Method for calculating volume of grain shaping area and related device

Abstract

The invention belongs to the technical field of solid grain shaping processing, and discloses a grain shaping area volume calculation method and a related device, and the method comprises the steps: carrying out the preprocessing of the obtained point cloud data of a grain, and obtaining the uniformly distributed preprocessed grain point cloud data; according to the preprocessed grain point cloud data, a random sample consistency algorithm is used for fitting the cylindrical surface of a grain, and parameters of a grain cylindrical model are obtained; according to the parameters of the grain cylinder model, a shaping area accurate point set belonging to the outside of the grain cylinder surface is segmented; and calculating the volume of the shaping area according to the accurate point set of the shaping area. According to the invention, automatic identification and measurement of the grain shaping area can be realized, so that the precision, efficiency and safety of the shaping process are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of solid grain shaping and processing, and particularly relates to a method for calculating the volume of a grain shaping area and related devices. Background Art

[0002] The shaping accuracy and efficiency of solid fuel engine grains have attracted increasing attention. How to ensure the high precision and consistency in the grain shaping process has become an important research direction in the current technical field.

[0003] Most of the existing grain shaping technologies rely on manual operations, which not only have poor processing accuracy and consistency but also pose relatively high safety hazards. To improve the efficiency and safety of shaping and processing, using robots and automated equipment to shape grains has become a research hotspot. However, the identification of the shaping area remains a key issue in automated shaping. Most traditional shaping area identification methods rely on manual observation and marking, which is inefficient and vulnerable to human factors, resulting in unstable shaping quality.

[0004] Currently, 3D scanning technology has been widely applied to the measurement and identification of grain shaping, capable of providing accurate point cloud data and offering the possibility for automatic identification of the shaping area. However, existing point cloud processing and registration methods still face many challenges in the identification process of complex grain surfaces. Common problems include insufficient registration accuracy, interference from outliers, and lack of efficient automated processing capabilities. These problems directly affect the identification accuracy of the grain shaping area, and thus the quality and consistency of the shaping process. In addition, due to the particularity of solid propellants themselves, the safety requirements for the shaping process are relatively high. Existing technologies are difficult to balance safety while ensuring shaping accuracy.

[0005] In terms of volume calculation, the minimum convex hull algorithm is a common method for estimating the volume of point clouds and is applicable to point cloud data with good convexity. However, for complex concave geometric structures commonly found in the grain shaping process, such as circular ring-shaped areas, it is difficult to accurately estimate their volume solely relying on the convex hull method. In addition, the microelement method can more precisely handle concave structures by dynamically dividing the point cloud into multiple small segments and calculating the volume of each segment separately. However, existing microelement methods still have room for improvement in terms of efficiency and applicability.

[0006] In summary, existing point cloud segmentation and volume calculation technologies still cannot fully meet the high-precision identification and measurement requirements of the grain shaping area. Summary of the Invention

[0007] To solve the problems existing in the prior art, the purpose of the present invention is to provide a method for calculating the volume of a grain shaping area and related devices. The present invention can achieve automatic identification and measurement of the grain shaping area, thereby improving the accuracy, efficiency, and safety of the shaping process.

[0008] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0009] A method for calculating the volume of the shaping area of a grain, comprising the following process:

[0010] Preprocess the acquired point cloud data of the grain to obtain uniformly distributed preprocessed grain point cloud data;

[0011] According to the preprocessed grain point cloud data, use the random sample consensus algorithm to fit the cylindrical surface of the grain and obtain the parameters of the grain cylindrical model;

[0012] According to the parameters of the grain cylindrical model, segment the precise point set of the shaping area outside the grain cylindrical surface;

[0013] Calculate the volume of the shaping area according to the precise point set of the shaping area.

[0014] Preferably, preprocessing the acquired point cloud data of the grain includes:

[0015] Perform statistical filtering on the acquired point cloud data of the grain to remove isolated points and voxel sampling preprocessing operations.

