kpeters / exploring-nasas-turbofan-datasetLinks
collection of predictive maintenance solutions for NASAs turbofan (CMAPSS) dataset
☆133Updated 4 years ago
Alternatives and similar repositories for exploring-nasas-turbofan-dataset
Users that are interested in exploring-nasas-turbofan-dataset are comparing it to the libraries listed below
Sorting:
- This repository contains code that implement common machine learning algorithms for remaining useful life (RUL) prediction.☆195Updated 5 months ago
- RUL prediction for Turbofan Engine (CMAPSS dataset) using CNN☆116Updated 4 years ago
- Source code of the paper "A stacked DCNN to predict the RUL of a turbofan engine", third place ranked in the PHM21 data challenge.☆84Updated 2 years ago
- N-CMAPSS data preparation for Machine Learning and Deep Learning models. (Python source code for new CMAPSS dataset)☆91Updated 2 years ago
- 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
- RUL prediction for C-MAPSS dataset, reproduction of this paper: https://personal.ntu.edu.sg/xlli/publication/RULAtt.pdf☆101Updated 2 years ago
- Remaining Useful Life Prediction Using RNN/LSTM/GRU Neural Networks☆141Updated 3 years ago
- 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
- Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).☆154Updated 2 years ago
- Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine☆242Updated 4 years ago
- Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo…☆262Updated 3 years ago
- Remaining useful life prediction for turbofan engine data (C-MAPSS)☆34Updated 5 years ago
- Using LSTM to predict Remaining Useful Life of CMAPSS Dataset☆88Updated 6 years ago
- Code used in Thesis "Convolutional Recurrent Neural Networks for Remaining Useful Life Prediction in Mechanical Systems".☆83Updated 6 years ago
- This is a repository of sample codes and implementation framework for industrial machine predictive maintenance tasks using deep learning…☆28Updated last year
- ☆50Updated 2 years ago
- ☆99Updated last year
- remaining Useful Life (RUL) Prediction of Mechanical Bearings using Continuous Wavelet Transform (CWT), Convolution Neural Network (CNN),…☆167Updated last year
- ☆56Updated 2 years ago
- In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbo…☆144Updated 2 years ago
- A collection of datasets for RUL estimation as Lightning Data Modules.☆47Updated last year
- 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
- Remaining useful life estimation of NASA turbofan jet engines using data driven approaches which include regression models, LSTM neural n…☆30Updated 3 years ago
- Predict remaining useful life of a machine from it's historical data using CNN and LSTM☆32Updated 6 years ago
- One model for RUL and fault prognostic prediction on XJTU bearing dataset☆95Updated 5 years ago
- Remaining Useful Life (NASA CMAPS Dataset)☆44Updated 6 years ago
- ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification☆30Updated last year
- LSTM Neural Network to predict NASA's engines failure based on know failures and parameters.☆23Updated 7 years ago
- Pytorch implementation for Domain Adaptive Remaining Useful Life Prediction with Transformer☆69Updated 2 years ago
- Predicting the Remaining Useful Life (RUL) of simulated turbofan data using Keras and LSTM.☆36Updated 6 years ago