A Novel Mechanical Fault Diagnosis Based on Transfer Learning with Probability Confidence Convolutional Neural Network Model

A Novel Mechanical Fault Diagnosis Based on Transfer Learning with Probability Confidence Convolutional Neural Network Model

For fault diagnosis, convolutional neural networks (CNN) have been performing as a data-driven method to identify mechanical fault features in forms of vibration signals. However, because of CNN’s ineffective and inaccurate identification of unknown fault categories, we propose a model based on tran...

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Bibliographic Details
Main Authors: Hsiao-Mei Lin, Ching-Yuan Lin, Chun-Hung Wang, Ming-Jong Tsai
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Applied Sciences
Subjects:
fault diagnosis
probability confidence
feature engineering
transfer learning
deep learning
convolutional neural networks
Online Access:https://www.mdpi.com/2076-3417/12/19/9670

Internet

https://www.mdpi.com/2076-3417/12/19/9670

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