[0016] Preferably, the parameters of the grain cylindrical model include the axis position, axis direction of the grain cylindrical model, and the radius of the column cylindrical model.

[0017] Preferably, according to the parameters of the grain cylindrical model and the point cloud on the grain cylindrical surface in the preprocessed grain point cloud data, extract the precise point set of the shaping area outside the grain cylindrical surface from the preprocessed grain point cloud data.

[0018] Preferably, according to the parameters of the grain cylindrical model and the point cloud on the grain cylindrical surface in the preprocessed grain point cloud data, extracting the precise point set of the shaping area outside the grain cylindrical surface from the preprocessed grain point cloud data includes:

[0019] Traverse each point in the preprocessed grain point cloud data;

[0020] Take the point with index i in the preprocessed grain point cloud data as the current point. First, determine whether the current point is marked as a point inside the grain cylindrical surface. If the current point is a point inside the grain cylindrical surface, skip the current point and read the point with index i + 1 for inspection; if the current point is not a point inside the grain cylindrical surface, determine whether the distance from the current point to the axis of the fitted grain cylindrical model is greater than the radius of the grain cylindrical model. If the distance from the current point to the axis of the fitted grain cylindrical model is greater than the radius of the grain cylindrical model, take the current point into the new point cloud data set and read the point with the next index to repeat the above process for inspection, otherwise skip the current point and read the point with index i + 1 to repeat the above process. Repeat this process in a loop until the traversal is completed, and use the new point cloud data set as the precise point set of the shaping area outside the grain cylindrical surface.

[0021] Preferably, according to the precise point set of the shaping area, the volume of the shaping area is calculated by combining the convex hull method and the microelement method.

[0022] Preferably, when calculating the volume of the shaping area according to the precise point set of the shaping area:

[0023] The shaping area is divided into microelements by the microelement method, and then the volume of each microelement is calculated by the convex hull method. The volumes of all microelements are summed up to obtain the volume of the entire shaping area.

[0024] The present invention also provides a system for calculating the volume of a grain shaping area, including:

[0025] A data preprocessing module: used for preprocessing the point cloud data of the acquired grain to obtain uniformly distributed preprocessed grain point cloud data;

[0026] A data fitting module: used for fitting the cylindrical surface of the grain according to the preprocessed grain point cloud data by using the random sample consensus algorithm to obtain the parameters of the grain cylindrical model;

[0027] A segmentation module: used for segmenting out the precise point set of the shaping area outside the grain cylindrical surface according to the parameters of the grain cylindrical model;

[0028] A calculation module: used for calculating the volume of the shaping area according to the precise point set of the shaping area.

[0029] The present invention also provides an electronic device, including:

[0030] One or more processors;

[0031] A storage device, on which one or more programs are stored;

[0032] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for calculating the volume of the grain shaping area as described above in the present invention.

[0033] The present invention also provides a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for calculating the volume of the shaped area of the propellant column as described above in the present invention is implemented.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The method for calculating the volume of the shaped area of the propellant column in the present invention uses a shaped area segmentation method based on the Random Sample Consensus (RANSAC) algorithm to achieve accurate recognition of the cylindrical surface of the propellant column and accurate segmentation of the shaped area of the propellant column, reducing the influence of outliers and improving the accuracy and efficiency of shaped area recognition.

[0036] Furthermore, according to the accurate point set of the shaped area, the volume of the shaped area is calculated by combining the convex hull method and the infinitesimal element method, realizing the accurate volume calculation of the shaped area and ensuring the quality consistency of the shaping process. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Schematic diagram of the shaped area identification and volume measurement process for the embodiment of the present invention;

[0038] Figure 2 Schematic diagram of the shaped area of the propellant column specimen for the embodiment of the present invention;

[0039] Figure 3 Schematic diagram of the point cloud data of the propellant column specimen for the embodiment of the present invention;

[0040] Figure 4 Flow chart of extracting the internal points of the cylindrical surface of the point cloud data of the specimen for the embodiment of the present invention;

[0041] Figure 5 Schematic diagram of the result of extracting the internal points of the cylindrical surface of the point cloud data of the specimen for the embodiment of the present invention;

[0042] Figure 6 Schematic diagram of the segmentation and convex hull construction of the circular ring point cloud data for the embodiment of the present invention.

