Dataset for Validation of Tans-Layer Model Learning of Multi-component Systems

Enclose are two datasets:
The first dataset is a industrial dataset generated by a commercial twin-shaft turbofan engine, which produced about 33000 lbs thrust for aircrafts. This data set 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 Trans-Layer Model Learning ( TLML).
The second dataset is 10 collections of system output of a simulative multi-component systems containing a paralell structure and a curcuit for closed-loop control. each collection contains 500 samples dispersed across the operation regime of the system, this dataset is meant to testify the capability of TLML to overcome measurement dificiency and generate high-fidelity models for components;

本卷收录了两大数据集：首项数据集为商业双轴涡轮风扇发动机所生成的工业数据集，该发动机为飞机提供约33000磅的推力。该数据集包含了500个样本，记录了发动机内部的温度动力学读数，这些读数描绘了此类发动机稳态巡航状态下的特性轮廓。本数据集旨在验证跨层模型学习（TLML）的建模精度与效率。次项数据集则由包含并行结构和闭环控制电路的模拟多组件系统输出组成，共分为10个集合。每个集合包含了500个样本，这些样本分散于系统的操作域内。该数据集旨在证明TLML克服测量困难并生成高保真模型的能力。