Underground garage comprehensive pipeline space conflict identification and optimization method based on BIM model

Abstract

The invention relates to an underground garage comprehensive pipeline space conflict identification and optimization method based on a BIM model, and aims to solve the problems of frequent occurrence of space conflicts, low identification efficiency and strong subjectivity of an optimization scheme in underground garage multi-professional pipeline layout. The method comprises the following steps: firstly, constructing a BIM model containing a structure and a pipeline component, extracting geometric and attribute parameters of the component, and performing data preprocessing; secondly, defining three types of space occupation models of an entity space (ES), a safe working space (SWS) and an efficient working space (EWS), detecting six types of space conflicts by adopting an axis alignment bounding box (AABB) and directed bounding box (OBB) algorithm, and calculating a space conflict severity index; and finally, outputting an optimal pipeline arrangement scheme and an updated conflict detection report through genetic algorithm iterative optimization by taking the conflict index and the pipeline path length as targets. According to the method, automatic and quantitative identification and global optimization of pipeline space conflicts are realized, and rationality and engineering practicability of underground garage pipeline layout are improved.

Description

Technical Field

[0001] This invention relates to the field of spatial conflict detection technology, specifically a method for identifying and optimizing spatial conflicts in integrated pipelines in underground parking garages based on BIM models. Background Technology

[0002] With the continuous advancement of urbanization, underground parking garages, as an indispensable supporting facility in building construction, have their internal integrated pipeline systems (covering multiple disciplines such as water supply and drainage, fire protection, HVAC, and electrical systems) whose layout rationality directly affects construction efficiency, subsequent operation and maintenance safety, and space utilization.

[0003] However, existing technologies for integrated pipeline design and optimization in underground parking garages have significant limitations: the definition of pipeline space occupancy lacks a systematic approach, relying heavily on experience-based judgments and failing to clearly distinguish between physical space, safe working space, and efficient working space, resulting in incomplete and inaccurate identification of spatial conflicts; conflict detection remains largely qualitative, making it difficult to quantify the severity of different types of conflicts and affecting the determination of optimization priorities; the optimization process relies heavily on manual adjustments or simple algorithms, which, when faced with complex scenarios involving the intersection of multiple professional pipelines, easily fall into local optima, failing to achieve a coordinated balance between minimizing global spatial conflicts and path economy. These problems frequently lead to collisions and insufficient spacing in underground parking garage pipeline layouts, increasing construction difficulty and costs, and even creating safety hazards for later operation and maintenance.

[0004] Based on this, a method for identifying and optimizing spatial conflicts of integrated pipelines in underground parking garages based on BIM models is proposed, aiming to solve the above-mentioned pain points through systematic spatial modeling, accurate conflict detection and global optimization algorithms. Summary of the Invention

[0005] To address the technical problems mentioned in the background section, this invention proposes a method for identifying and optimizing spatial conflicts in integrated pipelines in underground parking garages based on BIM models.

[0006] Therefore, the technical solution adopted by the present invention is as follows: a method for identifying and optimizing spatial conflicts of integrated pipelines in underground parking garages based on BIM models, the method comprising the following steps: Step S1: Under constraints, construct a BIM model of the underground parking garage; the BIM model includes structural components and pipeline components. Export and preprocess the BIM model to generate BIM data for conflict detection. Step S2: Using the BIM data as input, construct a space occupancy model based on the entity space ES, safe working space SWS, and efficient working space EWS of the pipeline component, and output the space occupancy geometric parameters of the pipeline component; Step S3: Using a collision detection algorithm, with the spatial occupancy geometric parameters of the pipeline components as input, sequentially select the i-th pipeline component and the j-th pipeline component to form a unique component pair. For the component Perform collision detection and output a collision detection report; Step S4: Using the BIM data, the spatial occupancy geometric parameters of the pipeline components, and the conflict detection report as input, a genetic algorithm is used to optimize the layout of the pipeline components to obtain the optimal pipeline component layout scheme.

