智能识别导致因素,构建起重机运行事故链
Jinlong Zhao1, Huaying Cui2, Zhenqi Hu3
1School of Emergency Management & Safety Engineering, University of Mining & Technology (Beijing), Beijing, 100083, China. 15210567787@163.com.
Scientific reports
|December 26, 2025
概括
本研究使用文本挖掘和网络分析确定了起重机事故的关键因素. "交叉并行操作"和"安全管理不足"至关重要,为建设中的目标安全改进提供了信息.
科学领域:
- 建筑工程安全 建筑工程安全
- 事故分析 事故分析
- 风险管理 风险管理
背景情况:
- 起重机在建筑中的使用越来越多,导致事故发生的频率越来越高.
- 鉴定关键的致病因素和事故链是具有挑战性的,因为大型数据集.
- 现有的方法很难有效地分析复杂的起重机事故数据.
研究的目的:
- 开发一种智能方法来确定起重机操作中的关键因素和事故链.
- 提高对起重机事故因果关系的理解,以改善安全管理.
- 为防止未来的起重机相关事故提供数据驱动的方法.
主要方法:
- 文本挖掘被用来识别203起重机事故 (2011-2022) 的致病因素.
- 使用术语频率-反向文档频率 (TF-IDF) 创建了一个指标系统.
- 复杂的网络分析和集成的解释性结构建模 (ISM) 被用来建立事故链.
主要成果:
- 确定的主要致病因素包括"交叉并行操作"和"安全管理不足".
- 通过复杂的网络分析,确定了影响起重机运行的关键因素.
- 解释性结构建模 (ISM) 成功建立了起重机事故链,通过案例研究验证.
结论:
- 开发的智能方法有效地识别了起重机操作中的关键因素和事故链.
- "交叉并行操作"和"安全管理不足"是起重机事故的重要原因.
- 这项研究为有针对性的安全管理提供了宝贵的见解,并提高了建筑业的起重机运行整体安全性.
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