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Implementing Intelligent Techniques for the Advanced Alarm Processing

机译:实现高级报警处理的智能技术

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A major power system disturbance could trigger hundreds and sometimes thousands of individual alarms and events. A better and simpler description of the problems affecting the power system is an urgent need for the operators. The task of an Intelligent Alarm Processor (IAP) is to analyze thousands of alarm messages and extract the information that explains causeeffect sequences associated with the network events. In this sense, Fuzzy Reasoning Petri-nets is a very powerful intelligent technique to deal with the complexities of the power system fault and alarm processing. A graphical FRPN model is build in this paper based on the optimal structure and uses fuzzy logic parameters to effectively tackle the uncertainties. Case studies are presented to demonstrate the capability of the IAP under real fault scenarios.
机译:主要的电力系统干扰可能触发数百个,有时数千个单独的报警和事件。对影响电力系统的问题的更好和更简单的描述是对操作员的迫切需要。智能警报处理器(IAP)的任务是分析数千条警报消息,并提取解释与网络事件相关联的AutheEffect序列的信息。从这个意义上讲,模糊推理Petri-net是一种非常强大的智能技术,可以处理电力系统故障和报警处理的复杂性。基于最佳结构,本文建立了一个图形FRPN模型,并使用模糊逻辑参数来有效地解决不确定性。提出了案例研究以证明IAP在实际故障方案下的能力。

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