklift accident reports officially notified in recent five years,16 accident-causing factors from four aspects,namely personnel,equipment,environment and management,were extracted,and the association rules among causative factors were mined by Apriori algorithm.Then,based on the co-occurrence matrix,the causative factor network diagram was drawn,and the key causative factors of forklift accidents were determined through the analysis on degree centrality,tight centrality and betweenness centrality.The results show that operation against rules,lack of safety awareness,inadequate investigation of potential safety hazards,lack of safety management system and inadequate safety education and training are the key factors leading to forklift accidents.
关键词
叉车事故/事故致因/文本挖掘/关联规则/Apriori算法Key words
forklift accident/causative factor of accident/text mining/Association rules/Apriori algorithm引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据