Unmanned aerial vehicle flight quality assessment method and device, storage medium and electronic equipment

Abstract

The invention relates to an unmanned aerial vehicle flight quality assessment method and device, a storage medium and electronic equipment. The method comprises the steps of obtaining a first index data set of a target unmanned aerial vehicle in a to-be-evaluated time period; Performing data preprocessing on the first index data set to obtain a second index data set; For each index sequence in thesecond index data set, performing secondary data processing on the index sequence according to the index characteristics of the index sequence to obtain a third index data set; And determining an evaluation value of each index value in each index sequence corresponding to the to-be-evaluated index in the third index data set. Therefore, the magnitude of each index value in the index sequence canreflect the advantages and disadvantages of the corresponding index, it can be ensured that the subsequently determined evaluation value of each index value is more accurate and visual, and a user canconveniently and accurately evaluate the flight quality of the target unmanned aerial vehicle. And a control system simulation model does not need to be constructed, so that time and labor are saved.In addition, the user can identify the flight fault of the unmanned aerial vehicle according to the combination of different evaluation values.

Description

technical field [0001] The present disclosure relates to the field of unmanned aerial vehicles, in particular, to a method, device, storage medium and electronic equipment for evaluating the flight quality of unmanned aerial vehicles. Background technique [0002] With the development of the UAV industry, users have higher and higher requirements for UAV products. Being able to accurately know the flight quality of UAVs is helpful for the identification of UAV flight failures, prediction of crash rates, and flight control strategies. Optimization has positive guiding significance. [0003] At present, the flight quality evaluation of UAVs is mainly carried out in the following two ways: (1) The flight quality of UAVs is evaluated by experienced personnel actually observing the flight status of no aircraft or checking the flight data of UAVs. The evaluation is easily affected by subjective factors, and the evaluation standards are not uniform; (2) By building a control syste...

AI Technical Summary

Problems solved by technology

Among them, ordinary normalization is to map the index data to the [0,1] interval, and ensure that the data size and interval ratio remain unchanged, but this method is not applicable to some indicators of drones, for example, accelerometer vibration indicators , because the accelerometer itself carries a lot of vibration and noise, its value is too large or too small may be faulty data, after ordinary normalization, the quality of the data is not reflected in the data size at the data processing level

The support vector machine algorithm has a good effect on the processing of binary classification problems, but it has certain difficulties in processing overly complex classification problems, and the neural network needs a large amount of sample data as training support to achieve a better result.

In the case of poor data preprocessing and limited sample data, it is difficult to achieve the desired effect by applying the above method to evaluate the flight quality of UAVs.

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