Automatic classification method and system for members of cylindrical double-layer bolted spherical reticulated shell structure

Abstract

The application discloses a kind of cylindrical double-layer bolt spherical shell structure rod automatic classification method and system, it is related to space grid structure engineering technical field, for the current artificial rod classification exists rod classification accuracy low, easy to make mistake and difficult to distinguish upper chord rod and lower chord rod accurately, a kind of cylindrical double-layer bolt spherical shell structure rod automatic classification method is proposed, comprising: obtaining the rod data of target net shell structure;Geometric feature analysis is carried out, and diagonal brace is identified;Non-diagonal brace is marked as chord;According to the spatial position coordinates of the end point of diagonal brace and chord, the diagonal brace and chord of support 1 region, the diagonal brace and chord of support 2 region and the diagonal brace and chord of midspan region are divided;Based on the judgment mechanism of diagonal brace geometric topological feature, determine chord as upper chord or lower chord;Generate data file containing rod classification attribute and visual drawing.The application can improve rod classification efficiency.

Description

Technical Field

[0001] This invention relates to the field of spatial grid structure engineering technology, specifically to an automatic classification method and system for cylindrical double-layer bolted spherical shell structure members. Background Technology

[0002] As a large-span spatial structure, the cylindrical double-layer bolted spherical reticulated shell structure is composed of thousands of members (including web members, top chord members, and bottom chord members) connected by bolted spherical joints. After point cloud recognition is completed, accurately distinguishing the positional attributes of each member (web members, top chord transverse members, top chord longitudinal members, bottom chord transverse members, and bottom chord longitudinal members) is a crucial foundational task in the structural modeling and verification, member damage statistical distribution mapping, and bill of quantities statistics.

[0003] In existing technologies, member classification mainly relies on manual experience or simple coordinate rules. Manual classification is extremely inefficient and prone to errors when dealing with large and complex reticulated shells; due to the curvature of cylindrical reticulated shells, it is often difficult to accurately distinguish between upper and lower chord members by simply relying on the Z-coordinate height, resulting in insufficient classification accuracy and seriously affecting subsequent engineering applications.

[0004] Traditional manual classification methods require technicians to measure or query the three-dimensional coordinate data of the two endpoints of each member in point cloud processing software or 3D modeling software, then switch to the member data table, find the corresponding member number by coordinate matching, and finally judge the position of the member in the spatial structure based on human experience and manually label the data.

[0005] Taking a medium-sized cylindrical reticulated shell project as an example, the number of members typically ranges from 3,000 to 5,000. Manually performing the aforementioned "measurement-search-judgment-entry" operations takes an average of 30-60 seconds per member. Processing 3,000 members requires a skilled engineer to work continuously for approximately 30-50 hours, which is extremely time-consuming. Furthermore, as working hours increase, visual fatigue can lead to problems such as data misreading and misaligned line numbers. Summary of the Invention

[0006] To address the aforementioned problems, this invention aims to provide an automatic classification method and system for cylindrical double-layer bolted spherical shell structures, thereby solving the problems of low classification efficiency and inaccurate member identification in existing technologies.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows: An automatic classification method for members of a cylindrical double-layer bolted spherical reticulated shell structure includes: This paper proposes an automatic classification method and system for members of a target reticulated shell structure, which includes the spatial coordinates of the endpoints of the members. The aim is to solve the problems of low classification efficiency and inaccurate member identification in existing technologies.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows: An automatic classification method for members of a cylindrical double-layer bolted spherical reticulated shell structure includes: Obtain the member data of the target reticulated shell structure, which includes the spatial coordinates of the endpoints of the members; Geometric feature analysis is performed on the members in the target reticulated shell structure to identify the web members; Based on the identification results of the web members, the non-web members in the target reticulated shell structure are marked as chord members, and the chord members are classified into longitudinal chord members and transverse chord members; Based on the geometric dimensions of the target reticulated shell structure, the height value, the width range of the first support, and the width range of the second support are set. According to the height value, the width range of the first support, and the width range of the second support, the space of the target reticulated shell structure is divided into the mid-span region, the support 1 region, and the support 2 region. Based on the spatial coordinates of the endpoints of each web member and chord member, delineate the web members in the branch 1 region, the chord members in the branch 1 region, the web members in the branch 2 region, the chord members in the branch 2 region, the web members in the mid-span region, and the chord members in the mid-span region. A judgment mechanism based on the geometric topological features of the web members is constructed to classify the chord members in the support 1 region, support 2 region and mid-span region into upper chord members and lower chord members. The upper chord members include upper chord transverse members and upper chord longitudinal members, and the lower chord members include lower chord transverse members and lower chord longitudinal members. Based on the classification results of web members, upper chord transverse members, upper chord longitudinal members, lower chord transverse members, and lower chord longitudinal members, a data file containing member classification attributes and a visualization drawing are generated.