[0043] In the figure, 1 - propellant column main body; 2 - shaped area. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0045] The present invention combines RANSAC fitting optimization, precise point cloud segmentation, and volume calculation techniques that combine the convex hull method and the infinitesimal element method to achieve efficient and automated recognition and volume measurement of complex shaping regions, significantly improving the accuracy and consistency of the shaping process while ensuring processing efficiency and safety.

[0046] Specifically, referring to Figure 1 , the method for calculating the volume of the shaped area of the propellant of the present invention includes the following steps:

[0047] Step 1: Preprocess the point cloud data of the obtained propellant to obtain preprocessed propellant point cloud data:

[0048] In order to improve the processing efficiency and accuracy of subsequent algorithms, statistical filtering is performed on the point cloud data to remove isolated points and voxel sampling preprocessing operations, reducing the data volume while ensuring data quality, so that subsequent processing and calculations are more efficient.

[0049] Step 2: For the preprocessed propellant point cloud data, use the Random Sample Consensus (RANSAC) algorithm to fit the cylindrical surface of the propellant to obtain the parameters of the cylindrical model, and the parameters include the axis position, direction, and radius of the cylinder.

[0050] Step 3: According to the obtained cylindrical model parameters and the point cloud marked as the cylindrical surface (i.e., the point cloud located on the cylindrical surface of the propellant in the preprocessed propellant point cloud data), extract the precise point set of the shaping area outside the cylindrical surface from the preprocessed propellant point cloud data, which specifically includes the following steps:

[0051] Traverse each point in the entire preprocessed propellant point cloud data;

[0052] Take the point with index i in the preprocessed propellant point cloud data as the current point. First, judge whether the current point is marked as an inner point of the cylindrical surface. If the current point is an inner point of the cylindrical surface, skip the current point and read the point with index i + 1 for inspection; if the current point is not an inner point of the cylindrical surface, judge whether the distance from the current point to the axis of the fitted cylindrical surface is greater than the radius of the fitted cylinder.

[0053] Among them, the distance from the current point to the axis of the cylindrical surface is calculated in the following way: Let p i be the vector pointing from the origin of coordinates to the current point, a be the vector pointing from the origin of coordinates to a point on the main axis of the fitted cylinder, and d be the main axis vector of the fitted cylinder. First, calculate the vector v pointing from the current point to a point on the main axis of the fitted cylinder.

[0054] The vector pointing from the current point to a point on the main axis of the fitted cylinder is calculated by the following formula:

[0055] v = p i - a

[0056] Subsequently, calculate the projection parameter t from the current point to the main axis of the fitted cylinder.

[0057] The projection parameter from the current point to the main axis of the fitted cylinder is calculated by the following formula:

[0058]

[0059] Where: v·d represents the projection of vector v on the main axis vector d of the fitted cylinder; d·d is the square modulus of the main axis vector of the cylinder, which is used for normalization.

[0060] According to the projection parameter t, calculate the nearest point q from the current point to the main axis of the fitted cylinder i 。

[0061] The coordinates of the nearest point from the current point to the main axis of the fitted cylinder are calculated by the following formula:

[0062] q i = a + t·d

[0063] Use the current point p i and the nearest point q from the current point to the main axis of the fitted cylinder i Calculate the distance from the current point to the fitted main axis using the Euclidean distance, and based on this distance, determine whether the distance from the current point to the main axis of the fitted cylindrical surface satisfies the condition of being greater than the radius of the fitted cylinder

[0064] For whether the distance from the current point to the main axis of the fitted cylindrical surface satisfies the condition of being greater than the radius of the fitted cylinder, it is calculated by the following inequality:

[0065]

[0066] Where: r is the radius of the fitted cylinder.

