Your Location:
Home >
Browse articles >
Fault Diagnosis Method for Hydroturbine Units Based on Transformer and Multimodal Heterogeneous Feature Fusion
Power Generation Technology   Vol. 47, Issue 4, Pages: 774-783(2026)
Frontier AI Technologies and Large Model Applications for New Power Systems|Updated:2026-09-01
  • Export

  • Collection

  • Album

    • Fault Diagnosis Method for Hydroturbine Units Based on Transformer and Multimodal Heterogeneous Feature Fusion

    • “A new breakthrough has been made in the field of fault diagnosis for water turbine units, and researchers have established a multimodal heterogeneous graph hybrid feature extraction model of "Transformer Gram angle field recursive graph two-dimensional gated cyclic unit", providing a solution to the problem of identifying nonlinear and multi-scale vibration abnormal signals.”
    • DOI:10.12096/j.2096-4528.pgt.260409    

      CLC:
    • Revised:2025-02-26,

    Scan QR Code

  •  
  •  

12

Views

3

Downloads

0

CSCD

Alert me when the article has been cited
Submit
Outline

Related Articles

Research on Fault Diagnosis Method of Photovoltaic Arrays Based on Improved Grey Wolf Algorithm Optimized Extreme Learning Machine
Bearing Faults Diagnosis Method Based on Stacked Auto-Encoder With Graph Regularization for Wind Turbines
Research Progress of Vibration Fault Diagnosis Technology for Steam Turbine Generator Sets
Transformer and Q Learning Dual-Driven Smart Generation Control for New Power Systems
Application and Challenges of Large Models in Power Industry

Related Author

ZHOU Dingxuan
ZHOU Ning
HAN Maolin
NIU Fengjie
YANG Chen
LI Dazi
BAO Yanyang
LIU Jianxun

Related Institution

College of Engineering Science and Technology, Shanghai Ocean University, Pudong New District
Beijing Pukang Measurement and Monitoring Tech Co., Ltd., Fengtai District
College of Information Science and Technology, Beijing University of Chemical Technology, Chaoyang District
Electric Power Research Institute of Guizhou Power Grid Co., Ltd.
School of Energy and Power Engineering, Changsha University of Science and Technology