Simulation study on multi-factor characteristic judgment of aircraft hard landing

Abstract

Abstract: Aiming at the low accuracy of aircraft hard landing recognition rate of domestic airlines, and the high false rate and miss rate of hard landing recognition, an improved AdaBoostSVM algorithm hard landing recognition model is proposed. On the basis of fully considering the relevant factors of hard landing, in order to improve the recognition rate of aircraft hard landing, the compressive stroke characteristic of main landing gear buffer pillar is used as the hard landing diagnostic index, adjusting the evaluation coefficients of AdaBoostSVM algorithm weak classifier and increasing the weight of weak classifier with high ability for recognizing hard landing. At the same time, the actual sample data of airlines fleet is simulated and verified, and the accuracy and reliability of hard landing recognition of three algorithms are compared. Simulation results show that in the case of sufficient sample, the improved AdaBoostSVM algorithm could significantly improve the accuracy of hard landing events recognition, reducing the false rate and miss rate of aircraft hard landing as well as security risks of aircraft flight and cutting down airlines爷maintenance cost, having strong practical engineering value.

Key words: aircraft, hard landing, multi-factor characteristic, recognition rate, AdaBoostSVM

CLC Number:

JIA Baohui, YING Chenwei, WANG Yuxin. Simulation study on multi-factor characteristic judgment of aircraft hard landing[J]. .

References

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