Pre-Trained Large Language Model Based Remaining Useful Life Transfer Prediction of Bearing

Laifa Tao; Zhengduo Zhao; Xuesong Wang; Bin Li; Wenchao Zhan; Xuanyuan Su; Shangyu Li; Qixuan Huang; Haifei Liu; Chen Lu; Zhixuan Lian

Pre-Trained Large Language Model Based Remaining Useful Life Transfer Prediction of Bearing

Systems and Control 2025-01-14 v1 Machine Learning Systems and Control

Authors: Laifa Tao , Zhengduo Zhao , Xuesong Wang , Bin Li , Wenchao Zhan , Xuanyuan Su , Shangyu Li , Qixuan Huang , Haifei Liu , Chen Lu , Zhixuan Lian

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Abstract

Accurately predicting the remaining useful life (RUL) of rotating machinery, such as bearings, is essential for ensuring equipment reliability and minimizing unexpected industrial failures. Traditional data-driven deep learning methods face challenges in practical settings due to inconsistent training and testing data distributions and limited generalization for long-term predictions.

Keywords

remaining useful life (RUL) transfer prediction bearing pre-trained large language model rotating machinery deep learning

Cite

@article{arxiv.2501.07191,
  title  = {Pre-Trained Large Language Model Based Remaining Useful Life Transfer Prediction of Bearing},
  author = {Laifa Tao and Zhengduo Zhao and Xuesong Wang and Bin Li and Wenchao Zhan and Xuanyuan Su and Shangyu Li and Qixuan Huang and Haifei Liu and Chen Lu and Zhixuan Lian},
  journal= {arXiv preprint arXiv:2501.07191},
  year   = {2025}
}

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