Alternatives and similar repositories for Industrial_BigData_Competition_2017:

Users that are interested in Industrial_BigData_Competition_2017 are comparing it to the libraries listed below

• ultimatejoe / rul_of_cutter
  刀具剩余寿命预测
  ☆71Updated 5 years ago
• zhbink / 2017-IndustryBigData
  2017工业大数据 风机叶片预测
  ☆54Updated 4 years ago
• schwxd / LSTM-Keras-CMAPSS
  Using LSTM to predict Remaining Useful Life of CMAPSS Dataset
  ☆87Updated 6 years ago
• yyxyz / CaseWesternReserveUniversityData
  ☆137Updated 7 years ago
• pinlank / kdxf2019top2
  2019科大讯飞工程机械赛题-亚军
  ☆39Updated 5 years ago
• ninja1mmm / 2018-phm-data-challenge
  2018 phm data challenge, ion mill machine RUL & fault diagnosis
  ☆68Updated 6 years ago
• mathworks / WindTurbineHighSpeedBearingPrognosis-Data
  Data set for Wind Turbine High-Speed Bearing Prognosis example in Predictive Maintenance Toolbox
  ☆50Updated 3 years ago
• Litchiware / cwru
  ☆166Updated 3 years ago
• fee78520 / Bearing-fault-prediction
  轴承有3种故障：外圈故障，内圈故障，滚珠故障，外加正常的工作状态。如表1所示，结合轴承的3种直径（直径1,直径2,直径3），轴承的工作状态有10类
  ☆32Updated 6 years ago
• xiaosongshine / bearing_detection_by_conv1d
  [深度应用]·DC竞赛轴承故障检测开源Baseline（基于Keras1D卷积 val_acc:0.99780）
  ☆185Updated 5 years ago
• luanshiyinyang / DataMiningProject
  包含一些比较常见的数据挖掘竞赛或者项目的源码
  ☆124Updated 5 years ago
• zhangxiaoling / Bearing-fault-detection
  轴承故障检测 训练赛第30名代码
  ☆127Updated 5 years ago
• MrTangsai / BearLSTM
  with LSTM method to solve bearing fault diagnosis classification
  ☆61Updated 7 years ago
• lankuohsing / Remaining-Useful-Life-Prediction-RNN
  Remaining Useful Life Prediction Using RNN/LSTM/GRU Neural Networks
  ☆138Updated 3 years ago
• shanpoqq / DiagnosisDL2TF
  使用TensorFlow建立简单的轴承故障诊断模型
  ☆101Updated 7 years ago
• raady07 / CNN-for-bearing-fault-diagnosis
  CNN applied to bearing signals for analysis
  ☆88Updated 5 years ago
• tashrifbillah / Remaining-Useful-Life-Estimation-of-Rocket-Engines
  Similarity matching based remaining useful life estimation
  ☆29Updated 7 years ago
• yanghedada / yang
  start tests
  ☆23Updated 6 years ago
• AiZhanghan / deep-learning-fault-diagnosis
  ☆60Updated 5 years ago
• Vardoom / PredictiveMaintenanceNASA
  LSTM Neural Network to predict NASA's engines failure based on know failures and parameters.
  ☆22Updated 7 years ago
• dou52885288 / Lstm_fault_detection
  fault detection in wind turbines
  ☆15Updated 4 years ago
• rz0718 / MHMS_DEEPLEARNING
  ☆93Updated 4 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
• iszeke / wind-turbine-phm
  for wind turbine phm
  ☆15Updated 6 years ago
• sabderra / predictive-maintenance-lstm
  Predicting the Remaining Useful Life (RUL) of simulated turbofan data using Keras and LSTM.
  ☆36Updated 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
• caidongqi / CNN-based_CWRU_Bearing_Fault_Diagonis
  Analysis of CWRU Bearing Data Set and Development of WeChat Mini Program Interface
  ☆44Updated 3 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
• soham97 / Remaining_useful_life_NASA
  RUL Nasa Turbofan Dataset (paper)
  ☆26Updated 4 years ago
• woshiyiduohua / paper-reading
  故障诊断方面的论文阅读
  ☆16Updated 5 years ago