[0007] Furthermore, the structural components and pipeline components are respectively: The structural components include, but are not limited to: beams, columns, slabs, and walls; The pipeline components include, but are not limited to: water supply and drainage pipelines, fire protection pipelines, HVAC pipelines, electrical pipelines, and communication pipelines; The structural components and the pipeline components are collectively referred to as components, which include the following key attribute parameters: unique ID, type, size, material, installation elevation, and connection relationship.

[0008] Furthermore, the constraints include: Spatial constraints: The pipeline model must be arranged within the space defined by the main structure; Regulatory constraints: The spacing and slope of pipeline components comply with national standards; Association constraints: Equipment and pipeline components are bound by a unique ID to ensure the integrity of the connection relationship.

[0009] Furthermore, the BIM model data export and preprocessing includes: The export process involves exporting the geometric and attribute data of the BIM model into IFC or RVT data formats supported by Navisworks clash detection software. The preprocessing involves model simplification and data validation of the exported IFC or RVT data format. The model simplification includes: geometric simplification, attribute simplification, and hierarchical simplification; The data verification includes: checking whether the component ID is complete; and checking whether the layout of pipeline components meets national requirements.

[0010] Furthermore, step S2 includes the following steps: Step S201: Model the entity space ES, where the entity space refers to the physical space occupied by the pipeline component body; The pipeline components are divided into regular components and irregular components, and their construction methods are as follows: The regular components: using the axis-aligned bounding box (AABB) method, for the i-th pipeline component, its AABB is determined by the minimum coordinate point. and the maximum coordinate point Together, the size of the solid space of the i-th pipeline component is defined as follows: in, The coordinates represent the coordinates of the solid space enclosed region of the i-th pipeline component; The irregular component: using the directed bounding box (OBB) method, for the i-th pipeline component, its OBB is defined by the center point E and three mutually orthogonal axes. and half length along each axis definition: in, , and The constraints are as follows: ; E represents the irregular component. The coordinates of the center point; Step S202: Model the safe working space (SWS). The safe working space refers to the minimum operating space required to ensure the safe operation of the pipeline. Based on the ES, the safe working space of the i-th pipeline component is extended outward by a distance, and the size of the safe working space is expressed as: in, This represents the safety expansion factor, which is an empirical parameter determined based on pipeline type, size, construction process, and safety specifications. The space expansion function represents the function that expands the space of the space. according to The coefficients are expanded; Step S203: Model the efficient workspace (EWS). The efficient workspace refers to the reasonable operating space under safe construction conditions. Based on the SWS, the model is further extended outward. The size of the efficient workspace of the i-th pipeline component is expressed as: in, Indicates the efficiency expansion factor; The space expansion function represents the function that expands the space of the space. according to The coefficients are expanded.

[0011] Furthermore, step S3 includes the following steps: Step S301: Input the spatial occupancy geometric parameters of the pipeline components. For the pipeline components included in the input parameters, sequentially select the i-th component and the j-th component to form a unique component pair. ; sequentially for the components Perform a conflict check on the occupied space; in, U represents the total number of pipeline components included in the BIM data; Step S302: Define the conflict types, which include six categories: ES-ES conflict, ES-SWS conflict, ES-EWS conflict, SWS-SWS conflict, SWS-EWS conflict and EWS-EWS conflict; Step S303: Perform collision detection using a collision detection algorithm, as follows: S3031: For the component Perform AABB overlap test; The AABB structure is represented as: The AABB structure is represented as: The overlap condition is: and and Then AABB overlaps; If the overlap condition is not met, then the components will be... Mark as conflict-free; if the overlap condition is met, perform OBB collision detection; S3032: For the components that satisfy the overlap condition... Perform OBB collision detection; Inspect 15 potential split shafts: member and Corresponding to and ,Pick and The three local coordinate axes are respectively and ; Calculation components Local coordinate axes and components The cross product of the local coordinate axes is calculated using the following formula: For any separate axis L, calculate the component. and The projection of L, if there exists such that Then the component and No conflict, the components are paired Mark as conflict-free, otherwise mark the component pair Marked as having a spatial conflict; in, Represents the q-th component Along the separation axis The projection; Step S304: Calculate the pairs of components marked as having spatial conflicts. The spatial conflict severity index is calculated using the following formula: in, Representing components and The volume of the overlapping region, Conflict priority coefficient, assigned a value based on conflict type and pipeline type; Weighting factors indicating conflict types; Calculate the total spatiotemporal conflict severity index for all component pairs marked as having spatial conflicts. The total spatiotemporal conflict severity index The calculation formula is: Where M is the total number of component pairs with spatial conflicts as indicated by the markings; Step S306: Generate a collision detection report, including: Conflict type, unique ID of conflicting components, and spatiotemporal conflict severity index of a single component. The spatiotemporal conflict severity index of the total components .

