Three-dimensional model driven pipeline assembly axonometric map generation method and system
By establishing a multi-level connection node database and a dynamic correction algorithm, the problem of node misalignment in the 3D model-driven isometric drawing generation system for pipeline components was solved, thereby improving the topological consistency and design efficiency of the isometric drawings.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-09
- Publication Date
- 2026-04-07
Smart Images
Figure CN121808867A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of isometric generation and calculation of pipe components, and in particular to a method and system for generating isometric drawings of pipe components driven by a three-dimensional model. Background Technology
[0002] While existing 3D model-driven isometric drawing generation systems for pipe components can improve efficiency by automatically generating drawings using model data, they struggle to accurately control the position of connection points based on topological relationships (pipe connection sequence, dependencies), leading to node misalignment (misalignment of the drawing due to deviation in the position of connection points). This results in distortion of the isometric drawing's topological structure (such as broken pipe connections or chaotic intersections), affecting the reference value for engineering design. Furthermore, the misalignment issues require repeated manual verification and correction, increasing the design cycle and labor costs, thus reducing the system's automation advantages and the efficiency of actual engineering applications. Summary of the Invention
[0003] The purpose of this invention is to provide a method and system for generating isometric views of pipe components driven by a three-dimensional model, so as to solve the problems mentioned in the background art.
[0004] To achieve the above objectives, the present invention provides the following technical solution: a method for generating isometric views of pipe components driven by a three-dimensional model, the method comprising the following steps: S1. Obtain the geometric parameters and topological relationships of pipe components in the 3D pipe model, and establish a multi-level connection node database; S2. Based on topological relationships and node database, construct spatial constraint rules and priority determination matrix between nodes; S3. Based on spatial constraint rules and priority judgment matrix, the spatial coordinates of conflict nodes are dynamically corrected through coordinate adjustment algorithm; S4. Map the corrected spatial coordinates of the conflicting nodes to the isometric projection plane to generate an isometric view of the pipeline component that includes topology consistency verification.
[0005] Preferably, the establishment of the multi-level connection node database in step S1 includes the following sub-steps: S11. Generate a topology diagram based on the geometric parameters and topological relationships of the pipeline components; S12. Establish a multi-level connection node database based on the topology diagram; S13. Assign dynamic learning coefficients to the nodes of the multi-level connected node database; S14. If the dynamic learning coefficient is lower than the preset threshold, generate optimization suggestions for the multi-level connection node database; otherwise, maintain the original multi-level connection node database.
[0006] Preferably, the establishment of the spatial constraint rules in step S2 includes the following sub-steps: S21. Calculate the deviation between the actual included angle between adjacent nodes of the pipe assembly and the preset standard angle; S22. When the deviation exceeds the preset deviation threshold, the angle compensation mechanism is triggered. S23. Based on the angle compensation mechanism, the compensation angle correction amount is decomposed into the rotation component of the three-dimensional coordinate system, and coordinate updates are performed to establish spatial constraint rules.
[0007] Preferably, the coordinate adjustment algorithm in step S3 includes the following sub-steps: A31. Calculate the displacement weight factor of each node based on the priority determination matrix between nodes; A32. Calculate the 3D coordinate correction based on the displacement weighting factor and spatial constraint rules to correct the node spacing; A33. If the corrected node spacing is less than the preset safety threshold, proportional displacement correction shall be performed according to the displacement weight factor and the normal vector direction. A34. Perform a topology consistency check between the proportional displacement corrected coordinates and the adjacent nodes. If the check fails, correct them again.
[0008] Preferably, the calculation of the displacement weighting factor includes the following sub-steps: A311. Obtain the node's hierarchical depth and the type of its associated pipeline component in the topology; A312. Calculate the initial weight factor based on the parameters of the acquired nodes and the preset weight function; A313. If the calculated initial weight factor is less than the preset weight factor, the preset weight factor is forcibly set as the final weight factor; otherwise, the initial weight factor is set as the final weight factor.
[0009] Preferably, the dynamic correction in step S3 includes the following steps: S31. Establish a node motion trajectory prediction model based on a multi-level connection node database to predict the future trajectory change trend of node coordinates; S32. If the predicted trajectory of a node conflicts with the safe zone of other nodes, a preventive correction is applied. S33. Dynamically correct node positions by adding the preventive correction amount to the current trajectory correction amount.
[0010] Preferably, the mapping of the axonometric projection plane in step S4 includes the following steps: B41. Calculate the node position error of the 3D model node located on the isometric projection plane; B42. When the node position error exceeds the preset position error threshold, adjust the 3D node coordinate correction amount in the opposite direction. B43. Perform bidirectional iterative correction on the node coordinates until the correction conditions are met, thereby adjusting the reverse node coordinate correction amount.
[0011] Preferably, the bidirectional iterative correction in step B43 includes the following sub-steps: B431. Record historical data of node coordinate correction and build a prediction model based on the historical data of coordinate correction; B432. If the rate of change of node position error tends to stabilize, the prediction model is activated to generate the prediction correction amount; otherwise, iterative correction continues. B433. Generate the final correction amount based on corrected historical data and predicted correction amounts.
[0012] Preferably, the topology consistency check includes: C41. Establish a flexible constraint relationship matrix between nodes based on topological relationships and node database; C42. When the corrected coordinates are detected to cause new spacing conflicts, a second correction is performed. C43. If conflicts still exist after the second correction, mark them as nodes to be manually verified and generate a conflict visualization interface.
[0013] Preferably, the secondary correction in step C42 is performed based on the elastic coefficient, and the determination of the elastic coefficient includes the following sub-steps: C421. Statistical analysis of material properties of piping components and system pressure rating parameters; C422. Elasticity coefficients are generated by dynamically calculating functions based on statistical parameters. C423. If the elastic coefficient exceeds the preset critical value, the three-dimensional model local reconstruction mechanism will be activated to update the geometric model of the affected pipeline area.
