Gearbox faults are a major cause of downtime and maintenance costs in offshore wind turbines. This paper presents a gearbox fault identification method that combines multi-domain feature fusion with a hybrid ensemble learning framework. Time-domain statistical features and frequency-domain spectral features are extracted and fused to capture both amplitude and frequency characteristics of vibration signals. A hybrid ensemble classifier integrating Support Vector Machine (SVM) and XGBoost is employed to improve classification robustness and accuracy under variable operating conditions. The method is validated using the NREL wind turbine gearbox benchmark dataset. Experimental results demonstrate high fault detection accuracy, outperforming single-domain and single-model approaches.
Chunying Xu, Wei Wei, Zhan Lian et al.· International Conference on...· 0 citations
Accurate computational prediction of antiviral peptides (AVPs) can accelerate peptide screening and reduce experimental costs. However, existing deep learning-based methods still suffer from severe class imbalance, over-reliance on handcrafted features and limited interpretability. Here, we propose PMAVP, a multi-task learning framework that integrates the ProtT5 pre-trained protein language model with a Mamba-inspired module for AVP identification and functional activity prediction. We use ProtT5 to extract deep semantic representations from peptide sequences and a Mamba module to capture long-range dependencies at a lower computational complexity. We introduce Focal Loss to mitigate class imbalance and leverage transfer learning to enhance performance on functional activity prediction. Experimental results demonstrate that our model achieves superior performance in terms of prediction accuracy, stability, and computational efficiency. Furthermore, DeepSHAP-based interpretability analysis reveals that the first 40 amino acid residues contribute substantially to AVP prediction.
Pei-Wei Wei, Wei-Hao Su, Qing-Song Qin et al.· International Journal of Mol...· 0 citations
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