[0012] Furthermore, step S4 includes the following steps: Step S401: Input the BIM data, the spatial occupancy geometric parameters of the pipeline components, and the conflict detection report; Step S402: Optimize pipeline layout based on genetic algorithm, the steps are as follows: S4021: Population Initialization An initial population is randomly generated, with a population size N of 50-100 chromosomes. Each chromosome represents a pipeline component layout scheme, defined as follows: Where U represents the total number of pipeline components included in the BIM data; m is the number of nodes in a single pipeline component; Represents the coordinates of the j-th node of the i-th pipeline component; Ensure that the pipeline component layout for each chromosome does not exceed the physical boundaries of the underground parking garage; S4022: Define the fitness function The formula for evaluating the quality of each chromosome is as follows: in, This represents the total spatial conflict severity index of the k-th scheme; The sum of the path lengths of the k-th pipeline layout scheme is expressed as follows: in, Indicates the weighting factor; Represents starting from the k-th chromosome The coordinates of the j-th node of the i-th pipeline component obtained from the analysis; S4023: Genetic operations: The genetic operations include selection, crossover / recombination, and mutation. Individuals generated through crossover / recombination and mutation are used to form a new population. The population is continuously updated to gradually determine the optimal chromosome. The specific steps are as follows: The selection process is as follows: Using roulette wheel selection, chromosomes The probability of being selected is inversely proportional to fitness; chromosomes Probability of being selected for: in, Represents the k-th chromosome The fitness of the population, where N is the population size; Repeated selection forms the parent population; The crossover / recombination operation process is as follows: Two parent chromosomes are selected from the parent population and crossover is performed at two points to generate offspring chromosomes. The process is as follows: Two parent chromosomes are randomly selected from the parent population. and ; Randomly from the parent chromosome and Choose two intersection points a and b; Exchange of two parent chromosomes and The gene fragment between crossover points a and b generates offspring chromosomes. and ; The mutation operation process is as follows: The coordinates of the generated offspring chromosome nodes are slightly perturbed: in, , and This represents the perturbation values ​​along the lower x, y, and z axes; S4024: Stop iterative updates when any of the following conditions are met: Condition 1: The number of iterations reaches a preset value; Condition 2: The rate of change of the optimal fitness value over 10 consecutive generations is less than 1%; Condition 3: Overall Spatiotemporal Conflict Severity Index And there are no ES-ES conflicts; After stopping the iteration, the optimal chromosome is output, which corresponds to the optimal pipeline layout scheme. The optimal pipeline layout scheme includes: Detailed path parameters for each pipeline component: 3D coordinates of all nodes contained in each pipeline component. It can directly import BIM models to generate visualization paths; Updated conflict detection report.

