A health-adaptive time-scale representation (HTSR) embedded convolutional neural network for gearbox fault diagnostics-Reference-Cited by-同舟云学术

A health-adaptive time-scale representation (HTSR) embedded convolutional neural network for gearbox fault diagnostics

Published:2022-03 Issue: Volume:167 Page:108575
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Kim Yunhan,Na Kyumin,Youn Byeng D.

Funder

National Research Foundation of Korea

Ministry of Science and ICT, South Korea

Kementerian Pendidikan Malaysia

Publisher

Elsevier BV

Subject

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

Reference44 articles.

1. Y. Kim, J. Park, K. Na, H. Yuan, B. D. Youn, C.-s. Kang, “Phase-based time domain averaging (PTDA) for fault detection of a gearbox in an industrial robot using vibration signals,” Mechanical Systems and Signal Processing, vol. 138, pp. 106544 1-19, 2020. https://doi.org/10.1016/j.ymssp.2019.106544.

2. Toothwise fault identification for a planetary gearbox based on a health data map;Ha;IEEE Trans. Ind. Electron.,2017

3. Pattern recognition based on-line vibration monitoring system for fault diagnosis of automobile gearbox;Praveenkumar;Measurement,2018

4. Autocorrelation-based time synchronous averaging for condition monitoring of planetary gearboxes in wind turbines;Ha;Mech. Syst. Sig. Process.,2016

5. A positive energy residual (PER) based planetary gear fault detection method under variable speed conditions;Park;Mech. Syst. Sig. Process.,2019

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