Alternatives and similar repositories for 1d-based-DCNN:

Users that are interested in 1d-based-DCNN are comparing it to the libraries listed below

• tianyushou / bearingRUL
  Using LSTM to predict bearings' remaining useful life
  ☆47Updated 4 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
• 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
• sivaji1233 / 09_turbofan_rul
  Remaining useful life prediction for turbofan engine data (C-MAPSS)
  ☆33Updated 5 years ago
• Christopher-bit / tcn_tool_wear
  Real time tool wear monitoring method based on a TCN model for PHM-2010 Dataset.
  ☆10Updated 2 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
• ddrrrr / projectRUL2
  ☆66Updated 4 years ago
• UtkarshPanara / Remaining-Useful-Life-Prediction-for-Turbofan-Engines
  RUL prediction for Turbofan Engine (CMAPSS dataset) using CNN
  ☆113Updated 4 years ago
• AiZhanghan / deep-learning-fault-diagnosis
  ☆60Updated 5 years ago
• abiodun-ayodeji / Attention_based_MultiHead_model_for_aircraft_engine_RUL_prediction_
  Attention-based multihead model for optimized aircraft engine remaining useful life prediction
  ☆54Updated 11 months ago
• lankuohsing / Remaining-Useful-Life-Prediction-RNN
  Remaining Useful Life Prediction Using RNN/LSTM/GRU Neural Networks
  ☆138Updated 3 years ago
• opensuh / GMFE
  Generalized Multiscale Feature Extraction for Remaining Useful Life Prediction of Bearings with Generative Adversarial Networks
  ☆40Updated 2 years ago
• ddrrrr / projectRUL
  to prediction the remain useful life of bearing based on 2012 PHM data
  ☆282Updated 4 years ago
• Abhijit-Bhumireddy99 / RUL_Prediction
  remaining Useful Life (RUL) Prediction of Mechanical Bearings using Continuous Wavelet Transform (CWT), Convolution Neural Network (CNN),…
  ☆159Updated last year
• 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…
  ☆147Updated 3 years ago
• OneBugMaker / PHM-RUL-Prediction-by-EM
  Remain useful life prediction of rolling bearing.
  ☆57Updated 4 years ago
• cputnam / FEMTO
  Spark - Bearing RUL Predictions
  ☆19Updated 8 years ago
• Junkun-Lu / RUL_Inception-Attention
  Remaining useful life prediction by Transformer-based Model
  ☆48Updated 2 years ago
• MrTangsai / BearLSTM
  with LSTM method to solve bearing fault diagnosis classification
  ☆61Updated 7 years ago
• schwxd / LSTM-Keras-CMAPSS
  Using LSTM to predict Remaining Useful Life of CMAPSS Dataset
  ☆87Updated 6 years ago
• foryichuanqi / RESS-Paper-2022.09-Remaining-useful-life-prediction-by-TaFCN
  The source code of paper: Trend attention fully convolutional network for remaining useful life estimation in the turbofan engine PHM of …
  ☆56Updated 2 years ago
• KodeWorker / phm-rul-estimation
  case study for remaining useful life estimation
  ☆31Updated last year
• songyer / Fault_Diagnosis
  基于深度学习的滚动轴承故障诊断方法
  ☆189Updated 6 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
• GXL-123 / Bearing-fault-Diagnosis-based-on-deep-learning
  基于深度学习的机械设备故障诊断方法研究
  ☆37Updated 2 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
  ☆96Updated 2 years ago
• Andy-design-code / Bayesian-MCMC-Prognostics
  this code implements the Bayesian-MCMC based prognostics model. PHM2010 data challenge data are used to verifty the model.
  ☆18Updated 4 years ago
• ZhenghuaNTU / RUL-prediction-using-attention-based-deep-learning-approach
  ☆55Updated 2 years ago
• win-z / diagnosis_of_rotating_machinery
  基于无监督和迁移学习的旋转机械故障诊断
  ☆32Updated 5 years ago
• Soyen-Song / DA-TCN-RUL
  ☆21Updated 4 years ago