Flight control capability simple evaluation method

Abstract

The invention discloses a flight control capability simple evaluation method, and belongs to the technical field of civil aviation flight. Flight actions are determined based on flight training essence, index evaluation and weight are clear, an evaluation calculation formula is formulated, and the method is simple, convenient, feasible, high in applicability and scientific and objective in result.The method does not need to use a complex mathematical model, does not need to change frequently after determining the flight action and the evaluation index weight, is simple and convenient in calculation, is suitable for various different flight subjects, is high in generalization, is scientific and objective in evaluation result, and is high in credibility.

Description

technical field [0001] The invention relates to the technical field of civil aviation flight, in particular to a simple and convenient evaluation method for flight control ability. Background technique [0002] The existing prior art closest to the present invention is the pilot flight quality evaluation model based on fuzzy logic proposed in the article "Pilot Flight Quality Evaluation Based on Fuzzy Logic" by Zhang Long and Xu Kaijun of Civil Aviation Flight Academy of China. This model establishes a flight quality evaluation index system based on the summary and analysis of a large number of literature and the study of simulated flight and real flight data, and then uses fuzzy logic theory to establish a pilot flight quality evaluation model based on fuzzy logic. The flight quality of the final approach phase is evaluated. The characteristic of this method is that the physiological signal data of pilot students and flight parameters are used for flight quality evaluation...

AI Technical Summary

Problems solved by technology

[0003] The existing technology evaluates the flight control ability by establishing the membership function and the fuzzy rule base. The calculation is relatively complicated. The accuracy of the evaluation results depends on whether the membership function and the fuzzy rule base are perfect. In the case of small data samples, the evaluation results There is a certain discrepancy with the actual situation; the physiological signal data used in the existing technology needs to be collected by the tested person carrying multiple personal sensors, and the data collection is difficult

The sensors carried are likely to affect the operation of the test personnel on the aircraft during the actual flight, and cannot fully reflect the test personnel's driving ability

Due to the actions of the test personnel performing aircraft manipulation and the turbulence of the aircraft, personal sensors often fall off and have poor contact, resulting in the loss of some physiological data, which will eventually lead to discrepancies between the evaluation results and the actual situation

This model can only be evaluated for a specific flight subject. If you want to evaluate other flight subjects, you need to re-establish the evaluation model, and the generalization is weak

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