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Anomaly characterization for the condition monitoring of rotating shafts exploiting data fusion and explainable convolutional neural networks

Author(s): ORCID (Massachusetts Institute of Technology, Department of Mechanical Engineering, MA, USA)
(Massachusetts Institute of Technology, Department of Mechanical Engineering, MA, USA)
(Massachusetts Institute of Technology, Department of Mechanical Engineering, MA, USA)
(Politecnico di Milano, Department of Mechanical Engineering, Milan, Italy)
(Politecnico di Milano, Department of Mechanical Engineering, Milan, Italy)
Medium: journal article
Language(s): English
Published in: Structural Health Monitoring
DOI: 10.1177/14759217241301288
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1177/14759217241301288.
  • About this
    data sheet
  • Reference-ID
    10816784
  • Published on:
    03/02/2025
  • Last updated on:
    03/02/2025
 
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