Bearing fault diagnosis based on frequency subbands feature extraction and multibranch one-dimension convolutional neural network

HIGHLIGHTS

• who: Extraction and collaborators from the Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan have published the article: Bearing Fault Diagnosis Based on Frequency Subbands Feature Extraction and Multibranch One-Dimension Convolutional Neural Network, in the Journal: Scientific Programming 100.0 of 29/08/2022
• what: To better analyze the bearing vibration signal from the time domain and frequency domain and reduce information loss the authors propose a model that decomposes the original bearing vibration signal with a length of 1024 by a two-layer wavelet packet. The authors propose a multiconvolutional neural_network . . .
  

   

  

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