├── Documentation
    └── Damage Propagation Modeling.pdf
└── README.md


/Documentation/Damage Propagation Modeling.pdf:
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https://raw.githubusercontent.com/hash-bash/NASA-Jet-Engine-RUL-Prediction-Notebook/HEAD/Documentation/Damage Propagation Modeling.pdf


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/README.md:
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 1 | # NASA Jet Engine Remaining Useful Life (RUL) Prediction Notebook
 2 | Prediction of Remaining Useful Life (RUL) using NASA Turbofan Jet Engine dataset with the help of libraries such as Numpy, Matplotlib and Pandas. Prediction is done by training a model using Keras (TensorFlow).
 3 | 
 4 | ### Dataset characteristics:
 5 | 
 6 |  - Data set name: NASA Turbojet (FD002)
 7 |  - Train trjectories: 260
 8 |  - Test trajectories: 259
 9 |  - Conditions: SIX
10 |  - Fault Modes: ONE (HPC Degradation)
11 | 
12 | ### Data is provided as a text file with 26 columns of numbers, separated by spaces. Each row is a snapshot of data taken during a single operational cycle, each column is a different variable. The columns correspond to:
13 | 
14 | - Unit number
15 | - Time, in cycles
16 | - Operational setting 1
17 | - Operational setting 2
18 | - Operational setting 3
19 | - Sensor measurement  1
20 | - Sensor measurement  2
21 | <br/>...<br/>
22 | - Sensor measurement  26
23 | 


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