Fault Prediction of Molecular Pump Based on DE-Bi-LSTM-Reference-Cited by-同舟云学术

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Fault Prediction of Molecular Pump Based on DE-Bi-LSTM

Published:2023-11-29 Issue: Volume: Page:1-11
ISSN:1536-1055
Container-title:Fusion Science and Technology
language:en
Short-container-title:Fusion Science and Technology

Author:

Zhou Yang¹²^ORCID,Jiang Ming¹²,Yuan Xiaolin³,Zuo Guizhong³,Chen Yue³,Hou Jilei³,Jia Kai¹²,Liu Peng¹²,Cheng Zhixin¹²

Affiliation:

1. Anhui Polytechnic University, Key Laboratory of Advanced Perception and Intelligence Control of High-End Equipment, Wuhu 241000, China

2. Anhui Polytechnic University, School of Electrical Engineering, Wuhu 241000, China

3. Chinese Academy of Sciences, Institute of Plasma Physics, Hefei 230031, China

Funder

National Nature Science Foundation of China

CASHIPS Director’s Fund

Nature Science Foundation of Anhui Province

Chinese Postdoctoral Science Found

Publisher

Informa UK Limited

Subject

Mechanical Engineering,General Materials Science,Nuclear Energy and Engineering,Nuclear and High Energy Physics,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15361055.2023.2275089

Reference21 articles.

1. Vacuum and wall conditioning system on EAST

2. A support vector machine framework for fault detection in molecular pump

3. An Expert System for Rotating Machine Fault Detection Using Vibration Signal Analysis

4. Research on Vibration Signal Analysis and Extraction Method of Gear Local Fault;YANG X. F.;Proc. SPIE,2018

5. Rolling bearing fault detection of electric motor using time domain and frequency domain features extraction and ANFIS

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