Study on real-time prediction and warning technology for negative acceleration flight test of civil airplanes

Abstract

The flight test of modern civil aircraft verifies the limits of aircraft design performance through a series of rigorous flight tests. Flight test mission is characterized by high risk and complex technology. The negative acceleration flight test is to verify that the aircraft power unit, auxiliary power unit, or any component or system related to it shall not have dangerous faults during negative acceleration. The risk level of negative acceleration flight test is high-risk. This paper presents a real-time prediction and alarm technology for negative acceleration flight test of civil airliners. Firstly, a fusion simulation system for the flight test scene of negative acceleration was developed. The accuracy verification results indicate that the system can meet the requirements of engineering applications. Secondly, the main factors that affect the negative acceleration flight test are given through theoretical analysis, which provides a guidance for simulation. Finally, the negative acceleration prediction model based on compensation factor is established by using BP neural network algorithm and XGBoost algorithm. And the real-time prediction and alarm program of negative acceleration flight test is developed, which is used in negative acceleration flight test of a certain civil aircraft. The prediction results indicate that the accuracy of real-time prediction and alarm program can meet the requirements of flight test monitoring.

Keywords

• negative acceleration flight test
• real-time prediction and warning
• bp neural network
• xgboost algorithm