[0009] Through the above technical solutions, further, Based on the above technical solutions, further geometric feature analysis is performed on the members in the target reticulated shell structure to identify the web members, including: Calculate the projected lengths of the member in the X, Y, and Z directions, and denot them as follows: ,when If all values ​​are greater than the first preset threshold, the member is determined to be a web member.

[0010] Based on the above technical solutions, and further, based on the identification results of the web members, the non-web members in the target reticulated shell structure are marked as chord members, and the chord members are classified into longitudinal chord members and transverse chord members, including: Based on the identification results of the web members, the non-web members in the target reticulated shell structure are marked as chord members; Calculate the projected length of the chord in the X direction, denoted as . ,when If the value is greater than the second preset threshold, the chord is determined to be a longitudinal chord; otherwise, the chord is determined to be a transverse chord.

[0011] Based on the above technical solution, and further, according to the geometric dimensions of the target reticulated shell structure, a height value, a first support width range, and a second support width range are set. Based on these values, the space of the target reticulated shell structure is divided into a mid-span region, a support 1 region, and a support 2 region, specifically including: Set the height value to H limit The width range of the first support is The width range of the second support is ; When the Z-coordinate of any member endpoint is less than the height value and the Y-coordinate of any member endpoint is within the width range of the first support, then the member is located in the support 1 region. When the Z-coordinate of any member endpoint is less than the height value and the Y-coordinate of any member endpoint is within the width range of the second support, then the member is located in the support 2 region. When the Z-coordinate of any member endpoint is greater than or equal to the height value, the member is located in the mid-span region. in, The minimum value of the Y-coordinate of the endpoints of all web members. This represents the maximum value of the Y-coordinates of the endpoints of all web members.

[0012] Based on the above technical solutions, and according to the spatial coordinates of the endpoints of each web member and chord member, the web members of branch support 1 region, the chord members of support 1 region, the web members of support 2 region, the chord members of support 2 region, the web members of mid-span region, and the chord members of mid-span region are further defined, including: When the Z-coordinate of the end point of the web member is less than the height value and the Y-coordinate of the end point of the web member is within the width range of the first support, it is marked as a web member of the support 1 region. When the Z-coordinate of the end point of the web member is less than the height value and the Y-coordinate of the end point of the web member is located within the width range of the second support, it is marked as a web member of the support 2 region. When the Z-coordinate of the endpoint of the web member is greater than or equal to the height value, it is marked as a web member in the mid-span region; When the Z-coordinate of the end point of the chord is less than the height value and the Y-coordinate of the end point of the chord is within the width range of the first support, it is marked as a chord in the support 1 region. When the Z-coordinate of the end point of the chord is less than the height value and the Y-coordinate of the end point of the chord is located within the width range of the second support, it is marked as a chord in the support 2 region. When the Z-coordinate of the endpoint of a chord is greater than or equal to the height value, it is marked as a chord in the mid-span region.

[0013] Based on the above technical solutions, a judgment mechanism based on the geometric topological characteristics of the web members is further constructed, classifying the chord members in the support 1 region, support 2 region, and mid-span region into upper chord members and lower chord members. The upper chord members include upper chord transverse members and upper chord longitudinal members, and the lower chord members include lower chord transverse members and lower chord longitudinal members, including: The chord members in the mid-span region, the support 1 region, and the support 2 region are classified and judged separately.

