Research on Fault Detection Method of FADS System
| Autor: | Qianlei Jia, Jingping Shi, Guangwen Li, Weiguo Zhang, Xiaoxiong Liu |
|---|---|
| Jazyk: | čínština |
| Rok vydání: | 2020 |
| Předmět: |
Basis (linear algebra)
Computer science Noise (signal processing) simulatio 020208 electrical & electronic engineering General Engineering parity equation TL1-4050 02 engineering and technology Aerodynamics 021001 nanoscience & nanotechnology Fault (power engineering) computer.software_genre Fault detection and isolation fault detection chi-square χ2 distribution ALARM 0202 electrical engineering electronic engineering information engineering flush air data sensing(fads) Data mining 0210 nano-technology Cfd software computer Motor vehicles. Aeronautics. Astronautics |
| Zdroj: | Xibei Gongye Daxue Xuebao, Vol 38, Iss 6, Pp 1210-1217 (2020) |
| ISSN: | 2609-7125 1000-2758 |
| Popis: | In order to solve the fault detection problem of flush air data sensing (FADS), an advanced airborne sensor, a new method is proposed in this paper. First, the high-precision FADS model is established on the basis of the database obtained from the CFD software and aerodynamics knowledge. Then, the distribution characteristics of each group of signals under fault condition are derived through strict formulas. Meanwhile, the threshold of alarm times is designed with statistical knowledge. For verifying the effectiveness of the newly proposed method, a comparison with other two widely adopted methods, including the methods based on parity equation and Chi-square χ2 distribution, is conducted under different measurement noise. Simulation results show that the proposed fault detection method for FADS possess higher accuracy and stronger anti-interference. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|