Remaining Useful Life Prediction for Rolling Bearings Based on TCN–Transformer Networks Using Vibration Signals

Remaining Useful Life Prediction for Rolling Bearings Based on TCN–Transformer Networks Using Vibration Signals

Remaining useful life (RUL) prediction plays a core role in industrial prognostics and health management (PHM), requiring data-driven models with higher predictive capability for accurate long time series prediction. Developing reliable deep learning-based models based on multi-sensor monitoring dat...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiaochao Jin, Yaping Ji, Shiteng Li, Kailang Lv, Jianzheng Xu, Haonan Jiang, Shengnan Fu
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Sensors
Subjects:
rolling bearings
deep learning
remaining useful life prediction
health index
performance degradation
Online Access:https://www.mdpi.com/1424-8220/25/11/3571
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/25/11/3571

Similar Items