[0014] A 3D model-driven isometric drawing generation system for pipe components, the system comprising: The topology processing module is used to obtain the geometric parameters and topology relationships of pipe components in the 3D pipe model, and to establish a multi-level connection node database based on the geometric parameters and topology relationships. The constraint rule generation module, based on topological relationships and a node database, is used to construct spatial constraint rules and priority determination matrices between nodes. The dynamic correction module, based on spatial constraint rules and priority determination matrix, dynamically corrects the spatial coordinates of conflicting nodes through a coordinate adjustment algorithm. The isometric projection module is used to map the spatial coordinates of the corrected nodes to the isometric projection plane, generating isometric diagrams of pipe components that include topology consistency checks.
[0015] The beneficial effects of this invention are: 1. This system effectively solves the node misalignment problem through multi-module collaboration: topology relationship processing provides basic data, constraint rule generation defines and adjusts the framework, and the core control algorithm of the dynamic correction module directly corrects position conflicts, ensuring topology consistency during isometric projection. This further reduces the misalignment rate when the system processes complex pipeline models.
[0016] 2. An iterative optimization method is adopted: First, conflicting nodes are detected (e.g., by identifying overlaps or angular deviations through distance calculation), then adjustment objects are selected based on the priority matrix (low-priority nodes are moved first), and finally, coordinate offset is applied (e.g., the least squares optimization algorithm is used to adjust the node coordinates while satisfying constraint rules). This solves the node misalignment problem, because misalignment in isometric drawings often stems from unresolved positional conflicts in the 3D model; through dynamic correction, it ensures that the connection point positions are adjusted to the correct topological relationship before projection.
[0017] 3. The generated isometric drawing is verified to be free of misalignment through consistency checks, improving the accuracy and readability of the drawing. The entire process efficiently integrates 3D model data processing, rule constraints, and dynamic control, achieving a seamless conversion from model to drawing. Attached Figure Description
[0018] Figure 1 This is a flowchart of the steps for generating isometric views of pipe components according to an embodiment of the present invention; Figure 2 This is a diagram illustrating the overall system architecture of an embodiment of the present invention. Figure 3 This is a flowchart illustrating the topology processing of the pipeline components in an embodiment of the present invention. Figure 4 This is a schematic diagram illustrating the adjustment and dynamic correction of the node coordinates of the pipeline component in an embodiment of the present invention; Figure 5 This is a diagram showing the spatial angle constraint and rotation component correction in an embodiment of the present invention; Figure 6 This is a flowchart of bidirectional iterative error correction in an embodiment of the present invention. Detailed Implementation
[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.
[0020] Reference Appendix Figures 1-6 This invention describes the steps of a method and system for generating isometric views of pipe components driven by a three-dimensional model.
[0021] First, the topology relationship processing module is responsible for obtaining the geometric parameters and topology relationship information of the pipe components in the 3D pipe model and establishing a multi-level connection node database.
[0022] Specifically, in the process of model parsing and pipe component identification and storage, the topology relationship processing module reads the model data file exported from CAD (such as STEP or IGES format) through data parsing algorithms. According to industry standards (such as the entity definition of pipe components in STEP and the geometric element encoding rules in IGES), it identifies the geometric parameters (diameter, length) and topology connection information (inlet / outlet association) of components such as pipes and valves in the file. Then, using a tree-like data structure (such as parent-child node hierarchy), it generates a topology diagram by system level - component level - local node, storing it hierarchically in the database. This achieves accurate parsing and structured storage, thereby ensuring that the position of all connection points, parent relationships, and hierarchical dependencies are encoded in the database for subsequent processing.
[0023] Specifically, in one embodiment, after importing data, the topology processing module identifies 10 pipe segments and 5 tee joints. When establishing the database, it first defines a system-level (main pipe junction point) and component-level (tee branch point) node hierarchy table structure based on the parsed pipe component data (such as information on 10 pipe segments and 5 tee joints) using a database modeling tool (or by programming to create data tables). Then, based on the topology and geometric parameters, it uses a data writing algorithm to set the main pipe junction point as the top-level node and the tee branch point as the middle-level node, and enters information such as relative coordinates and connection component IDs to generate a topology diagram. The hierarchical storage logic is used to avoid redundancy, thus completing the database construction.
[0024] Secondly, the constraint rule generation module extracts the topological relationship information of the pipeline connection points and constructs spatial constraint rules and priority determination matrices between nodes.
[0025] Specifically, this module defines spatial constraint rules based on a topological relationship network (such as an adjacency matrix representing node connections): including minimum distance constraints (to prevent node overlap), angle constraints (to ensure that the connection angle is within the range of 30-150 degrees), and direction constraints (to keep the pipeline flow direction consistent). At the same time, it generates a priority determination matrix (the matrix rows and columns are node IDs, and the values represent priority weights, which are calculated based on the node level or importance, such as the top-level node having a high priority).
[0026] Specifically, the minimum distance constraint calculates the 3D coordinate spacing by traversing node pairs and comparing it with a preset safety threshold (e.g., 1.5 times the pipe diameter). If the limit is exceeded, a conflict is marked. The angle constraint extracts the normal vector of the connecting node, calculates the included angle, and verifies it with a range of 30-150°. If the deviation is too large, a correction is triggered. The direction constraint relies on the pipe flow direction identifier (e.g., the inlet and outlet directions defined during modeling), compares the flow direction vectors of adjacent nodes, and adjusts them when they are inconsistent. The rule parameters are stored in a matrix simultaneously to achieve automated constraint judgment and control.
[0027] During operation, the constraint rule generation module traverses the node database and analyzes the dependencies between connected nodes. For example, the priority of the main pipeline node is set to 5 (highest), the branch node to 3, and the terminal node to 1. A priority determination matrix is used to prioritize adjusting lower-priority nodes in case of conflicts. Specifically, in one embodiment, the module identifies conflicting nodes in the topological network structure (such as two T-junctions being too close). For example, it sets a minimum distance constraint of 0.5 meters between rule nodes A and B and sets a priority matrix based on hierarchy (the main pipeline node has a weight of 0.9, and the branch node has a weight of 0.6) to ensure that higher-weight nodes are fixed in their positions first during subsequent corrections.