[0067] If the above condition is not satisfied, skip the current point and read the point with index i + 1, and repeat the above process for verification; if the above condition is satisfied, extract the current point into the new point cloud dataset and read a new point for verification, and so on in a loop until the traversal is completed, so as to form a point cloud dataset of the outer points of the cylindrical surface of the shaping area. In this way, the point cloud data representing the cylindrical surface structure of the propellant can be accurately extracted, ensuring the accuracy and consistency of the subsequent processing process.

[0068] Step 4, perform volume measurement on the segmented shaping area point set, and calculate the shaping area volume by combining the convex hull method and the infinitesimal element method, specifically as follows:

[0069] For the accurate point set of the shaping area belonging to the outside of the cylindrical surface, the present invention further evaluates the volume of the shaping area and calculates the volume using the convex hull method.

[0070] For a point cloud structure with good convexity, its volume can be estimated directly by constructing the minimum convex hull. For a point cloud of a centrosymmetric ring structure, since it is a concave point cloud, its volume cannot be directly estimated by constructing the minimum convex hull. Therefore, the shaping area is divided into infinitesimals by the infinitesimal method, and then the volume of each infinitesimal is calculated by the convex hull method. The volumes of all infinitesimals are summed to obtain the volume of the entire shaping area. Specifically, according to the RANSAC cylindrical surface fitting result, the main axis vector of the ring point cloud is taken as d, and a point on the main axis is taken as a to determine the main symmetry axis of the ring structure. Subsequently, with the main axis normal vector d as a reference, an initial plane passing through a point a on the main axis is constructed, and the point cloud is dynamically segmented into multiple small segments by gradually rotating the plane normal vector. Each segment corresponds to the point cloud between two adjacent rotated planes. Calculate the three-dimensional convex hull of the point cloud segmented in each segment. Finally, based on the triangular patches of each segment of the convex hull, its volume is calculated by the tetrahedron decomposition method, and the volumes of all segmented bodies are summed to approximate the overall volume of the ring. The calculated volume is compared with the volume of the standard template to evaluate the processing quality. The smaller the volume deviation, the closer the shaping process is to the expected size and shape.

[0071] The present invention realizes the automatic recognition and measurement of the shaping area through the shaping area segmentation method based on RANSAC and the calculation and evaluation of the shaping area volume, thereby improving the accuracy, efficiency and safety of the shaping process

[0072] Embodiment

[0073] As Figure 2 shown is a schematic diagram of the shaping area of the grain specimen in this embodiment, whose shape is a regular of revolution, and the shaping area is marked in red. Most traditional shaping area recognition methods rely on manual observation and marking, and the outer circle of the grain is processed by turning, with low efficiency and being easily affected by human factors, resulting in unstable shaping quality. This embodiment takes the Figure 2 shown cylindrical grain as an object, and describes this embodiment in view of problems such as insufficient recognition and registration accuracy of the shaping area, interference of outliers, and lack of high-efficiency automation processing ability during the grain shaping process of the engine.

[0074] The method for calculating the volume of the grain shaping area in this embodiment includes the following steps:

[0075] S1: Preprocess the obtained grain point cloud data:

[0076] Perform statistical filtering on the obtained grain point cloud data to remove isolated points and voxel sampling preprocessing operations.

[0077] Perform voxel filtering on the acquired grain point cloud data, set the minimum voxel size to 10mm×10mm×10mm, ensure data quality while reducing the data volume, and obtain evenly distributed point cloud data. The preprocessing results of the specimen point cloud data are as shown in Figure 3 shown. The original point cloud data is obtained by randomly sampling on the surface of the specimen model through Figure 2 .

[0078] S2: Use the RANSAC algorithm to fit the cylindrical surface of the grain:

[0079] For the preprocessed grain point cloud data obtained in step S1, use the Random Sample Consensus (RANSAC) algorithm for cylindrical surface fitting to obtain the parameters of the grain cylindrical model, and the parameters include the axis position, direction and radius of the cylinder.

