A centrifugal pump fault diagnosis framework based on supervised contrastive learning

HIGHLIGHTS

  • who: Sajjad Ahmad and colleagues from the Department of Electrical, Electronic and Computer Engineering, University of, have published the paper: A Centrifugal Pump Fault Diagnosis Framework Based on Supervised Contrastive Learning, in the Journal: Sensors 2022, 22, 6448. of /2022/
  • what: The proposed model also showed stability when the experiment was repeated 10 times; the model had higher accuracy than the referenced methods because the authors used contrastive learning that provided the classifier with highly discriminant features, while the other methods provided non-discriminant and indifferentiable features to the classifier, which resulted in low accuracy . . .

     

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