CN114966171A - A method and system for splicing lightning effect test waveforms - Google Patents

Abstract

The application relates to a lightning effect test waveform splicing method and a system, wherein the lightning effect test waveform splicing method comprises the following steps: waveform discrete data combinations of A waves, B waves, C waves and D waves of lightning impulse current components are obtained through a lightning impulse current component generating device and a collecting device, data processing is carried out on the collected waveform discrete data combinations to obtain splicing data with uniform and continuous data distribution, and the splicing data are displayed by using logarithmic coordinates; the data processing comprises the following steps of signal amplification, offset removal, filtering, down sampling, peak value detection, edge pulse width calculation, data splicing, polynomial interpolation and the like. The invention integrates the tests of different current component combinations into one system, thus greatly improving the test efficiency of the test; the problem of uneven thickness caused by sampling difference of different current component data is solved by adopting a weighted average algorithm; the problem of discontinuous splicing of current components is solved by adopting polynomial interpolation; the data display adopts logarithmic coordinates to solve the problem of uneven distribution of current components.

Description

A method and system for splicing lightning effect test waveforms

technical field

The application belongs to the technical field of aviation lightning protection experiments, and in particular relates to a method and a splicing system for testing waveforms of lightning effects.

Background technique

The aircraft lightning direct effect test divides the simulated lightning impulse current into several different components, and selects different current components and their combinations according to the lightning attachment area for testing.

There are four types of current components: A wave, B wave, C wave, and D wave. The current component A is the initial peak current, the peak value is 200kA, and the duration is less than or equal to 500μs; the current component B is the intermediate current, the average amplitude is 2kA, and the duration is less than or equal to 5ms; the current component C is the continuous current, the duration is 0.25 to 1s; the current component D is the repetitive discharge current, the peak value is 100kA, and the duration is less than or equal to 500μs.

The lightning attachment area includes 5 areas: 1A, 1B, 2A, 2B, and 3. Area 1A is a surface with a high initial lightning attachment probability and a high probability of the position of the attachment point changing with time, and the A and B components are used for the combined test; area 1B is a surface with a high initial lightning attachment probability and a low probability of changing the position of the attachment point with time. Surface, using A, B, C, D component combination test; area 2A is a surface with a high probability of lightning being blown through by the airflow from the initial attachment point position and a higher probability of the attachment point position changing with time, using B, C, D component combination test; area 2B is a surface with a high probability of lightning being blown through by the airflow from the initial attachment point position and a lower probability of the attachment point position changing with time, using the B, C, D component combination test; area 3 is the remaining surface, using the A, C component combination test.

At present, in the prior art, four generators A, B, C, and D are used to output the four current components of the test respectively, and then the waveform is obtained through the acquisition device to verify the reliability of the test. There are generally two collection methods:

Each generating device uses a separate acquisition device, which can capture the waveform characteristics of a single current component, but cannot acquire the characteristics of the combination of components;

All generating devices use one acquisition device, which can capture the characteristics of the current component combination, but the capture waveform is discontinuous and cannot obtain the waveform characteristics of each current component.

SUMMARY OF THE INVENTION

In order to solve the above deficiencies in the prior art, the present invention provides a method and system for splicing lightning effect test waveforms.

The technical scheme adopted by the present invention to solve the above-mentioned technical problems is:

A method for splicing waveforms for lightning effect testing. The waveform discrete data combination of A wave, B wave, C wave and D wave of lightning impulse current components is obtained through a lightning impulse current component generating device and a collecting device, and the collected waveform discrete data combination is collected. The stitched data with uniform and continuous data distribution is obtained by processing, and the stitched data is displayed using logarithmic coordinates.

