Slow feature-based feature fusion methodology for machinery similarity-based prognostics-Reference-Cited by-同舟云学术

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Slow feature-based feature fusion methodology for machinery similarity-based prognostics

Published:2024-09 Issue: Volume:152 Page:96-112
ISSN:0019-0578
Container-title:ISA Transactions
language:en
Short-container-title:ISA Transactions

Author:

Xue Bin,Xu Haoyan,Huang Xing,Xu Zhongbin^ORCID

Funder

Zhejiang University

Publisher

Elsevier BV

Reference57 articles.

1. Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications;Lee;Mech Syst Signal Pr,2014

2. A review of physics-based models in prognostics: Application to gears and bearings of rotating machinery;Cubillo;Adv Mech Eng,2016

3. Prognostic modelling options for remaining useful life estimation by industry;Sikorska;Mech Syst Signal Pr,2011

4. Construction of health indicators for condition monitoring of rotating machinery: A review of the research;Zhou;Expert Syst Appl,2022

5. Direct remaining useful life estimation based on support vector regression;Khelif;IEEE Trans Ind Electron,2017

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