Alternatives and similar repositories for ieee-phm-2012-data-challenge-dataset

Users that are interested in ieee-phm-2012-data-challenge-dataset are comparing it to the libraries listed below

• ddrrrr / projectRUL
  to prediction the remain useful life of bearing based on 2012 PHM data
  ☆290Updated 4 years ago
• ddrrrr / projectRUL2
  ☆66Updated 4 years ago
• Abhijit-Bhumireddy99 / RUL_Prediction
  remaining Useful Life (RUL) Prediction of Mechanical Bearings using Continuous Wavelet Transform (CWT), Convolution Neural Network (CNN),…
  ☆167Updated last year
• lankuohsing / Remaining-Useful-Life-Prediction-RNN
  Remaining Useful Life Prediction Using RNN/LSTM/GRU Neural Networks
  ☆141Updated 3 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…
  ☆55Updated 7 years ago
• wkzs111 / phm-ieee-2012-data-challenge-dataset
  Dataset that was used during the PHM IEEE 2012 Data Challenge, built by the FEMTO-ST Institute
  ☆136Updated 6 years ago
• UtkarshPanara / Remaining-Useful-Life-Prediction-for-Turbofan-Engines
  RUL prediction for Turbofan Engine (CMAPSS dataset) using CNN
  ☆116Updated 4 years ago
• kidozh / prognostic_and_rul_prediction_of_bearing_data
  One model for RUL and fault prognostic prediction on XJTU bearing dataset
  ☆95Updated 5 years ago
• zhangjiali1201 / Keras_bearing_fault_diagnosis
  ☆208Updated 5 years ago
• jiaxiang-cheng / PyTorch-LSTM-for-RUL-Prediction
  PyTorch implementation of remaining useful life prediction with long-short term memories (LSTM), performing on NASA C-MAPSS data sets. Pa…
  ☆151Updated 3 years ago
• huster123 / c-mapss-full-dataset-
  完整的航空发动机一维卷积神经网络训练模型
  ☆59Updated 6 years ago
• nicolasoyharcabal / ConvRNN_for_RUL_estimation
  Code used in Thesis "Convolutional Recurrent Neural Networks for Remaining Useful Life Prediction in Mechanical Systems".
  ☆83Updated 6 years ago
• jiaxiang-cheng / PyTorch-CNN-for-RUL-Prediction
  PyTorch implementation of CNN for remaining useful life prediction. Inspired by Babu, G. S., Zhao, P., & Li, X. L. (2016, April). Deep co…
  ☆91Updated 3 years ago
• AiZhanghan / deep-learning-fault-diagnosis
  ☆60Updated 5 years ago
• matheuscnali / bearing_rul_predict
  ☆50Updated 2 years ago
• Ali-Alhamaly / Turbofan_usefull_life_prediction
  given run to failure measurements of various sensors on a sample of similar jet engines, estimate the remaining useful life (RUL) of a ne…
  ☆65Updated 5 years ago
• cathysiyu / Mechanical-datasets
  ☆270Updated 7 years ago
• Litchiware / cwru
  ☆166Updated 3 years ago
• beifengchuizoudemeng / CWRU
  ☆104Updated 5 years ago
• jiaxiang-cheng / PyTorch-Transformer-for-RUL-Prediction
  Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo…
  ☆262Updated 3 years ago
• zhmou / Turbofan-engine-RUL-prediction
  RUL prediction for C-MAPSS dataset, reproduction of this paper: https://personal.ntu.edu.sg/xlli/publication/RULAtt.pdf
  ☆101Updated 2 years ago
• mathworks / WindTurbineHighSpeedBearingPrognosis-Data
  Data set for Wind Turbine High-Speed Bearing Prognosis example in Predictive Maintenance Toolbox
  ☆52Updated 3 years ago
• ZhaoZhibin / Probabilistic_RUL_Prediction
  ☆65Updated 4 years ago
• schwxd / LSTM-Keras-CMAPSS
  Using LSTM to predict Remaining Useful Life of CMAPSS Dataset
  ☆88Updated 6 years ago
• tvhahn / weibull-knowledge-informed-ml
  Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
  ☆154Updated 2 years ago
• ZhenghuaNTU / RUL-prediction-using-attention-based-deep-learning-approach
  ☆56Updated 2 years ago
• wangfin / 1DCNN_Fault_Detection
  1DCNN Fault Detection（1DCNN的轴承故障诊断）
  ☆169Updated 3 years ago
• TL-UESTC / Domain-Adaptive-Remaining-Useful-Life-Prediction-with-Transformer
  Pytorch implementation for Domain Adaptive Remaining Useful Life Prediction with Transformer
  ☆69Updated 2 years ago
• opensuh / GMFE
  Generalized Multiscale Feature Extraction for Remaining Useful Life Prediction of Bearings with Generative Adversarial Networks
  ☆41Updated 3 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.
  ☆83Updated 3 years ago