Pipeline three-dimensional automatic modeling method based on parameterized symbol library

Abstract

The invention relates to the technical field of automatic modeling, and discloses a parameterized symbol library-based pipeline three-dimensional automatic modeling method, which comprises the following steps of: establishing a parameterized symbol library, acquiring core parameters, uniformly importing the core parameters, calculating parameter constraint coefficients, and establishing a core parameter verification mechanism and a modular library structure; designing a multi-source data collaborative acquisition interface, performing de-noising conversion on laser point cloud data, calibrating pipeline coordinates, extracting geometric parameters, constructing a pipeline topological relation and checking connection reasonability; calling a corresponding pipeline component, calculating a linkage matching degree, and judging a matching level to carry out adaptive matching; combining the parameter constraint coefficient to adjust the core parameter, outputting a matching report and prompting an abnormal condition; a dynamic assembly rule is formulated, component space assembly is completed, the collision risk is judged, the model position and parameters are optimized in a targeted mode, and the model is simplified; and automatically updating a pipeline model, outputting a model and a parameter report, establishing association between the model and full life cycle information, and carrying out information bidirectional tracing.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic modeling, and particularly to a three-dimensional automatic modeling method for pipelines based on a parametric symbol library. Background Art

[0002] Existing three-dimensional automatic modeling methods for pipelines based on a parametric symbol library still have significant defects in aspects such as symbol library standardization, data fusion ability, intelligent decision-making, cross-platform integration, etc., and are particularly prominent in scenarios such as complex working conditions, large-scale data, and multi-disciplinary collaboration. In the operation steps, symbol library expansion, data preprocessing, automatic assembly, and collision detection are the core problems; In the prior art, it is difficult to accurately express the three-dimensional intersection relationship of pipelines in underground multi-layer spaces, and the influence of geological conditions is not fully considered; the modeling process relies on manual parameter input and cannot quickly handle the emergency modeling requirements for sudden accidents; the model lacks management attributes such as pipeline ownership, maintenance responsible person, inspection records, etc., and cannot support refined pipeline network operation and maintenance; the symbol library lacks parameter definitions for special working conditions such as high temperature, high pressure, and corrosion, and cannot accurately simulate physical properties such as pipeline thermal expansion and contraction and stress distribution; mainstream methods often ignore the creation of weld models, and the types of supports and hangers are single, unable to meet the requirements of a full-element model for a digital factory; it is difficult to be connected to sensors and monitoring systems in the pipe gallery in real time, and the linkage display of the model and environmental parameters cannot be achieved; it lacks the intelligent planning ability for the internal space of the pipe gallery and cannot automatically optimize the layout according to pipeline adjustment requirements; it cannot quickly generate a three-dimensional model of the accident section pipeline, affecting the formulation of emergency rescue plans and the efficiency of resource allocation; parameter naming is chaotic, and the definition of constraint relationships is fuzzy, resulting in model driving failure or abnormal geometric forms; when adding non-standard components, parameters, constraints, and connection rules need to be redefined, the operation is complex, and it requires high technical personnel, and it is difficult for ordinary users to expand independently; after the symbol library is updated, historical models cannot automatically adapt to new parameters, resulting in model and symbol library version incompatibility; after the pipeline route is changed, the assembled components cannot automatically adapt to the new path, and re-matching and assembly are required, and a brute-force algorithm is used for collision detection, and the calculation time is long when facing large-scale models, and the collision position and type cannot be feedback in real time; the association degree between the model and information such as original data, design documents, and construction records is low, and full-life cycle information traceability cannot be achieved; In view of this, a three-dimensional automatic modeling method for pipelines based on a parametric symbol library needs to be provided. Summary of the Invention

