科技报告详细信息
A Comparative Study on Computation of Cumulative Distribution Function in Predicting Time of Failure of Engineering Systems
Sierra, Gina ; Daigle, Matthew ; Goebel, Kai
关键词: FAILURE ANALYSIS;    SYSTEMS HEALTH MONITORING;    TIME DEPENDENCE;    COMPUTATION;    HAZARDS;    DISTRIBUTION FUNCTIONS;    PREDICTIONS;    PROBABILITY THEORY;    SAFETY;   
RP-ID  :  ARC-E-DAA-TN68615
学科分类:航空航天科学
美国|英语
来源: NASA Technical Reports Server
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【 摘 要 】
Estimating accurate Time-of-Failure (ToF) of a system is key in making the decisions that impact operational safety and optimize cost. In this context, it is interesting to note that different approaches have been explored to tackle the problem of estimating ToF. The difference is in part characterized by different definitions of the hazard zones. The conventional definition for the cumulative distribution function (CDF) calculation is assumed to have well-defined hazard zones, that is, hazard zones defined as a function of the system state trajectory. An alternate method suggests the use of hazard zones defined as a function of the system state at time , instead of hazard zones defined as a function of system state up to and including time k (Acuna and Orchard 2018, 2017). This paper explores these differences and their impact on ToF estimation. Results for the conventional CDF definition indicated that, (i) the cumulative distribution function is always an increasing function of time, even when realizations of the degradation process are not monotonic, (ii) the sum of all probabilities is always 1 and does not need to be normalized, and (iii) all probabilities are positive and less than or equal to 1. Similar results are not observed for CDF calculation with hazard zones defined as a function only of the system state at time . Results for ToF estimation using Acuna's definition differ, suggesting that there is an underlying assumption of independence in the hazard zone definition. Therefore, we present an alternate definition of hazard zone which guarantees the properties of a well-defined CDF with a more straightforward ToF definition.
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