Research Of Algorithm Of The Flush Airdata Sensing (FADS) System

This dissertation mainly introduces a new airdata sensing system, which is the Flush Airdata Sensing (FADS) system. Based on this system, an integrated algorithm is designed and validated. In the first part of this paper, conventional airdata sensing system is introduced in brief. Then the concept of FADS system is put forward. To the two systems, virtues and disadvantages are discussed. And the trends of development of the FADS system in the world are mentioned. According to the model of the X-33 Flush Airdata Sensing System, we detailedly introduce the configuration, theory and algorithm. In the second part of this paper, the other structure of FADS system is brought forward. Then the algorithms applied in this structure are designed, including the algorithm of angle of attack and angle of sideslip, the algorithm of calibration parameter and the kalman algorithm of impact pressure and free stream static pressure. And the stability of kalman algorithm is analyzed. With wind tunnel data and emulate data, the integrated algorithms are validated. Lastly, the technologies of pretreatment which is fit to the FADS system are expatiated. These technologies are used to avoid some iffy data into algorithm. And we must do with abnormal situations and analyze the influences which are aroused by these situations. The abnormal situations includes data error and sensor fault. In terms of data error, we mainly discuss influences of impact pressure, free stream static pressure and calibration parameter. In terms of sensor fault, we chiefly talk about influence of free stream Mach number, impact pressure and free stream static pressure.