Data processing method for high-dynamic physical simulation system

Abstract

The invention relates to the technical field of data processing, in particular to a data processing method for a high-dynamic physical simulation system. The method comprises the following steps: acquiring continuous multi-frame infrared image data of a high-speed moving object; performing region division on the continuous multi-frame infrared image data to obtain real object region data and background region data of the object; identifying ghosting data in the real object region data; and correcting the ghost data to obtain target simulation analysis data. According to the embodiment of the invention, the method can achieve the data correction of the ghost shadow of the high-speed moving object, provides more accurate simulation experiment data, and improves the accuracy of a simulation result.

Description

Technical Field

[0001] The present application belongs to the field of data processing technology, and specifically relates to a data processing method for a high-dynamic physical simulation system. Background Art

[0002] With the development of science and technology, physical simulation test platforms have become an important tool for complex system research. For various things that cannot be analyzed using specific physical objects, by building a physical simulation system, the actual state of the product and the different behaviors that may occur under the actual state can be simulated, so as to perform corresponding analysis and processing, helping staff to collect corresponding data information.

[0003] In the process of testing using a high-dynamic physical simulation system, it is necessary to analyze the performance of the warhead during flight under infrared conditions to provide comprehensive data support for testing and verification. However, since the warhead may fly too fast during flight, residual images may appear in the captured images, affecting the data collected by the simulation system, affecting subsequent experimental processing, and affecting the accuracy of the physical simulation. Summary of the invention

[0004] In order to solve the above problems, the present application provides a data processing method for a high-dynamic physical simulation system. The method comprises: Acquire continuous multi-frame infrared image data of high-speed moving objects; Performing region division on the continuous multiple frames of infrared image data to obtain physical region data and background region data of the object; identifying residual image data in the physical object area data; The residual image data is corrected to obtain target simulation analysis data.

[0005] Optionally, the acquiring of multiple frames of continuous infrared image data of a high-speed moving object includes: The infrared image data of multiple frames of a high-speed moving object are acquired by setting a frame length threshold.

[0006] Optionally, the dividing the continuous multiple frames of infrared image data into regions to obtain the physical region data and background region data of the object includes: Acquiring grayscale data of the continuous multiple frames of infrared images; Obtaining a frame difference data matrix between any two adjacent frames of the grayscale data; According to the frame difference data matrix, the physical area data and the background area data of the object are determined.

[0007] Optionally, determining the physical area data and the background area data of the object according to the frame difference data matrix includes: Obtaining infrared performance coefficients of any data in the frame difference data matrix; According to the infrared performance coefficient, construct an infrared performance coefficient sequence; According to the infrared expression coefficient sequence, the physical area data and the background area data of the object are determined.

[0008] Optionally, the identifying the residual image data in the physical area data includes: Determine the body contour point data of the object in the data matrix of the physical area data; Determining the body data of the object in the physical area data according to the body contour point data of the object; The residual image data is determined according to the physical object area data and the body data.

[0009] Optionally, the determining of the body contour point data of the object in the data matrix of the physical area data includes: Obtaining vertex data of the object; Acquiring row difference data and column difference data of a body area of ​​the object; Acquire row and column offset coefficients of contour points of the object according to the row difference data and the column difference data; The body contour point data of the object is determined according to the vertex data and the row and column offset coefficients.

[0010] Optionally, determining the residual image data according to the physical object area data and the body data includes: The main body data is removed from the physical area data to obtain the residual image data.

[0011] Optionally, the correcting the residual image data to obtain target simulation analysis data includes: Obtaining a correction coefficient for the residual image data; The afterimage data is corrected according to the correction coefficient to obtain target simulation analysis data.

[0012] Optionally, obtaining a correction coefficient of the residual image data includes: Acquiring entity data of the object; Acquire the minimum distance difference between the residual image data and the main body data of the object; A correction coefficient of the afterimage data is obtained according to the minimum distance difference.

[0013] Optionally, the correcting the afterimage data according to the correction coefficient to obtain target simulation analysis data includes: The target simulation analysis data is obtained according to the product of the correction coefficient and the residual image data.

