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Author

De-Qiang He

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Open access Aug 2026

STSNet: few-shot bearing fault diagnosis method based on spatio-temporal fusion and Siamese learnable metric

A novel few-shot bearing fault diagnosis method is proposed by integrating spatio-temporal feature fusion with a Siamese-based learnable metric framework, which achieves superior diagnostic performance under few-shot conditions compared with other approaches.

Xin-Yu Mo, De-Qiang He, Haiyuan Zhao et al. · 0 citations
Open access Jul 2026

A multi-level constrained vibration–acoustic multimodal contrastive learning for cross-machine motor fault diagnosis

A novel vibration–acoustic multimodal contrastive learning framework designed to jointly regularize vibration–acoustic features at the levels of sample distribution, feature statistics, and feature structure enhances multi modal consistency, feature discriminability, and information diversity.

Yuan Zhuang, Deqiang He, Zhen-Zhen Jin et al. · 0 citations

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