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Fuzzy Automata for Fault Diagnosis: A Syntactic Analysis Approach

机译:模糊自动机的故障诊断:一种句法分析方法

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摘要

Fuzzy automata are proposed for fault diagnosis. The output of the monitored system is partitioned into linear segments which are assigned to pattern classes (templates) with the use of fuzzy membership functions. A sequence of templates is generated and becomes input to fuzzy automata which have transitions that correspond to the templates of the properly functioning system. If the automata reach their final states, i.e. the input sequence is accepted by the automata with a membership degree that exceeds a certain threshold, then normal operation is deduced, otherwise, a failure is diagnosed. Fault diagnosis of a DC motor and detection of abnormalities in the ECG signal are used as case studies.
机译:提出了模糊自动机的故障诊断方法。被监视系统的输出被划分为线性段,这些段通过使用模糊隶属度函数分配给模式类(模板)。生成一系列模板并将其输入到模糊自动机中,模糊自动机具有对应于功能正常的系统的模板的过渡。如果自动机达到其最终状态,即输入顺序被具有超过某个阈值的隶属度的自动机所接受,则推断出正常操作,否则,诊断为故障。案例研究使用了直流电动机的故障诊断和ECG信号的异常检测。

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