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首页> 外文期刊>Electric power systems research >Fault diagnosis method of distribution network based on time sequence hierarchical fuzzy petri nets
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Fault diagnosis method of distribution network based on time sequence hierarchical fuzzy petri nets

机译：基于时间序分层模糊Petri网的分销网络故障诊断方法

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摘要

A large number of alarm information will be generated after the distribution network fails, these information can be used to identify fault components quickly. Since the existing fault diagnosis methods of Petri nets do not fully utilize the time sequence attribute of alarm information, and the time sequence reasoning and fuzzy reasoning are complicated, besides, there are few methods applied to distribution network. A novel fault diagnosis method based on time sequence hierarchical fuzzy Petri nets (TSHFPNs) is proposed for distribution network in this paper. A time interval is assigned for each proposition and rule of the TSHFPNs model to describe the timing constraint of alarm information. The matrix reasoning algorithm can be applied to different system structures, the model has good adaptability. The fuzzy reasoning and time sequence reasoning are implemented at the same time, therefore, the time point constraint and the confidence probability of fault component can be obtained at the same time. At the end of the reasoning process, Gaussian function is introduced to optimize the fault probability and improve the accuracy of fault diagnosis results. Through the comparison and analysis of the distribution system examples, the correctness and rationality of the proposed method are verified.
机译：将在分发网络失败后生成大量警报信息，这些信息可用于快速识别故障组件。由于Petri网的现有故障诊断方法没有充分利用警报信息的时间序列属性，并且其时间序列推理和模糊推理复杂，因此少量应用于分销网络。提出了一种基于时间序列分层模糊Petri网（TSHFPN）的新型故障诊断方法，用于本文的配送网络。为TSHFPNS模型的每个命题和规则分配了时间间隔，以描述警报信息的定时约束。矩阵推理算法可以应用于不同的系统结构，该模型具有良好的适应性。模糊推理和时间序列推理在同一时间内实现，因此，可以同时获得故障分量的时间点约束和置信度概率。在推理过程结束时，引入高斯功能以优化故障概率并提高故障诊断结果的准确性。通过对分布系统示例的比较和分析，验证了所提出的方法的正确性和合理性。

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