[0028] Furthermore, the dynamic correction module, based on the topological network structure and priority determination matrix, dynamically corrects the spatial coordinates of conflicting nodes using a coordinate adjustment algorithm to resolve node misalignment issues in isometric projection. The core of this module is the coordinate adjustment algorithm, which employs an iterative optimization method: first, it detects conflicting nodes (e.g., identifying overlaps or angular deviations through distance calculation); then, it selects adjustment targets based on the priority matrix (lower-priority nodes are moved first); and finally, it applies coordinate offsets (e.g., using a least-squares optimization algorithm to adjust node coordinates while satisfying constraint rules). This solves the node misalignment problem, as isometric projection misalignment often stems from unresolved positional conflicts in the 3D model; through dynamic correction, it ensures that the connection point positions are adjusted to the correct topological relationship before projection.
[0029] In a specific instance, if the module finds that a valve node conflicts with an adjacent tee node (the distance is only 0.3 meters, violating the 0.5-meter constraint), the algorithm dynamically shifts its coordinates by 0.2 meters along the pipe direction based on priority (the valve has a lower weight). After 3 iterations, the position stabilizes, avoiding line intersections caused by node misalignment in the isometric drawing.
[0030] Finally, the isometric projection module maps the corrected 3D node coordinates to the isometric projection plane, generating an isometric drawing of the pipeline that includes topology consistency verification. During operation, this module employs an isometric projection algorithm (e.g., converting 3D coordinates to 2D planar coordinates while maintaining a 120-degree viewing angle) and embeds consistency verification during the projection process: verifying topological relationships (e.g., checking the continuity of connection points) and geometric parameters (e.g., pipe length ratios) to ensure the generated isometric drawing is free of misalignment or breaks. The output after projection is a drawing in SVG or DXF format, along with a verification report (including the geometric parameters of the pipeline components, topological relationships, and verification results).
[0031] The entire system effectively solves the node misalignment problem through multi-module collaboration: topology relationship processing provides basic data, constraint rule generation defines and adjusts the framework, and the core control algorithm of the dynamic correction module directly corrects position conflicts, ensuring topology consistency during isometric projection. This further reduces the misalignment rate when the system processes complex pipeline models.
[0032] The optimization of the multi-level connection node database includes the following steps.
[0033] First, a dynamic learning coefficient is assigned to each node. This coefficient automatically adjusts with the number of conflict corrections to optimize the node's adaptive capability. Specifically, the dynamic learning coefficient α is defined as α = α0 / (1 + k × c), where α0 is the initial learning coefficient (range [0.1, 1.0], optimal value 0.5, representing moderate learning intensity), k is the decay factor (range [0.01, 0.1], optimal value 0.05, controlling the rate of decay), and c is the number of conflict corrections (integer ≥ 0). This formula shows that the dynamic learning coefficient α decreases as the number of conflict corrections c increases, simulating a reduction in correction requirements after node experience accumulation, thus avoiding over-adjustment; this setting balances learning efficiency and stability.
[0034] Specifically, for a pipe connection node, the initial value is α0=0.5. When the 3D model detects a pipe conflict (such as coordinate overlap), the number of conflict corrections c increases, and the dynamic learning coefficient α decreases (e.g., after the number of conflict corrections c=5, the dynamic learning coefficient α≈0.38), thereby reducing the sensitivity of the node in subsequent coordinate corrections.
[0035] Secondly, a learning mechanism based on historical correction values is introduced during the coordinate correction process to optimize current decisions using past data. This mechanism calculates the new correction value using the formula Δx_new = β × Δx_avg + (1 - β) × Δx_current, where Δx_avg is the average historical correction value (based on the most recent n times, n=5 being optimal), extracted from a multi-level connection node database that records historical data for each coordinate correction. Δx_current is the current required correction value, generated in real-time by the dynamic correction module, and β is a preset weighting coefficient (range [0.1, 0.9], optimal value 0.7, emphasizing historical trends). By weighted fusion of historical and current values, random fluctuations are reduced; this setting improves correction accuracy based on historical patterns. In one embodiment, when correcting pipe node coordinates (e.g., adjusting bend positions to avoid collisions), the system takes the historical Δx_avg (e.g., the average offset of the past 5 times is 2mm), combines it with the current requirement (Δx_current=3mm), and outputs a smooth Δx_new≈2.3mm, specifically avoiding jitter in the pipe isometric drawing.
[0036] Finally, when the learning coefficient falls below a preset threshold (e.g., α < 0.2), the system automatically generates structural optimization suggestions, indicating that the node's learning ability is insufficient and system-level improvements are needed. For example, in a pipeline system, if the node's α drops to 0.15, the system suggests optimizing the 3D model structure (e.g., adding support frames or changing the pipe branch angles) to reduce collision frequency and improve database stability.
[0037] The spatial constraint rules are established as follows.
[0038] The first step is to detect the deviation between the actual included angle and the standard connection angle between adjacent nodes. Using the three-dimensional coordinates of the pipe nodes, the direction vectors of the connecting line segments between adjacent nodes are extracted through three-dimensional geometric calculations. The actual included angle θ is calculated using the vector dot product formula cosθ = (v1 · v2) / (|v1| × |v2|). This is compared with a preset standard angle (e.g., 90°), and the difference is the deviation. This determines whether the angle deviation meets the design specifications, thus completing the angle deviation detection.