[0014] Based on the above technical solutions, further classification and judgment of chord members in the mid-section region are performed, including: Mark the end with the larger Z coordinate among all the ends of the web members in the mid-span region as the upper chord reference node of the mid-span region, and construct the upper chord node set of the mid-span region accordingly. Mark the end with the smaller Z coordinate among all the endpoints of the web members in the mid-span region as the lower chord reference node of the mid-span region, and construct the lower chord node set of the mid-span region accordingly; Calculate the distances between the two endpoints of the chord in the mid-span region and any node in the set of upper chord nodes or the set of lower chord nodes in the mid-span region. If the node with the closest distance between the two endpoints of the chord in the mid-span region is located in the set of upper chord nodes in the mid-span region, then the chord is determined to be an upper chord; otherwise, the chord is determined to be a lower chord. Based on the classification of chord members in the mid-span region into longitudinal chord members and transverse chord members, the upper chord members are further divided into upper transverse chord members and upper longitudinal chord members, and the lower chord members are divided into lower transverse chord members and lower longitudinal chord members.

[0015] Based on the above technical solutions, further: the chord members in the support 1 area are classified and judged, including: Mark the end with the smaller Y coordinate among all the ends of the web members in the support 1 region as the upper chord reference node of the support 1 region, and construct the upper chord node set of the support 1 region accordingly. Mark the end with the larger Y coordinate among all the ends of the web members in the support 1 region as the lower chord reference node of the support 1 region, and construct the lower chord node set of the support 1 region accordingly. Calculate the distances between the two endpoints of the chord member in support region 1 and any node in the set of upper chord nodes and the set of lower chord nodes in support region 1. If the node closest to the two endpoints of the chord member in support region 1 is located in the set of upper chord nodes in support region 1, then the chord member is determined to be an upper chord member; otherwise, the chord member is determined to be a lower chord member. Based on the classification of the chord members in support area 1 into longitudinal chord members and transverse chord members, the upper chord members are divided into upper transverse chord members and upper longitudinal chord members, and the lower chord members are divided into lower transverse chord members and lower longitudinal chord members.

[0016] Based on the above technical solutions, further: the chord members in the support 2 area are classified and judged, including: Mark the end with the larger Y coordinate among all the ends of the web members in the support 2 region as the upper chord reference node of the support 2 region, and construct the upper chord node set of the support 2 region accordingly. Mark the end with the smaller Y coordinate among all the web members in the support 2 region as the lower chord reference node of the support 2 region, and construct the lower chord node set of the support 2 region accordingly. Calculate the distances between the two endpoints of the chord member in support region 2 and any node in the set of upper chord nodes and the set of lower chord nodes in support region 2. If the node with the closest distance between the two endpoints of the chord member in support region 2 is located in the set of upper chord nodes in support region 2, then the chord member is determined to be an upper chord member; otherwise, the chord member is determined to be a lower chord member. Based on the classification of the chord members in support area 2 into longitudinal chord members and transverse chord members, the upper chord members are divided into upper transverse chord members and upper longitudinal chord members, and the lower chord members are divided into lower transverse chord members and lower longitudinal chord members.

[0017] The present invention also provides an automatic classification system for cylindrical double-layer bolted spherical shell structure members, comprising: a computer-readable storage medium and a processor; Computer-readable storage media are used to store executable instructions; The processor is used to read executable instructions stored in the computer-readable storage medium and execute the automatic classification method for cylindrical double-layer bolted spherical shell structure members as described above.

[0018] The beneficial effects of this invention are: (1) High accuracy: A judgment mechanism based on the geometric features of the web members is proposed. The natural topological connection between the web members and the chord members is used to judge the upper and lower chord members, which significantly improves the accuracy of classifying the upper and lower chord members in the mid-span curved surface region.

[0019] (2) High degree of automation: The entire process requires no human intervention and only takes a few minutes to process thousands of rods, which greatly improves the efficiency of engineering design and management.

[0020] This invention can automatically and accurately classify rods, effectively solve the problem of small coordinate deviations caused by construction errors in actual engineering, and significantly improve the efficiency and accuracy of reticulated shell structure analysis and construction drawing. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating the steps of an automatic classification method for cylindrical double-layer bolted spherical shell structure members proposed in this invention.

[0022] Figure 2 This is a logical diagram illustrating the region division of this invention.

[0023] Figure 3 This is a detailed flowchart of the mechanism for determining the upper and lower chords in the mid-span region, support 1 region, and support 2 region of the present invention.

[0024] Figure 4 This is a schematic diagram of a cylindrical double-layer bolted spherical shell structure to which this invention applies.

[0025] Figure 5 This is a schematic diagram illustrating the determination of the web member and chord member according to the present invention.

[0026] Figure 6 This is a schematic diagram illustrating the determination of the web member, transverse chord, and longitudinal chord in this invention.

