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A Method of Remote Fault Diagnosis Based on Region Synchronous Enlargement of Self-Organizing Feature Map

机译:一种基于区域同步放大自组织特征映射的远程故障诊断方法

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This paper proposes a novel Self-Organizing Feature Map (SOM) model for the Remote Fault Diagnosis. The proposed method is based on Region Synchronous Enlargement (RSE). The input vector in the proposed model can be processed automatically. By using the synchronous enlargement method, only the position of the regions is needed to find central seeds. Then synchronously enlarges these seeds to find the boundary point between them. Furthermore, the method is easy to be extended to n-dimensional system. The proposed method has been successfully evaluated using twelve different datasets, and had greatly improved the rate of correct classification.
机译:本文提出了一种用于远程故障诊断的新型自组织特征图(SOM)模型。该方法基于区域同步放大(RSE)。可以自动处理所提出的模型中的输入向量。通过使用同步放大方法,只需要区域的位置来找到中央种子。然后同步放大这些种子以找到它们之间的边界点。此外,该方法易于扩展到N维系统。已经使用12个不同的数据集成功评估了所提出的方法,并且大大提高了正确分类的速率。

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