基于训练飞行的数据可视化及飞行动作划分

Data Visualization and Flight Action Division Based on Training Flight

本文在飞行训练数据的基础上,使用Python可视化平台建立飞行曲线模型,通过参数曲线的形式对飞机的参数进行综合可视化,基于训练飞机的着陆特性,使用俯仰角为主,无线电高度和垂直加速度为辅的方式对Cessna172的接地点进行识别。通过制定飞行动作的划分规则,使用卷积平滑后的数据将飞行数据划分成飞行动作片段,然后利用飞行动作片段的组成特征进行飞行科目的识别,根据可视化后的结果,证明基于时间序列片段的飞行科目识别方法具有可行性。

Based on the flight training data,this paper uses the python visualization platform to establish a flight curve model,and comprehensively visualize the parameters of the aircraft in the form of parameter curves.Based on the landing characteristics of the training aircraft,the pitch angle is mainly used,and the radio altitude and vertical acceleration are Auxiliary way to identify the grounding point of Cessna172.By formulating the rules for dividing flight actions,the flight data is divided into flight action segments using the convolutional smoothed data,and then the composition characteristics of the flight action segments are used to identify the flight subjects.According to the visualized results,it is proved that the time series segment The method of identifying flight subjects is feasible.