[0027] Figure 7 This is a schematic diagram of the support 1 region, support 2 region, and mid-span region as defined in this invention.

[0028] Figure 8 This is a schematic diagram of the web members, upper chord transverse members, lower chord transverse members, upper chord longitudinal members, and lower chord longitudinal members used in determining the support 1 region, support 2 region, and mid-span region according to the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0030] See Figures 1-8 This application discloses an automatic classification method for members of a cylindrical double-layer bolted spherical reticulated shell structure, including: S1. Obtain the member data of the target reticulated shell structure. The member data includes the spatial coordinates of the endpoints of the members. S2. Perform geometric feature analysis on the members in the target reticulated shell structure to identify the web members; S3. Based on the identification results of the web members, the non-web members in the target reticulated shell structure are marked as chord members, and the chord members are classified into longitudinal chord members and transverse chord members; S4. Based on the geometric dimensions of the target reticulated shell structure, set the height value, the width range of the first support, and the width range of the second support. According to the height value, the width range of the first support, and the width range of the second support, divide the space of the target reticulated shell structure into the mid-span region, the support 1 region, and the support 2 region. S5. Based on the spatial coordinates of the endpoints of each web member and chord member, delineate the web members of the branch support 1 region, the chord members of the support 1 region, the web members of the support 2 region, the chord members of the support 2 region, the web members of the mid-span region, and the chord members of the mid-span region. S6. Construct a judgment mechanism based on the geometric topological features of the web members, and classify the chord members in the support 1 region, support 2 region and mid-span region into upper chord members and lower chord members. The upper chord members include upper chord transverse members and upper chord longitudinal members, and the lower chord members include lower chord transverse members and lower chord longitudinal members. S7. Based on the classification results of the web members, upper chord transverse members, upper chord longitudinal members, lower chord transverse members, and lower chord longitudinal members, generate a data file and visualization drawings containing member classification attributes.

[0031] Further, in S1, the member data of the target reticulated shell structure is acquired. The member data includes the spatial coordinates of the endpoints of the members. Specifically, this includes: reading the point cloud of the target reticulated shell members, identifying the members, and obtaining the member data, which includes the member number, the spatial coordinates (3D coordinates) of the endpoints of the members, and the member length. The member data of the reticulated shell structure is read through the data interface to establish a basic database containing the member number, the spatial coordinates of the endpoints of the members, and the member length.

[0032] Specifically, it reads the Excel or text data file provided by the project team. The data includes the unique ID of each member and the coordinates of its two endpoints. , .

[0033] in, For one end of the rod, For the other end of the rod, , , respectively rods The X, Y, and Z coordinates of the endpoint. respectively rods The coordinates of the endpoint in the X, Y, and Z directions.

[0034] In S2, geometric feature analysis is performed on the members in the target reticulated shell structure to identify the web members, including: calculating the projected lengths of the members in the X, Y, and Z directions, denoted as... ,when If all values ​​are greater than the first preset threshold, the member is determined to be a web member.

[0035] Specifically, a first preset threshold is set. For any member, calculate its projected length in each direction: , , If satisfied and and If so, then the member is marked as a web member.

[0036] in, Let be the projected length of the rod in the X direction. Let be the projected length of the rod in the Y direction. Let be the projected length of the rod in the Z direction.

[0037] In S3, based on the identification results of the web members, the non-web members in the target reticulated shell structure are marked as chord members, and the chord members are classified into longitudinal chord members and transverse chord members, including: Based on the results of the web member identification, non-web members are marked as chord members; Calculate the projected length of the chord in the X direction, denoted as . ,when Greater than the second preset threshold At that time, that is If the string length is within the acceptable range, it is determined to be a longitudinal string; otherwise, it is determined to be a transverse string. Based on the typical string length of a space frame, the second preset threshold... 2.0m is generally used.

[0038] In S4, based on the geometric dimensions of the target reticulated shell structure, a height value, a first support width range, and a second support width range are set. According to these values, the space of the target reticulated shell structure is divided into a mid-span region, a support 1 region, and a support 2 region. Specifically, this includes setting the height value as... H limit ; The width range of the first support is: ; The width range of the second support is: ; When the Z-coordinate of any member endpoint is less than the height value and the Y-coordinate of any member endpoint is within the width range of the first support, then the member is located in the support 1 region. When the Z-coordinate of any member endpoint is less than the height value and the Y-coordinate of any member endpoint is within the width range of the second support, then the member is located in the support 2 region. When the Z-coordinate of any member endpoint is greater than or equal to the height value, the member is located in the mid-span region. Therefore, the support 1 region is: ; The area of ​​support 2 is: ; The cross-regional area is: .