[0003] The purpose of the present invention is to provide a three-dimensional automatic modeling method for pipelines based on a parametric symbol library. To solve the above-mentioned problems of the prior art, the present invention is realized through the following technical solutions: In the first aspect, the three-dimensional automatic modeling method for pipelines based on a parametric symbol library provided by the embodiment of the present invention specifically includes the following steps: Step 1: Establish a parameterized symbol library and import core parameters uniformly, calculate parameter constraint coefficients, establish a core parameter verification mechanism and modular library structure, and store the symbol library in the cloud; Step 2: Based on the parametric symbol library, design a multi-source data collaborative acquisition interface to acquire structured and unstructured data, denoise and transform laser point cloud data, calibrate pipeline coordinates, extract geometric parameters, construct pipeline topology relationships and verify connection rationality, and organize them into a unified format; Step 3: Based on the preprocessed core parameters, call the corresponding pipeline components, calculate the linkage matching degree, determine the matching level, and perform adaptive matching; for the adaptively matched pipeline components, adjust the core parameters based on the parameter constraint coefficients, output a matching report, and indicate any abnormal situations. Step 4: Based on the matched pipeline components, formulate dynamic assembly rules, complete the spatial assembly of components, assess collision risks, and optimize the model position and parameters accordingly, and simplify the model. Step 5: Establish a linkage between the symbol library, pipeline model, and raw data to automatically update the pipeline model; design a multi-format output mechanism to synchronously output the model and parameter reports; establish the association between the model and full life cycle information; and perform bidirectional information traceability through the unique identifier of pipeline components.

[0004] Secondly, the pipeline 3D automatic modeling system based on a parametric symbol library provided in this embodiment of the invention specifically includes the following modules: Verification of the storage module: Establish a parameterized symbol library and import core parameters in a unified manner, calculate parameter constraint coefficients, establish a core parameter verification mechanism and modular library structure, and store the symbol library in the cloud; Data processing module: Based on the parametric symbol library, design a multi-source data collaborative acquisition interface to acquire structured and unstructured data, denoise and transform laser point cloud data, calibrate pipeline coordinates, extract geometric parameters, construct pipeline topology relationships and verify connection rationality, and organize into a unified format; Linkage matching module: Based on the preprocessed core parameters, it calls the corresponding pipeline components, calculates the linkage matching degree, determines the matching level, and performs adaptive matching; for adaptively matched pipeline components, it adjusts the core parameters based on the parameter constraint coefficients, outputs a matching report, and prompts abnormal situations. Judgment simplification module: Based on the matched pipeline components, formulate dynamic assembly rules, complete the spatial assembly of components, judge the collision risk, and optimize the model position and parameters in a targeted manner and simplify the model; Update output module: Establish a linkage between symbol library, pipeline model and raw data to automatically update pipeline model, design multi-format output mechanism, output model and parameter report synchronously, establish the association between model and full life cycle information, and perform bidirectional information traceability through unique identifier of pipeline components.

[0005] The beneficial effects of this invention are: 1. By combining parameter standardization with assembly conflict resolution through three types of core parameters and linkage constraint formulas, automatic parameter verification is achieved through constraint coefficients. At the same time, a modular symbol library structure is adopted to solve the problems of difficulty in symbol library expansion and non-standard parameters. A multi-source data collaborative processing mode is adopted, integrating multiple data acquisition modules. Unstructured laser point cloud data is converted into symbol library recognizable parameters through algorithms. Combined with dynamic coordinate calibration formulas, the problems of poor multi-source data adaptation and coordinate offset are solved. 2. Establish a pipeline component linkage matching mechanism, classify matching levels through correlation matching degree, realize adaptive parameter adjustment of pipeline components, avoid conflicts after adjustment by linkage parameter constraint coefficient, set dynamic assembly rules and collision detection collaborative optimization mode, formulate assembly rules in combination with operating condition parameters, accurately determine risks through collision risk coefficient and coordinately adjust parameters and positions, and realize the synchronous progress of assembly and parameter calibration; establish a full-process linkage linkage system and a binding mechanism for full life cycle information, realize automatic model update after parameter and operating condition changes, and bidirectional traceability of model and full life cycle information. Attached Figure Description

