商用模块化航空推进系统仿真数据集（CMAPSS）

C-MAPSS数据集通常用于工业健康指标时序预测，具体指标为RUL。待预测的指标是涡轮发动机能够进行运作的剩余工作循环次数。该数据是每个引擎在完全失效前通过21个传感器采集的全部时间序列。C-MAPSS数据集由四个子数据集组成。子数据集FD001和FD003有一个工作条件和一个或两种故障模式，而子数据集FD002和FD004有六种工作条件和一种或两种故障模式。每个子数据集被划分为训练集和测试集。在任意子数据集中，时间序列包含26列数据：引擎编号、当前已工作循环次数、三种操作设定和21个传感器数据。

The C-MAPSS dataset is widely utilized for industrial health indicator time-series forecasting, with the target metric being Remaining Useful Life (RUL). The metric to be predicted is the number of remaining operational cycles of a turbofan engine before it undergoes complete failure. This dataset contains full time-series data collected via 21 sensors for each engine prior to total engine failure. The C-MAPSS dataset is composed of four sub-datasets: sub-datasets FD001 and FD003 have one operating condition and one or two fault modes, while sub-datasets FD002 and FD004 feature six operating conditions and one or two fault modes. Each sub-dataset is partitioned into a training set and a test set. For any of the sub-datasets, the time-series includes 26 columns of data: engine ID, current total operational cycles, three operational settings, and 21 sensor readings.

搜集汇总

背景与挑战

背景概述

商用模块化航空推进系统仿真数据集（CMAPSS）主要用于工业健康指标时序预测，特别是涡轮发动机的剩余使用寿命（RUL）预测。该数据集包含四个子数据集，每个子数据集分为训练集和测试集，数据列包括引擎编号、工作循环次数、操作设定和21个传感器数据。