[0039] in, The minimum value of the Y-coordinate of all web member endpoints. The maximum value of the Y-coordinate of all web member endpoints. Let y be the Y-coordinate of any end point of the member, and z be the Z-coordinate of any end point of the member.

[0040] S5. Based on the spatial coordinates of the endpoints of each web member and chord member, delineate the web members in region 1, the chord members in region 1, the web members in region 2, the chord members in region 2, the web members in the mid-span region, and the chord members in the mid-span region, specifically including: When the Z-coordinate of the end point of the chord is less than the height value H limit When the Y-coordinate of the end point of the chord is located within the width range of the first support, it is marked as a chord in the support 1 region; When the Z-coordinate of the end point of the chord is less than the height value H limit When the Y-coordinate of the end point of the chord is located within the width range of the second support, it is marked as a chord in the support 2 region; When the Z-coordinate of the endpoint of the chord is greater than or equal to the height value H limit When this occurs, it is marked as a chord in the mid-span region; When the Z-coordinate of the end point of the web member is less than the height value H limit When the Y-coordinate of the end point of the web member is located within the width range of the first support, it is marked as the web member of the support 1 region; When the Z-coordinate of the end point of the web member is less than the height value H limit When the Y-coordinate of the end point of the web member is located within the width range of the second support, it is marked as the web member of the support 2 region; When the Z-coordinate of the endpoint of the web member is greater than or equal to the height value H limit When this occurs, it is marked as the web member in the mid-span region.

[0041] S6. Construct a judgment mechanism based on the geometric topological features of the web members, classifying the chord members in the support 1 region, support 2 region, and mid-span region into upper chord members and lower chord members. Upper chord members include upper chord transverse members and upper chord longitudinal members, and lower chord members include lower chord transverse members and lower chord longitudinal members; specifically including: (1) Classify and determine the chord members in the mid-section region; Feature extraction: Mark the end with the larger Z coordinate among all the ends of the web members in the mid-span region as the upper chord reference node of the mid-span region, and construct the upper chord node set of the mid-span region accordingly; Mark the end with the smaller Z coordinate among all the endpoints of the web members in the mid-span region as the lower chord reference node of the mid-span region, and construct the lower chord node set of the mid-span region accordingly; Node merging: The KD-tree algorithm is used to process the upper chord node set and the lower chord node set of the mid-span region, and a node tolerance threshold is set. Calculate the Euclidean distance between nodes. If the distance between two nodes is less than the node tolerance threshold... If the nodes are clustered, they are treated as the same physical node and assigned a unique node identifier to eliminate errors.

[0042] Matching and discrimination: Calculate the distance between the two endpoints of the chord in the mid-span region and any node in the upper chord node set or the lower chord node set in the mid-span region. If the node with the closest distance between the two endpoints of the chord in the mid-span region is located in the upper chord node set in the mid-span region, then the chord is determined to be an upper chord; otherwise, the chord is determined to be a lower chord. Based on the classification of chord members in the mid-span region into longitudinal chord members and transverse chord members, the upper chord members are further divided into upper transverse chord members and upper longitudinal chord members, and the lower chord members are divided into lower transverse chord members and lower longitudinal chord members.

[0043] (2) Classify and determine the chord members in the support 1 area; Feature extraction: Mark the end with the smaller Y coordinate among all web members in the support 1 region as the upper chord reference node of the support 1 region, and construct the upper chord node set of the support 1 region accordingly; Mark the end with the larger Y coordinate among all the ends of the web members in the support 1 region as the lower chord reference node of the support 1 region, and construct the lower chord node set of the support 1 region accordingly. Node merging: The KD-tree algorithm is used to process the upper chord node set and the lower chord node set of region 1 of support 1, and a node tolerance threshold is set. Calculate the Euclidean distance between nodes. If the distance between two nodes is less than the node tolerance threshold... If the nodes are clustered, they are treated as the same physical node and assigned a unique node identifier to eliminate errors.

