@inproceedings{fcef4022e15d48c4b178950582a91294,
title = "Satellite Fault Detection and Diagnosis based on Data Compression and Improved Decision Tree",
abstract = "Human exploration of space is always ongoing, and satellites play a huge role in this process. Therefore, the stable operation of satellites is very important, and how to detect and diagnose satellite faults has become a key issue. This paper presents a method based on data compression and improved decision tree algorithm, which has improved in both the accuracy and efficiency of satellite fault diagnosis and detection. In the experiment, we used the actually collected communication satellite telemetry data as the original data set to verify the performance and efficiency of the method proposed in this article. The results show that our method can save computing resources and significantly improve model training efficiency; at the same time, it can also resist overfitting and improve detection accuracy. This method can provide an effective solution for satellite fault detection and diagnosis.",
keywords = "data compression, decision tree, fault detection, fault diagnosis",
author = "Yanyan Hao and Chen Zhang and Senchun Chai and Zhaoyang Li and Xiaopeng Liu",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Chinese Automation Congress, CAC 2020 ; Conference date: 06-11-2020 Through 08-11-2020",
year = "2020",
month = nov,
day = "6",
doi = "10.1109/CAC51589.2020.9326615",
language = "English",
series = "Proceedings - 2020 Chinese Automation Congress, CAC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1686--1691",
booktitle = "Proceedings - 2020 Chinese Automation Congress, CAC 2020",
address = "United States",
}