Outlier elimination method and system based on fuzzy prediction system, and computer related product

A fuzzy prediction and fuzzy system technology, applied in fuzzy logic-based systems, calculations, aircraft parts, etc., can solve problems such as outlier identification accuracy and real-time performance are not ideal, unable to adapt to the diversity of flight parameter changes, etc. Adaptive tracking capability, wide application range, and the effect of reducing complexity

Pending Publication Date: 2021-06-15
BEIJING JUN MAO GUO XING TECH CO LTD
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  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to propose a method for eliminating outliers of data frames, so as to solve the problem that the accuracy and real-time performance of outlier identification are still not ideal due to the diversity of flight parameter changes in the prior art

Method used

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  • Outlier elimination method and system based on fuzzy prediction system, and computer related product
  • Outlier elimination method and system based on fuzzy prediction system, and computer related product
  • Outlier elimination method and system based on fuzzy prediction system, and computer related product

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specific example

[0070] The number of rules for constructing the fuzzy system is M=12, the number of residual sequences for identifying outliers using Dixon's criterion is n=4, and ε=0.02.

[0071] Select parameters with step and continuous changes for preprocessing, the results are as follows Figure 4 , Figure 5 shown. Figure 4 The sequence shown has a step characteristic with a false detection probability of 0.6%. Figure 5 The sequence shown is a continuously changing smooth curve with a false detection probability of 6.12%.

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Abstract

The invention provides an outlier elimination method and system based on a fuzzy prediction system, and a computer related product, and solves the problem that the outlier identification accuracy and real-time performance are still not ideal because the prior art cannot adapt to the diversity of flight parameter changes. The outlier elimination method based on the fuzzy prediction system comprises the following steps: 1) constructing a time sequence fuzzy prediction system at a moment k on line; 2) obtaining a predicted value at a k + 1 moment based on the time sequence fuzzy prediction system, and calculating a residual error between the predicted value and an observed value; 3) determining whether the residual error at the k + 1 moment is an abnormal value or not according to the Dick's criterion by using the residual error sequence before the k + 1 moment; if the residual error at the k + 1 moment is an abnormal value, determining that the current observation value is an outlier, and removing the outlier; otherwise, reserving the observed value and the residual error. The method has no special requirements on signals, is suitable for outlier elimination of various signals, and is wide in application range.

Description

technical field [0001] This application mainly relates to a method for eliminating outliers of flight data. Background technique [0002] Flight data such as speed, position, altitude, acceleration, and pressure measured by airborne sensors are all completed in dynamic measurement, and contain a large number of measured physical quantities, measurement and control equipment and systems, and external environmental interference. The observed data contains a large number of data points that seriously deviate from the true value of the measured value, and these abnormal data are called outliers. The existence of outliers seriously affects the reading and analysis of signals, especially in the fusion analysis of flight path and attitude, which seriously affects the calculation accuracy of simulation, and seriously affects the display effect of flight trajectory in real-time command display, causing misjudgment and other problems. [0003] In the article "Research on Aircraft Fli...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/215G06F16/2458G06N7/02B64D45/00
CPCG06F16/215G06F16/2465G06F16/2474G06N7/02B64D45/00
Inventor 王豪
Owner BEIJING JUN MAO GUO XING TECH CO LTD
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