采用一种包含加权水平可见图(WHVG)的图卷积网络(GCN)，对采样的轴承震动时间序列数据分析，进行滚动轴承故障诊断。其中，对HVG中两节点的边，以节点距离的倒数作为权重进行加权，以削弱噪声节点对其他距离较远节点的影响。
[1] Li C, Mo L, Yan R. Fault diagnosis of rolling bearing based on WHVG and GCN[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-11.
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打扰了我已经明白了
我将cwru数据9类故障分类 加健康一共10类 10个标签 然后进行训练 准确率上不去
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