基于FBN的高校实验室不安全行为风险评估*

doi:10.16265/j.cnki.issn1003-3033.2021.05.024

中国安全科学学报 ›› 2021, Vol. 31 ›› Issue (5): 160-167.doi: 10.16265/j.cnki.issn1003-3033.2021.05.024

• 安全社会科学与安全管理 • 上一篇下一篇

基于FBN的高校实验室不安全行为风险评估^*

安宇研究员, 李子琪^**, 王袆, 郭子萌, 张姜博南

中国矿业大学北京应急管理与安全工程学院,北京 100083

收稿日期:2021-02-03 修回日期:2021-04-11 出版日期:2021-05-28
作者简介:安宇 (1976—),男,黑龙江海伦人,博士,研究员,硕士生导师,主要从事校园安全管理、行为安全等方面的研究。E-mail:anyu@curntb.edu.cn。
基金资助:
国家自然科学基金资助(52074302);教育部第二批新工科研究与实践项目(E-AQGABQ20202706);中国高等教育学会“实验室管理研究”专项课题(2020SYD02)。

Risk assessment on unsafe behaviors of university laboratories based on FBN

AN Yu, LI Ziqi, WANG Hui, GUO Zimeng, ZHANG Jiangbonan

School of Emergency Management & Safety Engineering, China University of Mining & Technology-Beijing, Beijing 100083, China

Received:2021-02-03 Revised:2021-04-11 Published:2021-05-28

摘要/Abstract

摘要： 为有效减少高校实验室不安全行为,首先,利用人因分析和分类系统(HFACS)模型、贝叶斯网络法、专家评估法以及三角模糊数估算概率法,构建高校实验室不安全行为的模糊贝叶斯网络(FBN)模型;然后,应用模型推理分析,确定高校实验室不安全行为主要影响因素。结果表明:高校实验室不安全行为包括外部影响、组织影响、不安全监管、不安全行为的前提条件和不安全行为 5个层级,共24个风险因素,由此导致不安全行为的不可接受概率高达86%;在24个风险因素中,组织氛围不佳的灵敏度值为24.1%,对不安全行为的影响最大;导致不安全行为发生的最根本因素是立法不完善,进而传递到不可接受的外部因素和不安全监督,形成最可能致因链。

关键词: 模糊贝叶斯网络(FBN), 高校实验室, 不安全行为, 风险评估, 人因分析和分类系统(HFACS)模型

Abstract: In order to effectively reduce unsafe behavior in university laboratory. Firstly, FBN model of unsafe behaviors in university laboratories was constructed by using HFACS model, Bayesian network method, expert assessment and triangular fuzzy number probability estimation methods. Then, main influencing factors of unsafe behavior in university laboratory were determined by model reasoning analysis. The results show that there are many risk factors for unsafe behaviors in university laboratories, including 24 risk factors at five levels: external influence, organizational influence, unsafe supervision, preconditions for unsafe behaviors and unsafe behaviors. As a result, unacceptable probability of unsafe behavior is as high as 86 percent. Among 24 risk factors, sensitivity value of poor organizational climate is 24.1%, which has the greatest impact on unsafe behavior. The most fundamental factor leading to unsafe behavior is inadequate legislation, which in turn passes to unacceptable external factors and unsafe supervision, forming the most likely causal chain.

Key words: fuzzy Bayesian network (FBN), university laboratory, unsafe behavior, risk assessment, human factors analysis and classification system (HFACS) model

中图分类号:

X913.4

安宇, 李子琪, 王袆, 郭子萌, 张姜博南. 基于FBN的高校实验室不安全行为风险评估^*[J]. 中国安全科学学报, 2021, 31(5): 160-167.

AN Yu, LI Ziqi, WANG Hui, GUO Zimeng, ZHANG Jiangbonan. Risk assessment on unsafe behaviors of university laboratories based on FBN[J]. China Safety Science Journal, 2021, 31(5): 160-167.

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基于FBN的高校实验室不安全行为风险评估^*

Risk assessment on unsafe behaviors of university laboratories based on FBN

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