[0014] In summary, the embodiment of the present application provides a data processing method for a high-dynamic physical simulation system. The method includes: acquiring multiple continuous frames of infrared image data of a high-speed moving object; dividing the multiple continuous frames of infrared image data into regions to obtain physical region data and background region data of the object; identifying afterimage data in the physical region data; and correcting the afterimage data to obtain target simulation analysis data. The embodiment of the present application can realize data correction of afterimages of high-speed moving objects, provide more accurate simulation experimental data, and improve the accuracy of simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the implementation scheme of the present application, the drawings required for use in the implementation scheme will be briefly introduced below. It should be understood that the drawings only show certain implementation schemes of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on the drawings without paying creative work.

[0016] Figure 1 The present invention is a flow chart showing a data processing method for a high dynamic physical simulation system according to an exemplary embodiment.

[0017] Figure 2 The present invention is a flow chart showing a method for acquiring multiple frames of continuous infrared image data of a high-speed moving object according to an exemplary embodiment.

[0018] Figure 3 The present invention is a flowchart of a method for acquiring physical area data and background area data of an object according to an exemplary embodiment.

[0019] Figure 4 The flowchart is another method for acquiring physical area data and background area data of an object according to an exemplary embodiment.

[0020] Figure 5 The invention is a flowchart showing a method for identifying residual image data in physical area data according to an exemplary embodiment.

[0021] Figure 6 The present invention is a flowchart showing a method for determining body contour point data of an object in a data matrix of physical area data according to an exemplary embodiment.

[0022] Figure 7 The figure is a flowchart of a method for determining afterimage data according to an exemplary embodiment.

[0023] Figure 8 The present invention is a flowchart of a method for obtaining target simulation analysis data according to an exemplary embodiment.

[0024] Fig. 9 The figure is a flow chart showing a method for obtaining correction coefficients of afterimage data according to an exemplary embodiment.

[0025] Fig.10 The flowchart of another method for obtaining target simulation analysis data is shown according to an exemplary embodiment. DETAILED DESCRIPTION

[0026] In order to clearly illustrate the technical features of the present solution, the present application is described in detail below through specific implementation methods and in conjunction with the accompanying drawings.

[0027] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be construed as being limited to the embodiments described herein. Instead, these embodiments are provided to provide a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are only for exemplary purposes and are not intended to limit the scope of protection of the present application.

[0028] It should be understood that the various steps described in the method implementation of the present application can be performed in different orders and / or performed in parallel. In addition, the method implementation may include additional steps and / or omit the steps shown. The scope of the present application is not limited in this respect.

[0029] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0030] It should be noted that the concepts such as "first" and "second" mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0031] It should be noted that the modifications of "one" and "multiple" mentioned in this application are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more". In the description of this application, unless otherwise specified, "multiple" means two or more than two, and other quantifiers are similar; "at least one item", "one or more items" or similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one item a can represent any number of a; for another example, one or more items of a, b and c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple; "and / or" is a kind of association relationship that describes the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural.

[0032] Although the operations or steps are described in a specific order in the drawings in the embodiments of the present application, it should not be understood that it is required to perform these operations or steps in the specific order shown or in a serial order, or to perform all the operations or steps shown to obtain the desired results. In the embodiments of the present application, these operations or steps can be performed in series; these operations or steps can also be performed in parallel; or some of these operations or steps can be performed.

[0033] At the same time, it is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) should comply with the requirements of the relevant laws and regulations and relevant provisions. The present application is described below in conjunction with specific embodiments.

[0034] Figure 1 FIG. 1 is a flow chart showing a data processing method for a high dynamic physical simulation system according to an exemplary embodiment. Figure 1 As shown, the embodiment of the present application provides a data processing method for a high dynamic physical simulation system, and the method may include the following steps: In step S10, a plurality of continuous frames of infrared image data of a high-speed moving object are acquired.

[0035] In this step, multiple frames of continuous infrared image data of a high-speed moving object are obtained. Exemplarily, multiple frames of continuous infrared image data of a high-speed moving object can be obtained by an infrared thermal imager device with a set frame length threshold, and the set frame length threshold can be 0.1 seconds.

[0036] In step S20, the continuous multiple frames of infrared image data are divided into regions to obtain the physical region data and background region data of the object.

[0037] In this step, the continuous multiple frames of infrared image data are divided into regions to obtain the object's physical region data and background region data. Exemplarily, the grayscale data of the continuous multiple frames of infrared images can be first obtained, and then the frame difference data matrix of any two adjacent frames of the grayscale data can be obtained, and then the physical region data and background region data of the experimental object can be determined based on the frame difference data matrix.

