Park model lightweight method and device, electronic equipment and storage medium

Abstract

The invention provides a lightweight method and device based on a park model, electronic equipment and a storage medium, and relates to the technical field of engineering modeling processing, and the method comprises the steps: obtaining an initial park model comprising a building structure layout model and an initial electromechanical system model; extracting core component features and secondary component features from the component attribute information of the initial electromechanical system model according to the model precision simplification requirement and the spatial layout information; carrying out lightweight on the initial electromechanical system model based on fixed contour representation information obtained by carrying out necessary contour locking on the basis of core component characteristics and simplified contour representation information obtained by carrying out secondary contour simplification on the basis of secondary component characteristics; and integrating the building structure layout model and the lightweight target electromechanical system model to obtain a target park model. According to the method, the overall data volume of the park model can be reduced, key parts of the electromechanical system can be effectively prevented from being excessively simplified, and the usability of the lightweight park model in an operation and maintenance scene is improved.

Description

Technical Field

[0001] This application relates to the field of engineering modeling technology, and in particular to a method and apparatus for lightweighting a campus model, an electronic device, and a storage medium. Background Technology

[0002] Currently, traditional methods for lightweighting park models primarily employ general 3D model simplification techniques. These methods reduce the number of facets in the park's building model through geometric simplification algorithms and instantiate repetitive components to reduce data volume and achieve building simplification. However, since parks involve not only building systems but also electromechanical systems, traditional lightweighting methods, which are typically based on geometric error metrics, struggle to identify critical components such as major pipe connections and equipment interfaces within the park's electromechanical systems. This leads to oversimplification of key areas, resulting in the loss of important electromechanical component features and contour distortion in the simplified electromechanical system model. Consequently, the usability of the lightweighted park model in operational scenarios is significantly reduced. Therefore, improving the usability of lightweight park models has become a pressing technical challenge. Summary of the Invention

[0003] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application provides a method and apparatus, electronic device, and storage medium for lightweighting a campus model, thereby improving the usability of the lightweighted campus model.

[0004] To achieve the above objectives, a first aspect of this application proposes a lightweight campus model method, the method comprising: Obtain the initial park model corresponding to the target park and the model accuracy simplification requirements; wherein, the initial park model includes a building structure layout model and an initial electromechanical system model; Extract spatial layout information from the building structure layout model; The component attribute information is obtained by parsing the initial electromechanical system model. Based on the model accuracy simplification requirements and the spatial layout information, the component attribute information is subjected to component feature discrimination in order to extract core component features and secondary component features from the component attribute information; Based on the features of the core components, the initial electromechanical system model is locked with necessary contour boundaries to obtain fixed contour representation information; Based on the features of the secondary components, the initial electromechanical system model is simplified by the secondary contour to obtain simplified contour representation information. The initial electromechanical system model is lightweighted based on the fixed contour representation information and the simplified contour representation information to obtain the target electromechanical system model. By integrating the building structure layout model and the target electromechanical system model, the target park model is obtained.

[0005] In some embodiments, the component attribute information includes component geometric parameters; the core component features include core component appearance features; and the secondary component features include secondary component appearance features. The step of performing component feature discrimination on the component attribute information based on the model accuracy simplification requirements and the spatial layout information, in order to extract core component features and secondary component features from the component attribute information, includes: Obtain the appearance feature discrimination problem, and based on the appearance feature discrimination problem, obtain the component geometric category and component geometric elements of the component geometric parameters; Based on the spatial layout information and the component geometric category, the geometric elements of the component are subjected to visual resolution constraints to obtain geometric visual constraint information; Based on the model accuracy simplification requirements and the component geometry category, the main contour analysis constraint is performed on the component geometry elements to obtain the main contour constraint information; Based on the geometric visual constraint information and the main contour constraint information, prompts are constructed to obtain component appearance discrimination prompts; Based on the component appearance discrimination prompts, a pre-trained component feature discrimination model is used to perform appearance feature discrimination on the appearance feature discrimination problem, so as to extract the appearance features of the core component and the appearance features of the secondary component from the component geometric parameters.

[0006] In some embodiments, the component attribute information includes component usage parameters; the core component features include core component usage features; and the secondary component features include secondary component usage features. The step of performing component feature discrimination on the component attribute information based on the model accuracy simplification requirements and the spatial layout information, in order to extract core component features and secondary component features from the component attribute information, includes: Obtain the usage feature discrimination problem, and obtain the component function category of the component usage parameters based on the usage feature discrimination problem; Based on the functional category of the component and the spatial layout information, redundant parameter identification constraints are performed on the component's purpose parameters to obtain redundant component parameter constraint information; Based on the functional category of the component and the model accuracy simplification requirements, the main functional constraints of the component's usage parameters are analyzed and constrained to obtain the main component functional constraint information. Based on the redundant component parameter constraint information and the main component functional constraint information, prompts are constructed to obtain component usage discrimination prompts. Based on the component usage discrimination prompt, the component feature discrimination model is instructed to perform usage feature discrimination on the number of usage feature discrimination questions, so as to extract the core component usage features and the secondary component usage features from the component usage parameters.

