Abstract: Fault diagnosis of complex industrial processes becomes challenging due to temporal and spatial dependencies in process data. This means that the emergence and evolution of faults are ...
Abstract: Fault diagnosis for high-dimensional industrial process data with strong nonlinear coupling remains challenging. Most existing graph convolutional network–based methods rely on static or ...
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