[0039] By comparing the actual measured angles between nodes with the preset standard angles, the deviation value is calculated to assess whether it meets the design specifications. For example, in a 3D model-driven isometric drawing generation system for pipe components, nodes represent pipe connection points; the standard connection angle is 90 degrees (such as a right-angle elbow), while the actual included angle may be 88 degrees due to measurement error, with a deviation of 2 degrees, so the corresponding deviation value is 2 degrees.
[0040] The second step is to trigger the angle compensation mechanism when the angle deviation exceeds the allowable threshold. This step means that a deviation threshold (such as 1 degree) is preset. If the deviation exceeds this value, the compensation mechanism is automatically activated to correct the angle error and ensure system accuracy. Specifically, in one embodiment, if the deviation in the piping system is 2 degrees and the preset deviation threshold is set to 1 degree, the compensation mechanism is triggered to prevent cumulative errors in the generation of isometric drawings.
[0041] The third step is to decompose the compensation angle correction into rotational components in the three-dimensional coordinate system for coordinate updates. This means decomposing the overall angle correction (e.g., Δθ) into rotational components (Δα, Δβ, Δγ) around the X, Y, and Z axes, and applying these components to update the node coordinates. The formula is: correction decomposed into Δα, Δβ, Δγ, where Δθ = √(Δα² + Δβ² + Δγ²) (in radians). The parameters Δα, Δβ, and Δγ represent the rotation angles around the X, Y, and Z axes, typically ranging from [-π / 2, π / 2] radians (approximately -90° to 90°) to avoid gimbal lock issues; the optimal value is 0, indicating no deviation. Vector decomposition transforms the overall correction into orthogonal rotational components, ensuring precise adjustment in three-dimensional space. In piping systems, decomposition allows independent control of coordinate updates along each axis, avoiding nonlinear errors and improving model stability. For example, in a pipeline isometric mapping system, if the angle correction is 0.035 radians (about 2 degrees), it can be decomposed into Δα=0.02 radians, Δβ=0.01 radians, and Δγ=0.028 radians, and the node coordinates are updated to restore the elbow to the standard 90 degrees, thus jointly constructing a spatial constraint rule to control the node angle.
[0042] The coordinate adjustment algorithm includes the following steps.
[0043] First, the displacement weight factor of each node is calculated based on the node priority determination matrix. This step quantifies the importance of nodes through the priority matrix and calculates the displacement weight factor for each node. A larger displacement weight factor indicates higher mobility of the node during correction; nodes with higher priority have smaller weights to prioritize maintaining their positional stability. The formula is: w_i = p_i / max(p_j), where p_i represents the priority value of node i (range [0,1], with an optimal value of 1 representing the highest priority), and w_i is the displacement weight factor (range [0,1]). This formula ensures that high-priority nodes move at a small proportion, avoiding excessive displacement of critical components and improving system reliability.
[0044] Specifically, if the priority of pipe connection points such as flanges is set to 0.9 (high) and the priority of elbows is set to 0.7 (medium), then the flange weight factor w = 0.9 / 0.9 = 1 (less movement), and the elbow weight factor w = 0.7 / 0.9 ≈ 0.78 (more movement), so the flange position is protected first.
[0045] Secondly, a three-dimensional coordinate correction is established based on the displacement weight factor and spatial constraint rules for correction. This step defines the coordinate correction for each node according to preset spatial rules (such as minimum spacing requirements). The correction is calculated based on the deviation between the current coordinates and the constraints, ensuring that the model meets physical safety standards. The formula is: Δx = c · (d - d_min) · u, where Δx refers to the coordinate correction, d is the current spacing vector, d_min is the minimum constraint distance (range > 0, optimal value 0.1 meters), c is the correction coefficient (range [0.1, 1], optimal 0.5), and u is the unit direction vector. This formula quantifies the deviation and generates a linear correction to avoid overshoot. For example, if the distance between two adjacent nodes in a pipeline system is 0.15 meters, which is less than the constraint value of 0.2 meters, then the correction Δx = 0.5 · (0.2 - 0.15) · u = 0.025 · u meters is calculated and adjusted in the direction away from the constraint.
[0046] Next, when the node spacing is less than a preset safety threshold, proportional displacement correction is performed based on the displacement weighting factor and the direction of the normal vector. This step is triggered only when the spacing is below the threshold (e.g., 0.1 meters). It combines the weighting factor and the normal vector (perpendicular to the surface direction) for proportional displacement, with higher-weight nodes moving more and lower-weight nodes moving less, while avoiding collisions along the normal direction. The formula is: Δx = k · w · n, where k is the proportional factor (range [0.05, 0.2], optimal 0.1), w is the weighting factor, and n is the unit normal vector. This formula achieves smooth displacement and prevents node overlap. For example, if the pipe node spacing is 0.08 meters < the 0.1-meter threshold, the elbow weight w = 0.78, and the normal vector n points outwards, then the displacement Δx = 0.1 · 0.78 · n ≈ 0.078 · n meters, the elbow moves outwards, and the flange remains almost stationary.
[0047] Finally, the corrected coordinates are checked for topology consistency with adjacent nodes. This step verifies whether the corrected coordinates maintain the original connection relationships (such as pipe end alignment), ensuring the integrity of the topology structure and preventing breaks or distortions through distance and angle checks. For example, if the distance between the pipe flange and the adjacent elbow is restored to more than 0.2 meters after correction, and the connection angle error is less than 5 degrees, the check passes; otherwise, the correction is rolled back and readjusted.
[0048] The determination of the displacement weighting factor includes the following steps: First, the steps include obtaining the node's hierarchical depth in the topology and the type coefficient of the pipe assembly to which it belongs. This step involves collecting basic data, where hierarchical depth reflects the node's position in the topology (e.g., the number of layers from the root node), affecting the priority of displacement calculation; the type coefficient represents the inherent properties of the assembly type (e.g., the sensitivity of a valve or elbow), used to quantify the contribution of different assemblies to displacement. For example, in a 3D model-driven isometric projection generation system for pipe assemblies, a node might be a valve located on a secondary branch, with a hierarchical depth of 2 and a type coefficient of 0.8 (a relatively high coefficient due to the need for precise valve alignment).
