kokikwbt / predictive-maintenance
Datasets for Predictive Maintenance
☆110Updated last year
Alternatives and similar repositories for predictive-maintenance:
Users that are interested in predictive-maintenance are comparing it to the libraries listed below
- collection of predictive maintenance solutions for NASAs turbofan (CMAPSS) dataset☆131Updated 4 years ago
- This repository contains code that implement common machine learning algorithms for remaining useful life (RUL) prediction.☆177Updated last month
- In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbo…☆145Updated 2 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.☆77Updated last year
- ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification☆29Updated last year
- This repository contains data and code that implement common machine learning algorithms for machinery condition monitoring task.☆88Updated last month
- Papers and datasets for Vibration Analysis☆139Updated last week
- A notebook tutorial series for performing predictive maintenance using machine learning☆143Updated 4 years ago
- Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).☆146Updated last year
- This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.☆124Updated 3 years ago
- Python codes “Jupyter notebooks” for the paper entitled "A Hybrid Method for Condition Monitoring and Fault Diagnosis of Rolling Bearings…☆69Updated 8 months ago
- Anomaly detection on the UC Berkeley milling data set using a disentangled-variational-autoencoder (beta-VAE). Replication of results as …☆66Updated 3 years ago
- N-CMAPSS data preparation for Machine Learning and Deep Learning models. (Python source code for new CMAPSS dataset)☆81Updated last year
- RUL prediction for C-MAPSS dataset, reproduction of this paper: https://personal.ntu.edu.sg/xlli/publication/RULAtt.pdf☆94Updated last year
- A collection of datasets for RUL estimation as Lightning Data Modules.☆42Updated 8 months ago
- This is a repository of sample codes and implementation framework for industrial machine predictive maintenance tasks using deep learning…☆27Updated 8 months ago
- Dashboard designed to demonstrate the power of Machine Learning to predict failures (Remaining Useful Life (RUL)) in wind turbines. To pr…☆44Updated 2 years ago
- remaining Useful Life (RUL) Prediction of Mechanical Bearings using Continuous Wavelet Transform (CWT), Convolution Neural Network (CNN),…☆142Updated 10 months ago
- Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo…☆243Updated 3 years ago
- A curated list of datasets, publically available for machine learning research in the area of manufacturing☆150Updated 2 years ago
- RUL prediction for Turbofan Engine (CMAPSS dataset) using CNN☆109Updated 4 years ago
- The code of DAST☆54Updated 2 years ago
- Predictive Maintenance System for Digital Factory Automation☆43Updated 5 years ago
- This project is about predictive maintenance with machine learning. It's a final project of my Computer Science AP degree.☆57Updated 2 years ago
- remaining useful life, residual useful life, remaining life estimation, survival analysis, degradation models, run-to-failure models, con…☆27Updated 3 years ago
- Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine☆237Updated 4 years ago
- Baseline study on the development of predictive maintenance techniques using open data. Two problems are discussed: classifying a vibrati…☆20Updated 3 years ago
- University Project for Anomaly Detection on Time Series data☆81Updated 7 months ago
- Remaining Useful Life Prediction Using RNN/LSTM/GRU Neural Networks☆126Updated 3 years ago
- Supporting material and website for the paper "Anomaly Detection in Time Series: A Comprehensive Evaluation"☆75Updated 10 months ago