[0013] Compared with the prior art, the advantages of the present invention are as follows: 1. This invention constructs three types of models: Entity Space (ES), Safe Workspace (SWS), and Efficient Workspace (EWS), clearly defining the geometric boundaries and expansion rules of different spaces. The system covers six types of spatial conflicts, solving the problem that traditional technologies cannot fully identify potential issues such as insufficient safety distance and encroachment on maintenance space, and providing a complete dimension for comprehensively evaluating the rationality of pipeline layout.

[0014] 2. This invention and method adopt a process that combines AABB overlap testing and OBB collision detection, and designs a spatial conflict severity index to achieve quantitative detection of conflicts. This solves the problems of strong subjectivity and low accuracy in traditional assessments, and provides an objective basis for optimizing priority ranking.

[0015] 3. This invention constructs a multi-objective optimization system based on genetic algorithms. Through iterative evolution of operations such as population initialization, roulette wheel selection, two-point crossover, and random mutation, it outputs the globally optimal solution. The results are directly imported into the BIM model in the form of node three-dimensional coordinates, which solves the problems of traditional optimization being prone to getting trapped in local optima and being out of touch with construction. It takes into account both conflict minimization and path economy. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a flowchart illustrating step S3 of the present invention; Figure 3 This is a flowchart illustrating step S4 of the present invention. Detailed Implementation

[0018] To achieve the above objectives, the present invention provides a method for identifying and optimizing spatial conflicts of integrated pipelines in underground parking garages based on a BIM model. A flowchart of the method is provided below. Figure 1 The specific implementation process includes: Step 1: BIM Model Construction (1) Model composition and component classification In BIM software, structural and pipeline models of underground parking garages are constructed, and these models are composed of various types of components. The structural model includes, but is not limited to: beams, columns, slabs, and walls; The components of the pipeline model include, but are not limited to: water supply and drainage pipelines, fire protection pipelines, HVAC pipelines, electrical pipelines, communication pipelines, and other components; The structural components and the pipeline components are collectively referred to as components, which include the following key attribute parameters: unique ID, type, size, material, installation elevation, and connection relationship; (2) Model building constraints To ensure the feasibility of subsequent conflict detection and optimization processes, the model construction must meet the following constraints: Spatial constraints: Pipeline models must be arranged within the space defined by the main structure; Regulatory constraints: Pipeline spacing and slope must comply with national standards, for example: The minimum distance between water supply and drainage pipes and electrical conduits is 150mm; The pipe slope shall not be less than 0.002, and the specific constraint parameters shall be determined according to the pipeline type; Association constraints: Equipment and pipelines are bound by unique IDs to ensure complete connection relationships and consistency of upstream and downstream component IDs; (3) Data export and preprocessing Export the geometric and attribute data of the BIM model to the IFC or RVT data format supported by Navisworks clash detection software, and clean and simplify the exported data to generate BIM data for clash detection. The data cleaning and simplification includes model simplification and data validation: The model simplification includes: Geometric simplification: Remove short pipe segments at the ends of non-functional pipelines, and retain functional short pipes; Attribute simplification: Remove decorative parameters such as color and texture; retain parameters required for collision detection, such as size, elevation, and connectivity. Hierarchical simplification: Combine continuous straight sections of pipelines of the same type, material, and elevation into a single component to reduce the number of objects to be inspected; The data verification includes: Check the component ID coverage to ensure that 100% of components have unique IDs; if missing or duplicate IDs are found, automatically regenerate UUIDs and update connection relationships. Constraint inspection: Check whether pipeline spacing, slope and space constraints comply with national standards.

