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1. Introduction to C-MAPSS Dataset

In the field of fault diagnosis and predictive maintenance (PHM), the research on remaining life prediction methods based on artificial intelligence algorithms such as machine learning is extremely popular. Among them, the C-MAPSS dataset is widely used in this field. In order to facilitate the learning and understanding of colleagues, this article will give you a brief introduction.

1.1 Data characteristics

First of all, the C-MAPSS data set is simulated data. This is because the structure of aircraft engines is complex, and their gas path changes are complex and changeable; and the operating data of aircraft engines during flight and take-off and landing are usually confidential data of various airlines and are generally not easy to obtain. Therefore, NASA Generated using Commercial Modular Aero-Propulsion System Simulation software The purpose of this dataset is to test the performance of different models in combination with the operating characteristics of the engine.

1.2 Data Partitioning

2. Pytorch life prediction simple test</