Phase Division of Flight Data Based on Maximum Lyapunov Index

Abstract

In this paper, the flight phase partitioning method (FPPM) is proposed against the problems of low generalization and high training cost in the current flight phase division research. The method first utilize one-dimensional height data reflecting phase characteristics to complete phase space reconstruction (PSR), which aims to restore the original system dynamic characteristics in the phase space. Then the value of the maximum lyapunov index (MLI) of the reconstructed sequence at different stages is calculated to quantitatively describe the chaotic characteristics at each stage. Finally, different flight phases are distinguished according to the numerical difference in MLI of reconstruction sequences at each stages. Multiple real-life flight data from one certain model aircraft is exploited to verify the validity. The result shows that the FPPM can quickly and accurately identify the flight data at different stages, with strong practicability and generalization.