[0038] In step S30, afterimage data is identified in the physical object area data.

[0039] In this step, the residual image data is identified in the physical area data. Exemplarily, the body contour point data of the experimental object in the data matrix of the physical area data can be determined first, and then the body data of the experimental object in the physical area data can be determined based on the body contour point data of the experimental object, and then the residual image data of the experimental object can be determined based on the physical area data and the body data.

[0040] In step S40, the residual image data is corrected to obtain target simulation analysis data.

[0041] In this step, the residual image data is corrected to obtain the target simulation analysis data. Exemplarily, the correction coefficient of the residual image data can be obtained first, and then the residual image data is corrected according to the correction coefficient to obtain the target simulation analysis data.

[0042] In summary, the embodiment of the present application provides a data processing method for a high-dynamic physical simulation system. The method includes: acquiring multiple continuous frames of infrared image data of a high-speed moving object; dividing the multiple continuous frames of infrared image data into regions to obtain physical region data and background region data of the object; identifying afterimage data in the physical region data; and correcting the afterimage data to obtain target simulation analysis data. The embodiment of the present application can realize data correction of afterimages of high-speed moving objects, provide more accurate simulation experimental data, and improve the accuracy of simulation results.

[0043] Figure 2 FIG. 1 is a flow chart showing a method for acquiring multiple frames of continuous infrared image data of a high-speed moving object according to an exemplary embodiment. Figure 2 As shown, the acquisition of multiple frames of continuous infrared image data of a high-speed moving object may include the following steps: In step S101 , a plurality of continuous frames of infrared image data of a high-speed moving object are acquired by setting a frame length threshold.

[0044] In this step, a plurality of continuous frames of infrared image data of a high-speed moving object are acquired by setting a frame length threshold. For example, a plurality of continuous frames of infrared image data of a high-speed moving object can be acquired by an infrared thermal imager device by setting a frame length threshold, and the set frame length threshold can be 0.1 seconds.

[0045] Figure 3 FIG. 1 is a flow chart showing a method for obtaining physical area data and background area data of an object according to an exemplary embodiment. Figure 3 As shown, the region division of the continuous multiple frames of infrared image data to obtain the physical region data and background region data of the object may include the following steps: In step S201, grayscale data of the continuous multiple frames of infrared images are obtained.

[0046] In this step, the grayscale data matrix of the continuous multiple frames of infrared images is obtained. Exemplarily, the matrix is ​​constructed according to the grayscale value data in the image collected by the infrared thermal imager at each time t, and the grayscale data matrix corresponding to the data collected at the tth time , which can be expressed as: Formula 1 in, Indicates The gray value data of the first row and first column on the infrared image collected at the moment, Represents the gray value data of the i-th row and j-th column on the infrared image collected at the t-th time.

[0047] In step S202, a frame difference data matrix between any two adjacent frames of the grayscale data is obtained.

[0048] In this step, the frame difference data matrix of any two adjacent frames of grayscale data is obtained. , That is, the frame difference data matrix corresponding to the t-th moment. It can be expressed as: Formula 2 in, Indicates +The gray value data of the first row and first column on the infrared image collected at 1 moment, Represents the gray value data of the ith row and first column of the infrared image collected at the tth moment.

[0049] In step S203, the physical area data and the background area data of the object are determined according to the frame difference data matrix.

[0050] In this step, the physical area data and background area data of the object are determined according to the frame difference data matrix. Exemplarily, the infrared performance coefficient of any data in the frame difference data matrix can be obtained first, and then an infrared performance coefficient sequence can be constructed according to the infrared performance coefficient, and then the physical area data and background area data of the object can be determined according to the infrared performance coefficient sequence.

[0051] Figure 4 FIG. 1 is a flowchart of another method for obtaining physical area data and background area data of an object according to an exemplary embodiment. Figure 4 As shown, determining the physical area data and background area data of the object according to the frame difference data matrix may include the following steps: In step S2031, the infrared performance coefficient of any data in the frame difference data matrix is ​​obtained.

