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).
- Data set name: NASA Turbojet (FD002)
- Train trjectories: 260
- Test trajectories: 259
- Conditions: SIX
- Fault Modes: ONE (HPC Degradation)
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:
- Unit number
- Time, in cycles
- Operational setting 1
- Operational setting 2
- Operational setting 3
- Sensor measurement 1
- Sensor measurement 2
... - Sensor measurement 26