中国安全科学学报 ›› 2019, Vol. 29 ›› Issue (10): 160-166.doi: 10.16265/j.cnki.issn1003-3033.2019.10.025

• 公共安全 • 上一篇    下一篇

基于偏态分布的飞行品质风险度量方法

赵新斌1,2,3 助理研究员, 王岩**4 助理研究员   

  1. 1 中国民航科学技术研究院 航空安全研究所,北京 100028;
    2 北京市民航安全分析及预防工程技术研究中心,北京 100028;
    3 华东师范大学 统计学院,上海 200062;
    4 北京金融衍生品研究院 研究部,北京 100033
  • 收稿日期:2019-07-16 修回日期:2019-09-06 出版日期:2019-10-28 发布日期:2020-10-27
  • 通讯作者: ** 王 岩(1987—),女,北京人,学士,助理研究员,主要从事统计分析方面的研究。E-mail:wangyan@cffex.com.cn。
  • 作者简介:赵新斌 (1986—),男,山东青岛人,博士,助理研究员,主要从事航空安全、风险管理、统计分析方面的研究。E-mail: zhaoxb@mail.castc.org.cn。
  • 基金资助:
    国家自然科学基金民航联合基金资助(U1633117)。

Risk measurement method of flight operational quality based on skewed distribution

ZHAO Xinbin1,2,3, WANG Yan4   

  1. 1 Aviation Safety Institute, China Academy of Civil Aviation Science and Technology, Beijing 100028, China;
    2 Engineering and Technical Research Center of Civil Aviation Safety Analysis and Prevention of Beijing, Beijing 100028, China;
    3 School of Statistics, East China Normal University, Shanghai 200062, China;
    4 Research Department, CFFEX Institute for Financial Derivatives, Beijing 100033, China
  • Received:2019-07-16 Revised:2019-09-06 Online:2019-10-28 Published:2020-10-27

摘要: 为防控飞行风险,利用安全风险矩阵的构建思想和概率论知识,研究飞行品质风险的量化分析方法。通过对满足偏态性的数据进行正态性转换,由正态分布的概率密度函数得到事件发生的概率和事件严重度;基于“风险为概率与严重度乘积”的思想,提出飞行品质风险度量方法;从轻、中、重、综合等4个不同角度度量飞行品质风险,并运用快速存取记录(QAR)数据对方法进行分析论证。研究表明:该方法可整合事件发生的概率和事件的严重度,能够度量4类飞行品质风险,所得结果可用于指导风险的差异化管理。

关键词: 航空安全, 偏态分布, 飞行品质监控(FOQA), 风险度量, 快速存取记录(QAR)数据

Abstract: In order to prevent and control flight risks, construction of safety risk matrix and probability theory are used to study quantitative analysis method of flight operational quality risks. Firstly, probability and severity of events were obtained based on probability density function of normal distribution after normalizing skewed data. Then, a risk measurement method for flight operational quality was put forward based on the idea that “risk is a product of probability and severity”. Finally, flight risks were measured from four different perspectives: light, medium, heavy and comprehensive, and QAR data were used to analyze and verify the method. The research shows that the proposed method can integrate probability and severity of events and measure four types of flight risks. Results obtained from it can be used to guide differential management of risks.

Key words: aviation safety, skewed distribution, flight operational quality assurance (FOQA), risk measurement, quick access recorder (QAR) data

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