CN116303378A - A method and device for eliminating errors in flight test data - Google Patents

Abstract

The application belongs to the technical field of flight test data processing, and in particular relates to a method and device for eliminating errors in flight test data. The method includes step S1, obtaining flight test data composed of a plurality of flight test parameters sorted by time; step S2, removing outliers in the flight test data based on the second-order forward difference algorithm; step S3, for the flight test data after removing the outliers, The flight test parameter point where the outlier value is located is corrected by using the Lagrangian interpolation formula; step S4, low-pass digital filtering is performed on the corrected flight test data. This application identifies, eliminates and corrects the outliers caused by factors such as unstable test equipment, external interference, and operator errors. At the same time, low-pass digital filtering is used to filter out high-frequency components in the flight test data, making the test or flight test data The identification and analysis results are more accurate, providing accurate parameter information for engineering practice.

Description

Method and device for eliminating flight test data errors

technical field

The present application belongs to the technical field of flight test data processing, and in particular relates to a method and device for eliminating errors in flight test data.

Background technique

Due to the influence of many factors such as the complexity of the aircraft system itself and flight conditions, the non-ideality of sensors and data acquisition systems, and the imperfection of flight test design, the actual flight measurement data inevitably contains uncertain random errors. These errors will affect the interpretation, analysis and use of flight parameters. Therefore, before using the actual flight measurement data to work, the actual measurement data must be preprocessed to eliminate various errors introduced during the measurement process, and it is convenient for the analysis and analysis of the test data. deal with.

Contents of the invention

In order to solve the above problems, this application designs a method and device for eliminating errors in flight test data, which is used to design the aircraft system architecture model verification method, and eliminate various errors introduced in the measurement process through data processing, so as to facilitate the test data. Analysis, processing.

The first aspect of the present application provides a method for eliminating flight test data errors, which mainly includes:

Step S1, obtaining flight test data composed of multiple flight test parameters sorted by time;

Step S2, removing outliers in the flight test data based on the second-order forward differential algorithm;

Step S3, for the flight test data after removing the outliers, use the Lagrangian interpolation formula to correct the flight test parameter points where the outliers are located;

Step S4, performing low-pass digital filtering on the corrected flight test data.

Preferably, step S2 further includes:

Step S21, calculating the corrected values of the original values of each flight test parameter in the flight test data;

Step S22, calculating the absolute value of the difference between the correction value and the original value;

Step S23, if the absolute value is greater than or equal to the set value, then determine the original value of the flight test parameter as an outlier value.

Preferably, in step S23, when calculating the absolute value of the original value and the difference of the kth flight test parameter, the set value is:

为第i个试飞参数的修正值。Among them, y _i is the original value of the i-th flight test parameter,

is the correction value of the i-th flight test parameter.

Preferably, step S4 further includes:

Obtain the measured sampling period of the flight test data and the preset cut-off frequency of the low-pass filter;

Determine the coefficient matrix of the low-pass filter based on the butter function of matlab;

constructing a filter difference equation based on the coefficient matrix;

Low-pass digital filtering is performed on each flight test parameter in the flight test data based on the differential equation.

The second aspect of the application provides a flight test data error elimination device, mainly including:

The flight test data acquisition module is used to obtain flight test data composed of multiple flight test parameters sorted by time;

The outlier removal module is used to remove outliers in the flight test data based on the second-order forward difference algorithm;

The outlier correction module is used to correct the flight test parameter point where the outlier is located by using the Lagrangian interpolation formula for the flight test data after the outlier is removed;

The filtering module is used for performing low-pass digital filtering on the corrected flight test data.

Preferably, the outlier removal module includes:

The correction value calculation unit is used to calculate the correction value of the original value of each flight test parameter in the flight test data;

A difference calculation unit, which calculates the absolute value of the difference between the correction value and the original value;

The outlier judging unit is configured to judge the original value of the flight test parameter as an outlier if the absolute value is greater than or equal to the set value.

