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首页> 外文会议>Mediterranean Conference on Embedded Computing >Component-based combination of online-diagnosis methods using diagnostic directed acyclic graphs
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Component-based combination of online-diagnosis methods using diagnostic directed acyclic graphs

机译：使用诊断有向无环图的基于组件的在线诊断方法组合

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In safety-critical application domains online fault-diagnosis contributes to a significantly increased system reliability and safety by detecting and diagnosing occurred faults and, if applicable, making the system recover from faults. In order to enable fault-specific recovery actions, e.g., a reconfiguration of the system, cause-based fault identification is needed. This typically requires a large amount of data to be analyzed and evaluated during a diagnostic process. For sound decisions on occurred faults within complex systems, it is often beneficial to combine several online-diagnosis methods. In this work we present a component-based diagnostic framework based on a diagnostic dependency graph. Herein, multiple online-diagnosis methods are combined in the form of encapsulated tasks. The dependencies as well as the tasks adapt to the system at run time. Our diagnostic framework is demonstrated by means of an automotive use-case.
机译：在安全关键型应用领域中，在线故障诊断通过检测和诊断发生的故障，并在可能的情况下使系统从故障中恢复，从而显着提高了系统的可靠性和安全性。为了启用特定于故障的恢复操作，例如系统的重新配置，需要基于原因的故障识别。这通常需要在诊断过程中分析和评估大量数据。为了对复杂系统中发生的故障做出明智的决策，通常将几种在线诊断方法结合起来会很有用。在这项工作中，我们提出了基于诊断依赖图的基于组件的诊断框架。这里，多种在线诊断方法以封装任务的形式结合在一起。依赖关系以及任务在运行时都会适应系统。我们的诊断框架通过汽车用例进行了演示。

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