Yu Yang

ORCID: 0000-0001-9113-6023
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Machine Fault Diagnosis Techniques
  • Gear and Bearing Dynamics Analysis
  • Fault Detection and Control Systems
  • Advanced Algorithms and Applications
  • Advanced Sensor and Control Systems
  • Engineering Diagnostics and Reliability
  • Structural Health Monitoring Techniques
  • Advanced Computational Techniques and Applications
  • Industrial Technology and Control Systems
  • Advanced Measurement and Detection Methods
  • Machine Learning in Bioinformatics
  • Anomaly Detection Techniques and Applications
  • Spectroscopy and Chemometric Analyses
  • Tribology and Lubrication Engineering
  • Topic Modeling
  • Neural Networks and Applications
  • Face and Expression Recognition
  • Natural Language Processing Techniques
  • Refrigeration and Air Conditioning Technologies
  • Image and Signal Denoising Methods
  • Magnetic Bearings and Levitation Dynamics
  • Domain Adaptation and Few-Shot Learning
  • Non-Destructive Testing Techniques
  • Grey System Theory Applications
  • Machine Learning and Data Classification

Hunan University
2016-2025

China Southern Power Grid (China)
2024

Northwestern Polytechnical University
2010-2024

Shenyang University of Technology
2004-2024

Chinese People's Armed Police Force Engineering University
2011-2024

Hainan University
2024

State Grid Corporation of China (China)
2024

Lanzhou University of Technology
2012-2024

Glasgow Caledonian University
2024

Zhengzhou University
2024

10.1016/j.mechmachtheory.2013.08.014 article EN Mechanism and Machine Theory 2013-09-08

10.1016/j.ymssp.2004.11.002 article EN Mechanical Systems and Signal Processing 2004-12-29

10.1016/j.ymssp.2005.09.011 article EN Mechanical Systems and Signal Processing 2005-10-26

It is considerable to solve practical fault diagnosis task of gearbox under variable working conditions by introducing sufficient auxiliary data. For this purpose, a new approach called improved deep transfer auto-encoder proposed for intelligent faults with small training samples. First, multi-wavelet employed as activation function effectively learning useful features hidden in the non-stationary vibration Second, correntropy used modify cost enhance reconstruction quality. Third,...

10.1109/access.2019.2936243 article EN cc-by IEEE Access 2019-01-01
Coming Soon ...