[0052] In this step, the infrared performance coefficient of any data in the frame difference data matrix is ​​obtained. For example, the infrared performance coefficient of the data in the i-th row and j-th column of the frame difference data matrix corresponding to the t-th moment is It can be obtained by the following formula: Formula 3 in, Indicates The moment to The distance the object travels at a given moment, Indicates the first Line The data difference around the column data is less than 10, Indicates Line The number of data differences less than 10 around the column data, is any data in the frame difference data matrix, indicating the data in the i-th row and j-th column of the frame difference data matrix corresponding to the t-th moment, Represents the infrared performance coefficient of the data in the i-th row and j-th column in the frame difference data matrix corresponding to the t-th moment.

[0053] In the above formula, For flying objects, the value increases as the temperature of the object increases, but for the background, the value is more complex and shows no regularity.

[0054] In step S2032, an infrared expression coefficient sequence is constructed according to the infrared expression coefficient.

[0055] In this step, the infrared performance coefficient sequence is constructed according to the infrared performance coefficient of the data in the frame difference data matrix. .in, represents the infrared performance coefficient of the data in the i-th row and j-th column of the frame difference data matrix corresponding to the first moment, represents the infrared performance coefficient of the data in the i-th row and j-th column of the frame difference data matrix corresponding to the second moment, Represents the infrared performance coefficient of the data in the i-th row and j-th column in the frame difference data matrix corresponding to the t-th moment.

[0056] In step S2033, the physical area data and the background area data of the object are determined according to the infrared expression coefficient sequence.

[0057] In this step, according to the infrared performance coefficient sequence , determine the physical area data and background area data of the object. Exemplarily, when the data in the infrared performance coefficient data sequence is a gradually increasing regularity, that is, When Line The corresponding position of the column exists in the physical area of ​​the object. When the data in the infrared performance coefficient data sequence shows a disordered and irregular situation, that is, it does not meet When Line The column corresponding positions exist in the background area.

[0058] Figure 5 FIG. 1 is a flow chart showing a method for identifying residual image data in physical area data according to an exemplary embodiment. Figure 5 As shown, the identifying of the residual image data in the physical area data may include the following steps: In step S301, the body contour point data of the object in the data matrix of the physical area data is determined.

[0059] In this step, the body contour point data of the object in the data matrix of the physical area data is determined. Exemplarily, the vertex data of the object can be obtained first, and then the row difference data and column difference data of the body area of ​​the object can be obtained, and then the row and column offset coefficients of the contour points of the object can be obtained according to the row difference data and the column difference data, and finally the body contour point data of the object can be determined according to the vertex data and the row and column offset coefficients.

[0060] In step S302, the body data of the object in the physical area data is determined according to the body contour point data of the object.

[0061] In this step, the body data of the object in the physical area data is determined based on the body contour point data of the object. Exemplarily, the data within the body contour point of the object can be determined as the body data of the object in the physical area data.

[0062] In step S303, the residual image data is determined according to the physical object area data and the body data.

[0063] In this step, the residual image data is determined according to the real object area data and the body data. Exemplarily, the body data of the object can be removed from the real object area data to obtain the residual image data.

[0064] Figure 6 FIG. 1 is a flow chart showing a method for determining the body contour point data of an object in a data matrix of physical area data according to an exemplary embodiment. Figure 6 As shown, the determining of the body contour point data of the object in the data matrix of the physical area data may include the following steps: In step S3011, the vertex data of the object is obtained.

[0065] In this step, the vertex data of the object is obtained. Exemplarily, taking the object as a bullet, assuming that the bullet flies from left to right, obtain the leftmost, rightmost, topmost, and bottommost positions of this physical area in the data matrix. Since the bullet generally presents a square tail end and a curved head, the vertical direction of the leftmost position point can be obtained as the tail end of the bullet. The rightmost position point needs to be judged to determine whether the rightmost position point belongs to the middle position of the bullet area. Calculate the row number difference between the topmost position point and the bottommost position point in the matrix. , the difference in the number of rows It can be obtained by the following formula: Formula 4 in, The number of rows of the topmost position point of The row number of the bottom position point.

[0066] It can be seen that the number of rows at the top position point The number of rows with the bottom position point When they are equal, this point is the right vertex of the bullet.

[0067] In step S3012, row difference data and column difference data of the main body area of ​​the object are obtained.