[0019] Step 2: Construction of Integrated Pipeline Space Occupancy Model Using the BIM data as input, and considering the characteristics of integrated pipelines in underground parking garages, three types of space occupancy models are defined and constructed. The three types of spaces are: solid space (ES), safe working space (SWS), and efficient working space (EWS). The physical space: the physical space occupied by the pipeline component itself, which is determined by the outer diameter of the pipeline component; The pipeline components are divided into regular components and irregular components, and their model construction methods are as follows: The regular components: using the axis-aligned bounding box (AABB) method, for the i-th pipeline component, its AABB is determined by the minimum coordinate point. and the maximum coordinate point Together, the size of the solid space of the i-th pipeline component is defined as follows: in, The coordinates represent the coordinates of the solid space enclosed region of the i-th pipeline component; The irregular component: using the directed bounding box (OBB) method, for the i-th pipeline component, its OBB is defined by the center point E and three mutually orthogonal axes. and half length along each axis definition: in, , and The constraints are as follows: ; E represents the irregular component. The coordinates of the center point; The safe working space: the minimum operating space required to ensure pipeline operation safety, extended outward from the ES (Equivalent to the minimum operating space). The size of the safe working space for the i-th pipeline component is expressed as: in, This represents the safety expansion factor, which is an empirical parameter determined based on pipeline type, size, construction process, and safety specifications. The space expansion function represents the function that expands the space of the space. according to The coefficients are expanded; The efficiency workspace: To ensure the efficiency of pipeline construction and installation, as well as the reasonable operating space required for future maintenance and replacement of pipeline components, based on SWS, the distance is further extended outward. The size of the efficiency workspace of the i-th pipeline component is expressed as: in, Indicates the efficiency expansion factor; The space expansion function represents the function that expands the space of the space. according to The coefficients are expanded; The geometric parameters of ES, SWS, and EWS of each component are used as the spatial occupancy geometric parameters of the final output pipeline component, providing a quantized boundary for collision detection.

[0020] Step 3: Spatial Conflict Detection Model The spatial occupancy geometric parameters of the pipeline components output from the pipeline space occupancy model are used for spatial conflict detection, such as... Figure 2 As shown, the specific process is as follows: (1) For all components in the underground parking garage BIM data, select the i-th component and the j-th component in sequence to form a unique component pair. ; sequentially for the components Perform a conflict check on the occupied space; in, U represents the total number of pipeline components included in the BIM data; The space-occupying conflicts include six conflict types, which are: ES-ES conflict: The two component entities overlap in space; ES-SWS conflict: A component entity intrudes into the safety space of another component; ES-EWS conflict: A component entity intrudes into the efficient space of another component; SWS-SWS conflict: Overlapping safe workspaces; SWS-EWS conflict: Safe workspace encroaches on efficient workspace; EWS-EWS conflict: overlapping efficiency workspaces; (2) Collision detection is performed using a collision detection algorithm. The specific process of the collision detection algorithm is as follows: First, the components are... Perform an AABB overlap test; the principle of AABB overlap judgment is to check whether the projections on the X, Y, and Z axes all overlap. The AABB structure is represented as: The AABB structure is represented as: The overlap condition is: and and Then AABB overlaps; If the overlap condition is not met, then the components will be... Mark as conflict-free; if the overlap condition is met, perform OBB collision detection; OBB Collision Detection The OBB collision detection uses the Separating Axis Theorem (SAT). For the AABB overlapping components The process of performing OBB collision detection is as follows: Inspect 15 potential split shafts: For components and The two corresponding and Take each one separately and The three local coordinate axes; member The three local coordinate axes are represented as follows: ; member The three local coordinate axes are represented as follows: ; Calculation components Each local coordinate axis and component The cross product of each local coordinate axis, with a total of 9 separating axes, is calculated using the following formula: For any separate axis L, calculate the component. and The projection of L, if there exists such that Then the component and No conflict, the components are paired Mark as conflict-free, otherwise mark the component pair Marked as having a spatial conflict; in, Representing components Along the separation axis The projection; (3) Spatiotemporal conflict severity index Calculate the components whose markings have spatial conflicts. The spatiotemporal conflict severity index is calculated using the following formula: in, Representing components and The volume of the overlapping region, Conflict priority coefficient, assigned a value based on conflict type and pipeline type; Weighting factors indicating conflict types; Calculate the total spatiotemporal conflict severity index for all component pairs marked as having spatial conflicts. The total spatiotemporal conflict severity index The calculation formula is: Where M is the total number of component pairs with spatial conflicts as indicated by the markings; (4) Generate a conflict detection report The conflict check report includes: Conflict type; The unique ID of the conflicting component pair; Severity index of spatiotemporal conflict of single component ; Spatiotemporal conflict severity index of total components .

