An RBMs-BN method to RUL prediction of traction converter of CRH2 trains-Reference-Cited by-同舟云学术

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An RBMs-BN method to RUL prediction of traction converter of CRH2 trains

Published:2019-10 Issue: Volume:85 Page:46-56
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Zhang Chuanyu,Wang Cunsong,Lu Ningyun,Jiang Bin

Funder

National Natural Science Foundation of China

Nanjing University of Aeronautics and Astronautics Ph.D. short-term visiting scholar project

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference58 articles.

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2. Clinical outcomes following intravascular imaging-guided versus coronary angiography-guided percutaneous coronary intervention with stent implantation: a systematic review and Bayesian Network meta-analysis of 31 studied and 17882 patients;Buccheri;JACC-Cardiovascular Interventions,2017

3. Bayesian networks in fault diagnosis;Cai;IEEE Trans. Inform.,2017

4. Spectral-spatial classification of hyperspectral data based on deep belief network;Chen;IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.,2015

5. Availability model of a PHM-equipped component;Compare;IEEE Trans. Reliab.,2017

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1. Task-orientated probabilistic damage model with interdependent degradation behaviors for RUL prediction of traction converter systems;Reliability Engineering & System Safety;2024-10

2. Feature Analysis Network: An Interpretable Idea in Deep Learning;Cognitive Computation;2024-01-20

3. Dynamic time scales ensemble framework for similarity-based remaining useful life prediction under multiple failure modes;Engineering Applications of Artificial Intelligence;2024-01

4. Overview of fault prognosis for traction systems in high-speed trains: A deep learning perspective;Engineering Applications of Artificial Intelligence;2023-11

5. Mar-RUL: A remaining useful life prediction approach for fault prognostics of marine machinery;Applied Ocean Research;2023-11

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