[0068] In this step, the line difference data of the object's body area is obtained. Sum difference data . For example, the row difference data It can be obtained by the following formula: Formula 5 in, is the row number of the point at the jth column, is the row number of the point at the j+1th column position.

[0069] Column difference data It can be obtained by the following formula: Formula 6 in, is the column number of the j-th row position point, is the column number of the point at the j+1th row.

[0070] In step S3013, the row and column offset coefficients of the contour points of the object are obtained according to the row difference data and the column difference data.

[0071] In this step, according to the row difference data Sum difference data , get the row and column offset coefficients of the object's contour points For example, the row and column offset coefficients of the contour points of the object are It can be obtained by the following formula: Formula 7 in, Indicates the row difference of the rightmost position points of consecutive rows, Represents the column difference of the rightmost position points of consecutive rows, Indicates The column number of the rightmost point in the row, Indicates The row number of the rightmost position of the row, is the x-coordinate of the rightmost vertex point, is the y coordinate of the rightmost vertex position point, J is the total number of rows in the body area of ​​the object, and j is the jth row in the body area of ​​the object.

[0072] In step S3014, the body contour point data of the object is determined based on the vertex data and the row and column offset coefficients.

[0073] In this step, according to the vertex data ( ) and row-column offset coefficients , determine the object's body contour point data (x, y). Among them, the object's body contour point data (x, y) satisfies the following formula: Formula 8 Figure 7 FIG. 1 is a flow chart showing a method for determining residual image data according to an exemplary embodiment. Figure 7 As shown, determining the residual image data according to the physical object area data and the body data may include the following steps: In step S3031, the main body data is removed from the physical area data to obtain the residual image data.

[0074] In this step, the body data is removed from the physical area data to obtain the residual image data. Exemplarily, the body data of the object can be removed from the physical area data to obtain the residual image data.

[0075] Figure 8 FIG. 1 is a flow chart showing a method for obtaining target simulation analysis data according to an exemplary embodiment. Figure 8 As shown, the correction of the residual image data to obtain the target simulation analysis data may include the following steps: In step S401, a correction coefficient of the residual image data is obtained.

[0076] In this step, the correction coefficient of the residual image data is obtained. Exemplarily, the main body data of the object can be obtained first, and then the minimum distance difference between the residual image data and the main body data of the object can be obtained, and then the correction coefficient of the residual image data can be obtained according to the minimum distance difference.

[0077] In step S402, the afterimage data is corrected according to the correction coefficient to obtain target simulation analysis data.

[0078] In this step, the residual image data is corrected according to the correction coefficient to obtain the target simulation analysis data. Exemplarily, the target simulation analysis data can be obtained according to the product of the correction coefficient and the residual image data.

[0079] Fig. 9 FIG. 1 is a flow chart showing a method for obtaining correction coefficients of residual image data according to an exemplary embodiment. Fig. 9 As shown, the obtaining of the correction coefficient of the residual image data may include the following steps: In step S4011, the entity data of the object is obtained.

[0080] In this step, the body data of the object is obtained. Exemplarily, the data within the body contour points of the object can be determined as the body data of the object in the physical area data.

[0081] In step S4012, the minimum distance difference between the residual image data and the main body data of the object is obtained.

[0082] In this step, the minimum distance difference between the residual image data and the object's main body data is obtained. .in, Indicates the residual image data at time t Line The minimum distance difference between the corresponding position of the column and the body data position point of the object in the data matrix in the horizontal direction.

[0083] In step S4013, a correction coefficient of the residual image data is obtained according to the minimum distance difference.

[0084] In this step, according to the minimum distance difference , get the correction coefficient of the residual image data . Exemplarily, the correction coefficient of the residual image data is It can be obtained by the following formula: Formula 9 in, Indicates The gray value data of the i-th row and v-th column of the residual image data collected at the moment, No. The distance afterimage at this moment Line The cth gray value data closest to the corresponding position in the column.

[0085] Fig.10 FIG. 1 is a flowchart of another method for obtaining target simulation analysis data according to an exemplary embodiment. Fig.10 As shown, the correcting the afterimage data according to the correction coefficient to obtain the target simulation analysis data may include the following steps: In step S4021, the target simulation analysis data is obtained according to the product of the correction coefficient and the residual image data.

