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...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Hsiao-Mei Lin, Ching-Yuan Lin, Chun-Hung Wang, Ming-Jong Tsai
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2022-09-01
Sarja:	Applied Sciences
Aiheet:	fault diagnosis probability confidence feature engineering transfer learning deep learning convolutional neural networks
Linkit:	https://www.mdpi.com/2076-3417/12/19/9670
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