[0044] Matching and discrimination: Calculate the distance between the two endpoints of the chord in support 1 region and any node in the set of upper chord nodes and the set of lower chord nodes in support 1 region. If the node with the closest distance between the two endpoints of the chord in support 1 region is located in the set of upper chord nodes in support 1 region, then the chord is determined to be an upper chord; otherwise, the chord is determined to be a lower chord. Based on the classification of the chord members in support area 1 into longitudinal chord members and transverse chord members, the upper chord members are divided into upper transverse chord members and upper longitudinal chord members, and the lower chord members are divided into lower transverse chord members and lower longitudinal chord members.

[0045] (3) Classify and determine the chord members in the support 2 area: Feature extraction: Mark the end with the larger Y coordinate among all web members in the support 2 region as the upper chord reference node of the support 2 region, and construct the upper chord node set of the support 2 region accordingly; Mark the end with the smaller Y coordinate among all the web members in the support 2 region as the lower chord reference node of the support 2 region, and construct the lower chord node set of the support 2 region accordingly. Node merging: The KD-tree algorithm is used to process the upper chord node set and the lower chord node set of the support 2 region, and a node tolerance threshold is set. Calculate the Euclidean distance between nodes. If the distance between two nodes is less than the node tolerance threshold... If the nodes are clustered, they are treated as the same physical node and assigned a unique node identifier to eliminate errors.

[0046] Matching and discrimination: Calculate the distance between the two endpoints of the chord in support 2 region and any node in the set of upper chord nodes and the set of lower chord nodes in support 2 region. If the node with the closest distance between the two endpoints of the chord in support 2 region is located in the set of upper chord nodes in support 2 region, then the chord is determined to be an upper chord; otherwise, the chord is determined to be a lower chord. Based on the classification of the chord members in support area 2 into longitudinal chord members and transverse chord members, the upper chord members are divided into upper transverse chord members and upper longitudinal chord members, and the lower chord members are divided into lower transverse chord members and lower longitudinal chord members.

[0047] S7. Based on the classification results of the web members, upper chord transverse members, upper chord longitudinal members, lower chord transverse members, and lower chord longitudinal members, generate a data file and visualization drawings containing member classification attributes.

[0048] Specifically, the system automatically generates categorized reports and DXF files that distinguish member types using different colors. Color mapping is set as follows: web members (red), top chord longitudinal (green), top chord transverse (blue), bottom chord longitudinal (yellow), and bottom chord transverse (magenta). This is particularly suitable for automating structural analysis, construction drawing preparation, and quantity surveying.

[0049] The present invention also provides an automatic classification system for cylindrical double-layer bolted spherical shell structure members, characterized in that it includes: a computer-readable storage medium and a processor; Computer-readable storage media are used to store executable instructions; The processor is used to read executable instructions stored in the computer-readable storage medium and execute the automatic classification method for cylindrical double-layer bolted spherical shell structure members as described above.

[0050] like Figure 4 As shown, a schematic diagram of a cylindrical double-layer bolted spherical shell structure to which this invention is applicable is provided. Figure 5 This is a schematic diagram illustrating the determination of the web member and chord member according to the present invention. Figure 6 This is a schematic diagram illustrating the determination of the web member, transverse chord, and longitudinal chord in this invention. Figure 7 This is a schematic diagram of the support 1 region, support 2 region, and mid-span region as defined in this invention. Figure 8 This is a schematic diagram of the web members, upper chord transverse members, lower chord transverse members, upper chord longitudinal members, and lower chord longitudinal members used in determining the support 1 region, support 2 region, and mid-span region according to the present invention.

[0051] Taking a medium-sized cylindrical reticulated shell project as an example, the number of members is typically between 3,000 and 5,000. Traditional manual classification methods require technicians to measure or query the three-dimensional coordinates of the two endpoints of each member in point cloud processing software or 3D modeling software, then switch to a member data table to find the corresponding member number through coordinate matching, and finally determine the member's position in the spatial structure based on experience, manually labeling the data. This manual "measurement-search-judgment-entry" process takes an average of 30-60 seconds per member. Processing 3,000 members requires a skilled engineer to work continuously for approximately 30-50 hours, which is extremely time-consuming. Furthermore, as working time increases, visual fatigue can lead to data misreading and misaligned rows. Table 1 compares the efficiency, accuracy, and error rate of the method of this invention with traditional manual classification methods. Table 1. Comparison of the method of this invention with traditional manual classification methods: ; It can be concluded that the traditional manual classification method takes about 35 hours to classify the members of medium-sized cylindrical reticulated shell engineering, with an accuracy of 85%-92%; the automatic classification method of the present invention takes about 1.5 minutes, which greatly improves the classification efficiency, speeds up the work progress, and reduces the workload; the accuracy of the present invention is 100%, which is higher than that of the existing manual classification, and greatly improves the efficiency of engineering design and management.

