The NASA CMAPSS Turbofan Engine RUL Dataset provides multivariate time-series sensor data generated from a high-fidelity simulation. It is designed to support research in predictive maintenance, specifically for estimating the Remaining Useful Life (RUL) of aircraft engines as they degrade over time.
Use Cases
- Predicting Remaining Useful Life (RUL) of industrial equipment
- Developing anomaly detection algorithms for sensor streams
- Benchmarking time-series regression models
- Studying engine degradation trajectories
Strengths
- Standard industry benchmark for predictive maintenance
- Provides complex multivariate sensor trajectories
- Simulates realistic engine degradation patterns
Limitations
- Based on simulation (C-MAPSS) rather than real-world flight data
- Specific column metadata and units are not provided in this source summary
Provenance
- Source
- NASA
- Collection Method
- Commercial Modular Aero-Propulsion System Simulation (C-MAPSS)