A multi-level temporal graph network with LSTM, graph convolutions, multi-level pooling, and local-global fusion outperforms baselines on the Tennessee Eastman process for industrial fault diagnosis.
ANN based fault diagnosis of permanent magnet synchronous motor under stator winding shorted turn.Electric Power Systems Research, 125:67–82
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Multi-Level Temporal Graph Networks with Local-Global Fusion for Industrial Fault Diagnosis
A multi-level temporal graph network with LSTM, graph convolutions, multi-level pooling, and local-global fusion outperforms baselines on the Tennessee Eastman process for industrial fault diagnosis.