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Fault Propagation Modelling for Fluid System Health Monitoring

机译:用于流体系统健康监控的故障传播建模

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Fault diagnostics systems are incorporated to determine the health of the system they monitor. There are however times when the diagnostics system reports faults which do not exist. This situation commonly arises at system start-up when high vibration levels exist and the systems are not performing in the same way as when they are operational. Unnecessary shutdowns can occur due to transient behaviour of the system. On autonomous vehicles, such as Unmanned Aerial Vehicles (UAVs), information about the health of the system can be used to support the decision making process and to plan the future system operation. When faults are reported on autonomous systems, where there is no pilot to interpret the conditions reported, a method is needed to establish whether the reported faults do exist. Utilising a fault propagation modelling technique deviations in system variables can be propagated through the system until further evidence of fault presence is observed. If some evidence that contradicts the fault presence is found, the fault can be cancelled and unnecessary shutdowns can be avoided. In this paper a propagation table method is developed to model fault propagation through a system. The system is broken down into its constituent components and each model shows how process variables depend not only on the state of the component but also on the state of the entire system. The outputs of the two-way fault propagation modelling are values of process variables at different locations in the system. These values can be compared with the symptoms observed and used to cancel or confirm faults. This comparison process is accomplished at each phase that the system goes through during its defined mission. The illustration of the fault propagation methodology is given using an example system, and its application for the fault cancellation process is discussed.
机译:集成了故障诊断系统以确定它们监视的系统的运行状况。但是,有时诊断系统会报告不存在的故障。这种情况通常在系统启动时出现,即存在高振动级别,并且系统的运行方式与运行时不同。由于系统的瞬态行为,可能会发生不必要的关机。在无人飞行器(UAV)等自动驾驶汽车上,有关系统运行状况的信息可用于支持决策过程并计划未来的系统运行。在自治系统上报告故障时,没有飞行员可以解释所报告的状况,因此需要一种方法来确定所报告的故障是否确实存在。利用故障传播建模技术,可以将系统变量中的偏差传播到整个系统中,直到观察到故障存在的进一步证据为止。如果找到与故障存在矛盾的证据,则可以取消故障并避免不必要的停机。在本文中,开发了一种传播表方法来模拟故障在系统中的传播。该系统分为其组成组件,每个模型都显示过程变量不仅取决于组件的状态,还取决于整个系统的状态。双向故障传播建模的输出是系统中不同位置处的过程变量的值。这些值可以与观察到的症状进行比较,并用于消除或确认故障。该比较过程是在系统在其定义的任务期间经历的每个阶段完成的。使用实例系统给出了故障传播方法的说明,并讨论了其在故障消除过程中的应用。

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