Preferably, in the lightning effect test waveform splicing method of the present invention, the data processing comprises the following steps:

Signal amplification, converting the waveform discrete data combination into an actual waveform combination by A1=A0/μ, A1 represents the actual waveform data combination, A0 represents the collected waveform discrete data combination, and μ represents the current attenuation coefficient;

To remove the offset, use the arithmetic mean for the 0-10% data segment of A1 to obtain the average offset X, and subtract the average offset X from A1 to obtain the waveform data combination A2 after the offset is removed;

Filtering, using the moving average filtering algorithm for A2 to obtain the filtered waveform data combination A3;

Downsampling, using the weighted average algorithm for A3 to reduce the number of samples to obtain the data combination A4;

Peak detection, use the peak detection algorithm to find the peak point for A4, and traverse A4 in the reverse direction with the peak point as the starting point, take 90% of the peak points as tr90, 50% of the peak points as tr50, 10% of the peak points as tr10, and take the peak point as The starting point traverses A4 in the forward direction, and takes the 50% peak point as tt50;

Edge pulse width calculation, calculate the waveform rise time and pulse width according to the peak point in the peak detection step, rise time Tr=(tr90-tr10)/0.8, pulse width Td=(tr90-tr10)*0.5/0.8+(tt50- tr50);

Data splicing, according to the current component peak value, the rise time Tr and the pulse width Td to determine the current component type, and sort according to the order of A wave, B wave, C wave and D wave;

Polynomial interpolation is used to obtain the 0% peak point of the rising time period and the 0% peak point of the falling time period as the start and end points of the current component A wave and D wave by the peak detection method. If the 0% peak point of the fall time period is not obtained, Taking the end point of A4 as the 0% peak point of the falling time period, obtain the 95% peak point of the rising time period and the 95% peak point of the falling time period as the starting point and ending point of the B wave and C wave of the current components. Polynomial interpolation is performed between the endpoint and the end point.

Preferably, in the lightning effect test waveform splicing method of the present invention, the polynomial interpolation is an order linear interpolation.

The invention also provides a lightning effect test waveform splicing system, including a device driving module, a data processing module and a data display module, the device driving module is used for four lightning impulse current components A wave, B wave, C wave, The D-wave generating device and the acquisition device are controlled to obtain a discrete waveform data set. The data processing module performs data processing on the collected waveform discrete data set to obtain spliced data with uniform and continuous data distribution. The data display module uses logarithmic data. The coordinates show the processed waveform.

Preferably, in the lightning effect test waveform splicing system of the present invention, the data processing module includes the following submodules:

The signal amplification sub-module converts the waveform discrete data combination into an actual waveform combination through A1=A0/μ, A1 represents the actual waveform data combination, A0 represents the collected waveform discrete data combination, and μ represents the current attenuation coefficient;

De-offset quantum module, use arithmetic mean for 0-10% data segment of A1 to obtain the average offset X, and subtract the average offset X from A1 to obtain the waveform data combination A2 after the offset is removed;

The filtering sub-module uses the moving average filtering algorithm for A2 to obtain the filtered waveform data combination A3;

The down-sampling sub-module uses the weighted average algorithm for A3 to reduce the number of samples to obtain the data combination A4;

The peak detection sub-module uses the peak detection algorithm to find the peak point of A4, and traverses A4 in the reverse direction with the peak point as the starting point, taking 90% of the peak points as tr90, 50% of the peak points as tr50, and 10% of the peak points as tr10. The point is the starting point, traverse A4 in the forward direction, and take the 50% peak point as tt50;

The edge pulse width calculation sub-module calculates the waveform rise time and pulse width according to the peak point of the peak detection sub-module, the rise time Tr=(tr90-tr10)/0.8, and the pulse width Td=(tr90-tr10)*0.5/0.8+( tt50-tr50);

The data splicing sub-module judges the type of the current component according to the peak value of the current component, the rise time Tr and the pulse width Td, and sorts it in the order of A wave, B wave, C wave and D wave;

The polynomial interpolation sub-module uses the peak detection method to obtain the 0% peak value of the rising time period and the 0% peak value of the falling time period as the starting point and ending point of the current component A wave and D wave. If the 0% peak value of the falling time period is not obtained Take the end point of A4 as the 0% peak point of the falling time period, and obtain the 95% peak point of the rising time period and the 95% peak point of the falling time period as the starting point and ending point of the current component B wave and C wave. Polynomial interpolation is performed between the start and end points.

