Instance-based ensemble deep transfer learning network: A new intelligent degradation recognition method and its application on ball screw-Reference-Cited by-同舟云学术

Instance-based ensemble deep transfer learning network: A new intelligent degradation recognition method and its application on ball screw

Published:2020-06 Issue: Volume:140 Page:106681
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Zhang Li,Guo Liang^ORCID,Gao Hongli,Dong Dawei,Fu Guoqiang,Hong Xin

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Planning Project of Science & Technology Department of Sichuan Province

Publisher

Elsevier BV

Subject

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

Reference40 articles.

1. Investigation of ball screw preload variation based on dynamic modeling of a preload adjustable feed-drive system and spectrum analysis of ball-nuts sensed vibration signals;Feng;Int. J. Mach. Tool. Manuf.,2012

2. Robust compensation of elastic deformations in ball screw drives;Kamalzadeh;Int. J. Mach. Tool. Manuf.,2010

3. W. Jin, Y. Chen, J. Lee, Methodology for ball screw component health assessment and failure analysis, ASME 2013 International Manufacturing Science and Engineering Conference collocated with the 41st North American Manufacturing Research Conference, American Society of Mechanical Engineers. (2013). Madison Wisconsin, USA.

4. Prognosability study of ball screw degradation using systematic methodology;Li;Mech. Syst. Signal. Process.,2018

5. K. Wang, Y. Huang, L. Gong, C. Cai, Y. Zhang, State-wise LSTM-GRU method for ball screw prediction, 2019 IEEE Aerospace Conference, 2019, pp. 1–8.

Cited by 56 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A systematic literature review of deep learning for vibration-based fault diagnosis of critical rotating machinery: Limitations and challenges;Journal of Sound and Vibration;2024-11

2. IDTL-rPPG: Remote heart rate estimation using instance-based deep transfer learning;Biomedical Signal Processing and Control;2024-09

3. Joint Domain Adaptation-Based Lightweight Approach for Cross-Domain Diagnosis Compatible With Different Devices and Multimodal Sensing;IEEE Sensors Journal;2024-09-01

4. Small data challenges for intelligent prognostics and health management: a review;Artificial Intelligence Review;2024-07-23

5. A Fault Diagnosis Method for Key Components of the CNC Machine Feed System Based on the DoubleEnsemble–LightGBM Model;Machines;2024-05-01