[0006] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0007] Figure 1 This is a flowchart of the steps of the automatic 3D modeling method for pipelines based on a parametric symbol library provided in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the structure of the pipeline three-dimensional automatic modeling system based on a parametric symbol library provided in Embodiment 2 of the present invention. Detailed Implementation

[0008] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0009] Example 1: As Figure 1 As shown in the figure, the pipeline 3D automatic modeling method based on a parametric symbol library provided in this embodiment of the invention specifically includes the following steps: Step 1: Establish a parameterized symbol library and import core parameters uniformly, calculate parameter constraint coefficients, establish a core parameter verification mechanism and modular library structure, and store the symbol library in the cloud; In a specific embodiment, a three-dimensional automatic modeling model of the pipeline is established, and the core parameters of the parametric symbol library are clearly divided into three categories, with unified naming throughout the process. The core parameters include, but are not limited to, geometric parameters, physical parameters, and functional parameters. Geometric parameters include: pipe diameter, pipe length, bending angle, and connection diameter; Physical parameters include: pressure rating, temperature resistance rating, corrosion coefficient, and material density; Functional parameters include: media type, process flow direction, maintenance level, and weld grade; The basic values ​​of the above parameters are obtained through industrial plant process design drawings, equipment ledgers, and on-site testing data. Among them, the corrosion coefficient is obtained through on-site sampling and testing, the temperature resistance and pressure rating are extracted from the equipment qualification certificate, the geometric parameters are extracted from CAD process drawings, and the functional parameters are extracted from process flow diagrams and operation and maintenance records. All data are imported into the modeling system through a unified interface to solve the problem of low efficiency in obtaining multi-source data. The parameter constraint rules of the design model are implemented through calculation formulas to achieve linkage constraints between core parameters. These formulas can simultaneously solve two problems: non-standard symbol library parameters and assembly conflicts. The formulas are as follows: ; Analysis yields parameter constraint coefficients The value range is [0.8, 1.2]. For pressure ratings, the value for process piping in industrial plants is 0.1. For temperature resistance ratings, industrial plant process piping is rated at [-20℃, 800℃]. The pipe diameter is 10. The corrosion coefficient is determined based on the type of medium. For corrosive media, the value is [0.6, 0.9], and for non-corrosive media, the value is [1.0, 1.2]. If the parameter constraint coefficient is within this range, the parameter combination is reasonable and the model can be driven normally. If it exceeds the range, it is determined to be a parameter conflict, triggering an automatic verification prompt. The design incorporates a modular symbol library structure. If a non-standard component is added, a corresponding parameter module is added, the core parameters are entered, and the constraint formula is substituted for verification. An automatic parameter verification mechanism is established. After the parameters are entered, the system automatically calculates the parameter constraint coefficient values. If the values ​​exceed the range, a parameter conflict is immediately indicated, and adjustment suggestions are provided to resolve the defects of parameter entry errors and difficulties in expanding the symbol library. The completed parameterized symbol library is stored on a cloud server, supporting cross-platform calls. During the call, all core parameters and constraint rules are automatically synchronized, solving the defects of poor cross-platform compatibility and parameter loss of the symbol library. Step 2: Based on the parametric symbol library, design a multi-source data collaborative acquisition interface to acquire structured and unstructured data, denoise and transform laser point cloud data, calibrate pipeline coordinates, extract geometric parameters, construct pipeline topology relationships and verify connection rationality, and organize them into a unified format; Design a multi-source data collaborative acquisition interface, integrating CAD drawing reading module, laser point cloud acquisition module, equipment ledger import module, and on-site testing data entry module to achieve synchronous acquisition of multiple types of data; For structured data: The interface automatically reads pipeline geometric coordinates (X, Y, Z), pipe diameter, and pipe length data from CAD process drawings; and automatically imports pressure rating, temperature rating, and media type parameters from equipment ledgers. Unstructured data: The process pipelines on the factory site are scanned by laser point cloud acquisition equipment to obtain point cloud data of the pipeline surface. The pipeline surface point cloud data includes: the actual geometric shape of the pipeline and the connection position of the components, which is automatically transmitted to the modeling system through the interface; Transform unstructured data into driving parameters that can be recognized by the symbol library, while simultaneously performing data cleaning and calibration; Specifically, the laser point cloud data is denoised to remove environmental interference points and scanning error points. A neighborhood point clustering algorithm is used to extract the pipeline centerline and component feature points. The feature point coordinates are then converted into symbol library geometric parameters, including the pipeline diameter DN and bending angle θ, using the following conversion formula: ; Analysis yielded the pipe diameter These are the geometric parameters in the symbol library. Parameter explanation: The cross-sectional area of ​​the pipeline extracted from the laser point cloud is calculated using the coordinates of the cross-sectional feature points. To address the offset errors in the acquired pipeline coordinate data (X, Y, Z), a coordinate calibration formula is designed. This formula simultaneously resolves coordinate offset and topology connection errors, specifically through the following formula: ; The coordinates of the calibrated pipeline center point were obtained through analysis. Parameter explanation: The original coordinates are obtained from CAD drawings or laser point clouds. , , This is the coordinate offset, obtained through comparison with field control points, with a value range of [-0.5m, 0.5m]. The calibration range is dynamically adjusted based on the pipe diameter, obtained through point cloud data conversion or CAD drawings, to avoid over-calibration of small-diameter pipes and under-calibration of large-diameter pipes. Based on the calibrated pipeline center point coordinates and symbol library parameter constraints, pipeline branches, intersections, and connection nodes are automatically identified, and topological relationships are constructed. The rationality of component connections is determined by analyzing the topological relationship data between the connection diameters and parameter constraint coefficients of adjacent pipelines. If the connection diameter does not match or the parameter constraint coefficient exceeds the preset range, it will be automatically marked and prompted for adjustment to resolve the defect of topology connection error; otherwise, it will not be marked. The processed core parameters, calibrated pipeline center point coordinates, and topological relationship data are organized into a unified format that can be directly recognized by the symbol library and stored in the system database for symbol library calls and component matching; Step 3: Based on the preprocessed core parameters, call the corresponding pipeline components, calculate the linkage matching degree, determine the matching level, and perform adaptive matching; for the adaptively matched pipeline components, adjust the core parameters based on the parameter constraint coefficients, output a matching report, and indicate any abnormal situations. Based on the preprocessed core parameters, the corresponding type of pipeline component is automatically retrieved from the cloud symbol library. Pipeline components include: pipes, elbows, tees, valves and welds. When retrieving, all core parameters and constraint rules of the component are read synchronously to avoid parameter loss. A matching algorithm combined with core parameters is used for linked matching, and the matching judgment formula is as follows: ; Analysis yields the linkage matching degree of pipeline components. Parameter explanation: , , This refers to the pipe diameter, pressure rating, and temperature resistance rating obtained after pretreatment. , , The pipe diameter, pressure rating, and temperature rating corresponding to the component retrieved from the symbol library; If the linkage matching degree is within the range of [2.8, 3.2], it is considered a perfect match; if the linkage matching degree is within the range of [2.5, 2.8) or (3.2, 3.5], it is considered an adaptive match; if the linkage matching degree is outside the range of [2.5, 3.5], it is considered a failed match. For pipeline components with a linkage matching degree in the range of [2.5, 2.8) or (3.2, 3.5], the core parameters of the pipeline components in the symbol library are automatically and adaptively adjusted. This is achieved through linkage adjustment of parameter constraint coefficients to ensure parameter matching degree and avoid parameter conflicts after adjustment. The adjustment formula is as follows: ; The analysis yielded the adjusted pipe diameter, pressure rating, and temperature resistance rating of the symbol library pipeline components. Ensure compatibility with core pipeline parameters, correct mismatches, and eliminate assembly gaps. Parameter explanation: , , This refers to the pipe diameter, pressure rating, and temperature resistance rating obtained after pretreatment. The parameter constraint coefficients are used. After the matching is completed, the system will automatically output a matching report, marking the linkage matching degree and parameter adjustment status of each component. If there are components that fail to match, the system will automatically recommend components with similar parameters in the symbol library and prompt manual confirmation to avoid matching errors. Step 4: Based on the matched pipeline components, formulate dynamic assembly rules, complete the spatial assembly of components, assess collision risks, and optimize the model position and parameters accordingly, and simplify the model. Dynamic assembly rules are developed based on the high-temperature and high-pressure operating conditions of process pipelines in industrial plants. The core of these rules incorporates operating condition parameters from a symbol library, including pressure rating, temperature rating, and process flow direction. Specifically, the connection strength of the components is determined according to the pressure rating. If the pressure rating is greater than or equal to 10MPa, a welding connection is adopted and the assembly gap is controlled to be 0. If the pressure rating is less than 10MPa, a flange connection is adopted and the assembly gap is controlled to be [0.5mm, 1mm]. The bending angle θ of the component is determined according to the temperature resistance level. If the temperature resistance level is greater than or equal to 400℃, the bending angle θ of the elbow is less than or equal to 90° to avoid stress concentration at high temperatures. If the temperature resistance level is less than 400℃, θ is adjusted to 30°, 45°, 60° and 90° according to the space constraints. The assembly direction of components is determined according to the