Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions-Reference-Cited by-同舟云学术

Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

Published:2023-08 Issue: Volume:197 Page:110359
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Xiong Jiawei,Fink Olga,Zhou Jian,Ma Yizhong

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference56 articles.

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3. Remaining Useful Life Prediction Based on a Double-Convolutional Neural Network Architecture;Yang;IEEE Trans. Ind. Electron.,2019

4. Remaining useful lifetime prediction via deep domain adaptation;da Costa;Reliab. Eng. Syst. Saf.,2020

5. Remaining useful life prediction for an adaptive skew-Wiener process model;Huang;Mech. Syst. Sig. Process.,2017

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