Preferably, in the outlier determination unit, when calculating the absolute value of the original value of the kth flight test parameter and the difference, the set value is:

为第i个试飞参数的修正值。Among them, y _i is the original value of the i-th flight test parameter,

is the correction value of the i-th flight test parameter.

Preferably, the filter module includes:

The parameter extraction unit is used to obtain the actual sampling period of the flight test data and the preset cut-off frequency of the low-pass filter;

A coefficient matrix calculation unit, used to determine the coefficient matrix of the low-pass filter based on the butter function of matlab;

A differential equation design unit, configured to construct a filter differential equation based on the coefficient matrix;

A low-pass digital filtering unit, configured to perform low-pass digital filtering on various flight test parameters in the flight test data based on the differential equation.

This application identifies, eliminates and corrects the outliers caused by factors such as unstable test equipment, external interference, and operator errors. At the same time, low-pass digital filtering is used to filter out high-frequency components in the flight test data, making the test or flight test data The identification and analysis results are more accurate, providing accurate parameter information for engineering practice.

Description of drawings

Fig. 1 is a flow chart of a preferred embodiment of the flight test data error elimination method of the present application.

Fig. 2 is a flow chart of identifying and eliminating outliers in a preferred embodiment of the present application.

Fig. 3 is an effect diagram of removing outliers and low-pass filtering in the present application.

Detailed ways

In order to make the objectives, technical solutions and advantages of the implementation of the application clearer, the technical solutions in the implementation manners of the application will be described in more detail below in conjunction with the drawings in the implementation manners of the application. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some, but not all, embodiments of the present application. The embodiments described below by referring to the figures are exemplary and are intended to explain the present application, and should not be construed as limiting the present application. Based on the implementation manners in this application, all other implementation manners obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application. Embodiments of the present application will be described in detail below in conjunction with the accompanying drawings.

Due to the complexity of the aircraft system itself and flight conditions, the non-ideality of sensors and data acquisition systems, the imperfection of flight test design and many other factors, the actual flight measurement data is introduced into various errors during the measurement process. The purpose of the invention is to Eliminate various errors introduced in the measurement process through data processing, and facilitate the analysis and processing of test data.

The first aspect of the present application provides a method for eliminating flight test data errors, as shown in Figure 1, which mainly includes:

Step S1. Obtain flight test data composed of multiple flight test parameters sorted by time.

Step S2, removing outliers in the flight test data based on the second-order forward difference algorithm.

During the flight test, due to the unstable operation of the test instrument, the signal occasionally jumps, the influence of external abnormal interference, and the operator's error, etc., often lead to some very unreasonable jump points in the measurement data, which are called wild value. If the outliers are not excluded from the test data, the analysis of the test data must be incorrect, so the outliers must be eliminated and corrected during the data preprocessing process.

In some optional implementation manners, step S2 further includes:

Step S21, calculating the corrected values of the original values of each flight test parameter in the flight test data;

Step S22, calculating the absolute value of the difference between the correction value and the original value;

Step S23, if the absolute value is greater than or equal to the set value, then determine the original value of the flight test parameter as an outlier value.

In this embodiment, the seven-point second-order forward difference algorithm is used to predict and judge outliers, and the formula used is as follows:

为第i个试飞参数的修正值。在计算第k个试飞参数的原值与差值的绝对值时，E为恒定设定值，若点k满足下式，则将其判断为野值并将其剔除。Use formula (1) to calculate the correction value of the first six points, use formula (2) to calculate the correction value of the remaining points, where y _i is the original value of the i-th flight test parameter,

is the correction value of the i-th flight test parameter. When calculating the absolute value of the original value and the difference of the kth flight test parameter, E is a constant set value. If point k satisfies the following formula, it will be judged as an outlier value and eliminated.

为第i个试飞参数的修正值。Among them, y _i is the original value of the i-th flight test parameter,

is the correction value of the i-th flight test parameter.

