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The early implementation of failure modes into existing component model libraries

机译：故障模式的早期实施到现有组件模型库中

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This research addresses a need in systems engineering to verify that a system can meet performance requirements; this is done by integrating failure behavior into the system's nominal model during the initial stages of design. In general, failure behavior is not used in early assessments, lending toward increased uncertainty in the model's validity. Current libraries do not model failures and thus cannot confidently address how a design will function in the intended operational environments. Since failures occur from effects on the environment, they should be included during verification and validation efforts. Current approaches capture off-nominal behavior using parameter variation where flow variables and parameters are varied to measure the system-level effect. This approach is ad hoc and does not accurately capture failure mode behavior. To address this limitation, an approach is developed to under-stand and implement failure mode behavior into nominal models. The Modelica Standard Library (MSL) is used as an example for the component library of nominal models. MSL has a significant amount of basic nominal component behavior and therefore is desirable for this research. Two approaches are developed to implement failure mode behavior; the first uses transfer function and use case graphs, and the second uses existing literature. In addition, complex systems often have a large number of components and an even larger number of failure modes. Since the goal is to limit the development time, we generate an approach to identify high-risk failure modes. This captures an early system-level effect of each failure mode and uses an occurrence to calculate risk. To show the usefulness of each method, two examples are provided including a vehicle drivetrain subsystem with a variety of failures and a diesel engine with fuel injector and valve failures.
机译：该研究满足了系统工程中验证系统可以满足性能要求的需求;这是通过在设计的初始阶段将故障行为集成到系统的名义模型中来完成的。通常，在早期评估中不使用失效行为，从而增加了模型有效性的不确定性。当前的库不对故障建模，因此无法自信地解决设计在预期的操作环境中的功能。由于故障是由于对环境的影响而发生的，因此应在验证和确认工作中包括这些故障。当前的方法使用参数变化来捕获偏离名义的行为，其中流量变量和参数被变化以测量系统级效果。这种方法是临时的，不能准确地捕获故障模式的行为。为了解决此限制，开发了一种方法来理解故障模式行为并将其实施到名义模型中。 Modelica标准库（MSL）用作标称模型组件库的示例。 MSL具有大量的基本标称成分行为，因此对于本研究而言是理想的。开发了两种方法来实现故障模式行为：第一个使用传递函数和用例图，第二个使用现有文献。另外，复杂的系统通常具有大量的组件和更多的故障模式。由于目标是限制开发时间，因此我们生成了一种识别高风险故障模式的方法。这捕获了每种故障模式的早期系统级影响，并使用事件来计算风险。为了显示每种方法的实用性，提供了两个示例，包括具有各种故障的车辆传动系统子系统和具有喷油器和气门故障的柴油发动机。

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