[0052] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. An automatic classification method for members of a cylindrical double-layer bolted spherical reticulated shell structure, characterized in that, The method includes: Obtain the member data of the target reticulated shell structure, which includes the spatial coordinates of the endpoints of the members; Geometric feature analysis is performed on the members in the target reticulated shell structure to identify the web members; Based on the identification results of the web members, the non-web members in the target reticulated shell structure are marked as chord members, and the chord members are classified into longitudinal chord members and transverse chord members; Based on the geometric dimensions of the target reticulated shell structure, the height value, the width range of the first support, and the width range of the second support are set. According to the height value, the width range of the first support, and the width range of the second support, the space of the target reticulated shell structure is divided into the mid-span region, the support 1 region, and the support 2 region. Based on the spatial coordinates of the endpoints of each web member and chord member, delineate the web members in the branch 1 region, the chord members in the branch 1 region, the web members in the branch 2 region, the chord members in the branch 2 region, the web members in the mid-span region, and the chord members in the mid-span region. A judgment mechanism based on the geometric topological features of the web members is constructed to classify the chord members in the support 1 region, support 2 region and mid-span region into upper chord members and lower chord members. The upper chord members include upper chord transverse members and upper chord longitudinal members, and the lower chord members include lower chord transverse members and lower chord longitudinal members. Based on the classification results of web members, upper chord transverse members, upper chord longitudinal members, lower chord transverse members, and lower chord longitudinal members, a data file containing member classification attributes and a visualization drawing are generated.

2. The method according to claim 1, characterized in that, Geometric feature analysis is performed on the members in the target reticulated shell structure to identify the web members, including: Calculate the projected lengths of the member in the X, Y, and Z directions, and denot them as follows: ,when If all values ​​are greater than the first preset threshold, the member is determined to be a web member.

3. The method according to claim 2, characterized in that, Based on the identification results of the web members, the non-web members in the target reticulated shell structure are marked as chord members, and the chord members are classified into longitudinal chord members and transverse chord members, including: Based on the identification results of the web members, the non-web members in the target reticulated shell structure are marked as chord members; Calculate the projected length of the chord in the X direction, denoted as . ,when If the value is greater than the second preset threshold, the chord is determined to be a longitudinal chord; otherwise, the chord is determined to be a transverse chord.

4. The method according to claim 3, characterized in that, Based on the geometric dimensions of the target reticulated shell structure, a height value, a first support width range, and a second support width range are defined. According to these values, the space of the target reticulated shell structure is divided into a mid-span region, a support 1 region, and a support 2 region, specifically including: Set the height value to H limit The width range of the first support is The width range of the second support is ; When the Z-coordinate of any member endpoint is less than the height value and the Y-coordinate of any member endpoint is within the width range of the first support, then the member is located in the support 1 region. When the Z-coordinate of any member endpoint is less than the height value and the Y-coordinate of any member endpoint is within the width range of the second support, then the member is located in the support 2 region. When the Z-coordinate of any member endpoint is greater than or equal to the height value, the member is located in the mid-span region. in, The minimum value of the Y-coordinate of the endpoints of all web members. This represents the maximum value of the Y-coordinates of the endpoints of all web members.

5. The method according to claim 4, characterized in that, Based on the spatial coordinates of the endpoints of each web member and chord member, delineate the web members in region 1, the chord members in region 1, the web members in region 2, the chord members in region 2, the web members in the mid-span region, and the chord members in the mid-span region, including: When the Z-coordinate of the end point of the web member is less than the height value and the Y-coordinate of the end point of the web member is within the width range of the first support, it is marked as a web member of the support 1 region. When the Z-coordinate of the end point of the web member is less than the height value and the Y-coordinate of the end point of the web member is located within the width range of the second support, it is marked as a web member of the support 2 region. When the Z-coordinate of the endpoint of the web member is greater than or equal to the height value, it is marked as a web member in the mid-span region; When the Z-coordinate of the end point of the chord is less than the height value and the Y-coordinate of the end point of the chord is within the width range of the first support, it is marked as a chord in the support 1 region. When the Z-coordinate of the end point of the chord is less than the height value and the Y-coordinate of the end point of the chord is located within the width range of the second support, it is marked as a chord in the support 2 region. When the Z-coordinate of the endpoint of a chord is greater than or equal to the height value, it is marked as a chord in the mid-span region.