[0086] In this step, the correction factor With afterimage data The product of . Exemplary, target simulation analysis data It can be obtained by the following formula: Formula 10 This allows you to analyze data based on your target simulation Construct the corresponding simulation data matrix Perform simulation. Since the simulation data matrix The influence of ghosting is eliminated, thus improving the accuracy of simulation results.

[0087] In summary, the embodiment of the present application provides a data processing method for a high-dynamic physical simulation system. The method includes: acquiring multiple continuous frames of infrared image data of a high-speed moving object; dividing the multiple continuous frames of infrared image data into regions to obtain physical region data and background region data of the object; identifying afterimage data in the physical region data; and correcting the afterimage data to obtain target simulation analysis data. The embodiment of the present application can realize data correction of afterimages of high-speed moving objects, provide more accurate simulation experimental data, and improve the accuracy of simulation results.

[0088] The present application also provides a computer-readable storage medium on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of the data processing method for a high-dynamic physical simulation system provided by the present application are implemented.

[0089] In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a programmable electronic device, and the computer program has a code portion for executing the above-mentioned data processing method for a high-dynamic physical simulation system when executed by the programmable electronic device.

[0090] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application.

Claims

1. A data processing method for a high dynamic physical simulation system, characterized in that: The method comprises: Acquire continuous multi-frame infrared image data of high-speed moving objects; Performing region division on the continuous multiple frames of infrared image data to obtain physical region data and background region data of the object; identifying residual image data in the physical object area data; The residual image data is corrected to obtain target simulation analysis data.

2. The data processing method for a high dynamic physical simulation system according to claim 1, characterized in that: The step of acquiring continuous multiple frames of infrared image data of a high-speed moving object comprises: The infrared image data of multiple frames of a high-speed moving object are acquired by setting a frame length threshold.

3. The data processing method for a high dynamic physical simulation system according to claim 1, characterized in that: The step of dividing the continuous multiple frames of infrared image data into regions to obtain the physical region data and background region data of the object includes: Acquiring grayscale data of the continuous multiple frames of infrared images; Obtaining a frame difference data matrix between any two adjacent frames of the grayscale data; According to the frame difference data matrix, the physical area data and the background area data of the object are determined.

4. The data processing method for a high dynamic physical simulation system according to claim 3, characterized in that: Determining the physical area data and the background area data of the object according to the frame difference data matrix includes: Obtaining infrared performance coefficients of any data in the frame difference data matrix; According to the infrared performance coefficient, construct an infrared performance coefficient sequence; According to the infrared expression coefficient sequence, the physical area data and the background area data of the object are determined.

5. The data processing method for a high dynamic physical simulation system according to claim 1, characterized in that: The identifying the residual image data in the physical area data includes: Determine the body contour point data of the object in the data matrix of the physical area data; Determining the body data of the object in the physical area data according to the body contour point data of the object; The residual image data is determined according to the physical object area data and the body data.

6. The data processing method for a high dynamic physical simulation system according to claim 5, characterized in that: The determining of the body contour point data of the object in the data matrix of the physical area data includes: Obtaining vertex data of the object; Acquiring row difference data and column difference data of a body area of ​​the object; Acquire row and column offset coefficients of contour points of the object according to the row difference data and the column difference data; The body contour point data of the object is determined according to the vertex data and the row and column offset coefficients.

7. The data processing method for a high dynamic physical simulation system according to claim 5, characterized in that: The determining the residual image data according to the physical object area data and the body data includes: The main body data is removed from the physical area data to obtain the residual image data.

8. The data processing method for a high dynamic physical simulation system according to claim 1, characterized in that: The correcting the residual image data to obtain target simulation analysis data includes: Obtaining a correction coefficient for the residual image data; The afterimage data is corrected according to the correction coefficient to obtain target simulation analysis data.

9. The data processing method for a high dynamic physical simulation system according to claim 8, characterized in that: The obtaining of the correction coefficient of the residual image data comprises: Acquiring entity data of the object; Acquire the minimum distance difference between the residual image data and the main body data of the object; A correction coefficient of the afterimage data is obtained according to the minimum distance difference.

10. The data processing method for a high dynamic physical simulation system according to claim 8, characterized in that: The correcting the residual image data according to the correction coefficient to obtain target simulation analysis data includes: The target simulation analysis data is obtained according to the product of the correction coefficient and the residual image data.

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