Dislocated time sequences – deep neural network for broken bearing diagnosis

HIGHLIGHTS

• who: Pramudyana Agus Harlianto and collaborators from the Western Reserve UniversityDeep architectures can be utilized with the purpose of simplifying or avoiding any traditional feature extraction process. DNN is utilized for have published the paper: Dislocated time sequences - deep neural network for broken bearing diagnosis, in the Journal: (JOURNAL)
• how: This study experimentally explores the progress of network (DTS-DNN) used to improve multi-class broken bearing diagnosis by using public data from Case Western Reserve University. architectures can be utilized with the purpose of simplifying or avoiding any traditional feature extraction process. The obtained . . .
  

   

  

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