Multi-domain extreme learning machine for bearing failure detection based on variational modal decomposition and approximate cyclic correntropy

HIGHLIGHTS

• who: Bearing Failure Detection Based and collaborators from the of Electrical and, Normal University, Zhanjiang, China have published the Article: Multi-Domain Extreme Learning Machine for Bearing Failure Detection Based on Variational Modal Decomposition and Approximate Cyclic Correntropy, in the Journal: (JOURNAL)
• what: The multi-dimensional features from the two domains were input into MKELM to classify the health of the Experimental studies were carried out to investigate the proposed method in fault and identification. Despite its wide application, this approach has two problems. In this paper, entropy is calculated with the cyclic correntropy function . . .
  

   

  

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