An analytical method for generating steel bar processing data from a digital twin model of a bridge

Abstract

The present invention discloses an analysis method for generating steel bar processing data from a bridge digital twin model, comprising the following steps: defining a data interface applicable to the requirements of domestic steel bar processing equipment; a concrete component filtering algorithm based on feature requirements; parsing and extracting the spatial node coordinates of all steel bars belonging to the concrete component; classifying steel bars based on processing requirements such as number or diameter; grading the steel bar details based on construction requirements; converting the steel bar spatial node coordinates into steel bar processing equipment interface data; and outputting steel bar processing data based on the extensible markup language. The present invention realizes parsing the digital twin model to extract the spatial node coordinates of steel bars according to features such as number or diameter; realizes the grading standard of steel bar details applicable to bridge construction requirements and automatically outputs steel bar processing data by level; realizes converting the three-dimensional spatial coordinates of any steel bar detail into the interface data required by the steel bar processing equipment. The present invention has good popularization and application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of steel bar processing data, and specifically relates to an analysis method for generating steel bar processing data from a bridge digital twin model. Background Art

[0002] At present, there is no perfect interface between the digital twin model in the bridge field and the steel bar processing equipment. The two are mainly connected by the BVBS data released by the German Industry Alliance, and there is a lack of an analysis algorithm for generating steel bar processing data from the bridge digital twin model.

[0003] At the same time, the steel bar data processing interface lacks autonomy, which restricts the research and development of steel bar numerical control processing equipment and control programs to a certain extent. Summary of the Invention

[0004] The present invention is proposed to solve the problems existing in the prior art, and its purpose is to provide an analysis method for generating steel bar processing data from a bridge digital twin model.

[0005] The technical solution of the present invention is: an analysis method for generating steel bar processing data from a bridge digital twin model, including the following steps:

[0006] A. Define a data interface S1 suitable for the requirements of domestic steel bar processing equipment;

[0007] B. A concrete member filtering algorithm S2 based on feature requirements;

[0008] C. Analyze and extract the spatial node coordinates of all steel bars belonging to the concrete member S3;

[0009] D. Classify steel bars based on processing requirements such as number or diameter S4;

[0010] E. A steel bar detail grading S5 based on construction requirements;

[0011] F. Convert the steel bar spatial node coordinates into steel bar processing equipment interface data S6;

[0012] G. Output steel bar processing data based on Extensible Markup Language S7.

[0013] Furthermore, step A defines a data interface suitable for the requirements of domestic steel bar processing equipment, and the specific process is as follows:

[0014] Considering the readability of steel bar processing data, Extensible Markup Language is used for data storage. The steel bar processing data includes serial number, member name, member type, steel bar number, steel bar type, quantity, steel bar grade, steel bar diameter, number of steel bar nodes, steel bar length, corners, head and tail hooks.

[0015] Further, the concrete component filtering algorithm based on feature requirements in step B is as follows:

[0016] Based on the feature requirements of the construction plan, construction process, complexity of the rebar details, and the capabilities of existing processing equipment, filter and select the required concrete unit components according to the matching conditions of the concrete component names;

[0017] Then obtain the rebar numbers, rebar grades, rebar diameters, number of rebar nodes, start-end hook, and end-end hook parameters of all rebar groups and single rebars attached to the component.

[0018] Further, the specific process of step C for parsing and extracting the spatial node coordinates of all rebars belonging to the concrete component is as follows:

[0019] Combined with the digital twin model data hosting platform, use the GetRebarGeometries method to extract the shape geometry information of the rebar groups and single rebars in the digital twin model, and uniformly return the extracted information to a group of RebarGeometry objects. Each object mainly contains the three-dimensional information of a single rebar in the corresponding rebar group in the model coordinate system;

[0020] At the same time, the RebarGeometry class has a Shape property, which is an instance of a PolyLine. Through the Shape property, a group of Points objects can be obtained. The Points objects store the coordinate values of the start point, end point, and each intermediate bending point of the rebar in the model coordinate system.