[0049] Secondly, the step involves calculating the initial weighting factor using a preset weighting function. This weighting function is defined as weight_initial = depth × coeff_type + offset, where depth is the layer depth (integer range 1 to 10, with an optimal value of 5 representing a medium-importance layer), coeff_type is the type coefficient (floating-point range 0.1 to 1.0, with an optimal value of 0.7 corresponding to critical components such as flanges), and offset is the offset constant (fixed value 0.1, range 0 to 0.5, ensuring basic weight). By linearly combining depth and type coefficient, the relative weight of nodes in displacement calculation is evaluated; this setting balances topological location and component characteristics, avoiding the dominance of a single factor. Specifically, in one embodiment, if the node is a bend at depth 3 (type coefficient 0.5), then the initial weighting factor weight_initial = 3 × 0.5 + 0.1 = 1.6.
[0050] Finally, when the calculated weight factor is less than the preset weight factor, the preset weight factor is forcibly set as the minimum correction strength. This step means introducing a lower limit protection to ensure that the weight is not lower than the preset weight factor threshold (e.g., min_weight=0.2), preventing unimportant nodes from causing calculation instability. For example, in a pipeline system, if a straight pipe with a depth of 1 (type coefficient 0.1) has a calculated weight of 0.1 × 1 + 0.1 = 0.2, but the preset minimum value is 0.3, it is forcibly set to 0.3 to maintain the correction strength.
[0051] The dynamic correction process includes the following steps: First, establish a single-node motion trajectory prediction model to predict the coordinate change trend within a preset time period. This step analyzes the historical motion data of the node through mathematical modeling, infers the future position offset, and identifies potential risks in advance. The node represents the pipeline connection point, and the prediction model estimates the moving direction within the next 5 seconds based on the historical coordinate changes. Specifically, the formula P(t) = P0 + V × t is used for prediction, where P(t) is the predicted position (a three-dimensional vector) at time t, P0 is the initial position (range: system coordinate space), V is the average velocity vector (range: [-10, 10] mm / s, and the optimal value is fitted based on historical data), and t is the time (range: [0, T], where T = 5 seconds is the preset optimal value). This formula simplifies the calculation, ensures real-time performance, and is applicable to the scenario of smooth pipeline adjustment.
[0052] Second, when the predicted trajectory conflicts with the safety area of other nodes, apply a preventive correction amount. This step detects whether the predicted position invades the safety buffer of adjacent nodes. First, obtain the three-dimensional coordinates of the predicted trajectory node and the adjacent node, and calculate the distance d between the two nodes. Then, compare it with the safety buffer radius r (such as 10 mm). If d < r, it is determined that the "safety buffer is invaded", triggering preventive correction; (such as a spherical area with a radius of 10 mm), and generate a preventive offset to avoid collisions. In one embodiment, if the pipeline system predicts that the trajectory of node A will invade the safety area of node B, then apply a correction amount ΔP (such as [-2, 0, 1] mm). The formula ΔP = K × D is used for calculation, where D is the invasion distance vector (range: positive real number), and K is the gain coefficient (range: [0.5, 2], and the optimal value 1.0 is used to balance the response speed), which means proportional control of the invasion depth. Such a setting can minimize overshoot.
[0053] Finally, superimpose the preventive correction amount onto the current correction amount. This step integrates the preventive offset into the real-time adjustment, updates the node position, and ensures the dynamic optimization of the system. For example, when the pipeline is generated, the current correction amount is [1, 0, 0] mm. After superimposing ΔP, it becomes [-1, 0, 1] mm, avoiding pipeline interference. The entire process improves safety and accuracy.
[0054] Next, describe the mapping of the isometric projection plane of the present invention. This mapping process includes the following steps: First, calculate the node position error in the projection plane coordinate system. Second, when the error exceeds the preset position error threshold, reverse-adjust the three-dimensional coordinate correction amount. Finally, perform two-way iterative correction until the error reaches the standard or the preset number of iterations is reached.
[0055] The first step involves calculating the node position error in the projection plane coordinate system. This error represents the deviation between the actual and desired positions of the 3D model nodes on the projection plane. The node position error *e* is calculated using the formula... , where x a and y a These are the actual projected coordinates of the node, typically ranging from any real number (unit: pixels or millimeters), x e and y e These are the desired projected coordinates, with an optimal value of 0, indicating no error. This formula quantifies positional differences to determine projection accuracy; its setting is intended to capture Euclidean distances, ensuring that errors are measurable.
[0056] Specifically, for pipe connection nodes, calculate the error between their actual position on the isometric projection plane and the expected position on the design drawings. If the x-axis of the pipe node... a and y a From the projection of the 3D model, and x e and y e According to engineering specifications, an error exceeding 1mm will trigger an adjustment.
[0057] In the second step, when the node position error exceeds a preset position error threshold, the 3D coordinate correction is adjusted in reverse. This means that if the node position error exceeds the threshold, the 3D model coordinates are modified in reverse to reduce projection deviation. This step involves the formula ΔP = -α · ∇e, where ΔP is the 3D coordinate correction (unit: mm), α is the learning rate (range 0.01-0.1, optimal value 0.05), and ∇e is the error gradient vector. Optimizing the coordinates using the negative gradient direction is set for efficient convergence and to avoid over-adjustment. For example, in a pipeline system, specifically, if the projection error of a pipeline node is 2mm (exceeding the allowable 1mm), its 3D coordinates are adjusted in reverse, such as by reducing the vertical position of the pipeline node to correct the offset under the isometric viewpoint.
