NASA-CMAPSS-Turbofan is a dataset for prognostics and health management (PHM) research, originally published by NASA. It likely contains simulated sensor readings and operational settings from a fleet of turbofan engines run to failure. The dataset is hosted on Kaggle, but specific details on size, columns, and version are not provided in the metadata.
Use Cases
- Train a model to predict remaining useful life (RUL) of turbofan engines (inferred from domain, verify after download)
- Benchmark prognostics and health management (PHM) algorithms on a standard dataset (inferred from domain, verify after download)
- Analyze multivariate time-series sensor data for fault detection patterns (inferred from domain, verify after download)
Strengths
- Published by NASA, a recognized authority in aerospace research.
- Hosted on Kaggle, a major platform for data science and machine learning.
Limitations
- Metadata is minimal; actual content requires verification after download.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count, file formats, and license information are unknown.
Provenance
- Source
- NASA
- Collection Method
- Likely generated via the Commercial Modular Aero-Propulsion System Simulation (CMAPSS) software.