6. The method according to claim 5, characterized in that, A judgment mechanism based on the geometric topological features of the web members is constructed to classify the chord members in the support 1 region, support 2 region, and mid-span region into upper chord members and lower chord members. The upper chord members include upper chord transverse members and upper chord longitudinal members, and the lower chord members include lower chord transverse members and lower chord longitudinal members, including: The chord members in the mid-span region, the support 1 region, and the support 2 region are classified and judged separately.

7. The method according to claim 6, characterized in that, Classify and determine the chord members in the mid-section region, including: Mark the end with the larger Z coordinate among all the ends of the web members in the mid-span region as the upper chord reference node of the mid-span region, and construct the upper chord node set of the mid-span region accordingly. Mark the end with the smaller Z coordinate among all the endpoints of the web members in the mid-span region as the lower chord reference node of the mid-span region, and construct the lower chord node set of the mid-span region accordingly; Calculate the distances between the two endpoints of the chord in the mid-span region and any node in the set of upper chord nodes or the set of lower chord nodes in the mid-span region. If the node with the closest distance between the two endpoints of the chord in the mid-span region is located in the set of upper chord nodes in the mid-span region, then the chord is determined to be an upper chord; otherwise, the chord is determined to be a lower chord. Based on the classification of chord members in the mid-span region into longitudinal chord members and transverse chord members, the upper chord members are further divided into upper transverse chord members and upper longitudinal chord members, and the lower chord members are divided into lower transverse chord members and lower longitudinal chord members.

8. The method according to claim 7, characterized in that: Classify and determine the chord members in support area 1, including: Mark the end with the smaller Y coordinate among all the ends of the web members in the support 1 region as the upper chord reference node of the support 1 region, and construct the upper chord node set of the support 1 region accordingly. Mark the end with the larger Y coordinate among all the ends of the web members in the support 1 region as the lower chord reference node of the support 1 region, and construct the lower chord node set of the support 1 region accordingly. Calculate the distances between the two endpoints of the chord member in support region 1 and any node in the set of upper chord nodes and the set of lower chord nodes in support region 1. If the node closest to the two endpoints of the chord member in support region 1 is located in the set of upper chord nodes in support region 1, then the chord member is determined to be an upper chord member; otherwise, the chord member is determined to be a lower chord member. Based on the classification of the chord members in support area 1 into longitudinal chord members and transverse chord members, the upper chord members are divided into upper transverse chord members and upper longitudinal chord members, and the lower chord members are divided into lower transverse chord members and lower longitudinal chord members.

9. The method according to claim 8, characterized in that: Classify and determine the chord members in support area 2, including: Mark the end with the larger Y coordinate among all the ends of the web members in the support 2 region as the upper chord reference node of the support 2 region, and construct the upper chord node set of the support 2 region accordingly. Mark the end with the smaller Y coordinate among all the web members in the support 2 region as the lower chord reference node of the support 2 region, and construct the lower chord node set of the support 2 region accordingly. Calculate the distances between the two endpoints of the chord member in support region 2 and any node in the set of upper chord nodes and the set of lower chord nodes in support region 2. If the node with the closest distance between the two endpoints of the chord member in support region 2 is located in the set of upper chord nodes in support region 2, then the chord member is determined to be an upper chord member; otherwise, the chord member is determined to be a lower chord member. Based on the classification of the chord members in support area 2 into longitudinal chord members and transverse chord members, the upper chord members are divided into upper transverse chord members and upper longitudinal chord members, and the lower chord members are divided into lower transverse chord members and lower longitudinal chord members.

10. An automatic classification system for cylindrical double-layer bolted spherical shell structure members, characterized in that, include: Computer-readable storage media and processors; Computer-readable storage media are used to store executable instructions; The processor is used to read executable instructions stored in the computer-readable storage medium and execute the automatic classification method for cylindrical double-layer bolted spherical shell structure members according to any one of claims 1-9.

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