process flow direction. The assembly direction of valves and flow meters is consistent with the process flow direction to avoid affecting the flow of media and detection accuracy. Based on the preprocessed pipeline coordinates and topological relationships, combined with the preset assembly rules and the core parameters of the pipeline components in the symbol library, the spatial assembly of the pipeline components is automatically completed. During the assembly process, the parameter constraint coefficients and linkage matching degree are called in real time. If an assembly conflict occurs, the assembly angle and position of the components are automatically adjusted, and the core parameters of the pipeline components are adjusted in linkage to achieve the coordination of assembly and core parameter adjustment, resolve assembly conflicts and eliminate collision risks. A collision detection method combining symbol library parameters is adopted to detect collision risks caused by geometric collisions and parameter conflicts, using the following detection formula: ; Analysis yields collision risk coefficient Parameter explanation: The minimum spatial distance between two adjacent components. The maximum pipe diameter between two adjacent components. These are parameter constraint coefficients; If the collision risk coefficient is less than 0.3, it is determined that there is a serious collision risk; if the collision risk coefficient is greater than or equal to 0.3 and less than or equal to 0.8, it is determined that there is a minor collision risk; if the collision risk coefficient is greater than 0.8, it is determined that there is no collision risk. The collision risk is judged in combination with parameter compatibility to ensure that there is no geometric collision while the core parameters are compatible. In response to collision detection risks, the system automatically optimizes the model. For minor collision risks, it automatically adjusts the component assembly positions and increases the spatial spacing while keeping the core parameters of pipeline components unchanged. For severe collision risks, it automatically adjusts the component assembly positions and core parameters while optimizing pipeline routing to ensure that the spacing meets the requirements and that the parameter constraint coefficients are within a reasonable range. A parameter-preserving lightweight method is adopted to simplify redundant geometric details of components, retain all core parameters of the symbol library, and ensure that the lightweight model supports process performance analysis and operation and maintenance management, thus making up for the defect of losing key parameters in lightweighting. Step 5: Establish a linkage between the symbol library, pipeline model, and raw data to automatically update the pipeline model; design a multi-format output mechanism to synchronously output the model and parameter reports; establish the association between the model and full life cycle information; and perform bidirectional information traceability through the unique identifier of pipeline components. Establish a linkage between the parametric symbol library and the pipeline model and raw data, so that the model is automatically updated when changes or adjustments occur; For symbol library parameter updates, if the core parameters of the pipeline component in the symbol library are updated, all pipeline models that call the component will be automatically identified, and the core parameters of the model will be adjusted by adjusting the formula, and the model geometry and assembly status will be updated synchronously. If the core parameters of the pipeline change, the preprocessed data will be automatically updated, the symbol library pipeline components will be called in conjunction with the changes, the linkage matching degree and assembly rules will be adjusted, and the model and topology relationship will be updated synchronously. In response to adjustments in operating conditions, if the process conditions of an industrial plant are adjusted, the parameter constraint coefficients will be automatically recalculated, the core parameters and assembly rules of pipeline components will be adjusted, and the model layout will be optimized to ensure that the model is adapted to the new operating conditions. Design a multi-format output mechanism that supports simultaneous output of dedicated and general formats, and carries all symbol library parameters during output. Output in a format specific to mainstream modeling platforms for process design and model refinement; It outputs a universal format that supports cross-platform display and sharing, enabling visualized factory management; The parameter output synchronously outputs a parameter report, which includes all symbol library parameters, pipeline core parameters, linkage matching degree and constraint coefficients, and performs parameter verification and archiving. Establish a mechanism to link the model with pipeline lifecycle information, using symbol library parameters as the core of the link, and provide model updates and information traceability through the linked information; The associated information includes: design information, construction information, and operation and maintenance information. Design information is associated with CAD process drawings, process flow diagrams, and parameter design reports; construction information is associated with component installation records, weld inspection reports, and construction acceptance data; and operation and maintenance information is associated with inspection records, corrosion detection data, and maintenance records. The association method binds the unique identifier of the pipeline component in the symbol library with the parameter constraint coefficient, and maps the pipeline component in the model to the associated information one by one. For any pipeline component in the model, the full life cycle information of the pipeline component can be directly queried, and the symbol library parameters and original data can be traced back through the information.