[0021] Further, the specific process of step D for classifying rebars based on processing requirements such as numbers or diameters is as follows:

[0022] First, classify all the rebars read in step B based on processing requirements such as rebar numbers or rebar diameters;

[0023] Then, group the rebars with the same number or the same diameter into one category;

[0024] Finally, extract the total rebar length, rebar diameter, rebar grade, number of rebar nodes, node coordinates, and start-end and end-end hook attributes of each rebar contained in each category.

[0025] Further, step E is the classification of rebar details based on construction requirements,

[0026] Based on construction requirements, consider classifying the details of each category of rebars. The specific classification method is as follows:

[0027] a. If the lengths of the rebars in this category are all the same, they belong to the same level, and directly extract the number of rebars and the rebar length attributes;

[0028] b. If the length of the steel bars in this category gradually changes, then according to the large sample grading standard values and the length differences between the steel bars required by the construction requirements, this category of steel bars is gradually divided level by level, and for each level of steel bars, the steel bar with the smallest length is taken as the automatic processing data of this level of steel bars.

[0029] Furthermore, step F converts the spatial node coordinates of the steel bars into the interface data of the steel bar processing equipment. The specific process is as follows:

[0030] According to the large sample grading of the steel bars in step E, read the steel bar numbers, quantities, grades, diameters, starting end bends, and end bends parameters of each level of steel bars;

[0031] According to the spatial coordinates of the bending nodes of each level of steel bars in step C, through the development interface and bending specification format, the spatial nodes are planarized, and the steel bar bending rules that meet the processing requirements are calculated through the planar nodes.

[0032] Furthermore, step G outputs the steel bar processing data based on the Extensible Markup Language (XML). The specific process is as follows:

[0033] Output the steel bar processing data of each level of steel bars as an XML steel bar processing data file in accordance with the data storage format in step A, as the processing input data file for the steel bar processing equipment.

[0034] Furthermore, in the process of outputting the steel bar processing data based on the Extensible Markup Language (XML) in step G, convert the component and steel bar processing data information into an Excel file for data verification.

[0035] The beneficial effects of the present invention are as follows:

[0036] The present invention realizes extracting the spatial node coordinates of steel bars by parsing the digital twin model according to features such as numbers or diameters; realizes the large sample grading standard for steel bars suitable for bridge construction requirements and automatically outputs the steel bar processing data by level; realizes converting the three-dimensional spatial coordinates of any large sample of steel bars into the interface data required by the steel bar processing equipment.

[0037] The present invention realizes parsing the steel bar processing data from the bridge digital twin model and automatically editing the data according to the interface standard, reducing the human - involved data processing links, and has good promotion and application value. Description of the Drawings

[0038] Figure 1 is the flowchart of the method of the present invention. Detailed Embodiments

[0039] Hereinafter, the present invention will be described in detail with reference to the drawings and embodiments:

[0040] As Figure 1As shown in the figure, a parsing method for generating steel bar processing data from a bridge digital twin model includes the following steps:

[0041] A. Define a data interface S1 suitable for the requirements of domestic steel bar processing equipment;

[0042] B. A filtering algorithm S2 for concrete components based on feature requirements;

[0043] C. Parse and extract the spatial node coordinates of all steel bars belonging to the concrete component S3;

[0044] D. Classify steel bars based on processing requirements such as number or diameter S4;

[0045] E. A grading of steel bar details based on construction requirements S5;

[0046] F. Convert the spatial node coordinates of the steel bars into data for the steel bar processing equipment interface S6;

[0047] G. Output steel bar processing data based on Extensible Markup Language S7.

[0048] Step A defines a data interface suitable for the requirements of domestic steel bar processing equipment. The specific process is as follows:

[0049] Considering the readability of the steel bar processing data, Extensible Markup Language is used for data storage. The steel bar processing data includes serial number, component name, component type, steel bar number, steel bar type, quantity, steel bar grade, steel bar diameter, number of steel bar nodes, steel bar length, corners, start and end hooks.

