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.
Deep convolutional neural network model based chemical pro- cess fault diagnosis.Computers & chemical engineering, 115:185–197
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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.