Alternatives and similar repositories for A-New-Convolutional-Neural-Network-Based-Data-Driven-Fault-Diagnosis-Method:

Users that are interested in A-New-Convolutional-Neural-Network-Based-Data-Driven-Fault-Diagnosis-Method are comparing it to the libraries listed below

• Zichen-Yan / Fault-diagnosis
  Fault Diagnosis on Bearing Dataset
  ☆32Updated 5 years ago
• ddrrrr / bearing-fault-diagnosis
  domain adaption with LSGAN for bearing fault diagnosis
  ☆73Updated 6 years ago
• bhushangawde / Fault-Diagnosis-of-Roller-Bearings
  ☆23Updated 2 years ago
• monologuesmw / bearing-fault-diagnosis-cnn
  Siamese network for bearing fault diagnosis
  ☆86Updated 5 years ago
• Gearboxdata / Gear-Box-Fault-Diagnosis-Data-Set
  : Faulty and healthy gear box Data sets need to be analyzed in detail. Here, we created this dataset for those who do research in wind tu…
  ☆49Updated 7 years ago
• MrTangsai / BearLSTM
  with LSTM method to solve bearing fault diagnosis classification
  ☆61Updated 7 years ago
• AiZhanghan / deep-learning-fault-diagnosis
  ☆60Updated 5 years ago
• zhangjunzhao-00 / DANN-Bearing-fault-diagnosis
  Transfer learning
  ☆50Updated 3 years ago
• monologuesmw / bearing-fault-diagnosis-by-wdcnn
  wdcnn model for bearing fault diagnosis
  ☆32Updated 5 years ago
• nicolasoyharcabal / ConvRNN_for_RUL_estimation
  Code used in Thesis "Convolutional Recurrent Neural Networks for Remaining Useful Life Prediction in Mechanical Systems".
  ☆82Updated 6 years ago
• kidozh / prognostic_and_rul_prediction_of_bearing_data
  One model for RUL and fault prognostic prediction on XJTU bearing dataset
  ☆92Updated 5 years ago
• cyrilli / SSVAE
  try out bearing fault diagnosis with semi-supervised vae
  ☆38Updated 7 years ago
• QinYi-team / Code
  ☆101Updated 2 years ago
• erphm / MA1DCNN
  The code of Understanding and Learning Discriminant Features based on Multi-Attention 1DCNN for Wheelset Bearing Fault Diagnosis.
  ☆24Updated 5 years ago
• denggang123 / fault_diagnosis_spiral_CNN
  基于CNN、特征螺旋排列、奇异值分解、Hankel矩阵的故障诊断方法
  ☆10Updated 5 years ago
• ddrrrr / project_FD
  deep learning methods for bearing fault diagnosis
  ☆13Updated 6 years ago
• XiubenWu / GANFORCWRU
  New GAN models in dataset of CWRU
  ☆39Updated 3 years ago
• Scallopwang / Rotating-machinery-fault-diagnosis-dataset
  It comes from eight universities, Case Western Reserve University(CWRU), Beijing University of Aeronautics and Astronautics(BUAA), Southe…
  ☆20Updated 5 years ago
• hezhijing / Intelligent-fault-diagnosis-of-wind-turbine-gearbox-based-on-CNN
  ☆16Updated 5 years ago
• ziapple / fd-dann
  基于迁移学习DANN模型，对不同工况轴承进行故障诊断
  ☆41Updated 3 years ago
• OneBugMaker / PHM-RUL-Prediction-by-EM
  Remain useful life prediction of rolling bearing.
  ☆57Updated 4 years ago
• liguge / DLWCB
  基于Laplace小波卷积和BiGRU的少量样本故障诊断方法 (Small sample fault diagnosis based on Laplace wavelet convolution and BiGRU)
  ☆52Updated last year
• zhangqingqingq / Fault-diagnosis-based-on-LSTM
  TE data diagnosis using pytorch
  ☆20Updated 6 years ago
• Abdulhamid97Mousa / 1D_CNN_VibrationSignal_BearingFaultDiagnosis
  1D-CNN Vibration Signal Bearing Fault Diagnosis
  ☆52Updated last year
• ZhaoZhibin / Few-shot-Transfer-Learning
  Few-shot Transfer Learning for Intelligent Fault Diagnosis of Machine
  ☆17Updated 4 years ago
• he-zh / vibration_gan
  Implement GANs to generate time-series signals for imbalanced learning problem. The experiments are conducted using CWRU bearing data.
  ☆81Updated 3 years ago
• NPUStarBoy / Deep-transfer-network-for-fault-diagnosis
  ☆21Updated 4 years ago
• ZhaoZhibin / Basic-Rotating-Machine-Vibration-Analysis
  These codes realize data transformation and simple data processing for fault diagnosis.
  ☆86Updated 7 years ago
• alliens / -
  基于迁移学习的离心泵滚动轴承故障自动识别方法研究
  ☆15Updated 4 years ago
• zggg1p / A-Domain-Adaption-Transfer-Learning-Bearing-Fault-Diagnosis-Model-Based-on-Wide-Convolution-Deep-Neu
  Inspired by the idea of transfer learning, a combined approach is proposed. In the method, Deep Convolutional Neural Networks with Wide …
  ☆118Updated last month