[0050] Step B is a filtering algorithm for concrete components based on feature requirements. The specific process is as follows:

[0051] Based on the feature requirements of the construction organization plan, construction technology processes, complexity of steel bar details, and capabilities of existing processing equipment, the required concrete unit components are filtered and selected according to the matching conditions of the concrete component name;

[0052] Then, obtain the steel bar numbers, steel bar grades, steel bar diameters, number of steel bar nodes, start-end hook parameters of all steel bar groups and single steel bars attached to the component.

[0053] Step C parses and extracts the spatial node coordinates of all steel bars belonging to the concrete component. The specific process is as follows:

[0054] Combined with the data-bearing platform of the digital twin model, use the GetRebarGeometries method to extract the shape geometric information of the steel bar groups and single steel bars in the digital twin model, and uniformly return the extracted information to a group of RebarGeometry objects. Each object is mainly the three-dimensional information of a steel bar in the corresponding steel bar group in the model coordinate system;

[0055] Meanwhile, the RebarGeometry class has a Shape property, which is an instance of PolyLine. Through the Shape property, a set of Points objects can be obtained, and the Points objects store the coordinate values of the starting point, ending point, and each bending point of the rebar in the model coordinate system.

[0056] Step D classifies the rebars based on processing requirements such as number or diameter. The specific process is as follows:

[0057] First, classify all the rebars read in Step B based on processing requirements such as rebar number or rebar diameter.

[0058] Then, group the rebars with the same number or the same diameter into one category.

[0059] Finally, extract the total length, diameter, grade, number of rebar nodes, node coordinates, and start and end hook attributes of each rebar contained in each category.

[0060] Step E classifies the rebar details based on the construction requirements.

[0061] Based on the construction requirements, consider classifying the details of each category of rebars. The specific classification method is as follows:

[0062] a. If the lengths of the rebars in this category are all the same, they belong to the same level, and directly extract the number of rebars and the length attribute of the rebars.

[0063] b. If the lengths of the rebars in this category change gradually, then classify this category of rebars step by step according to the standard values of the rebar detail classification required by the construction requirements and the length differences between the rebars. For each level of rebars, take the rebar with the smallest length as the automatic processing data of the rebars at this level.

[0064] Step F converts the spatial node coordinates of the rebars into the interface data of the rebar processing equipment. The specific process is as follows:

[0065] According to the rebar detail classification in Step E, read the rebar number, number of rebars, grade, diameter, start-end hook, and end hook parameters of each level of rebars.

[0066] According to the spatial coordinates of the bending nodes of each level of rebars in Step C, through the development interface and bending specification format, planarize the spatial nodes, and calculate the rebar bending rules that meet the processing requirements through the planar nodes.

[0067] Step G outputs the rebar processing data based on the Extensible Markup Language. The specific process is as follows:

[0068] Output the rebar processing data of each level of rebars as an Extensible Markup Language rebar processing data file in accordance with the data storage format in Step A, which serves as the processing input data file for the rebar processing equipment.

[0069] Furthermore, in step G, when outputting the steel bar processing data based on the Extensible Markup Language, the component and the steel bar processing data information are converted into an excel file for data verification.

[0070] Specifically, the steel bar processing data is various types of steel bar processing data in concrete components constructed by prefabrication, in-situ casting, and cantilever casting methods.

[0071] Specifically, the steel bar processing data can be output as classified and graded steel bar processing data according to construction requirements, or the processing data of each steel bar in the component can be directly output.

[0072] Specifically, step B can output the steel bar processing data based on the three-dimensional space model of any concrete component.

[0073] Specifically, step E can output the steel bar processing data according to any grading standard of the large sample.

[0074] Specifically, step F can realize the extraction and calculation of the processing data of any geometric shape of the steel bar.