[0058] In the third step, bidirectional iterative correction is performed until the error meets the standard or reaches the preset number of iterations. This means that error calculation and coordinate adjustment are performed repeatedly until the error is less than the tolerance value or the number of iterations reaches the upper limit (e.g., 10 times). There is no specific formula for this process, but the iteration count N is preset to 5-20 times, with an optimal value of 10 times to ensure efficiency. For example, in one embodiment, for a pipe isometric drawing, the system repeatedly corrects the three-dimensional coordinates and projection errors of multiple nodes. Specifically, if the initial error is 3mm, it is reduced to 0.5mm (meeting the standard) after 3 iterations, or terminated after 10 iterations to avoid infinite looping.
[0059] The entire process ensures that the isometric projection accurately maps the 3D model. In the example, it is applied to a piping system and can optimize node positions to generate accurate isometric drawings.
[0060] Next, the bidirectional iterative process of the present invention will be described.
[0061] First, the steps include: recording historical coordinate correction data and establishing a prediction model; when the error rate of change tends to stabilize, using the prediction model to generate the final correction scheme (predicted correction amount); and weighted fusion of the predicted correction amount and the current correction amount. The meaning of each step is as follows.
[0062] Recording historical coordinate correction data and building a predictive model involves collecting historical information (such as correction amounts and error values) for each coordinate adjustment during the iteration process, and training a predictive model (such as a linear regression or time series model) based on this information to infer future correction trends. Specifically, this involves recording the coordinate offset (such as X and Y direction correction values) for each iteration and using this data to build a predictive model. Specifically, a simple linear model is trained using historical correction sequences to predict the correction amount for the next round, thereby reducing the number of subsequent iterations.
[0063] When the rate of change of node position error tends to stabilize, the prediction model is activated to generate the final correction scheme. This involves monitoring the rate of change of coordinate error (such as derivative or relative change). When the value is lower than a set threshold (e.g., less than 0.01), it indicates that the iteration has converged. At this point, the prediction model is activated to output the optimized correction scheme, avoiding invalid iterations. For example, in the above-mentioned pipeline isometric mapping system, the system calculates the rate of change of the root mean square error of the coordinates. When this rate stabilizes below 0.005, the prediction model is activated to generate the final correction scheme. The final correction scheme is output by the prediction model based on the convergence error: when the rate of change of coordinate error is lower than the threshold (e.g., 0.01), it is determined that the iteration has converged. The prediction model combines historical correction data and geometric constraint rules to output the "adjusted node coordinate set" (including the three-dimensional displacement of each node), directly replacing the original coordinates, quickly optimizing the alignment accuracy of the isometric drawing, avoiding repeated iterations, and improving generation efficiency.
[0064] Specifically, the model outputs an adjusted coordinate set to directly optimize the alignment accuracy of the isometric drawing and improve generation efficiency.
[0065] Weighted fusion of the predicted correction and the current correction involves combining the predicted correction (Δ_pred) generated by the prediction model with the correction calculated in the current iteration (Δ_current), and generating the final correction (Δ_final) using a weighted formula to balance the prediction trend and real-time feedback. The formula is: Δ_final = w × Δ_pred + (1 - w) × Δ_current, where w is a weighting factor (ranging from 0 to 1, with an optimal value of 0.6, based on empirical testing to ensure a smooth transition). The parameter w controls the contribution of the prediction; too high a value (e.g., >0.8) may ignore current noise, while too low a value (e.g., <0.4) weakens the prediction advantage; the optimal value of 0.6 minimizes oscillations in most scenarios. By fusing the two, random errors are reduced. This setting improves robustness because the prediction model may lag, and the current correction contains noise. For example, in a pipeline isometric drawing system, the predicted correction is Δ_pred = 0.5 mm (X direction), the current correction is Δ_current = 0.8 mm, and Δ_final = 0.6 × 0.5 + 0.4 × 0.8 = 0.62 mm is calculated with w = 0.6. Specifically, it is applied to the coordinate correction of pipeline connection points to ensure that the isometric drawing converges quickly to the accurate position.
[0066] Next, the topology consistency verification of the present invention will be described.
[0067] First, establish a matrix of flexible constraint relationships between nodes. Based on safety specifications (e.g., valve-to-pipe spacing ≥ 0.5 meters), define node pair constraint rules, traverse the node pairs, and fill the minimum spacing into the corresponding positions in the matrix to complete the construction. This step defines the minimum spacing constraints between nodes and stores the ideal distance relationships in matrix form, ensuring the layout complies with safety specifications. Nodes include pipe connection points or valve interfaces; the constraint matrix records the minimum spacing between nodes, such as the distance between valve and pipe connection points should be no less than 0.5 meters to avoid collisions.
[0068] Secondly, when the corrected coordinates cause new spacing conflicts (such as node spacing being less than a threshold), a secondary correction based on the elasticity coefficient is performed. This step adjusts the coordinates using the formula Δx_i = k * (d_{ij} - d_{\min}) * \frac{\partial d_{ij}}{\partial x_i}. Where Δx_i is the coordinate adjustment amount, d_{ij} is the actual spacing, d_{min} is the minimum allowable spacing (e.g., 0.5 meters), and k is the elasticity coefficient (ranging from 0.1 to 0.9, with an optimal value of 0.7, used to control the correction intensity). The formula means: gradient adjustment is calculated based on the spacing deviation to gradually reduce conflict energy. This setting avoids drastic changes and achieves smooth convergence. Specifically, in a piping system, if the valve node spacing after correction is 0.4 meters, the formula is applied to adjust the position; when k=0.7, Δx_i makes the spacing approach d_{min}.
[0069] Finally, if conflicts still exist after the second correction, they are marked as nodes requiring manual verification, and a conflict visualization interface is generated. This step identifies nodes that cannot be resolved automatically and provides an interactive view to assist decision-making. For example, in the pipe isometric drawing interface, conflicting nodes (such as pipe connection points spaced 0.45 meters apart) are highlighted in red, allowing engineers to manually adjust them to avoid design errors.
[0070] Next, the determination of the elastic coefficient of the present invention will be described.
