Bearing Faulty Prediction Method Based on Federated Transfer Learning and Knowledge Distillation

Bearing Faulty Prediction Method Based on Federated Transfer Learning and Knowledge Distillation

In this paper, a novel bearing faulty prediction method based on federated transfer learning and knowledge distillation is proposed with three stages: (1) a “signal to image” conversion method based on the continuous wavelet transform is used as the data pre-processing method to satisfy the input ch...

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Bibliographic Details
Main Authors: Yiqing Zhou, Jian Wang, Zeru Wang
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Machines
Subjects:
knowledge distillation
federated transfer learning
parameter size
knowledge transference
edge-computing deployment
Online Access:https://www.mdpi.com/2075-1702/10/5/376

Internet

https://www.mdpi.com/2075-1702/10/5/376

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