FADS系统在背部进气布局机型的应用研究  

Application Research of FADS System in Dorsal Intake Layout Model

作　　者：傅奕涵 李鹏[1] 郭理想 FU Yihan;LI Peng;GUO Lixiang(School of Automation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)

机构地区：[1]南京航空航天大学自动化学院,南京211106

出　　处：《自动化与仪表》2024年第10期1-4,23,共5页Automation & Instrumentation

摘　　要：对于背部进气的飞行器,在借助嵌入式大气数据传感系统(FADS)解算大气参数时,当发动机工况不同时易产生不同的进气道流量,进而影响测压点压力值。该文针对背部进气的扁平头部飞行器提出了一种基于径向基神经网络的FADS系统算法,将进气道出口流量纳入了大气参数的解算因素。根据扁平头部特征确定了测压点配置,对马赫数、迎角、侧滑角建立了3个单输出RBF神经网络。将是否考虑发动机工况影响的两组神经网络解算结果进行了对比,结果表明,未考虑发动机工况影响的神经网络解算算法精度良好,考虑发动机工况影响的神经网络解算精度得到了进一步提高,马赫数、迎角、侧滑角绝对误差分别达到0.001Ma、0.15°和0.3°。For aircraft with dorsal intake,when using the flush air data sensing system(FADS)to calculate the atmosphere parameters,different engine working conditions may lead to different intake flow rates,which affect the pressure at the pressure measurement point.In this paper,a FADS system algorithm based on radial basis function(RBF)neural network was proposed for the flat head aircraft with dorsal intake.The outlet flow rate of the intake was added as one of the calculation factors for atmosphere parameters.The pressure measurement point configuration was determined based on the flat head characteristics of the aircraft.Three RBF neural networks with single output were established for Mach number,angle of attack and angle of sideslip respectively.The results of the two groups of neural network solutions were compared whether the engine working condition was taken into account.The simulation results showed that the neural network solution algorithm without taking the engine working condition into account had good accuracy,and the solution accuracy of the neural network considering the engine working condition was further improved,the absolute error of Mach number,the angle of attack and angle of sideslip reduced to 0.001 Ma,0.15°and 0.3°respectively.

关 键 词：嵌入式大气数据传感系统 背部进气 径向基神经网络 

分 类 号：TP216.1[自动化与计算机技术—检测技术与自动化装置]