GitHub topics: remaining-useful-life-prediction
RamtinMoslemi/RUL-Papers
An awesome list of papers on remaining useful life (RUL) prediction from arXiv
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VedantModhave/Nasa-Turbofan-Anomaly-Dashboard
An interactive dashboard for analyzing the NASA Turbofan Engine dataset to detect anomalies and predict remaining useful life (RUL).
Language: Python - Size: 60.5 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

tilman151/rul-datasets
A collection of datasets for RUL estimation as Lightning Data Modules.
Language: Python - Size: 1.13 MB - Last synced at: about 23 hours ago - Pushed at: over 1 year ago - Stars: 47 - Forks: 2

lucianolorenti/ceruleo
CeRULEo: Comprehensive utilitiEs for Remaining Useful Life Estimation methOds
Language: Python - Size: 84.1 MB - Last synced at: 4 days ago - Pushed at: about 1 year ago - Stars: 29 - Forks: 6

mriusero/predictive-maintenance-on-industrial-robots
This project develops predictive maintenance models for industrial robots in nuclear fuel replacement, leveraging data analytics, machine learning, and decision-making frameworks to optimize robot fleet management and extend operational uptime. Key phases include data exploration, feature engineering, RUL prediction, and maintenance decision-making
Language: Python - Size: 2.03 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0

Neel-Dandiwala/Lithium-Batteries-RUL-ANN
An artificial neural network (ANN) based method is developed for achieving more accurate remaining useful life prediction of Lithium Ion batteries subject to condition monitoring. The ANN model takes the capacity attribute as a target against multiple measurement values as the inputs, and the life expectancy as the output.
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XiuzeZhou/RUL
Transformer Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
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Abhijit-Bhumireddy99/RUL_Prediction
remaining Useful Life (RUL) Prediction of Mechanical Bearings using Continuous Wavelet Transform (CWT), Convolution Neural Network (CNN), and Long Short Term Memory (LSTM) unit
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foryichuanqi/ADVEI-Paper-2024.3-Degradation-path-approximation-for-remaining-useful-life-estimation
Remaining useful life prediction. Degradation path approximation (DPA) is a highly easy-to-understand and brand-new solution way for data-driven RUL prediction. Many research directions on DPA can be further studied.
Language: Python - Size: 1.24 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

adam-aalah/Feature-clustering-and-XAI-for-RUL-estimation
Feature clustering and XIA for RUL estimation
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KiKi0016/State-of-Health-Estimation-of-Electric-Vehicle-Batteries-Using-DeTransformer
Deep learning of lithium-ion battery SOH using the DeTransformer model learns the aging characteristics of the battery and then makes predictions about the battery SOH in order to monitor the health of batteries in electric vehicles.
Language: Python - Size: 77.1 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

XinyuanLiao/AttnPINN-for-RUL-Estimation
A Framework for Remaining Useful Life Prediction Based on Self-Attention and Physics-Informed Neural Networks
Language: Python - Size: 5.11 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 39 - Forks: 7

xxl4tomxu98/NASA-Jet-Engine-Maintenance
ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification
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Eason0227/Turbofan-Engine-Remaining-Useful-Life-Prediction
Remaining Useful Life Prediction
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delta1epsilon/turbofan-remaining-life-prediction
Remaining Useful Life (RUL) prediction for Turbofan Engines
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mohyunho/NAS_transformer
Evolutionary Neural Architecture Search on Transformers for RUL Prediction
Language: Python - Size: 15.4 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 13 - Forks: 3

Eng-Ismail7/Forecasting-and-classification-of-mechanical-faults
predictive-maintenance-fault-classification(CWRU data)-and-remaining-useful-life(NASA’s Turbofan Engine )
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mohyunho/N-CMAPSS_DL
N-CMAPSS data preparation for Machine Learning and Deep Learning models. (Python source code for new CMAPSS dataset)
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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 CMAPSS dataset. Signal selection, Attention mechanism, and Interpretability of deep learning are explored.
Language: Python - Size: 50.5 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 19 - Forks: 1

zhmou/Turbofan-engine-RUL-prediction
RUL prediction for C-MAPSS dataset, reproduction of this paper: https://personal.ntu.edu.sg/xlli/publication/RULAtt.pdf
Language: Python - Size: 52.4 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 24 - Forks: 2

mohyunho/MOO_ELM
Multi-Objective Optimization of ELM for RUL Prediction
Language: Python - Size: 224 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 7 - Forks: 1

ShubhankarKG/RUL_Prediction_SVM
Bearing remaining useful life prediction using support vector machine and hybrid degradation tracking model - Implementation of Research Paper : https://doi.org/10.1016/j.isatra.2019.08.058
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kaushikmupadhya/Anomaly-Detection-in-Time-Series-Data
Anomaly Detection in Time Series Data using Autoencoders approach.
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