首页> 外文会议>MICAI 2011;Mexican international conference on artificial intelligence >Estimating Probability of Failure of a Complex System Based on Inexact Information about Subsystems and Components, with Potential Applications to Aircraft Maintenance
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Estimating Probability of Failure of a Complex System Based on Inexact Information about Subsystems and Components, with Potential Applications to Aircraft Maintenance

机译:根据子系统和组件的不精确信息估算复杂系统的故障概率,并将其潜在地应用于飞机维修

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In many real-life applications (e.g., in aircraft maintenance), we need to estimate the probability of failure of a complex system (such as an aircraft as a whole or one of its subsystems). Complex systems are usually built with redundancy allowing them to withstand the failure of a small number of components. In this paper, we assume that we know the structure of the system, and, as a result, for each possible set of failed components, we can tell whether this set will lead to a system failure. For each component A, we know the probability P(A) of its failure with some uncertainty: e.g., we know the lower and upper bounds P_(A) and P(A) for this probability. Usually, it is assumed that failures of different components are independent events. Our objective is to use all this information to estimate the probability of failure of the entire the complex system. In this paper, we describe a new efficient method for such estimation based on Cauchy deviates.
机译:在许多实际应用中(例如,飞机维修中),我们需要估算复杂系统(例如飞机整体或其子系统之一)发生故障的可能性。复杂的系统通常以冗余构建,从而使其能够承受少量组件的故障。在本文中,我们假设我们知道系统的结构,因此,对于每组可能发生故障的组件,我们都可以判断出该组是否会导致系统故障。对于每个组件A,我们都知道其具有某些不确定性的故障概率P(A):例如,我们知道此概率的上下限P_(A)和P(A)。通常,假定不同组件的故障是独立事件。我们的目标是使用所有这些信息来估计整个复杂系统的故障概率。在本文中,我们描述了一种基于柯西偏差的高效估计方法。

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