航空学报 > 2009, Vol. 30 Issue (9): 1683-1690

风险可能数——一种基于最大信息熵理论的风险度量和风险排序新方法

王贵宝1,2,黄洪钟1,张小玲1   

  1. 1电子科技大学 机械电子工程学院 2中国人民解放军驻三七二厂军事代表室
  • 收稿日期:2008-07-24 修回日期:2008-10-21 出版日期:2009-09-25 发布日期:2009-09-25
  • 通讯作者: 黄洪钟

Risk Possibility Number—A New Model for Risk Evaluation and Prioritization Based on Maximum Entropy Theory

Wang Guibao1,2, Huang Hongzhong1, Zhang Xiaoling1   

  1. 1.School of Mechatronic Engineering, University of Electronic Science and Technology of China 2.PLA Representative Office Stationed at Factory 372
  • Received:2008-07-24 Revised:2008-10-21 Online:2009-09-25 Published:2009-09-25
  • Contact: Huang Hongzhong

摘要: 分析了风险优先数(RPN)方法中严重性S、发生率O和探测度D这3个评价指标的离散性与得分主观性不足。基于信息熵定理和最大信息熵推论,指出了RPN方法在评价风险不确定程度时,存在函数方差的依赖性和未能均衡各种风险要素的不合理性。针对多维信息的不确定性问题,分析了如何合理选取风险评价指标和权重分配。为了实现对风险程度的一致性测量,基于公理化的假设条件,给出了一种区别于RPN的风险可能数(RPoN)的定义和计算方法,并证明了RPoN方法能够一致性地用于风险的不确定程度评价。实验数据结果表明:RPoN方法用于风险的定量计算以及进行风险排序的效果优于RPN方法。

关键词: 风险优先数, 信息理论, 多元控制系统, 熵, 测量, 风险可能数

Abstract: This article analyzes the deficiencies of discreteness and subjectivity of the current method of risk priority number (RPN) in dealing with the three key information factors of severity, occurrence and detection of failure. Based on information entropy theory and maximum entropy inference, it demonstrates that when being used to evaluate the degree of uncertainty of risks, the substantial irrationalities of the RPN method are its dependency on the mean and the variance of the RPN function so that it cannot integrate the risk factors in proper proportion. Meanwhile, considering the uncertainty of multi-dimensional information, the problem of how to select the indexes for risk evaluation and allocate their weights for forecasting risk events is analyzed. For the realization of measuring the degree of risks consistently, a new definition and calculation by the name of the risk possibility number(RPoN)is proposed, which is different from the RPN. The formulation of the RPoN is based on and deduced from the continuity, monotonicity, and additivity assumptions of axioms of information entropy theory. The property of consistency of the RPoN approach is also proved when it is used to evaluate the degree of risks in the process of statistical decision-making. Experimental results suggest that the RPoN approach is better than the RPN method on quantitative calculation and prioritization of risks.

Key words: risk priority number, information theory, multivariable control system, entropy, measurements, risk possibility number

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