Novel deep learning framework for aeroengine-bearing fault diagnosis: Optimizing VMD parameters with TTAO

Wan Anping, Zhang Fei, Khalil Al-Bukhaiti, Xiaomin Cheng, Xiaosheng Ji, Jinglin Wang, Tianmin Shan, Department of Mechanical Engineering, Hangzhou City University, Wireless Communication and Artificial Intelligence Industry Research Center, Zhengzhou Digital Industry Institute, Zhejiang Key Laboratory of Advanced Equipment Manufacturing and Measurement Technology, School of Mechanical Engineering, Zhejiang University, Aviation Key Laboratory of Science and Technology on Fault Diagnosis Health Management, Shanghai Institute of Aeronautical Measurement and Control Technology, China Aviation Industry Corporation

Journal of Vibration and Control

Published online on November 14, 2025

Abstract

Journal of Vibration and Control, Ahead of Print.
Early and accurate bearing fault diagnosis is crucial for aeroengine safety and operational efficiency. This paper proposes a novel deep learning framework for aeroengine-bearing fault diagnosis, leveraging the strengths of variational mode decomposition (...