[0021] Step 4: Pipeline layout optimization based on genetic algorithm Using the BIM data, the spatial occupancy geometric parameters of the pipeline components, and the conflict detection report as input, a genetic algorithm is used to minimize spatial conflicts and path lengths, optimizing the pipeline layout for each pipeline component. Figure 3 As shown, the specific steps are as follows: (1) Population initialization: An initial population is randomly generated, with a population size N of 50-100 chromosomes. Each chromosome represents a pipeline layout scheme, defined as follows: Where U represents the total number of pipeline components included in the BIM data; m is the number of nodes in a single pipeline component; Represents the coordinates of the j-th node of the i-th pipeline component; Ensure that the pipeline layout plan for each chromosome does not exceed the physical boundaries of the underground parking garage; (2) Fitness function: Define fitness function The formula for evaluating the quality of each chromosome is as follows: in, This represents the total spatial conflict severity index of the k-th scheme; The sum of the path lengths of the k-th pipeline layout scheme is expressed as follows: in, Indicates the weighting factor; Represents starting from the k-th chromosome The coordinates of the j-th node of the i-th pipeline component obtained from the analysis; (3) Genetic manipulation: The genetic operations include selection, crossover / recombination, and mutation. Individuals generated through crossover / recombination and mutation are used to form a new population. The population is continuously updated to gradually determine the optimal chromosome. The specific steps are as follows: The selection process is as follows: Using roulette wheel selection, chromosomes The probability of being selected is inversely proportional to fitness; chromosomes Probability of being selected for: in, Represents the k-th chromosome The fitness of the population, where N is the population size; Repeated selection forms the parent population; The crossover / recombination operation process is as follows: Two parent chromosomes are selected from the parent population and crossover is performed at two points to generate offspring chromosomes. The process is as follows: Two parent chromosomes are randomly selected from the parent population. and ; Randomly from the parent chromosome and Choose two intersection points a and b; Exchange of two parent chromosomes and The gene fragment between crossover points a and b generates offspring chromosomes. and ; The mutation operation process is as follows: The coordinates of the generated offspring chromosome nodes are slightly perturbed: in, , and This represents the perturbation values ​​along the lower x, y, and z axes; S4024: Stop iterative updates when any of the following conditions are met: Condition 1: The number of iterations reaches a preset value; Condition 2: The rate of change of the optimal fitness value over 10 consecutive generations is less than 1%; Condition 3: Overall Spatiotemporal Conflict Severity Index And there are no ES-ES conflicts; After stopping the iteration, the optimal chromosome is output, which corresponds to the optimal pipeline layout scheme. The optimal pipeline layout scheme includes: Detailed path parameters for each pipeline component: 3D coordinates of all nodes contained in each pipeline component. It can directly import BIM models to generate visualization paths; Updated conflict detection report.

[0022] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for identifying and optimizing spatial conflicts of integrated pipelines in underground parking garages based on BIM models, characterized in that, The method includes the following steps: Step S1: Under constraints, construct a BIM model of the underground parking garage; the BIM model includes structural components and pipeline components. Export and preprocess the BIM model to generate BIM data for conflict detection. Step S2: Using the BIM data as input, construct a space occupancy model based on the entity space ES, safe working space SWS, and efficient working space EWS of the pipeline component, and output the space occupancy geometric parameters of the pipeline component; Step S3: Using a collision detection algorithm, with the spatial occupancy geometric parameters of the pipeline components as input, sequentially select the i-th pipeline component and the j-th pipeline component to form a unique component pair. For the component Perform collision detection and output a collision detection report; Step S4: Using the BIM data, the spatial occupancy geometric parameters of the pipeline components, and the conflict detection report as input, a genetic algorithm is used to optimize the layout of the pipeline components to obtain the optimal pipeline component layout scheme.

