中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (8): 15-23.doi: 10.16265/j.cnki.issn1003-3033.2023.08.1948

• 安全社会科学与安全管理 • 上一篇    下一篇

强降雨导致的建设工程安全事故人因分析HC-GC模型

陈伟1(), 田仪帅1,**(), 曾卫华2, 郭道远2, 赵卓雅1   

  1. 1 武汉理工大学 土木工与建筑学院,湖北 武汉 430070
    2 中国市政工程中南设计研究总院有限公司,湖北 武汉 430014
  • 收稿日期:2023-03-11 修回日期:2023-06-14 出版日期:2023-10-08
  • 通讯作者:
    **田仪帅(1999—),男,湖北武汉人,硕士研究生,研究方向为工程项目管理。E-mail:
  • 作者简介:

    陈 伟 (1970—),男,湖北武汉人,博士,教授,博士生导师,主要从事工程项目管理方面的研究。E-mail:

  • 基金资助:
    武汉理工大学校级科研项目(20221h0128)

HC-GC human factors analysis model for construction engineering safety accidents caused by heavy rainfall

CHEN Wei1(), TIAN Yishuai1,**(), ZENG Weihua2, GUO Daoyuan2, ZHAO Zhuoya1   

  1. 1 School of Civil Engineering and Architecture,Wuhan University of Technology, Wuhan Hubei 430070, China
    2 Central & Southern China Municipal Engineering Design and Research Institute Co., Ltd.,Wuhan Hubei 430014, China
  • Received:2023-03-11 Revised:2023-06-14 Published:2023-10-08

摘要:

为降低强降雨导致建设工程安全事故发生率,有效解决该类安全事故人因分析复杂问题,提出新的安全事故人因分析模型方法。基于人为因素分析与分类系统(HFACS),建立包括 6层 24个因素的建设工程强降雨事故(CPHRA)框架模型(HC);联用遗传算法(GA)优化连续关联规则挖掘算法(CARMA)(GC)分析人为致因关联,绘制事故人为致因链;选取150起强降雨导致建设工程事故典型案例进行模型验证与应用分析。结果表明:优化后的人因分析HC-GC模型具有更优的性能与效率;在事故人因链中,政府安全主管部门监督不足与企业安全文化缺失是深层次因素,现场违规监管与现场安全管理漏洞是主要连接因素,技能水平低与失误违章会进一步强化事故负反馈,事故上报与响应不及时是强降雨导致建设工程事故扩大蔓延最直接原因。

关键词: 强降雨, 建设工程安全事故, 建设工程强降雨事故(CPHRA)下人为因素分析与分类系统(HFACS)(HC), 遗传算法(GA) 优化的连续关联规则挖掘算法(CARMA)(GC), 人为致因

Abstract:

In order to reduce the incidence of construction engineering safety accidents caused by heavy rainfall and effectively solve the complex problem of the human factor analysis of such safety accidents, an optimization method of human factor analysis model was proposed. Based on HFACS, an HFACS-CPHRA, including 6 layers and 24 factors, was established. Then GA-CARMA were jointly used to analyze the association of human causes, and draw the chain of human causes of accidents. 150 typical cases of construction accidents caused by heavy rainfall were selected for model verification and application analysis. The results show that the optimized HC-GC model has better performance and efficiency. In the accident human causation chain, the insufficient government department in charge of safety supervision and lack of enterprise safety culture are the deep factor. Site in violation of regulation and security management loophole are the main connection factor, low level of skills and illegal will further strengthen the accident emergency disposition of negative feedback, untimely incident reporting and response is the most direct reason for the expansion and spread of construction engineering accidents caused by heavy rainfall.

Key words: heavy rainfall, construction safety accidents, human factors analysis and classification system(HFACS) under construction project heavy rainfall accident(CPHRA) (HC), genetic algorithm(GA) optimized continuous association rule mining algorithm(CARMA) (GC), human causation