Skip to content
View liguge's full-sized avatar
😆
On working
😆
On working
630 followers · 108 following
  • Beijing Jiaotong University
  • Beijing, China
Block or Report

Block or report liguge

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
liguge/README.md

❤️ Academic homepage

📫 Google scholar

📫 ResearchGate

📫 学术镜像

📫 WOS

📫 Scopus

🌱 My published papers：

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

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

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

  4. Interpretable Modulated Differentiable STFT and Physics-informed Balanced Spectrum Metric for Freight Train Wheelset Bearing Cross-machine Transfer Fault Diagnosis under Speed FluctuationsCitation Count

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

​ $\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow\Downarrow$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 Citation Count
  2. 基于Laplace小波卷积和BiGRU的少量样本故障诊断方法
  3. Rolling Bearing Sub-Health Recognition via Extreme Learning Machine Based on Deep Belief Network Optimized by Improved Fireworks Citation Count

💬 Published papers that I try to reproduce（unofficial code）

  1. Deep Residual Shrinkage Networks for Fault Diagnosis. paper code
  2. A Rolling Bearing Fault Diagnosis Method Using Multi-Sensor Data and Periodic Sampling. paper code
  3. Deep discriminative transfer learning network for cross-machine fault diagnosis. paper code
  4. GTFE-Net: A Gramian Time Frequency Enhancement CNN for bearing fault diagnosis. paper code
  5. Capsule network for fault diagnosis. paper code
  6. Milling chatter recognition. code
  7. A fault diagnosis method for rotating machinery based on CNN with mixed information. paper code
  8. CNN parameter design based on fault signal analysis and its application in bearing fault diagnosis. paper code
  9. Maximum mean square discrepancy: A new discrepancy representation metric for mechanical fault transfer diagnosis. paper code
  10. A blind deconvolution algorithm based on backward automatic differentiation and its application to rolling bearing fault diagnosis. paper code

🌐 Follow Me

GitHub ohmycaptainnemo

ResearchGate

Google Scholar

ResearchGate

Google Scholar

⚡ Social

  • chaohe#bjtu.edu.cn
  • huantaihechao#163.com

✅ Views

🏠 CountTop Langs.

Top Langs

🎁 GitHub Streak.

GitHub Streak

🏀 GitHub stats.

Anurag's GitHub stats

⚽ GitHub trophy.

trophy

⚾ Github activity graph.

Ashutosh's github activity graph

💻 Tech Stack

C C++ Java HTML5 MarkdownPython NumPy Pandas Plotly PyTorch scikit-learn SciPy Visual Studio Code

Pinned

  1. Journals-of-Prognostics-and-Health-Management Journals-of-Prognostics-and-Health-Management Public

    智能故障诊断和寿命预测期刊（Journals of Intelligent Fault Diagnosis and Remaining Useful Life）

    218 34

  2. EWSNet EWSNet Public

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

    Python 50 5

  3. Fault-diagnosis-for-small-samples-based-on-attention-mechanism Fault-diagnosis-for-small-samples-based-on-attention-mechanism Public

    基于注意力机制的少量样本故障诊断 pytorch

    Python 163 10

  4. 1D-Grad-CAM-for-interpretable-intelligent-fault-diagnosis 1D-Grad-CAM-for-interpretable-intelligent-fault-diagnosis Public

    智能故障诊断中一维类梯度激活映射可视化展示 1D-Grad-CAM for interpretable intelligent fault diagnosis

    Python 77 14

  5. Deep-Residual-Shrinkage-Networks-for-intelligent-fault-diagnosis-DRSN- Deep-Residual-Shrinkage-Networks-for-intelligent-fault-diagnosis-DRSN- Public

    Deep Residual Shrinkage Networks for Intelligent Fault Diagnosis（pytorch） 深度残差收缩网络应用于故障诊断

    Python 179 29

  6. WIDAN WIDAN Public

    Interpretable Physics-informed Domain Adaptation Paradigm for Cross-machine Transfer Fault Diagnosis （故障诊断）

    Python 9