@inproceedings{97dbf506c4e6406987677662eb2d149c,
title = "Research on the Fault Detection of FADS",
abstract = "During the flight, whether the fault of sensors is detected in time will directly affect the flight safety. The main contribution of the paper is to achieve the fault detection of flush air data sensing (FADS). First of all, a high-precision FADS model is established based on the aerodynamics data obtained from a CFD software and the aerodynamics knowledge under subsonic and supersonic conditions. Subsequently, the distribution characteristics of each group of signal under the fault condition are derived through strict formulas. Meanwhile, the threshold of alarm times is designed with statistical knowledge. Then, a representative fault case is adopted to demonstrate the method. For further confirming the validity and feasibility in the engineering practice, the comparison with other two existing methods, the parity equation and$$\chi ^2$$ distribution, is conducted.",
keywords = "Distribution, Fault detection, Flush air data sensing (FADS), Parity equation",
author = "Qianlei Jia and Weiguo Zhang and Guangwen Li and Jingping Shi and Jiayue Hu",
note = "Publisher Copyright: {\textcopyright} 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Guidance, Navigation and Control, ICGNC 2020 ; Conference date: 23-10-2020 Through 25-10-2020",
year = "2022",
doi = "10.1007/978-981-15-8155-7_220",
language = "英语",
isbn = "9789811581540",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "2625--2636",
editor = "Liang Yan and Haibin Duan and Xiang Yu",
booktitle = "Advances in Guidance, Navigation and Control - Proceedings of 2020 International Conference on Guidance, Navigation and Control, ICGNC 2020",
}