Step S3 , for the flight test data after removing the outliers, use the Lagrangian interpolation formula to correct the flight test parameter points where the outliers are located.

In order to ensure the integrity of the flight test data, it is necessary to correct the eliminated outlier points. Most of the actual data outlier points are continuous points, but generally the number of continuous outlier points does not exceed 3, here let m=3.

In this paper, the Lagrangian interpolation formula is used to correct the outlier points.

Among them, t is the time, which is used to correct the outlier value of the lth point in formula (4), and _tl is the flight test data collection time of the lth point, and the meanings of other parameters are the same.

The process of identifying, eliminating and correcting outliers is shown in Figure 2.

Step S4, performing low-pass digital filtering on the corrected flight test data.

Flight test data often contain high-frequency components, so spectrum analysis should be performed on the measured data to analyze unreasonable high-frequency components. Since the motion frequency of the rigid body dynamics system is relatively low, these high-frequency components are also high-frequency noise. The existence of high-frequency noise will seriously affect the application of flight parameters such as the accuracy of aerodynamic parameter identification, so these high-frequency noises should be The usual method is to design a low-pass digital filter to filter it out.

In order to enable the low-pass filter to process different types of aircraft and different sampling frequency flight measured data, in some optional implementations, designing a fourth-order low-pass filter, that is, step S4 further includes:

Obtain the measured sampling period of the flight test data and the preset cut-off frequency of the low-pass filter;

Determine the coefficient matrix of the low-pass filter based on the butter function of matlab;

constructing a filter difference equation based on the coefficient matrix;

Low-pass digital filtering is performed on each flight test parameter in the flight test data based on the differential equation.

When designing the filter parameters, first determine the sampling period T _S of the flight measured data and the cut-off frequency f _c of the digital low-pass filter. According to T _S , f _c is calculated to obtain parameter ω _n :

ω _s =2×π/T _s ω _c =2×π×f _c

Use the matlab instruction: [B, A] = butter (4, ω _n , 'low'), to get the designed low-pass filter coefficient matrix A and B. Then write the difference equation of the filter according to the A and B matrices:

为滤波后的数据。Among them, y is the data before filtering,

is the filtered data.

Finally, the effect after outlier removal and low-pass filtering is shown in Figure 3. Figure 3 shows that this application reduces the impact of flight test data errors, and facilitates later analysis, processing and use of test data.

The second aspect of the present application provides a flight test data error elimination device corresponding to the above method, mainly including:

The flight test data acquisition module is used to obtain flight test data composed of multiple flight test parameters sorted by time;

The outlier removal module is used to remove outliers in the flight test data based on the second-order forward difference algorithm;

The outlier correction module is used to correct the flight test parameter point where the outlier is located by using the Lagrangian interpolation formula for the flight test data after the outlier is removed;

The filtering module is used for performing low-pass digital filtering on the corrected flight test data.

In some optional implementation manners, the outlier removal module includes:

The correction value calculation unit is used to calculate the correction value of the original value of each flight test parameter in the flight test data;

A difference calculation unit, which calculates the absolute value of the difference between the correction value and the original value;

The outlier judging unit is configured to judge the original value of the flight test parameter as an outlier if the absolute value is greater than or equal to the set value.

In some optional implementation manners, in the outlier determination unit, when calculating the absolute value of the original value and the difference of the kth flight test parameter, the set value is:

为第i个试飞参数的修正值。Among them, y _i is the original value of the i-th flight test parameter,

is the correction value of the i-th flight test parameter.

In some optional implementation manners, the filtering module includes:

The parameter extraction unit is used to obtain the actual sampling period of the flight test data and the preset cut-off frequency of the low-pass filter;

A coefficient matrix calculation unit, used to determine the coefficient matrix of the low-pass filter based on the butter function of matlab;

A differential equation design unit, configured to construct a filter differential equation based on the coefficient matrix;

A low-pass digital filtering unit, configured to perform low-pass digital filtering on various flight test parameters in the flight test data based on the differential equation.