[0071] First, the material properties of the pipeline components and the system pressure rating parameters are statistically analyzed. This step involves collecting the inherent characteristics of the pipeline material (such as elastic modulus and Poisson's ratio) and the operating pressure range of the system to establish basic data input. Second, an elastic coefficient that varies with operating conditions is generated through a dynamic calculation function. This function dynamically adjusts the elastic coefficient based on the input parameters to reflect the influence of actual operating conditions. The specific formula is E = E_m × (1 + β × P), where E_m represents the material's elastic modulus (range: 50-400 GPa, depending on the material type, e.g., the optimal value for carbon steel is 200 GPa), β is the pressure sensitivity coefficient (range: 0.001-0.1, optimal value 0.01, used for fine-tuning pressure effects), and P is the real-time system pressure (range: 0-100 MPa, typical for pipeline applications). By calculating the effective elastic coefficient under operating conditions, the changes in material behavior caused by pressure are simulated. This setting is because pipelines may undergo slight deformation under high pressure; dynamic adjustment can improve model accuracy and avoid errors caused by static coefficients. Then, when the elastic coefficient exceeds a critical value (such as the threshold corresponding to the material's yield strength, which is usually set to 1.1 times E_m), a local reconstruction mechanism for the three-dimensional model is activated. This mechanism only updates the geometric model of the affected pipe region to handle potential deformation or stress concentration problems.
[0072] In one embodiment, a 3D model-driven isometric drawing generation system for pipeline components is applied to a chemical plant's pipeline network. For example, the component material is stainless steel (E_m = 193 GPa), and the pressure rating is 15 MPa. When the system pressure rises to 20 MPa, the dynamic calculation function generates an elastic coefficient E = 193 × (1 + 0.01 × 20) = 231.6 GPa. If the critical value is set to 210 GPa (based on material safety margin), E_m exceeds the threshold, triggering a local reconstruction mechanism: the system automatically updates the 3D model of the high-pressure pipeline segment and regenerates the isometric drawing to ensure that the drawing accurately reflects the deformed pipeline layout and avoids design conflicts.
[0073] The present invention discloses a method and system for generating isometric views of pipe components driven by a 3D model, comprising: First, obtaining the geometric parameters (such as diameter, length, and bending angle) and topological relationship information (such as parent-child relationships and adjacency relationships of connecting nodes) of the pipe components in the 3D pipe model through a topology relationship processing module, and establishing a multi-level connection node database based on this. This database stores the connection attributes between nodes hierarchically (such as master nodes, child nodes, and their spatial coordinates), providing a structured data foundation for subsequent processing. Second, a constraint rule generation module extracts the topological relationship network structure of pipe connection points from the database (e.g., identifying connection paths and dependencies between nodes), and constructs spatial constraint rules (such as minimum distance constraints and angle alignment rules) and a priority determination matrix between nodes accordingly. (This matrix assigns priority to nodes according to their hierarchy and importance in the network, for example, primary connection points have higher priority than branch points) to ensure that critical conflict points are handled first during the control process. Next, the dynamic correction module, based on the aforementioned topological network structure and priority determination matrix, dynamically corrects the spatial coordinates of conflicting nodes (e.g., overlapping or misaligned connection points in 3D space) using coordinate adjustment algorithms (such as iterative optimization algorithms or gradient descent). This algorithm calculates the node position offset in real time and adjusts the positions of high-priority nodes according to the priority matrix to eliminate conflicts, thereby ensuring that all connection points are accurately aligned in 3D space and avoiding node misalignment problems in the isometric drawing. Finally, the isometric projection module maps the corrected 3D node coordinates to the isometric projection plane (using isometric or biaxial projection algorithms) to generate a pipeline isometric drawing that includes topology consistency verification (the verification process compares the projected node connection relationships with the original topology database to ensure there are no misalignments or breaks).
[0074] To address the issue of node misalignment in isometric projections by adjusting the positions of pipe connection points based on the topological relationships in a 3D model, this system employs a constraint rule generation module and a dynamic correction module working collaboratively. Specifically, the constraint rule generation module analyzes the topological network structure (e.g., connection paths and dependencies between nodes), constructs spatial constraint rules (e.g., requiring adjacent nodes to maintain specific distances and angles) and a priority determination matrix (which categorizes nodes into high-priority (e.g., trunk connection points) and low-priority (e.g., branch connection points)), thus providing a rule-based foundation for adjustment. When the 3D model is directly projected, node misalignment often results from spatial conflicts (e.g., coordinate overlap or angular deviation), leading to mismatched connection points in the isometric projection. The dynamic correction module, based on these rules and matrices, uses coordinate adjustment algorithms (e.g., minimizing positional errors between nodes through iterative calculations) to prioritize adjusting the coordinates of high-priority nodes (e.g., moving conflicting points to conform to constraint rules) and dynamically updates the positions of low-priority nodes, ensuring spatial consistency across the entire network. This process, through real-time correction of conflicting nodes (e.g., eliminating coordinate overlap), ensures precise alignment of connection points in 3D space, maintaining topological integrity after isometric projection and completely resolving the node misalignment problem. Ultimately, the isometric drawing generated by the system passed a consistency check to verify that there were no misalignments, improving the accuracy and readability of the drawing. The entire process efficiently integrates 3D model data processing, rule constraints, and dynamic control, achieving a seamless conversion from model to drawing.
[0075] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another.
[0076] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process. Furthermore, the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functionality involved.
[0077] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus or device (such as a computer-based system, a processor-included system or other system that can fetch and execute instructions from, an instruction execution system, apparatus or device).
[0078] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. All or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware, the program being stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiments.
[0079] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. This storage medium can be a read-only memory, a disk, or an optical disk, etc.