[0075] Specifically, the xml file of the steel bar processing data output by step G can be directly read by the steel bar processing equipment.

[0076] Embodiment 1

[0077] An analysis method for generating steel bar processing data from a bridge digital twin model includes the following steps:

[0078] A. Define a data interface S1 suitable for the requirements of domestic steel bar processing equipment;

[0079] Considering the readability of the steel bar processing data, it is studied to use the Extensible Markup Language XML for data storage, making it easy to read and write data in any application program.

[0080] Specifically, the automatic processing data format and the content are as follows:

[0081] <component>

[0082] <ordernumber> 2< / ordernumber>

[0083] <component>DWGPROFILE Steel Bar Processing Data< / component>

[0084] <componenttype>GTBZL32.6< / componenttype>

[0085] <rebarnumber> A1< / rebarnumber>

[0086] <rebartype> 0< / rebartype>

[0087] <num> 274< / num>

[0088] <level>HRB400< / level>

[0089] <diameter> 12< / diameter>

[0090] <shapepoint> 6< / shapepoint>

[0091] <length> 5220.32< / length>

[0092] <edgeandangle> 151 0 -90 0 0,2430 0 90 0 0,98 0 90 0 0,2430 0 -900 0,151 0 0 0 0,< / edgeandangle>

[0093] <frontandrail> -90 -90< / frontandrail>

[0094] < / component>

[0095] Among them,

[0096] Order Number represents the serial number;

[0097] Component represents the component name;

[0098] ComponentType represents the component type;

[0099] RebarNumber represents the steel bar number;

[0100] RebarType represents the type of steel bars, which is distinguished between single steel bars and groups of steel bars;

[0101] Num represents the quantity of steel bars;

[0102] Level represents the grade of steel bars;

[0103] Diameter represents the diameter of steel bars;

[0104] ShapePoint represents the number of nodes that make up the steel bar;

[0105] Length represents the length of the steel bar;

[0106] EdgeAndAngle represents the edge and angle;

[0107] FrontAndRail represents the front and rear hook bends.

[0108] The edge and angle are arranged in the order from the head to the tail of the steel bar in the format of "side length, arc radius, angle 1, tolerance, number of reduction scales".

[0109] Among them, the side length: when it is an arc, this is the arc length of the arc; when it is a straight edge, it is the length of the straight edge;

[0110] Arc radius: when it is an arc, this is the radius of the arc; when it is a straight edge, this side is 0;

[0111] Angle 1: is the included angle between the sides or the included angle between the side and the arc in the edge and angle structure, with a value range of [-180, 180], following the right-hand system rule, and 0 indicates that the steel bar is a two-dimensional steel bar;

[0112] Tolerance: used for reduction scales.

[0113] B. Concrete member filtering algorithm S2 based on feature requirements

[0114] Based on feature requirements such as construction organization plan, construction technology processes, complexity of steel bar details, and capabilities of existing processing equipment, the GetAllObjects method in the Model object of the bridge digital twin model-based hosting platform is used to traverse and search from the group of component objects in the model, and the required concrete unit components are filtered and selected according to the matching conditions of the concrete member names.

[0115] Then, the GetChildren method of the component is used to obtain parameters such as the steel bar numbers, grades, diameters, number of steel bar nodes, start-end hook bends, and end hook bends of all groups of steel bars and single steel bars attached to the component.

[0116] C. Analyze and extract the spatial node coordinates of all steel bars belonging to the concrete member S3

[0117] Based on the digital twin model hosting platform, for the shape geometric coordinate values of the RebarGroup and SingleRebar, the GetRebarGeometries method is mainly used during the steel bar data extraction process. The GetRebarGeometries method contains a steel bar numbering function value. Given a steel bar number, the GetRebarGeometries method will extract the geometric information of all steel bars from the filtered concrete components, that is, return a set of RebarGeometry objects, and each object corresponds to the three-dimensional information of a steel bar in the steel bar group in the model coordinate system.