This application identifies, eliminates and corrects the outliers caused by factors such as unstable test equipment, external interference, and operator errors. At the same time, low-pass digital filtering is used to filter out high-frequency components in the flight test data, making the test or flight test data The identification and analysis results are more accurate, providing accurate parameter information for engineering practice.

Although the present application has been described in detail with general descriptions and specific implementations above, it is obvious to those skilled in the art that some modifications or improvements can be made on the basis of the present application. Therefore, the modifications or improvements made on the basis of not departing from the spirit of the present application all belong to the protection scope of the present application.

Claims (8)

1. A flight test data error elimination method is characterized in that, comprising: Step S1, obtaining flight test data composed of multiple flight test parameters sorted by time; Step S2, removing outliers in the flight test data based on the second-order forward differential algorithm; Step S3, for the flight test data after removing the outliers, use the Lagrangian interpolation formula to correct the flight test parameter points where the outliers are located; Step S4, performing low-pass digital filtering on the corrected flight test data. 2. flight test data error elimination method as claimed in claim 1, is characterized in that, step S2 further comprises: Step S21, calculating the corrected values of the original values of each flight test parameter in the flight test data; Step S22, calculating the absolute value of the difference between the correction value and the original value; Step S23, if the absolute value is greater than or equal to the set value, then determine the original value of the flight test parameter as an outlier value. 3. flight test data error elimination method as claimed in claim 2, is characterized in that, in step S23, when calculating the absolute value of the original value of the kth flight test parameter and difference, described setting value is:

Among them, y _i is the original value of the i-th flight test parameter,

is the correction value of the i-th flight test parameter. 4. flight test data error elimination method as claimed in claim 1, is characterized in that, step S4 further comprises: Obtain the measured sampling period of the flight test data and the preset cut-off frequency of the low-pass filter; Determine the coefficient matrix of the low-pass filter based on the butter function of matlab; constructing a filter difference equation based on the coefficient matrix; Low-pass digital filtering is performed on each flight test parameter in the flight test data based on the differential equation. 5. A flight test data error elimination device is characterized in that, comprising: The flight test data acquisition module is used to obtain flight test data composed of multiple flight test parameters sorted by time; The outlier removal module is used to remove outliers in the flight test data based on the second-order forward difference algorithm; The outlier correction module is used to correct the flight test parameter point where the outlier is located by using the Lagrangian interpolation formula for the flight test data after the outlier is removed; The filtering module is used for performing low-pass digital filtering on the corrected flight test data. 6. flight test data error elimination device as claimed in claim 5, is characterized in that, described outlier removal module comprises: The correction value calculation unit is used to calculate the correction value of the original value of each flight test parameter in the flight test data; A difference calculation unit, which calculates the absolute value of the difference between the correction value and the original value; The outlier judging unit is configured to judge the original value of the flight test parameter as an outlier if the absolute value is greater than or equal to the set value. 7. flight test data error eliminating device as claimed in claim 6, is characterized in that, in described outlier judging unit, when calculating the original value of kth flight test parameter and the absolute value of difference, described setting value for:

Among them, y _i is the original value of the i-th flight test parameter,

is the correction value of the i-th flight test parameter. 8. flight test data error elimination device as claimed in claim 5, is characterized in that, described filtering module comprises: The parameter extraction unit is used to obtain the actual sampling period of the flight test data and the preset cut-off frequency of the low-pass filter; A coefficient matrix calculation unit, used to determine the coefficient matrix of the low-pass filter based on the butter function of matlab; A differential equation design unit, configured to construct a filter differential equation based on the coefficient matrix; A low-pass digital filtering unit, configured to perform low-pass digital filtering on various flight test parameters in the flight test data based on the differential equation.

Images