2. The method according to claim 1, characterized in that, The structural components and pipeline components are as follows: The structural components include, but are not limited to: beams, columns, slabs, and walls; The pipeline components include, but are not limited to: water supply and drainage pipelines, fire protection pipelines, HVAC pipelines, electrical pipelines, and communication pipelines; The structural components and the pipeline components are collectively referred to as components, which include the following key attribute parameters: unique ID, type, size, material, installation elevation, and connection relationship.

3. The method according to claim 1, characterized in that, The constraints include: Spatial constraints: The pipeline model must be arranged within the space defined by the main structure; Regulatory constraints: The spacing and slope of pipeline components comply with national standards; Association constraints: Equipment and pipeline components are bound by a unique ID to ensure the integrity of the connection relationship.

4. The method according to claim 1, characterized in that, The BIM model data export and preprocessing includes: The export process involves exporting the geometric and attribute data of the BIM model into IFC or RVT data formats supported by Navisworks clash detection software. The preprocessing involves model simplification and data validation of the exported IFC or RVT data format. The model simplification includes: geometric simplification, attribute simplification, and hierarchical simplification; The data verification includes: checking whether the unique ID of the component is complete; and checking whether the layout of the pipeline components meets national requirements.

5. The method according to claim 1, characterized in that, Step S2 includes the following steps: Step S201: Model the entity space ES, where the entity space refers to the physical space occupied by the pipeline component body; The pipeline components are divided into regular components and irregular components, and their construction methods are as follows: The regular components: using the axis-aligned bounding box (AABB) method, for the i-th pipeline component, its AABB is determined by the minimum coordinate point. and the maximum coordinate point Together, the size of the solid space of the i-th pipeline component is defined as follows: in, Represents the coordinates of the solid space of the i-th pipeline component; The irregular component: using the directed bounding box (OBB) method, for the i-th pipeline component, its OBB is defined by the center point E and three mutually orthogonal axes. and half length along each axis definition: in, , and The constraints are as follows: ； E represents the irregular component. The coordinates of the center point; Step S202: Model the safe working space (SWS). The safe working space refers to the minimum operating space required to ensure the safe operation of the pipeline. Based on the ES, the safe working space of the i-th pipeline component is extended outward by a distance, and the size of the safe working space is expressed as: in, This represents the safety expansion factor, which is an empirical parameter determined based on pipeline type, size, construction process, and safety specifications. The space expansion function represents the function that expands the space of the space. according to The coefficients are expanded; Step S203: Model the efficient workspace (EWS). The efficient workspace refers to a reasonable operating space that ensures safe construction. Based on the SWS, the model is further extended outward. The size of the efficient workspace of the i-th pipeline component is expressed as: in, Indicates the efficiency expansion factor; The space expansion function represents the function that expands the space of the space. according to The coefficients are expanded.

