Abstract
As a safety critical system, affected by cognitive uncertainty and flight environment variability, aircraft electrical power system proves highly uncertain in its failure occurrence and consequences. However, there are few studies on how to reduce the uncertainty in the system design stage, which is of great significance for shortening the development cycle and ensuring flight safety during the operation phrase. For this reason, based on the variance decomposition theory, this paper proposes an importance measure index of the influence of component failure rate uncertainty on the uncertainty of power supply reliability (system reliability). Furthermore, an algorithm to calculate the measure index is proposed by combining with the minimum path set and Monte Carlo simulation method. Finally, the proposed method is applied to a typical series-parallel system and an aircraft electrical power system, and a criteria named as “quantity and degree optimization criteria” is drawn from the case study. Results demonstrate that the proposed method indeed realizes the measurement of the contribution degree of component failure rate uncertainty to system reliability uncertainty, and combined with the criteria, proper solutions can be quickly determined to reduce system reliability uncertainty, which can be a theoretical guidance for aircraft electrical power system reliability design.
Highlights
The aircraft electrical power system (AEPS) is a system that provides electrical energy for equipment related to flight safety such as navigation, control, and communication
For a quantitative analysis on AEPS, Telford et al [13] analyzed the characteristics of fault tree, Markov chain, and Bayes’ theorem in the reliability assessment of AEPS, and proposed a system reliability design tool for AEPS based on these methods
This paper proposes to establish an importance measure index/indicator to measure the contribution of component failure rate uncertainty to system reliability uncertainty under a given system time, so that components with high contribution to system reliability uncertainty can be quickly locked based on the ranking of index
Summary
The aircraft electrical power system (AEPS) is a system that provides electrical energy for equipment related to flight safety such as navigation, control, and communication. Cao et al [33] and Qi et al [34] proposed the concept of the optimal probability distribution of the component failure rate based on cross entropy theory, and used the power supply system of a multi-electric aircraft as an example to apply this method to the uncertainty analysis of power supply reliability. There is little research on how to help designers effectively reduce such uncertain risks in the design stage For this reason, this paper proposes to establish an importance measure index/indicator to measure the contribution of component failure rate uncertainty to system reliability uncertainty under a given system time, so that components with high contribution to system reliability uncertainty can be quickly locked based on the ranking of index. Vars[Rs] is the unconditional variance of power supply reliability of the sink node s; Es,λ∼i (Rs|λi) is the conditional expected value of power supply reliability of the sink node s, and to be specific, it is on the condition that the failure rate of the i-th component is given; Vars,λi Es,λ∼i (Rs|λi) is the variance of Es,λ∼i (Rs|λi)
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