Fault Diagnosis of Bearings with Small Sample Size Using Improved Capsule Network and Siamese Neural Network

Fault Diagnosis of Bearings with Small Sample Size Using Improved Capsule Network and Siamese Neural Network

This paper addresses the challenges of low accuracy and long transfer learning time in small-sample bearing fault diagnosis, which are often caused by limited samples, high noise levels, and poor feature extraction. We propose a method that combines an improved capsule network with a Siamese neural...

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Bibliographic Details
Main Authors: Jarula Yasenjiang, Yang Xiao, Chao He, Luhui Lv, Wenhao Wang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
small sample
capsule network
Siamese neural network
SKNet
Online Access:https://www.mdpi.com/1424-8220/25/1/92
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