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PPN: A probabilistic model for fault detection and diagnosis

机译:PPN:故障检测和诊断的概率模型

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摘要

To analyze the composite fault in Discrete Event System (DES), a Probabilistic Petri net (PPN) and a fault diagnosis method for power system are proposed. Firstly, the PPN models are established on every fault spread direction. Secondly, the failed component is determined by the application of Petri net reasoning and probabilistic calculation. At last, the result is given by fusing all parties' results using mean method. Diagnosis analysis shows that the method can adapt to topology changes and obtain satisfying diagnosis results with incomplete information. In the PPN reasoning, calculating the fault probability of component is based on the prior probability from statistics, so the subjectivity of setting related parameters can be avoided.
机译:为了分析离散事件系统(DES)中的复合故障,提出了一种概率Petri网(PPN)和一种电力系统故障诊断方法。首先,在每个故障扩展方向上建立PPN模型。其次,通过Petri网推理和概率计算确定失效组件。最后,通过使用均值方法融合各方的结果来给出结果。诊断分析表明,该方法能够适应拓扑变化,获得信息不完整的满意诊断结果。在PPN推理中,基于统计的先验概率来计算组件的故障概率,因此可以避免设置相关参数的主观性。

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