Mechanical fault time series prediction by using EFMSAE-LSTM neural network-Reference-Cited by-同舟云学术

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Mechanical fault time series prediction by using EFMSAE-LSTM neural network

Published:2021-03 Issue: Volume:173 Page:108566
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Guo Jianwen,Lao Zhenpeng,Hou Ming,Li Chuan,Zhang Shaohui

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference42 articles.

1. Fault analysis and adaptive design of wind turbine lubrication system;Cen;Int. J. Performability Eng.,2019

2. Motion planning and scheduling for human and industrial-robot collaboration;Pellegrinelli;CIRP Ann. - Manuf. Technol.,2017

3. Motor anomaly detection for unmanned aerial vehicles using reinforcement learning;Lu;IEEE Internet Things J.,2018

4. Vibration-based bearing fault detection for operations and maintenance cost reduction in wind energy;Peeters;Renew. Energy.,2018

5. An artificial neural network approach for early fault detection of gearbox bearings;Bangalore;IEEE Trans. Smart Grid.,2015

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