Meirong Wei
Papers
2
Total Citations
13
H-Index
1
About
Dr. Meirong Wei is a leading researcher in intelligent fault diagnosis and machinery health monitoring, with a focus on rotating machinery critical to ship operations. Her work addresses the pressing challenge of detecting faults under extreme data scarcity—particularly zero-fault samples and severe sample imbalance. Dr. Wei pioneered the Wavelet Knowledge-Driven Transformer, a novel deep learning framework that integrates physical knowledge with wavelet transforms to enable fault detection without any real fault samples, achieving 12 citations since 2024. She further advanced the field by combining physical information with contrastive learning, tackling extreme sample imbalance conditions in rotating machinery fault diagnosis. Her contributions are vital for ensuring the reliability and safety of marine and industrial equipment, where timely fault detection prevents catastrophic failures. With a citation trajectory reflecting growing impact, Dr. Wei’s research bridges the gap between laboratory-generated data and real-world operational conditions, offering practical solutions for intelligent maintenance. Her work is essential reading for engineers and researchers developing robust, data-efficient diagnostic systems for critical machinery.
Research Focus
Key Achievements
Top Papers
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