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Yunyi Zhu

ORCID: 0000-0002-3746-6184
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About
Contact & Profiles
A5101860824
Research Areas
  • Machine Fault Diagnosis Techniques
  • Power System Reliability and Maintenance
  • Fault Detection and Control Systems
  • Gear and Bearing Dynamics Analysis
  • Energy Load and Power Forecasting
  • Mechanical Failure Analysis and Simulation
  • Anomaly Detection Techniques and Applications

Beihang University
 2023

 Fault diagnosis of wind turbine gearbox under limited labeled data through temporal predictive and similarity contrast learning embedded with self-attention mechanism
OPENALEX - Publications 
Yunyi Zhu Bin Xie Anqi Wang Zheng Qian

10.1016/j.eswa.2023.123080 article EN Expert Systems with Applications 2023-12-27
 Wind turbine fault detection and identification through self-attention-based mechanism embedded with a multivariable query pattern
OPENALEX - Publications 
Anqi Wang Yan Pei Yunyi Zhu Zheng Qian

10.1016/j.renene.2023.05.003 article EN Renewable Energy 2023-05-09
 Wind turbine fault detection and identification via self-attention-based dynamic graph representation learning and variable-level normalizing flow
OPENALEX - Publications 
Yunyi Zhu Bin Xie Anqi Wang Zheng Qian

10.1016/j.ress.2024.110554 article EN Reliability Engineering & System Safety 2024-10-06
 Anomaly detection for wind turbine gearbox oil pressure difference based on SCADA data
OPENALEX - Publications 
Y.F. Bo Xiangjun Zeng Ming Yang Yunyi Zhu

Abstract In this paper, a SCADA data-based fault detection method for gearbox oil pressure difference is proposed, and the core of Spare Bayesian Learning (SBL) algorithm. The probability estimation model can be constructed by training historical normal operating based on SBL. Then, distribution interval estimated. abnormal state judged observing whether actual value within interval. addition, statistical hypothesis testing used to verify reliability anomaly results. Through method, problem...

10.1088/1755-1315/354/1/012115 article EN IOP Conference Series Earth and Environmental Science 2019-10-01
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