The beneficial effects of the present invention are:

The invention integrates the test of different current component combinations into one system, which greatly improves the test test efficiency; adopts the weighted average algorithm to solve the problem of uneven thickness caused by the difference of data sampling of different current components; adopts polynomial interpolation to solve the problem of current component splicing. Continuous problem; data show that the use of logarithmic coordinates solves the problem of uneven distribution of current components.

Description of drawings

The technical solutions of the present application will be further described below with reference to the accompanying drawings and embodiments.

Fig. 1 is the current component waveform diagram in the background technology of the present application;

Fig. 2 is the data processing step flow chart of the lightning effect test waveform splicing method of the embodiment of the present application;

Fig. 3 is the structural block diagram of the lightning effect test waveform splicing system of the embodiment of the present application;

FIG. 4 is a structural block diagram of a data processing module according to an embodiment of the present application.

Detailed ways

It should be noted that the embodiments in the present application and the features of the embodiments may be combined with each other in the case of no conflict.

The technical solutions of the present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

Example 1

This embodiment provides a method for splicing waveforms for lightning effect testing. The waveform discrete data combination of A wave, B wave, C wave and D wave of lightning impulse current components is obtained through a lightning impulse current component generating device and a collecting device, and the collected waveforms are discrete Perform data processing on data combination to obtain spliced data with uniform and continuous data distribution, and display the spliced data using logarithmic coordinates.

The data processing steps in this embodiment are as shown in Figure 2, and the details are as follows:

S1, signal amplification, convert the waveform discrete data combination into an actual waveform combination by A1=A0/μ, A1 represents the actual waveform data combination, A0 represents the collected waveform discrete data combination, and μ represents the current attenuation coefficient;

S2, remove the offset, use the arithmetic mean to obtain the average offset X of the 0-10% data segment of A1, and subtract the average offset X from A1 to obtain the waveform data combination A2 after the offset is removed;

S3, filtering, using the moving average filtering algorithm for A2 to obtain the filtered waveform data combination A3;

S4, downsampling, using the weighted average algorithm for A3 to reduce the number of samples to obtain the data combination A4;

S5, peak detection, use the peak detection algorithm to find the peak point on A4, and traverse A4 in reverse with the peak point as the starting point, take the 90% peak point as tr90, the 50% peak point as tr50, and the 10% peak point as tr10. The point is the starting point, traverse A4 in the forward direction, and take the 50% peak point as tt50;

S6, edge pulse width calculation, calculate the waveform rise time and pulse width according to the peak point in the peak detection step, the rise time Tr=(tr90-tr10)/0.8, the pulse width Td=(tr90-tr10)*0.5/0.8+( tt50-tr50);

S7, data splicing, according to the peak value of the current component, the rise time Tr and the pulse width Td to determine the type of the current component, and sort in the order of A wave, B wave, C wave, and D wave;

S8, polynomial interpolation, obtain the 0% peak value of the rising time period and the 0% peak value of the falling time period by the peak detection method as the starting point and end point of the current component A wave and D wave, if the 0% peak value of the falling time period is not obtained. Take the end point of A4 as the 0% peak point of the falling time period, and obtain the 95% peak point of the rising time period and the 95% peak point of the falling time period as the starting point and ending point of the current component B wave and C wave. Polynomial interpolation is performed between the start and end points.

The polynomial interpolation method described in this embodiment is first-order linear interpolation. In addition, parabolic interpolation and cubic polynomial interpolation can also be used. Polynomial interpolation can make the current component splicing continuous and complete.

Example 2

This embodiment provides a lightning effect test waveform splicing system, as shown in FIG. 3 .