6. The method according to claim 1, characterized in that, Step S3 includes the following steps: Step S301: Input the spatial occupancy geometric parameters of the pipeline components. For the pipeline components included in the input parameters, sequentially select the i-th component and the j-th component to form a unique component pair. ; sequentially for the components Perform a conflict check on the occupied space; in, U represents the total number of pipeline components included in the BIM data; Step S302: Define the conflict types, which include six categories: ES-ES conflict, ES-SWS conflict, ES-EWS conflict, SWS-SWS conflict, SWS-EWS conflict and EWS-EWS conflict; Step S303: Perform collision detection using a collision detection algorithm, as follows: S3031: For the component Perform AABB overlap test; The AABB structure is represented as: The AABB structure is represented as: The overlap condition is: and and Then AABB overlaps; If the overlap condition is not met, then the components will be... Mark as conflict-free; if the overlap condition is met, perform OBB collision detection; S3032: For the components that satisfy the overlap condition... Perform OBB collision detection; Inspect 15 potential split shafts: member and Corresponding to and ,Pick and The three local coordinate axes are respectively and ; Calculation components Local coordinate axes and components The cross product of the local coordinate axes is calculated using the following formula: For any separate axis L, calculate the component. and The projection of L, if there exists such that Then the component and No conflict, the components are paired Mark as conflict-free, otherwise mark the component pair Marked as having a spatial conflict; in, Represents the q-th component Along the separation axis The projection; Step S304: Calculate the pairs of components marked as having spatial conflicts. The spatial conflict severity index is calculated using the following formula: in, Representing components and The volume of the overlapping region, Conflict priority coefficient, assigned a value based on conflict type and pipeline type; Weighting factors indicating conflict types; Calculate the total spatiotemporal conflict severity index for all component pairs marked as having spatial conflicts. The total spatiotemporal conflict severity index The calculation formula is: Where M is the total number of component pairs with spatial conflicts as indicated by the markings; Step S306: Generate a collision detection report, including: Conflict type, unique ID of conflicting components, and spatiotemporal conflict severity index of a single component. The spatiotemporal conflict severity index of the total components .

7. The method according to claim 1, characterized in that, Step S4 includes the following steps: Step S401: Input the BIM data, the spatial occupancy geometric parameters of the pipeline components, and the conflict detection report; Step S402: Optimize pipeline layout based on genetic algorithm, the steps are as follows: S4021: Population Initialization An initial population is randomly generated, with a population size N of 50-100 chromosomes. Each chromosome represents a pipeline component layout scheme, defined as follows: Where U represents the total number of pipeline components included in the BIM data; m is the number of nodes in a single pipeline component; Represents the coordinates of the j-th node of the i-th pipeline component; Ensure that the pipeline component layout for each chromosome does not exceed the physical boundaries of the underground parking garage; S4022: Define the fitness function The formula for evaluating the quality of each chromosome is as follows: in, This represents the total spatial conflict severity index of the k-th scheme; The sum of the path lengths of the k-th pipeline layout scheme is expressed as follows: in, Indicates the weighting factor; Represents starting from the k-th chromosome The coordinates of the j-th node of the i-th pipeline component obtained from the analysis; S4023: Genetic operations: The genetic operations include selection, crossover / recombination, and mutation. Individuals generated through crossover / recombination and mutation are used to form a new population. The population is continuously updated to gradually determine the optimal chromosome. The specific steps are as follows: The selection process is as follows: Using roulette wheel selection, chromosomes The probability of being selected is inversely proportional to fitness; chromosomes Probability of being selected for: in, Represents the k-th chromosome The fitness of the population, where N is the population size; Repeated selection forms the parent population; The crossover / recombination operation process is as follows: Two parent chromosomes are selected from the parent population and crossover is performed at two points to generate offspring chromosomes. The process is as follows: Two parent chromosomes are randomly selected from the parent population. and ; Randomly from the parent chromosome and Choose two intersection points a and b; Exchange of two parent chromosomes and The gene fragment between crossover points a and b generates offspring chromosomes. and ; The mutation operation process is as follows: The coordinates of the generated offspring chromosome nodes are slightly perturbed: in, , and This represents the perturbation values ​​along the lower x, y, and z axes; S4024: Stop iterative updates when any of the following conditions are met: Condition 1: The number of iterations reaches a preset value; Condition 2: The rate of change of the optimal fitness value over 10 consecutive generations is less than 1%; Condition 3: Overall Spatiotemporal Conflict Severity Index And there are no ES-ES conflicts; After stopping the iteration, the optimal chromosome is output, which corresponds to the optimal pipeline layout scheme. The optimal pipeline layout scheme includes: Detailed path parameters for each pipeline component: 3D coordinates of all nodes contained in each pipeline component. It can directly import BIM models to generate visualization paths; Updated conflict detection report.

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