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A Novel Real-Time Fault Diagnostic System by Using Strata Hierarchical Artificial Neural Network

机译:基于分层层次神经网络的新型实时故障诊断系统

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The real-time fault diagnosis system is very great important for steam turbine generator set due to a serious fault results in a reduced amount of electricity supply in power plant. A novel real-time fault diagnosis system is proposed by using strata hierarchical fuzzy CMAC neural network. A framework of the fault diagnosis system is described. Hierarchical fault diagnostic structure is discussed in detail. The model of a novel fault diagnosis system by using fuzzy CMAC are built and analyzed. A case of the diagnosis is simulated. The results show that the real-time fault diagnostic system is of high accuracy, quick convergence, and high noise rejection. It is also found that this model is feasible in real-time fault diagnosis. This electronic document is a 'live' template. The various components of your paper [title, text, heads, etc.] are already .defined on the style sheet, as illustrated by the portions given in this document.
机译:实时故障诊断系统对于汽轮发电机组非常重要,因为严重的故障会导致电厂的电力供应减少。利用层次分层模糊CMAC神经网络,提出了一种新颖的实时故障诊断系统。描述了故障诊断系统的框架。详细讨论了分层故障诊断结构。建立并分析了一种基于模糊CMAC的新型故障诊断系统的模型。模拟诊断情况。结果表明,该实时故障诊断系统具有精度高,收敛速度快,噪声抑制率高的特点。还发现该模型在实时故障诊断中是可行的。该电子文档是“实时”模板。样式表已经定义了纸张的各种组成部分[标题,文本,标题等],如本文档中给出的部分所示。

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