The lightning effect test waveform splicing system includes a device driving module, a data processing module and a data display module, and the device driving module is used for generating devices for four lightning impulse current components A-wave, B-wave, C-wave and D-wave Control with the acquisition device to obtain waveform discrete data sets of A wave, B wave, C wave, and D wave, and the data processing module analyzes and processes the collected waveform discrete data set to obtain uniform and continuous splicing data with data distribution, so The data display module described above uses logarithmic coordinates to display the processed waveform.

The data processing module of this embodiment is shown in Figure 4, and specifically includes the following sub-modules:

The signal amplification sub-module converts the waveform discrete data combination into an actual waveform combination through A1=A0/μ, A1 represents the actual waveform data combination, A0 represents the collected waveform discrete data combination, and μ represents the current attenuation coefficient;

De-offset quantum module, use arithmetic mean for 0-10% data segment of A1 to obtain the average offset X, and subtract the average offset X from A1 to obtain the waveform data combination A2 after the offset is removed;

The filtering sub-module uses the moving average filtering algorithm for A2 to obtain the filtered waveform data combination A3;

The down-sampling sub-module uses the weighted average algorithm for A3 to reduce the number of samples to obtain the data combination A4;

The peak detection sub-module uses the peak detection algorithm to find the peak point of A4, and traverses A4 in the reverse direction with the peak point as the starting point, taking 90% of the peak points as tr90, 50% of the peak points as tr50, and 10% of the peak points as tr10. The point is the starting point, traverse A4 in the forward direction, and take the 50% peak point as tt50;

The edge pulse width calculation sub-module calculates the waveform rise time and pulse width according to the peak point of the peak detection sub-module, the rise time Tr=(tr90-tr10)/0.8, and the pulse width Td=(tr90-tr10)*0.5/0.8+( tt50-tr50);

The data splicing sub-module judges the type of the current component according to the peak value of the current component, the rise time Tr and the pulse width Td, and sorts it in the order of A wave, B wave, C wave and D wave;

The polynomial interpolation sub-module uses the peak detection method to obtain the 0% peak value of the rising time period and the 0% peak value of the falling time period as the starting point and ending point of the current component A wave and D wave. If the 0% peak value of the falling time period is not obtained Take the end point of A4 as the 0% peak point of the falling time period, and obtain the 95% peak point of the rising time period and the 95% peak point of the falling time period as the starting point and ending point of the current component B wave and C wave. Polynomial interpolation is performed between the start and end points.

Due to the large difference in the pulse widths of the current components A wave, B wave, C wave, and D wave, it is difficult to display the short pulse width current components (A and D current components) of less than or equal to 500 μs using a general coordinate axis. Therefore, this embodiment uses The logarithmic axis shows the spliced waveform data to make the above current flow distribution more uniform.

Taking the above ideal embodiments according to the present application as inspiration, and through the above descriptions, relevant personnel can make various changes and modifications without departing from the technical idea of the present application. The technical scope of the present application is not limited to the content in the description, and the technical scope must be determined according to the scope of the claims.

Claims (5)

1. A lightning effect test waveform splicing method is characterized in that waveform discrete data combinations of lightning impulse current components A waves, B waves, C waves and D waves are obtained through a lightning impulse current component generating device and a collecting device, data processing is carried out on the collected waveform discrete data combinations to obtain splicing data with uniform and continuous data distribution, and the splicing data are displayed by using logarithmic coordinates.

2. The lightning effect test waveform stitching method of claim 1, wherein the data processing comprises the steps of:

signal amplification, converting the waveform discrete data combination into an actual waveform combination through A1-A0/mu, wherein A1 represents the actual waveform data combination, A0 represents the acquired waveform discrete data combination, and mu represents a current attenuation coefficient;

de-offsetting, namely obtaining an average offset X by using arithmetic mean on 0-10% data segments of A1, and obtaining a waveform data combination A2 after removing the offset by subtracting the average offset X from A1;

filtering, namely obtaining a filtered waveform data combination A3 by using a moving average filtering algorithm for A2;

down-sampling, and reducing the number of samples of A3 by using a weighted average algorithm to obtain a data combination A4;

