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Remaining Useful Life Prediction With Partial Sensor Malfunctions Using Deep Adversarial Networks

Xiang Li Yixiao Xu Naipeng Li Bin Yang Yaguo Lei

自动化学报：英文版2023，Vol.10Issue(1)：P.121-134,14.

Remaining Useful Life Prediction With Partial Sensor Malfunctions Using Deep Adversarial Networks

Xiang Li ¹Yixiao Xu ²Naipeng Li ¹Bin Yang ³Yaguo Lei⁴

作者信息

1. IEEE the Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System,Xi’an Jiaotong University,Xi’an 710049,China
2. IEEE
3. the Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System,Xi’an Jiaotong University,Xi’an 710049,China Student Member
4. the Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System,Xi’an Jiaotong University,Xi’an 710049,China Senior Member
折叠

摘要

关键词

Adversarial training/data fusion/deep learning/remaining useful life(RUL)prediction/sensor malfunction

分类

信息技术与安全科学

引用本文复制引用

Xiang Li,Yixiao Xu,Naipeng Li,Bin Yang,Yaguo Lei..Remaining Useful Life Prediction With Partial Sensor Malfunctions Using Deep Adversarial Networks[J].自动化学报：英文版,2023,10(1):P.121-134,14.

基金项目

supported by the National Science Fund for Distinguished Young Scholars of China(52025056) （52025056）

Fundamental Research Funds for the Central Universities(xzy012022062)。（xzy012022062）

自动化学报：英文版

OACSCDCSTPCDEI

ISSN：2329-9266

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