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A Fusion Method of Rough Set and Neural for Network Fault Diagnosis

机译:粗糙集与神经网络融合的故障诊断方法

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摘要

In the paper, a fusion method of rough set and neural network for fault is put forward and used in generator fault diagnosis. At first, rough set theory is utilized to reduce attribute of diagnosis system. Set in accordance with the practical needs, optimized decision attribute set acts as the input of artificial neural network used for fault diagnosis, which has been used for Fengman hydroelectric power station and testified the feasibility of integration of rough set and neural network. Given enough data, this method could be popularized to other generators.
机译:提出了一种粗糙集与神经网络融合的故障诊断方法,并用于发电机故障诊断。首先,利用粗糙集理论来减少诊断系统的属性。根据实际需要进行设置,优化后的决策属性集作为用于故障诊断的人工神经网络的输入,已被用于丰满水电站,证明了粗糙集与神经网络集成的可行性。如果有足够的数据,此方法可以推广到其他生成器。

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