[0118] There is a Shape property in the RebarGeometry class. The Shape property is an instance of a PolyLine. Through the Shape property, a set of Points objects can be obtained, and the coordinates of the starting point, ending point, and each bending point in the middle of the steel bar are stored in the Points objects in the model coordinate system.

[0119] D. Classify steel bars based on processing requirements such as number or diameter S4

[0120] Based on processing requirements such as the steel bar number or steel bar diameter, classify all the steel bars read in step B. Steel bars with the same number or the same diameter are grouped into one category, and then extract the properties such as the steel bar length, steel bar diameter, steel bar grade, number of steel bar nodes, steel bar node coordinates, and end hooks of each steel bar contained in each category.

[0121] E. Grade the detailed drawings of steel bars based on construction requirements S5

[0122] Based on the requirements proposed for construction, consider grading the detailed drawings of each category of steel bars. The specific grading method is as follows:

[0123] If the lengths of the steel bars in this category are all the same, they belong to the same level, and directly extract properties such as the number of steel bars and the length of the steel bars.

[0124] If the lengths of the steel bars in this category change gradually, then according to the standard value of the detailed drawing grading proposed for construction requirements and the length difference between the steel bars, this category of steel bars is graded step by step, and the steel bar with the smallest length in each level is taken as the automatic processing data of the steel bars in this level.

[0125] F. Convert the spatial node coordinates of steel bars into interface data for steel bar processing equipment S6

[0126] According to the grading of the detailed drawings of steel bars in step E, read the parameters such as the number, quantity, grade, diameter, starting hook, and ending hook of each level of steel bars.

[0127] According to the spatial coordinates of the bending nodes of each level of steel bars, through the development interface and the bending specification format, the spatial nodes are planarized. In the order from the starting node to the ending node, the side lengths of each side are calculated successively according to the spatial coordinates of two adjacent nodes, and the included angles between sides are calculated successively according to the spatial coordinates of three adjacent nodes, so as to obtain the steel bar bending rules that meet the processing requirements.

[0128] G. Outputting steel bar processing data based on Extensible Markup Language S7

[0129] Based on the C# language, the data storage format defined in step A is used to output each level of steel bars as xml files in sequence, serving as the data interface required by the steel bar processing equipment. At the same time, information such as components and parameters of each level of steel bars is converted into an excel file for data verification.

[0130] The steel bar processing data is various steel bar processing data in concrete components constructed by prefabrication, in-situ casting, and cantilever casting methods. It can output the steel bar classification and grading processing data according to the construction requirements, or directly output the processing data of each steel bar in the component.

[0131] The above step B can output steel bar processing data based on the three-dimensional space model of any concrete component; the above step E can output steel bar processing data according to any grading standard of large details;

[0132] The above step F can realize the extraction and calculation of processing data for any geometric shape of steel bars; the xml file of the steel bar processing data output in the above step G can be directly read by the steel bar processing equipment.

[0133] The present invention realizes extracting the spatial node coordinates of steel bars by parsing the digital twin model according to features such as numbers or diameters; realizes the large detail grading standard of steel bars suitable for bridge construction requirements and automatically outputs the steel bar processing data by levels; realizes converting the three-dimensional spatial coordinates of any large detail of steel bars into the interface data required by the steel bar processing equipment.

[0134] The present invention realizes parsing the steel bar processing data from the bridge digital twin model and automatically editing the data according to the interface standard, reducing the human-involved data processing links, and having good promotion and application value.

