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Power Grid Fault Diagnosis Method Using Intuitionistic Fuzzy Petri Nets Based on Time Series Matching

机译:基于时间序列匹配的直觉模糊Petri网电网故障诊断方法

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摘要

To improve the reliability of power grid fault diagnosis by enhancing the processing ability of uncertain information and adequately utilizing the alarm information about power grids, a fault diagnosis method using intuitionistic fuzzy Petri Nets based on time series matching is proposed in this paper. First, the alarm hypothesis sequence and the real alarm sequence are constructed using the alarm information and the general grid protection configuration model, and the similarity of the two sequences is used to calculate the timing confidence. Then, an intuitionistic fuzzy Petri Nets fault diagnosis model, with an excellent ability to process uncertain information from intuitionistic fuzzy sets, is constructed, and the initial place value of the model is corrected by the timing confidence. Finally, an application of the fault diagnosis model for the actual grid is established to analyze and verify the diagnostic results of the new method. The results for some test cases show that the new method can improve the accuracy and fault tolerance of fault diagnosis, and, furthermore, the abnormal state of the component can be inferred.
机译:为了提高电网故障诊断的可靠性来通过提高不确定信息的加工能力和充分利用关于电网的警报信息,本文提出了一种基于时间序列匹配的直觉模糊Petri网的故障诊断方法。首先,使用警报信息和常规网格保护配置模型构建警报假设序列和实际报警序列,并且两个序列的相似性用于计算定时置信度。然后,构建了一种直觉模糊Petri网故障诊断模型,具有优异的处理来自直觉模糊组的不确定信息,并且模型的初始位置被定时置信纠正。最后,建立了对实际网格的故障诊断模型的应用,以分析和验证新方法的诊断结果。一些测试用例的结果表明,新方法可以提高故障诊断的准确性和容错,而且,可以推断成分的异常状态。

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