Dataset for Validation of Hybrid Tans-level Model Learning Strategy of Multi-component Systems
Description
Enclose are two datasets: The first dataset is a collection of system output of a simulative multi-component systems containing a paralell structure and a curcuit for closed-loop control. The dataset contains 500 samples dispersed across the operation regime of the system, this dataset is meant to testify the capability of Hybrid Trans-level Model Learning Strategy ( HTMLS) to overcome measurement dificiency and generate high-fidelity models for components; The second dataset is a industrial dataset generated by a commercial twin-shaft turbofan engine, which produced about 33000 lbs thrust for aircrafts. This data set also contains 500 samples of the thermal-dynamical reading inside the engine, which characterized the profile of the steady cruise state of this type of engine. This dataset was meant to validate the modeling accuracy and efficiency of HTMLS.
Files
Steps to reproduce
Both datasets are unique and unreproducable.
Institutions
- Harbin Institute of Technology