Flight test data missing value filling method based on wavelet denoising optimization

A flight test and wavelet denoising technology, applied in the field of data processing, can solve the problem of low filling accuracy of missing values ​​in flight test data, and achieve the effect of improving wavelet denoising accuracy, ensuring integrity, and improving filling accuracy.

Pending Publication Date: 2022-07-01
XIDIAN UNIV
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Problems solved by technology

[0007] The purpose of the present invention is to aim at the above-mentioned deficiencies in the prior art, propose a kind of flight test data missing value filling method based on wavelet denoising optimization, be used to solve the problems in the flight test data in the prior art under the condition of low signal-to-noise ratio The technical problem of low filling accuracy of missing values

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  • Flight test data missing value filling method based on wavelet denoising optimization
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  • Flight test data missing value filling method based on wavelet denoising optimization

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[0025] The present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the present invention complies with the provisions of Article 2, Item 2 of the Patent Law, and at the same time does not belong to the non-granting of patents stipulated in Article 25 of the Patent Law. subject of rights.

[0026] refer to figure 1 , the present invention comprises the steps:

[0027] Step 1, perform linear regression filling on the flight test data f(n) with missing values:

[0028] Step 1a) Initialize the time series value n that contains Q missing data in the unprocessed flight test data f(n) of length N m ={n m (1),n m (2),...,n m (q),...,n m (Q)} and the time-series values ​​n for the K nonmissing data o ={n o (1),n o (2),...,n o (k),...,n o (K)}, and construct each missing data time series value n m (q) The nearest L non-missing data time series values ​​around x=[n o (k),n o (k...

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Abstract

The invention provides a flight test data missing value filling method based on wavelet denoising optimization. The method is used for solving the technical problem that in the prior art, flight test data missing value filling precision is low under the condition of a low signal-to-noise ratio. The method comprises the following implementation steps of: performing local linear regression filling on flight test data f (n) with missing values; performing wavelet denoising on the complete flight test data g (n) after the initial filling; acquiring flight test data y (n) after the flight test data missing value is filled; according to the method, a multi-filling thought is adopted, after a rough estimation result of a missing value is obtained by adopting a local linear regression filling method with relatively good stability, a fine estimation result of a final missing value is obtained by combining wavelet denoising with a segmented cubic Hermite interpolation method; the problem that the filling precision of the missing value of the flight test data is low under the condition of low signal-to-noise ratio in the prior art is solved.

Description

technical field [0001] The invention belongs to the technical field of data processing, and relates to a method for filling missing values ​​of flight test data, in particular to a method for filling missing values ​​of flight test data based on wavelet denoising optimization. Background technique [0002] Flight test data refers to the actual measurement data generated by the aviation equipment during the test flight process, the speed, position, altitude, acceleration, pressure and other internal sensor data measured by the sensors on the aviation equipment during the test flight process, as well as the measurement data of external measurement equipment such as radar. composition, usually presented as time-series data that is highly correlated with time. The follow-up analysis and research based on flight test data is the necessary means and key link for the development of aviation equipment models and application technology research. However, in the actual data collectio...

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Application Information

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IPC IPC(8): G06F16/215G06F17/18G06F17/15
CPCG06F16/215G06F17/18G06F17/15
Inventor 禄晓飞徐竟翔左磊赵政赵民刘佳琪李治国高永婵
Owner XIDIAN UNIV
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