中国安全科学学报 ›› 2021, Vol. 31 ›› Issue (9): 21-28.doi: 10.16265/j.cnki.issn1003-3033.2021.09.004

• 安全社会科学与安全管理 • 上一篇    下一篇

企业安全生产关键指标体系与风险评价模型*

阎红巧1 工程师, 陈怡玥2, 田琨1 工程师, 胡瑾秋**2 教授, 冒亚明1 高级工程师, 周靖桐2   

  1. 1 中国石油集团安全环保技术研究院有限公司 HSE信息中心,北京 102200;
    2 中国石油大学(北京) 安全与海洋工程学院,北京 102249
  • 收稿日期:2021-06-24 修回日期:2021-08-14 出版日期:2021-09-28
  • 作者简介:阎红巧 (1988—),女,山东济南人,硕士,工程师,主要从事油气行业生产运行安全预警技术研究及大数据技术应用研究。E-mail: yanhongqiao@cnpc.com.cn。
  • 基金资助:
    国家自然科学基金资助(52074323)。

Research on key index system and risk evaluation model of enterprise work safety

YAN Hongqiao1, CHEN Yiyue2, TIAN Kun1, HU Jinqiu2, MAO Yaming1, ZHOU Jingtong2   

  1. 1 HSE Information Center, CNPC Safety and Environmental Technology Research Institute Co., Ltd., Beijing 102200, China;
    2 College of Safety and Ocean Engineering, China University of Petroleum (Beijing), Beijing 102249, China
  • Received:2021-06-24 Revised:2021-08-14 Published:2021-09-28

摘要: 为对企业安全生产现状进行全面、实时的客观评价,避免传统风险评价方法中人工干预造成的偏差,首先,根据事故致因理论提出了屏障-损失层次化关键指标体系,通过挖掘事故事件等结构化数据以及检查文本等非结构化数据实现指标量化;然后,结合主成分分析法(PCA)和熵权法 (EW)进行数据降维与风险评价,采用指数平滑方法预测企业下一周期的风险水平,进而建立企业安全生产风险评价模型;最后,将该模型应用于2个油气生产企业。结果表明:该风险评价模型可以通过获取、处理与学习屏障-损失历史数据,实现对当前企业的风险评价以及未来周期的风险预测,并为企业安全管理方向提供指导(消减防护、消除防护以及化学品类危险源屏障等)。

关键词: 企业安全生产, 关键指标体系, 风险评价, 文本匹配, 主成分分析法(PCA), 熵权法 (EW)

Abstract: In order to perform a comprehensive and real-time objective evaluation of the status quo of enterprise work safety and to avoid deviation caused by manual intervention in traditional risk evaluation methods, firstly, a barrier-consequence hierarchical key indicator system was proposed according to accident cause theory, and indicators were quantified through mining structured data such as accidents and unstructured data such as checking text. Then, PCA and EW were adopted for data dimensionality reduction and risk evaluation, and exponential smoothing method was used to predict risk level of enterprises in the next cycle before an risk evaluation and early warning model was established. Finally, the model was applied to two oil and gas production enterprises. The results show that this risk evaluation model can accomplish assessment of current risks and prediction of risks in future cycles through acquisition, processing and learning of barrier-consequence historical data, and provide guidance for enterprises' safety management (risk reduction, risk elimination, and that of chemical hazard barriers, etc.).

Key words: enterprise word safety, key index system, risk evaluation, text matching, principal component analysis (PCA), entropy weight method (EW)

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