kpeters / exploring-nasas-turbofan-dataset
collection of predictive maintenance solutions for NASAs turbofan (CMAPSS) dataset
☆124Updated 3 years ago
Related projects: ⓘ
- This repository contains code that implement common machine learning algorithms for remaining useful life (RUL) prediction.☆162Updated last year
- RUL prediction for Turbofan Engine (CMAPSS dataset) using CNN☆95Updated 3 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.☆72Updated last year
- N-CMAPSS data preparation for Machine Learning and Deep Learning models. (Python source code for new CMAPSS dataset)☆72Updated last year
- RUL prediction for C-MAPSS dataset, reproduction of this paper: https://personal.ntu.edu.sg/xlli/publication/RULAtt.pdf☆85Updated last year
- given run to failure measurements of various sensors on a sample of similar jet engines, estimate the remaining useful life (RUL) of a ne…☆60Updated 5 years ago
- Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine☆220Updated 3 years ago
- Remaining Useful Life Prediction Using RNN/LSTM/GRU Neural Networks☆117Updated 2 years ago
- PyTorch implementation of remaining useful life prediction with long-short term memories (LSTM), performing on NASA C-MAPSS data sets. Pa…☆118Updated 3 years ago
- Remaining useful life prediction for turbofan engine data (C-MAPSS)☆29Updated 4 years ago
- ☆48Updated last year
- Predict remaining useful life of a machine from it's historical data using CNN and LSTM☆28Updated 5 years ago
- Remaining Useful Life (RUL) prediction for Turbofan Engines☆24Updated 2 years ago
- Using LSTM to predict Remaining Useful Life of CMAPSS Dataset☆80Updated 5 years ago
- ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification☆27Updated 9 months ago
- Predicting the Remaining Useful Life (RUL) of simulated turbofan data using Keras and LSTM.☆37Updated 5 years ago
- remaining Useful Life (RUL) Prediction of Mechanical Bearings using Continuous Wavelet Transform (CWT), Convolution Neural Network (CNN),…☆118Updated 5 months ago
- Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo…☆216Updated 2 years ago
- Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).☆129Updated last year
- ☆47Updated last year
- Code used in Thesis "Convolutional Recurrent Neural Networks for Remaining Useful Life Prediction in Mechanical Systems".☆77Updated 5 years ago
- The code of DAST☆49Updated last year
- Remaining useful life estimation of NASA turbofan jet engines using data driven approaches which include regression models, LSTM neural n…☆26Updated 2 years ago
- ☆73Updated 7 months ago
- This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.☆118Updated 3 years ago
- This is a repository of sample codes and implementation framework for industrial machine predictive maintenance tasks using deep learning…☆26Updated 3 months ago
- In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbo…☆131Updated 2 years ago
- PyTorch implementation of CNN for remaining useful life prediction. Inspired by Babu, G. S., Zhao, P., & Li, X. L. (2016, April). Deep co…☆76Updated 3 years ago
- Datasets for Predictive Maintenance☆97Updated 9 months ago
- Predict remaining useful life of a component based on historical sensor observations using automated feature engineering☆229Updated last year