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Determination of Timed Transitions in Identified Discrete-Event Models for Fault Detection

机译:用于故障检测的识别离散事件模型中定时转换的确定

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Model-based fault detection compares modeled and observed behavior to decide whether a system operates properly or not. The key issue in this paper is to model large-scale Discrete Event Systems (DESs) with little a-priori knowledge. For this class of systems a new approach to black-box determination of timed transitions for timed automata is proposed. The method identifies a set of time guards leading to an advantageous trade-off between the fault detection errors: false alarms and missed detections. A real industrial system is applied for evaluation of time guard determination. It is shown that applying the proposed method results in a better trade-off between the fault detection errors than using common methods (e.g. Min/Max, Normal Distribution).
机译:基于模型的故障检测比较建模和观察到的行为来决定系统是否正常运行。 本文的关键问题是模拟大规模离散事件系统(DESS),具有很少的A-Priori知识。 对于这类系统,提出了一种新方法,用于黑盒子测定定时自动机的定时转换。 该方法识别一组时间警卫,导致故障检测错误之间有利的权衡:误报和错过检测。 应用真正的工业系统用于评估时间防范确定。 结果表明,应用所提出的方法导致故障检测误差与使用常用方法之间的更好的权衡(例如,Min / Max,Normal分布)。

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