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Fault diagnosis of discretely controlled continuous systems by means of discrete-event models

机译：离散事件模型对离散控制连续系统的故障诊断

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Discretely controlled continuous systems consist of continuous plants whose operation mode is switched by a feedback controller. Fault diagnosis has to use the measured switching sequence and the measured continuous movement to detect and identify faults. In order to get the diagnostic algorithm with the least possible complexity, the kind of measurement information and the granularity of the model have to be chosen in accordance with the faults to be detected. The paper presents five diagnostic methods in a uniform way, which differ with respect to the model and the measurement information used. From the hybrid model of discretely controlled continuous systems, four more abstract representations are derived, which have the form of embedded maps, semi-Markov processes, timed automata and nondeterministic automata. The validity of the diagnostic result is ensured by the claim that the models should be complete and, hence, consistent with all the input-output sequences of the discretely controlled system in the appropriate fault case. In this way a hierarchy of models and of diagnostic results is obtained. The methods are illustrated by an example.
机译：离散控制的连续系统由连续工厂组成，其运行模式由反馈控制器切换。故障诊断必须使用测得的开关顺序和测得的连续运动来检测和识别故障。为了获得尽可能少的复杂性的诊断算法，必须根据要检测的故障选择测量信息的类型和模型的粒度。本文以统一的方式介绍了五种诊断方法，它们在模型和使用的测量信息方面有所不同。从离散控制的连续系统的混合模型中，可以得到四个更多的抽象表示，它们具有嵌入式映射，半马尔可夫过程，定时自动机和不确定自动机的形式。诊断结果的有效性是通过这样的主张来保证的：模型应完整，并因此在适当的故障情况下与离散控制系统的所有输入-输出序列一致。以这种方式，获得了模型和诊断结果的层次结构。举例说明了这些方法。

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