[0080] Take the maximum number of iterations as 1000 and the distance threshold as 1.5. The fitting results output by the program are as follows:

[0081] Cylinder coefficients:

[0082] -Point on axis: (300.011, 562.39, 299.988)

[0083] -Axis direction: (0.00108339, -0.999999, -0.00111994)

[0084] -Radius: 249.951

[0085] S3: Segment the precise point set of the shaping area outside the cylindrical surface according to the cylindrical surface fitting result:

[0086] According to the cylindrical model parameters obtained in step S2 and the point cloud marked as the cylindrical surface, extract the precise point set of the shaping area outside the cylindrical surface in the preprocessed grain point cloud data obtained in step S1.

[0087] Specifically, traverse each point in the entire preprocessed grain point cloud data.

[0088] Take the point with index i in the preprocessed grain point cloud data as the current point. First, judge whether the current point is marked as a point inside the cylindrical surface. If it is a point inside the cylindrical surface, skip the current point and read the point with index i + 1 for inspection; if it is not a point inside the cylindrical surface, judge whether the distance from the point to the axis of the fitted cylindrical surface is greater than the radius of the fitted cylinder.

[0089] The distance from the current point to the axis of the cylindrical surface is calculated as follows: Let p iLet \(p\) be the vector pointing from the origin of coordinates to the current point, \(a\) be the vector pointing from the origin of coordinates to a point on the main axis of the fitted cylinder, and \(d\) be the main axis vector of the fitted cylinder. First, calculate the vector \(v\) pointing from the current point to a point on the main axis of the fitted cylinder.

[0090] The vector pointing from the current point to a point on the main axis of the fitted cylinder is calculated by the following formula:

[0091] \(v = p\) i - \(a\)

[0092] Subsequently, calculate the projection parameter \(t\) from the current point to the main axis of the fitted cylinder.

[0093] The projection parameter from the current point to the main axis of the fitted cylinder is calculated by the following formula:

[0094]

[0095] where: \(v\cdot d\) represents the projection of the vector \(v\) on the main axis vector \(d\) of the fitted cylinder; \(d\cdot d\) is the square modulus of the main axis vector of the cylinder, which is used for normalization.

[0096] According to the projection parameter \(t\), calculate the nearest point \(q\) from the current point to the main axis of the fitted cylinder i .

[0097] The coordinates of the nearest point from the current point to the main axis of the fitted cylinder are calculated by the following formula:

[0098] \(q\) i = \(a + t\cdot d\)

[0099] Use the Euclidean distance between the current point \(p\) i and the nearest point \(q\) from the current point to the main axis of the fitted cylinder i to calculate the distance from the current point to the fitted main axis, and use this distance as a basis to determine whether the distance from the current point to the main axis of the fitted cylinder surface satisfies the condition of being greater than the radius of the fitted cylinder

[0100] For whether the distance from the current point to the main axis of the fitted cylinder surface satisfies the condition of being greater than the radius of the fitted cylinder, it is calculated by the following inequality:

[0101]

[0102] where: \(r\) is the radius of the fitted cylinder.

[0103] If the above condition is not satisfied, skip the current point and read the point with index \(i + 1\) for inspection; if the condition is satisfied, extract it into the new point cloud dataset and read a new point for inspection, and so on until the traversal is completed, so as to form an external point cloud dataset of the cylinder surface in the shaping area.

[0104] According to the fitting result of the RANSAC cylinder surface, the axis distance judgment condition r = 249.951 is taken. The extraction process of the internal points of the cylinder surface of the specimen point cloud data is as follows Figure 4 shown. The extraction result of the external point set of the cylinder surface of the specimen point cloud data is as follows Figure 5 shown. To facilitate the display of the segmentation result, the point set marked as the cylinder surface is set to red, the point set (shaped area) within the cylinder surface is set to green, and the point set outside the cylinder surface is set to gray.