[0010] Example 2: Figure 2 As shown in the figure, the pipeline 3D automatic modeling system based on a parametric symbol library provided in this embodiment of the invention specifically includes the following modules: Verification of the storage module: Establish a parameterized symbol library and import core parameters in a unified manner, calculate parameter constraint coefficients, establish a core parameter verification mechanism and modular library structure, and store the symbol library in the cloud; Data processing module: Based on the parametric symbol library, design a multi-source data collaborative acquisition interface to acquire structured and unstructured data, denoise and transform laser point cloud data, calibrate pipeline coordinates, extract geometric parameters, construct pipeline topology relationships and verify connection rationality, and organize into a unified format; Linkage matching module: Based on the preprocessed core parameters, it calls the corresponding pipeline components, calculates the linkage matching degree, determines the matching level, and performs adaptive matching; for adaptively matched pipeline components, it adjusts the core parameters based on the parameter constraint coefficients, outputs a matching report, and prompts abnormal situations. Judgment simplification module: Based on the matched pipeline components, formulate dynamic assembly rules, complete the spatial assembly of components, judge the collision risk, and optimize the model position and parameters in a targeted manner and simplify the model; Update output module: Establish a linkage between symbol library, pipeline model and raw data to automatically update pipeline model, design multi-format output mechanism, output model and parameter report synchronously, establish the association between model and full life cycle information, and perform bidirectional information traceability through unique identifier of pipeline components.

