├── CMAPSSData ├── Damage Propagation Modeling.pdf ├── RUL_FD001.txt ├── RUL_FD002.txt ├── RUL_FD003.txt ├── RUL_FD004.txt ├── readme.txt ├── test_FD001.txt ├── test_FD002.txt ├── test_FD003.txt ├── test_FD004.txt ├── train_FD001.txt ├── train_FD002.txt ├── train_FD003.txt └── train_FD004.txt ├── LICENSE ├── PHM08 ├── Challenge Data Description 2016.pdf ├── final_test.txt ├── readme.txt ├── test.txt └── train.txt ├── Papers ├── Damage Propagation Modeling for Aircraft Engine Run-to-Failure Simulation.pdf ├── Deep Belief Network Based State Classification for Structural Health Diagnosis.pdf ├── Deep Convolutional Neural Network Based Regression Approach for Estimation of Remaining Useful Life.pdf ├── Deep Learning and Its Applications to Machine Health Monitoring A Survey.pdf ├── Ensemble of data-driven prognostic algorithms for robust prediction of remaining useful life.pdf ├── Estimation of Remaining Useful Life Based on Switching Kalman Filter Neural Network Ensemble.pdf ├── Health index synthetization and remaining useful life estimation for turbofan engines based on run-to-failure datasets.pdf ├── Long Short-Term Memory Network for Remaining Useful Life Estimation.pdf ├── Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks.pdf ├── Readme.pdf ├── Recurrent Neural Networks for Remaining Useful Life Estimation.pdf └── Review and Analysis of Algorithmic Approaches Developed for Prognostics on CMAPSS Dataset.pdf ├── README.md ├── data_processing.py ├── model.py ├── screenshots ├── CMAPSSData_snapshot.PNG ├── data_augmentation.PNG ├── piece-wise.gif ├── system_model.PNG ├── training_data_plot0103.PNG └── training_data_plot0204.PNG └── utils_laj.py /CMAPSSData/Damage Propagation Modeling.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LahiruJayasinghe/RUL-Net/HEAD/CMAPSSData/Damage Propagation Modeling.pdf 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