[0105] S4: Measure the volume of the segmented shaped area point set, and calculate the volume of the shaped area by combining the convex hull method and the infinitesimal element method;

[0106] Based on the accurate point set of the shaped area outside the cylinder surface obtained in step S3, in this embodiment, the volume of the shaped area is further evaluated, and the convex hull method is used for volume calculation.

[0107] For the circular ring point cloud data of the shaped area, observing its geometric shape shows that it is a concave point cloud. Therefore, it is impossible to directly estimate its volume by constructing the minimum convex hull. So, the shaped area is divided into infinitesimal elements by the infinitesimal element method, and then the volume of each infinitesimal element is calculated by the convex hull method, and the volumes of all infinitesimal elements are summed to obtain the volume of the entire shaped area. Specifically, according to the fitting result of the RANSAC cylinder surface, the main axis vector of the circular ring point cloud is taken as d = (-0.00108339, -0.999999, -0.00111994), and a point on the main axis is a(300.011, 562.39, 299.988) to determine the main symmetry axis of the annular structure. Subsequently, with the main axis normal vector d as a reference, an initial plane passing through a point a on the main axis is constructed, and the point cloud is dynamically segmented into multiple small segments by gradually rotating the plane normal vector. Each segment corresponds to the point cloud between two adjacent rotated planes. Calculate the three-dimensional convex hull of the point cloud segmented in each segment. Finally, based on the triangular patches of each segment of the convex hull, calculate its volume by the tetrahedron decomposition method, and sum the volumes of all segmented bodies to approximate the overall volume of the circular ring. Set the number of segmented infinitesimal elements to 64. The segmentation and convex hull construction of the circular ring point cloud data are as follows Figure 6 shown. The convex hull volume data output by the program is as follows:

[0108] Total volume = 3.74758e 7 .

[0109] The calculated volume is compared with the volume of the standard template to evaluate the processing quality. The smaller the volume deviation, the closer the shaping process is to the expected size and shape.

[0110] In summary, through the efficient shaping area segmentation algorithm and the shaping area volume calculation method of the present invention, the automation level and accuracy of the engine grain shaping are significantly improved, which is suitable for the requirements of high-precision and high-consistency processing in the aerospace industry.

[0111] In addition, the embodiment of the present invention also provides a system for implementing the above-mentioned grain shaping area volume calculation method of the present invention. The system includes:

[0112] Data preprocessing module: used to preprocess the point cloud data of the obtained grain to obtain uniformly distributed preprocessed grain point cloud data;

[0113] Data fitting module: used to fit the cylindrical surface of the grain using the random sample consensus algorithm according to the preprocessed grain point cloud data, and obtain the parameters of the grain cylindrical model;

[0114] Segmentation module: used to segment the accurate point set of the shaping area outside the grain cylindrical surface according to the parameters of the grain cylindrical model;

[0115] Calculation module: used to calculate the volume of the shaping area according to the accurate point set of the shaping area.

[0116] The embodiment of the present invention also provides a corresponding electronic device and a computer-readable storage medium for implementing the solution provided by the embodiment of the present invention.

[0117] Among them, the device includes a memory and a processor. The memory is used to store instructions or codes, and the processor is used to execute the instructions or codes so that the device executes the grain shaping area volume calculation method described in any embodiment of the present application.

[0118] The computer program is stored on the storage medium. Among them, when the computer program is executed by the processor, it implements the grain shaping area volume calculation method described in any embodiment of the present application.

[0119] Obviously, the described embodiments are only partial embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0120] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: the specific implementation manners of the present invention can still be modified or equivalently replaced, and any modification or equivalent replacement without departing from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A method for calculating the volume of a shaped area of a propellant grain, characterized in that, It includes the following processes: Preprocess the acquired point cloud data of the propellant grain to obtain uniformly distributed preprocessed propellant grain point cloud data; According to the preprocessed propellant grain point cloud data, use the Random Sample Consensus (RANSAC) algorithm to fit the cylindrical surface of the propellant grain and obtain the parameters of the propellant grain cylindrical model; According to the parameters of the propellant grain cylindrical model, segment the precise point set of the shaping area outside the propellant grain cylindrical surface; Calculate the volume of the shaping area according to the precise point set of the shaping area.

