Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis
  • Author : Ruqiang Yan
  • Release Date : 15 January 2023
  • Publisher : Elsevier
  • Genre : Business & Economics
  • Pages : 300
  • ISBN 13 : 0323999891
  • Total Download : 885
  • File Size : 44,6 Mb

Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis PDF Summary

Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis provides an introduction to the theory and latest applications of transfer learning on rotary machine fault diagnosis and prognosis.Transfer learning-based rotary machine fault diagnosis is a relatively new subject, and this innovative book draws together recent advances from academia and industry to provide systematic guidance. The basic principles are described before key questions are answered including the applicability of transfer learning to rotary machine fault diagnosis and prognosis, the technical details of the models, and an intro to deep transfer learning. Case studies for every method are provided, helping readers to apply the techniques described in their own work. Comparisons with traditional machine learning methods are also discussed to facilitate the identification of where transfer learning should and should not be applied. Case studies for each transfer learning algorithm are described The transfer learning models provided are optimized to solve specific engineering problems The roles of transfer components, transfer fields, and transfer order in intelligent machine diagnosis and prognosis are described separately