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Worst-case false alarm analysis of fault detection systems

机译:故障检测系统最坏情况的虚警分析

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Model-based fault detection methods can be used to reduce the size, weight, and cost of safety-critical aerospace systems. However, the implementation of these methods is based on models. Therefore, disturbance and model uncertainty must be considered in order to certify the fault detection system. This paper considers the worst-case false alarm probability over a class of stochastic disturbances and model uncertainty. This is one analysis needed to assess the overall system reliability. The single step, worst-case false alarm probability is shown to be equivalent to a robust ℌ2 analysis problem. Hence known results from the robust ℌ2 literature can be used to upper bound this worst-case probability. Next, bounds are derived for the worst-case false alarm probability over multiple time steps. The multi-step analysis is important because reliability requirements for aerospace systems are typically specified over a time window, e.g. per hour. The bounds derived for the multi-step analysis account for the time correlations introduced by the system dynamics and fault detection filters. Finally, a numerical example is presented to demonstrate the proposed technique.
机译:基于模型的故障检测方法可用于减小安全关键型航空航天系统的尺寸,重量和成本。但是,这些方法的实现是基于模型的。因此,必须考虑扰动和模型不确定性以认证故障检测系统。本文考虑了一类随机扰动和模型不确定性的最坏情况下的虚警概率。这是评估整体系统可靠性所需的一种分析。单步最坏情况的虚警概率被证明等同于鲁棒的ℌ2分析问题。因此,来自the2文献的已知结果可用于将该最坏情况的概率上限。接下来,得出多个时间步长上最坏情况的虚警概率的界限。多步分析之所以重要,是因为通常在一个时间窗口内指定航空航天系统的可靠性要求,例如,每小时。为多步分析得出的界限说明了由系统动力学和故障检测过滤器引入的时间相关性。最后,给出一个数值例子来说明所提出的技术。

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