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Big data mining-based method for deleting flight parameter outliers in classified manner

A technology of flight parameters and big data, applied in data mining, electrical digital data processing, special data processing applications, etc., can solve the problems of complex calculation methods, long processing time, and large amount of calculation, so as to ensure accuracy and improve processing ability, the effect of meeting the needs of fault detection and normal processing of data

Active Publication Date: 2017-07-07
CHINA ACAD OF AEROSPACE AERODYNAMICS
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AI Technical Summary

Problems solved by technology

However, the above methods all have the disadvantages of large amount of calculation, long processing time or relatively complicated calculation method. When the flight data is large, it will take more time

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  • Big data mining-based method for deleting flight parameter outliers in classified manner
  • Big data mining-based method for deleting flight parameter outliers in classified manner
  • Big data mining-based method for deleting flight parameter outliers in classified manner

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Embodiment Construction

[0028] In the present invention, the unmanned aerial vehicle adopts GPS to realize navigation and positioning, and the data recorder records the GPS signal and other sensor signals during the flight, and when the unmanned aerial vehicle stops flying, the GPS data recorded in the data recorder is read out , for post processing and analysis. However, in GPS signals, unreasonable outliers are often encountered. Their existence will adversely affect the analysis of aircraft flight performance and interfere with people's understanding of aircraft performance. Therefore, before processing GPS data, it is necessary to first Outliers are processed to meet the needs of subsequent analysis.

[0029] like figure 1 As shown, a kind of method that the present invention provides is based on big data mining classification and eliminates the method of flight parameter outlier, and the steps are as follows:

[0030] (1) The present invention first needs to train the RBN neural network as the...

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Abstract

The invention provides a big data mining-based method for deleting flight parameter outliers in a classified manner. In a flight process of an aircraft, flight parameters are recorded in a flight recorder; and data contains illogical outliers, so that postmortem analysis requirements can be met by deleting the outliers. The flight data is regularly decomposed by adopting a data segmentation method; related data points can be quickly matched by utilizing a characteristic of curve fitting, and related statistical information is obtained; the statistical information of different flight parameters are combined into a variance set; flight parameter segments containing the outliers can be quickly identified by utilizing a radial basis neural network classification characteristic; then, for ill data segments, the positions of the outliers are quickly identified according to characteristics of maximum and minimum values and a mean value; and the subsequent process is performed in the same way, so that outlier points of all the data segments of the different flight parameters are obtained. The method adopts a big data mining thought, is different from a general method for mining the outliers by multi-point filtering, and has relatively high speed and accuracy especially for massive data containing the outlier points.

Description

technical field [0001] The invention provides a method for classifying and eliminating outliers of flight parameters based on big data mining, which belongs to the field of data processing in flight control systems and is mainly used in the outlier processing of flight data of unmanned aerial vehicles. Background technique [0002] In the UAV flight test, it is necessary to measure various flight parameters in the UAV flight and save them in the data recorder for later analysis. However, due to equipment or signal problems during the measurement, the recorded data contains outliers. If such outliers are not eliminated, it will have a great impact on the post-event analysis of aircraft performance. Therefore, it is necessary to take certain methods before data analysis. Eliminate outliers to ensure data integrity and reliability. [0003] In the existing outlier removal methods, multi-point smoothing filtering is generally used to calculate the prior mean value, and then the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06F17/17
CPCG06F16/2465G06F17/17G06F2216/03
Inventor 苏浩秦吕达宋璟舒胜林清尹永鑫胡强
Owner CHINA ACAD OF AEROSPACE AERODYNAMICS
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