peak detection, namely solving a peak point of A4 by using a peak detection algorithm, reversely traversing A4 by taking the peak point as an initial point, taking 90% of the peak point as tr90, 50% of the peak point as tr50 and 10% of the peak point as tr10, forwardly traversing A4 by taking the peak point as the initial point, and taking 50% of the peak point as tt 50;

calculating the rising time and the pulse width of the waveform according to the peak point in the peak detection step, wherein the rising time Tr is (Tr90-Tr10)/0.8, and the pulse width Td is (Tr90-Tr10) × 0.5/0.8+ (tt50-Tr 50);

data splicing, namely judging the type of the current component according to the peak value, the rising time Tr and the pulse width Td of the current component, and sequencing according to the sequence of A waves, B waves, C waves and D waves;

and (3) polynomial interpolation, namely acquiring a peak value point of 0% of a rising time period and a peak value point of 0% of a falling time period as the starting point and the ending point of the A wave and the D wave of the current components in a peak value detection mode, if the peak value point of 0% of the falling time period is not acquired, taking the ending point of A4 as the peak value point of 0% of the falling time period, acquiring a peak value point of 95% of the rising time period and a peak value point of 95% of the falling time period as the starting point and the ending point of the B wave and the C wave of the current components, and performing polynomial interpolation between the starting point and the ending point of the current components.

3. The lightning effect test waveform stitching method of claim 2, wherein the polynomial interpolation is an order linear interpolation.

4. The utility model provides a lightning effect test waveform splicing system, its characterized in that includes equipment driver module, data processing module and data display module, equipment driver module is used for controlling generating device and the collection system of four thunder and lightning impulse current component A ripples, B ripples, C ripples, D ripples, acquires the discrete data set of waveform, data processing module carries out data processing to the discrete data set of waveform who gathers and obtains the even and continuous concatenation data of data distribution, data display module uses the wave form after logarithmic coordinate display handles.

5. The lightning effect test waveform stitching system of claim 4, wherein the data processing module comprises sub-modules that:

the signal amplification sub-module converts the waveform discrete data combination into an actual waveform combination through A1-A0/mu, A1 represents the actual waveform data combination, A0 represents the acquired waveform discrete data combination, and mu represents a current attenuation coefficient;

the offset removing submodule is used for obtaining an average offset X by using arithmetic mean on 0-10% data segments of A1, and the average offset X is subtracted from A1 to obtain a waveform data combination A2 after offset removal;

the filtering submodule obtains a filtered waveform data combination A3 by using a moving average filtering algorithm for A2;

the down-sampling submodule reduces the number of samples of A3 by using a weighted average algorithm to obtain a data combination A4;

the peak detection submodule is used for solving a peak point of A4 by using a peak detection algorithm, reversely traverses A4 by taking the peak point as a starting point, takes 90% of the peak point as tr90, 50% of the peak point as tr50 and 10% of the peak point as tr10, forwardly traverses A4 by taking the peak point as the starting point and takes 50% of the peak point as tt 50;

an edge pulse width calculation submodule for calculating a waveform rise time and a pulse width according to a peak point of the peak detection submodule, wherein the rise time Tr is (Tr90-Tr10)/0.8, and the pulse width Td is (Tr90-Tr10) × 0.5/0.8+ (tt50-Tr 50);

the data splicing submodule judges the type of the current component according to the peak value of the current component, the rising time Tr and the pulse width Td and sorts the current component according to the sequence of A waves, B waves, C waves and D waves;

and the polynomial interpolation sub-module acquires a peak point of 0% of a rising time period and a peak point of 0% of a falling time period as the starting point and the ending point of the A wave and the D wave of the current components in a peak detection mode, and acquires a peak point of 95% of the rising time period and a peak point of 95% of the falling time period as the starting point and the ending point of the B wave and the C wave of the current components by taking the ending point of A4 as the peak point of the falling time period and taking the starting point and the ending point of the B wave and the C wave of the current components if the peak point of 0% of the falling time period is not acquired, and performs polynomial interpolation between the starting point and the ending point of the current components.

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