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电梯安全风险因素分析及预警研究 被引量:15

Factors Analysis and Early Warning of Elevator Safety Risk
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摘要 为提高城市化进程下电梯行业发展的速度,减少电梯安全事故发生的概率,降低电梯生产运营风险系数,研究电梯安全风险因素已成为一项重要任务。采用文献分析和经验资料凝练的方式,运用扎根理论开展电梯安全风险三阶段编码研究,确定了主要风险因素;通过构建结构方程模型,探讨了影响电梯安全的多重风险因素及其作用机理并进行实证分析;最后基于模糊评价法建立了电梯安全风险预警指标体系并对其进行评估。结果表明:与电梯安全风险有关的人员、环境、设备、管理、预警技术因素与电梯安全风险暴露之间呈显著性正相关,并间接影响风险预警的准确性,电梯安全风险预警指标体系的构建可为电梯生产制造、安全使用、管理维护和更新改造工作提供一定的安全管理启示。 In order to speed up the development of the elevator industry in the process of urbanization,reduce the frequency of elevator safety accidents,and reduce the risk coefficient of elevator production and operation,research on elevator safety risk factors has become an important task.First,using literature analysis and the empirical data condensed method,this paper uses the grounded theory to carry out elevator safety risk three-stage coding research to determine the main risk factors.Then,through the construction of a structural equation model,the paper explores the multiple risk factors affecting elevator safety and their mechanism and conducts empirical analysis.Finally,the paper establishes the elevator safety risk early warning index system based on the fuzzy evaluation method,and conducts the evaluation on elevator safety risk.The results show that there is a significantly positive correlation between the personnel,environment,equipment,management,early warning technical factors related to elevator safety risks and elevator safety risk exposure,which indirectly affects the accuracy of risk early warning,and the construction of elevator safety risk early warning index system can provide certain management enlightenment for elevator manufacturing,safe use,management and maintenance and renovation work.
作者 杜娅 谢科范 梁本部 冼蕾 DU Ya;XIE Kefan;LIANG Benbu;XIAN Lei(School of Management,Wuhan University of Technology,Wuhan 430070,China)
出处 《安全与环境工程》 CAS CSCD 北大核心 2021年第4期71-79,共9页 Safety and Environmental Engineering
关键词 电梯安全 风险因素 扎根理论 结构方程模型 风险预警 模糊评价 elevator safety risk factor grounded theory structural equation model risk early warning fuzzy evaluation
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