[0080] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions or improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A method for generating isometric views of a pipe assembly driven by a three-dimensional model, characterized in that, The method includes the following steps: S1. Obtain the geometric parameters and topological relationships of pipe components in the 3D pipe model, and establish a multi-level connection node database; S2. Based on topological relationships and node database, construct spatial constraint rules and priority determination matrix between nodes; S3. Based on spatial constraint rules and priority judgment matrix, the spatial coordinates of conflict nodes are dynamically corrected through coordinate adjustment algorithm; S4. Map the corrected spatial coordinates of the conflicting nodes to the isometric projection plane to generate an isometric view of the pipeline component that includes topology consistency verification.
2. The method for generating isometric views of pipe components driven by a three-dimensional model according to claim 1, characterized in that, The establishment of the multi-level connection node database in step S1 includes the following sub-steps: S11. Generate a topology diagram based on the geometric parameters and topological relationships of the pipeline components; S12. Establish a multi-level connection node database based on the topology diagram; S13. Assign dynamic learning coefficients to the nodes of the multi-level connected node database; S14. If the dynamic learning coefficient is lower than the preset threshold, generate optimization suggestions for the multi-level connection node database; otherwise, maintain the original multi-level connection node database.
3. The method for generating isometric views of pipe components driven by a three-dimensional model according to claim 1, characterized in that, The establishment of spatial constraint rules in step S2 includes the following sub-steps: S21. Calculate the deviation between the actual included angle between adjacent nodes of the pipe assembly and the preset standard angle; S22. When the deviation exceeds the preset deviation threshold, the angle compensation mechanism is triggered. S23. Based on the angle compensation mechanism, the compensation angle correction amount is decomposed into the rotation component of the three-dimensional coordinate system, and spatial constraint rules are established by updating the coordinates.
4. The method for generating isometric views of pipe components driven by a three-dimensional model according to claim 1, characterized in that, The coordinate adjustment algorithm in step S3 includes the following sub-steps: A31. Calculate the displacement weight factor of each node based on the priority determination matrix between nodes; A32. Calculate the 3D coordinate correction based on the displacement weighting factor and spatial constraint rules to correct the node spacing; A33. If the corrected node spacing is less than the preset safety threshold, proportional displacement correction shall be performed according to the displacement weight factor and the normal vector direction. A34. Perform a topology consistency check between the proportional displacement corrected coordinates and the adjacent nodes. If the check fails, correct them again.
5. The method for generating isometric views of pipe components driven by a three-dimensional model according to claim 4, characterized in that, The calculation of the displacement weighting factor includes the following sub-steps: A311. Obtain the node's hierarchical depth and the type of its associated pipeline component in the topology; A312. Calculate the initial weight factor based on the parameters of the acquired nodes and the preset weight function; A313. If the calculated initial weight factor is less than the preset weight factor, the preset weight factor is forcibly set as the final weight factor; otherwise, the initial weight factor is set as the final weight factor.
6. The method for generating isometric views of pipe components driven by a three-dimensional model according to claim 1, characterized in that, The dynamic correction in step S3 includes the following steps: S31. Establish a node motion trajectory prediction model based on a multi-level connection node database to predict the future trajectory change trend of node coordinates; S32. If the predicted trajectory of a node conflicts with the safe zone of other nodes, a preventive correction is applied. S33. Dynamically correct node positions by adding the preventive correction amount to the current trajectory correction amount.
7. The method for generating isometric views of pipe components driven by a three-dimensional model according to claim 1, characterized in that, The mapping of the axonometric projection plane in step S4 includes the following steps: B41. Calculate the node position error of the 3D model node located on the isometric projection plane; B42. When the node position error exceeds the preset position error threshold, adjust the 3D node coordinate correction amount in the opposite direction. B43. Perform bidirectional iterative correction on the node coordinates until the correction conditions are met, thereby adjusting the reverse node coordinate correction amount.
8. The method for generating isometric views of a pipe assembly driven by a three-dimensional model according to claim 7, characterized in that, The bidirectional iterative correction in step B43 includes the following sub-steps: B431. Record historical data of node coordinate correction and build a prediction model based on the historical data of coordinate correction; B432. If the rate of change of node position error tends to stabilize, the prediction model is activated to generate the prediction correction amount; otherwise, iterative correction continues. B433. Generate the final correction amount based on corrected historical data and predicted correction amounts.
9. The method for generating isometric views of pipe components driven by a three-dimensional model according to claim 1, characterized in that, The topology consistency check includes: C41. Establish a flexible constraint relationship matrix between nodes based on topological relationships and node database; C42. When the corrected coordinates are detected to cause new spacing conflicts, a second correction is performed. C43. If conflicts still exist after the second correction, mark them as nodes to be manually verified and generate a conflict visualization interface.
10. A method for generating isometric views of a pipe assembly driven by a three-dimensional model according to claim 9, characterized in that, The secondary correction in step C42 is performed based on the elasticity coefficient, and the determination of the elasticity coefficient includes the following sub-steps: C421. Statistical analysis of material properties of piping components and system pressure rating parameters; C422. Elasticity coefficients are generated by dynamically calculating functions based on statistical parameters. C423. If the elastic coefficient exceeds the preset critical value, the three-dimensional model local reconstruction mechanism will be activated to update the geometric model of the affected pipeline area.
11. A three-dimensional model-driven isometric drawing generation system for pipe components, characterized in that, The system is used to implement the method for generating isometric views of a three-dimensional model-driven pipeline assembly as described in any one of claims 1 to 10, and the system includes: The topology processing module is used to obtain the geometric parameters and topology relationships of pipe components in the 3D pipe model, and to establish a multi-level connection node database based on the geometric parameters and topology relationships. The constraint rule generation module, based on topological relationships and a node database, is used to construct spatial constraint rules and priority determination matrices between nodes. The dynamic correction module, based on spatial constraint rules and priority determination matrix, dynamically corrects the spatial coordinates of conflicting nodes through a coordinate adjustment algorithm. The isometric projection module is used to map the spatial coordinates of the corrected nodes to the isometric projection plane, generating isometric diagrams of pipe components that include topology consistency checks.