2. The method for calculating the volume of the grain shaping area according to claim 1, wherein Preprocessing the acquired point cloud data of the propellant grain includes: Perform statistical filtering on the acquired point cloud data of the propellant grain to remove isolated points and perform voxel sampling preprocessing operations.

3. The method for calculating the volume of the grain shaping area according to claim 1, characterized in that, The parameters of the propellant grain cylindrical model include the axis position, axis direction of the propellant grain cylindrical model, and the radius of the cylindrical model.

4. A method for calculating the volume of a shaped area of a propellant charge according to claim 1, characterized in that According to the parameters of the propellant grain cylindrical model and the point cloud on the propellant grain cylindrical surface in the preprocessed propellant grain point cloud data, extract the precise point set of the shaping area outside the propellant grain cylindrical surface from the preprocessed propellant grain point cloud data.

5. A method for calculating the volume of the grain shaping area according to claim 4, characterized in that According to the parameters of the propellant grain cylindrical model and the point cloud on the propellant grain cylindrical surface in the preprocessed propellant grain point cloud data, extracting the precise point set of the shaping area outside the propellant grain cylindrical surface includes: Traverse each point in the preprocessed propellant grain point cloud data; Take the point with index in the preprocessed grain point cloud data as the current point. First, determine whether the current point is marked as a point inside the grain cylindrical surface. If the current point is a point inside the grain cylindrical surface, skip the current point and read the point with index for inspection; if the current point is not a point inside the grain cylindrical surface, then determine whether the distance from the current point to the axis of the fitted grain cylindrical model is greater than the radius of the grain cylindrical model. If the distance from the current point to the axis of the fitted grain cylindrical model is greater than the radius of the grain cylindrical model, then take the current point into the new point cloud data set and read the point with the next index to repeat the above process for inspection. Otherwise, skip the current point and read the point with index to repeat the above process. Loop in this way until the traversal is completed, and use the new point cloud data set as the precise point set of the shaping area outside the grain cylindrical surface.

6. The method for calculating the volume of the grain shaping area according to claim 1, wherein According to the precise point set of the shaping area, calculate the volume of the shaping area by combining the convex hull method and the infinitesimal element method.

7. A method for calculating the volume of the shaped area of a propellant grain according to claim 6, characterized in that, When calculating the volume of the shaping area according to the precise point set of the shaping area: Divide the shaping area into infinitesimal elements by the infinitesimal element method, then calculate the volume of each infinitesimal element by the convex hull method, and sum up the volumes of all infinitesimal elements to obtain the volume of the entire shaping area.

8. A volume calculation system for the shaping area of a propellant grain, characterized in that, It includes: Data preprocessing module: used to preprocess the acquired point cloud data of the propellant grain to obtain uniformly distributed preprocessed propellant grain point cloud data; Data fitting module: used to fit the cylindrical surface of the propellant grain using the Random Sample Consensus (RANSAC) algorithm according to the preprocessed propellant grain point cloud data and obtain the parameters of the propellant grain cylindrical model; Segmentation module: used to segment the precise point set of the shaping area outside the propellant grain cylindrical surface according to the parameters of the propellant grain cylindrical model; Calculation module: used to calculate the volume of the shaping area according to the precise point set of the shaping area.

9. An electronic device, characterized in that, It includes: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for calculating the volume of the shaping area of the propellant grain as described in any one of claims 1-7.

10. A storage medium, characterized in that, A computer program is stored thereon, and when the computer program is executed by a processor, it implements the method for calculating the volume of the shaping area of the propellant grain as described in any one of claims 1-7.

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