[0011] The above provides a detailed description of one embodiment of the present invention, but the content described is only a preferred embodiment of the present invention and should not be considered as limiting the scope of the present invention. The above formulas are all dimensionless numerical calculations, and the formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world situation. The preset parameters in the formulas are set by those skilled in the art based on actual conditions and historical experience, and can be adjusted according to actual conditions. The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. All equivalent changes and improvements made in accordance with the scope of the present invention should still fall within the patent coverage of the present invention.

Claims

1. A method for automatic 3D modeling of pipelines based on a parametric symbol library, characterized in that, Includes the following steps: Establish a parameterized symbol library and obtain core parameters for unified import, calculate parameter constraint coefficients, establish a core parameter verification mechanism and modular library structure, and store the symbol library in the cloud; Based on a parametric symbol library, a multi-source data collaborative acquisition interface is designed to acquire structured and unstructured data, denoise and transform laser point cloud data, calibrate pipeline coordinates, extract geometric parameters, construct pipeline topology relationships and verify connection rationality, and organize them into a unified format. Based on the preprocessed core parameters, the corresponding pipeline components are called to calculate the linkage matching degree and determine the matching level for adaptive matching. For adaptive matching pipeline components, the core parameters are adjusted in conjunction with the parameter constraint coefficients, and a matching report is output with an alert for abnormal situations. Based on the matched pipeline components, dynamic assembly rules are formulated to complete the spatial assembly of components, collision risks are assessed, and the model position and parameters are optimized and the model is simplified accordingly. Establish a symbol library, link pipeline models with raw data to automatically update pipeline models, design a multi-format output mechanism to synchronously output model and parameter reports, establish the association between the model and full life cycle information, and enable bidirectional information traceability through the unique identifier of pipeline components.

2. The method for automatic 3D pipeline modeling based on a parametric symbol library according to claim 1, characterized in that, The method for calculating the constraint coefficients is as follows: A 3D automatic modeling model of the pipeline is established, and the core parameters of the parametric symbol library are clearly divided into three categories with consistent naming throughout the process. Parameter constraint rules for the model are designed, and the linkage constraints between core parameters are achieved through calculation formulas. These formulas can simultaneously solve two problems: non-standard symbol library parameters and assembly conflicts. The formulas are as follows: ; Analysis yields parameter constraint coefficients The value range is [0.8, 1.2]. Pressure level, For temperature resistance rating, The pipe diameter is 10. The corrosion coefficient; The design incorporates a modular symbol library structure. If a non-standard component is added, a corresponding parameter module is added, the core parameters are entered, and the constraint formula is substituted for verification. An automatic parameter verification mechanism is established. After the parameters are entered, the system automatically calculates the parameter constraint coefficient values. If the values ​​exceed the range, a parameter conflict is immediately indicated, and adjustment suggestions are provided.

3. The method for automatic 3D pipeline modeling based on a parametric symbol library according to claim 1, characterized in that, The method for calibrating pipeline coordinates is as follows: Denoising is performed on the laser point cloud data to remove environmental interference points and scanning error points. A neighborhood point clustering algorithm is used to extract the pipeline centerline and component feature points. The coordinates of these feature points are then converted into symbol library geometric parameters. A coordinate calibration formula is designed to address both coordinate offset and topology connection errors. Specifically, the formula is as follows: ; The coordinates of the calibrated pipeline center point were obtained through analysis. Parameter explanation: The original coordinates are obtained from CAD drawings or laser point clouds. , , This represents the coordinate offset, with a value range of [-0.5m, 0.5m]. This refers to the pipe diameter.

4. The method for automatic 3D pipeline modeling based on a parametric symbol library according to claim 1, characterized in that, The method for verifying the validity of the connection is as follows: Based on the calibrated pipeline center point coordinates and symbol library parameter constraints, pipeline branches, intersections, and connection nodes are automatically identified, and topological relationships are constructed. The rationality of component connections is determined by analyzing the topological relationship data between the connection diameters and parameter constraint coefficients of adjacent pipelines. If the connection diameter does not match or the parameter constraint coefficient exceeds the preset range, it will be automatically marked and an adjustment prompt will be given; otherwise, it will not be marked. The processed core parameters, calibrated pipeline center point coordinates, and topological relationship data are organized into a unified format that can be directly recognized by the symbol library.

