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ITDFNet: a multi-dimensional fusion image and temporal dual-branch network for bearing fault diagnosis

Shaobin Cai1, Yangsheng Zhang2

  • 1College of Information Engineering, Huzhou University, Huzhou, China.

Scientific Reports
|April 7, 2026
PubMed
Abstract

No abstract available in PubMed .

Keywords:
Anti-noise robustnessConvolutional neural networkFault diagnosisFeature representationMultimodal fusion

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When analyzing a single line-to-ground fault from phase A to ground at a three-phase bus, it is important to consider the fault impedance. This impedance is zero for a bolted fault, equal to the arc impedance for an arcing fault, and represents the total fault impedance for a transmission-line insulator flashover. To derive sequence and phase currents, fault conditions are translated from the phase domain to the sequence domain.
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