Claims

1. A parsing method for generating steel bar processing data from a bridge digital twin model, characterized in that: It includes the following steps: (A) Define a data interface applicable to the requirements of domestic steel bar processing equipment; (B) A concrete member filtering algorithm based on characteristic requirements; (C) Parse and extract the spatial node coordinates of all steel bars belonging to the concrete member; (D) Classify steel bars based on processing requirements such as number or diameter; (E) Grade the large-scale drawings of steel bars based on construction requirements; (F) Convert the spatial node coordinates of steel bars into steel bar processing equipment interface data; (G) Output steel bar processing data based on Extensible Markup Language; In step (C), the process of parsing and extracting the spatial node coordinates of all steel bars belonging to the concrete member is as follows: Combine the digital twin model data carrier platform, and use the GetRebarGeometries method to extract the shape geometry information of the steel bar group and single steel bar in the digital twin model, Obtain the coordinate values of the starting point, ending point, and each intermediate bending point of the steel bar in the model coordinate system; In step (F), the process of converting the spatial node coordinates of steel bars into steel bar processing equipment interface data is as follows: According to the grading of the large-scale drawings of steel bars in step (E), read the steel bar number, steel bar quantity, steel bar grade, steel bar diameter, starting end hook, and end hook parameters of each level of steel bars; According to the bending node spatial coordinates of each level of steel bars in step (C), through the development interface and bending specification format, planarize the spatial nodes, and calculate the steel bar bending rules that meet the processing requirements through the planar nodes.

2. The parsing method for generating steel bar processing data from a bridge digital twin model according to claim 1, characterized in that: In step (A), the process of defining a data interface applicable to the requirements of domestic steel bar processing equipment is as follows: Considering the readability of steel bar processing data, use Extensible Markup Language for data storage. The steel bar processing data includes serial number, member name, member type, steel bar number, steel bar type, quantity, steel bar grade, steel bar diameter, number of steel bar nodes, steel bar length, corners, and start and end hooks.

3. The parsing method for generating steel bar processing data from a bridge digital twin model according to claim 1, characterized in that: In step (B), the concrete member filtering algorithm based on characteristic requirements is as follows: Based on the characteristic requirements of the construction organization plan, construction technology processes, complexity of steel bar large-scale drawings, and capabilities of existing processing equipment, filter and select the required concrete unit members according to the matching conditions of the concrete member name; Then obtain the steel bar numbers, steel bar grades, steel bar diameters, number of steel bar nodes, starting end hooks, and end hook parameters of all steel bar groups and single steel bars attached to the member.

4. The parsing method for generating steel bar processing data from a bridge digital twin model according to claim 1, characterized in that: In step (D), the process of classifying steel bars based on processing requirements such as number or diameter is as follows: First, classify all the steel bars read in step (B) based on processing requirements such as steel bar number or steel bar diameter; Then, combine the steel bars with the same number or the same diameter into one category; Finally, extract the total length, diameter, grade, number of steel bar joints, joint coordinates, and end hook attributes of each steel bar contained in each category.

5. An analytical method for generating steel bar processing data from a bridge digital twin model according to claim 1, characterized in that: Step (E) is based on the detailed drawing grading of steel bars required for construction, Based on the construction requirements, consider the detailed drawing grading of each type of steel bar. The specific grading method is as follows: a. If the lengths of the steel bars in this category are the same, they belong to the same level, and directly extract the number of steel bars and the length attribute of the steel bars; b. If the lengths of the steel bars in this category change gradually, then according to the standard values of the detailed drawing grading required for construction and the length differences between the steel bars, this category of steel bars is divided into levels one by one. For each level of steel bars, take the steel bar with the smallest length as the automatic processing data of the steel bars at this level.

6. An analytical method for generating steel bar processing data from a bridge digital twin model according to claim 1, characterized in that: Step (G) outputs the steel bar processing data based on Extensible Markup Language. The specific process is as follows: Output the steel bar processing data of each level of steel bars as an Extensible Markup Language steel bar processing data file in accordance with the data storage format in step (A), as the processing input data file for the steel bar processing equipment.

7. An analytical method for generating steel bar processing data from a bridge digital twin model according to claim 1, characterized in that: In step (G) of outputting the steel bar processing data based on Extensible Markup Language, convert the component and steel bar processing data information into an excel file for data verification.

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