5. The method for automatic 3D pipeline modeling based on a parametric symbol library according to claim 1, characterized in that, The method for adaptive matching is as follows: Based on the preprocessed core parameters, the corresponding type of pipeline component is automatically called from the cloud symbol library. During the call, all core parameters and constraint rules of the component are read synchronously. A matching algorithm combined with core parameters is used for linked matching, and the matching judgment formula is as follows: ; Analysis yields the linkage matching degree of pipeline components. Parameter explanation: , , This refers to the pipe diameter, pressure rating, and temperature resistance rating obtained after pretreatment. , , This specifies the pipe diameter, pressure rating, and temperature rating corresponding to the component retrieved from the symbol library.

6. The method for automatic 3D pipeline modeling based on a parametric symbol library according to claim 1, characterized in that, The method for indicating abnormal situations is as follows: For pipeline components with a linkage matching degree in the range of [2.5, 2.8) or (3.2, 3.5], the core parameters of the symbol library pipeline components are automatically and adaptively adjusted through linkage adjustment of parameter constraint coefficients, using the following adjustment formula: ; The analysis yielded the adjusted pipe diameter, pressure rating, and temperature resistance rating of the symbol library pipeline components. Parameter explanation: , , This refers to the pipe diameter, pressure rating, and temperature resistance rating obtained after pretreatment. The parameter constraint coefficients are used. After the matching is completed, the system automatically outputs a matching report, marking the linkage matching degree and parameter adjustment status of each component. If there are components that fail to match, the system automatically recommends components with similar parameters from the symbol library and prompts for manual confirmation.

7. The method for automatic 3D modeling of pipelines based on a parametric symbol library according to claim 1, characterized in that, The method for formulating dynamic assembly rules is as follows: Based on the high temperature and high pressure conditions of process pipelines in industrial plants, dynamic assembly rules are formulated. The core of the rules combines the operating parameters of the symbol library, and automatically completes the spatial assembly of pipeline components according to the pre-processed pipeline coordinates and topological relationships, combined with the preset assembly rules and the core parameters of pipeline components in the symbol library.

8. The method for automatic 3D modeling of pipelines based on a parametric symbol library according to claim 1, characterized in that, The method for simplifying the model is as follows: The system calls the parameter constraint coefficients and linkage matching degree in real time. If an assembly conflict occurs, it automatically adjusts the assembly angle and position of the components and simultaneously adjusts the core parameters of the pipeline components. A collision detection method combining symbol library parameters is adopted to detect collision risks caused by geometric collisions and parameter conflicts. The collision risk coefficient is obtained by analyzing the detection formula. In response to collision detection risks, the system automatically optimizes the model. For minor collision risks, it automatically adjusts the component assembly positions and increases the spatial spacing while keeping the core parameters of the pipeline components unchanged. For severe collision risks, it automatically adjusts the component assembly positions and core parameters while optimizing the pipeline routing. A parameter-preserving lightweight approach is adopted to simplify redundant geometric details of components while retaining all core parameters of the symbol library.

9. The method for automatic 3D modeling of pipelines based on a parametric symbol library according to claim 1, characterized in that, The method for designing a multi-format output mechanism is as follows: Establish a linkage between the parameterized symbol library and the pipeline model and raw data, so that the model is automatically updated when changes or adjustments occur; design a multi-format output mechanism to support simultaneous output of special and general formats, and carry all symbol library parameters with the output; output parameter reports simultaneously with parameter output, and perform parameter verification and archiving.

10. The method for automatic 3D pipeline modeling based on a parametric symbol library according to claim 1, wherein the method for bidirectional information tracing is as follows: Establish a mechanism to link the model with pipeline lifecycle information, using symbol library parameters as the core of the link, and provide model updates and information traceability through the linked information; The association method binds the unique identifier of the pipeline component in the symbol library with the parameter constraint coefficient, and maps the pipeline component in the model to the associated information one by one. For any pipeline component in the model, the full life cycle information of the pipeline component can be directly queried, and the symbol library parameters and original data can be traced back through the information.

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