MCAGU-Net: A model for composite fault diagnosis of multi-sensor node networks

Kangshuai Zhang, Quancheng Zhang, Qi Liu, Yang Yang, Yunduan Cui, Lei Peng

Abstract: Highlights•Measure heterogeneous correlation using mutual information and symmetric uncertainty.•Graph structure realizes the unified representation of signal and correlation.•MCAGU-Net uses SCConv to reduce feature redundancy to enhance feature representation.•Channel attention mechanism to adaptively learn the importance of different channel.•MSKloss foster composite fault diagnosis on imbalanced class distributions.