Remaining useful life prediction of rolling bearing under limited data based on adaptive time-series feature window and multi-step ahead strategy-Reference-Cited by-同舟云学术

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Remaining useful life prediction of rolling bearing under limited data based on adaptive time-series feature window and multi-step ahead strategy

Published:2022-11 Issue: Volume:129 Page:109630
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Kong Weili,Li Hai

Publisher

Elsevier BV

Subject

Software

Reference66 articles.

1. A review of artificial intelligence methods for condition monitoring and fault diagnosis of rolling element bearings for induction motor;AlShorman;Shock. Vib.,2020

2. Condition monitoring and fault detection in roller bearing used in rolling mill by acoustic emission and vibration analysis;Nirwan;Mater. Today Proc.,2022

3. An end-to-end framework for remaining useful life prediction of rolling bearing based on feature pre-extraction mechanism and deep adaptive transformer model;Su;Comput. Ind. Eng.,2021

4. A new method for the estimation of bearing health state and remaining useful life based on the moving average cross-correlation of power spectral density;Xu;Mech. Syst. Signal Process.,2020

5. A review on data-driven fault severity assessment in rolling bearings;Cerrada;Mech. Syst. Signal Process.,2018

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3. Advancements in bearing remaining useful life prediction methods: a comprehensive review;Measurement Science and Technology;2024-06-10

4. Predictive Maintenance for Gantry Crane Shafts: Enhancing Sensor Features With Dynamic Dual-Domain Competitive Attention GRU Autoencoder;IEEE Sensors Journal;2024-06-01

5. Rolling Bearing Residual Useful Life Prediction Model Based on the Particle Swarm Optimization-Optimized Fusion of Convolutional Neural Network and Bidirectional Long–Short-Term Memory–Multihead Self-Attention;Electronics;2024-05-29

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