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1. Physics-informed Interpretable Wavelet Weight Initialization and Balanced Dynamic Adaptive Threshold for Intelligent Fault Diagnosis of Rolling Bearings

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2. IDSN: A one-stage Interpretable and Differentiable STFT domain adaptation Network for traction motor of high-speed trains cross-machine diagnosis

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3. Interpretable Physics-informed Domain Adaptation Paradigm for Cross-machine Transfer Diagnosis

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4. Interpretable modulated differentiable STFT and physics-informed balanced spectrum metric for freight train wheelset bearing cross-machine transfer fault diagnosis under speed fluctuations

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5. Journals of Prognostics and Health Management（智能故障诊断和寿命预测期刊）

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​ $\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow$Publications during the master 's degree$\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow$

1. Fault diagnosis for small samples based on attention mechanism
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2. 基于Laplace小波卷积和BiGRU的少量样本故障诊断方法
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3. Rolling Bearing Sub-Health Recognition via Extreme Learning Machine Based on Deep Belief Network Optimized by Improved Fireworks
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1. Deep Residual Shrinkage Networks for Fault Diagnosis.

2. A Rolling Bearing Fault Diagnosis Method Using Multi-Sensor Data and Periodic Sampling.

3. Deep discriminative transfer learning network for cross-machine fault diagnosis.

4. GTFE-Net: A Gramian Time Frequency Enhancement CNN for bearing fault diagnosis.

5. Capsule network for fault diagnosis.

6. Milling chatter recognition.

7. A fault diagnosis method for rotating machinery based on CNN with mixed information.

8. CNN parameter design based on fault signal analysis and its application in bearing fault diagnosis.

9. Maximum mean square discrepancy: A new discrepancy representation metric for mechanical fault transfer diagnosis.

10. A blind deconvolution algorithm based on backward automatic differentiation and its application to rolling bearing fault diagnosis.

11. xLSTM for Intelligent Fault Diagnosis of Rolling Bearings.

12. Variance discrepancy representation: A vibration characteristic-guided distribution alignment metric for fault transfer diagnosis.

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