[0007] In some embodiments, the process of simplifying the initial electromechanical system model based on the secondary component features to obtain simplified contour representation information includes: If the secondary component feature is the appearance feature of the secondary component, then the initial electromechanical system model is geometrically simplified based on the appearance feature of the secondary component to obtain simplified appearance contour representation information; If the secondary component feature is the secondary component usage feature, then the initial electromechanical system model is simplified based on the secondary component usage feature to obtain simplified component outline characterization information; The simplified appearance contour representation information and the simplified component contour representation information are integrated to obtain the simplified contour representation information.

[0008] In some embodiments, the initial electromechanical system model consists of multiple target meshes, and each target mesh consists of multiple target triangular facets; The step of performing a geometric simplification operation on the initial electromechanical system model based on the appearance features of the secondary components to obtain simplified appearance contour representation information includes: According to the preset simplification strategy, the target triangle facets in the target mesh corresponding to each of the secondary component features are subjected to triangle edge folding processing to obtain the initial simplified triangle facets; During the triangular edge folding process, the appearance error of each target mesh is accumulated based on the initial simplified triangular facet and the target triangular facet to obtain the appearance error accumulation value. The simplification strategy is adjusted according to the preset simplified appearance error constraints and the cumulative appearance error value to obtain the target simplification strategy; The initial simplified triangular facet is simplified and updated according to the target simplification strategy to obtain the target simplified triangular facet, and the target simplified triangular facet is integrated to obtain the simplified appearance contour representation information.

[0009] In some embodiments, the step of locking the necessary contour boundaries of the initial electromechanical system model based on the features of the core components to obtain fixed contour representation information includes: Geometric boundary analysis is performed on the core component features to obtain the component boundary line features; Vertex sampling is performed on the boundary lines of the component to obtain the vertices of the boundary triangle; Obtain the vertex coordinates of the boundary triangle vertices, and lock the boundary triangle vertices based on the vertex coordinates to obtain the locked vertices; The fixed contour representation information is determined based on the locked vertices.

[0010] In some embodiments, after performing lightweight processing on the initial electromechanical system model based on the fixed contour representation information and the simplified contour representation information to obtain the target electromechanical system model, the method further includes: Boundary appearance defect detection is performed on the target electromechanical system model to obtain boundary appearance defect data; The initial boundary data corresponding to the boundary appearance defect data is obtained from the initial electromechanical system model, and the defect deviation is calculated based on the boundary appearance defect data and the initial boundary data to obtain the boundary defect deviation data. Generate repair triangle vertices based on the boundary defect deviation data; The boundary appearance defects are filled with triangular patches based on the vertices of the repair triangle to obtain the repaired electromechanical system model, and the repaired electromechanical system model is determined as the target electromechanical system model.

[0011] Secondly, embodiments of this application provide a lightweighting device for a park model, comprising: The park model and simplified requirements acquisition module allows users to obtain an initial park model and simplified model accuracy requirements corresponding to the target park; wherein, the initial park model includes a building structure layout model and an initial electromechanical system model; The layout information extraction module is used to extract spatial layout information from the building structure layout model. The component attribute parsing module is used to parse the component attributes of the initial electromechanical system model to obtain component attribute information. The component feature discrimination module is used to perform component feature discrimination on the component attribute information according to the model accuracy simplification requirements and the spatial layout information, so as to extract core component features and secondary component features from the component attribute information; The contour boundary locking module is used to perform necessary contour boundary locking on the initial electromechanical system model based on the features of the core components, so as to obtain fixed contour representation information. The secondary contour simplification processing module is used to perform secondary contour simplification processing on the initial electromechanical system model based on the features of the secondary components to obtain simplified contour representation information; The lightweight processing module is used to perform lightweight processing on the initial electromechanical system model based on the fixed contour representation information and the simplified contour representation information to obtain the target electromechanical system model. The model integration module is used to integrate the building structure layout model and the target electromechanical system model to obtain the target park model.

[0012] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the campus model lightweighting method as described in any one of the embodiments of the first aspect of this application.

[0013] Fourthly, embodiments of this application provide a computer-readable storage medium storing a program that is executed by a processor to implement the campus model lightweighting method as described in any one of the embodiments of the first aspect of this application.

[0014] The proposed lightweight campus model method first obtains an initial campus model containing a building structure layout model and an initial electromechanical system model, and extracts spatial layout information from it. This establishes spatial location relationships between building spaces and electromechanical equipment, providing a spatial constraint benchmark for subsequent electromechanical system simplification. Second, by analyzing the component attributes of the initial electromechanical system model and performing component feature discrimination based on model accuracy simplification requirements and spatial layout information, core component features and secondary component features are extracted from the component attribute information. This method identifies the core component features in the electromechanical system model, thus preventing the loss of features of important electromechanical components during the simplification process from the outset, and solving the problem of traditional methods relying solely on... The problem of difficulty in identifying key electromechanical components due to the unification and simplification of geometric error measurement standards is addressed. Furthermore, necessary contour boundary locking is performed on the initial electromechanical system model based on the features of core components, ensuring the integrity of the geometric features of key electromechanical components. Contour simplification based on the features of secondary components effectively reduces the data volume of the electromechanical system model. Finally, by integrating the target electromechanical system model that retains the features of core components with the building structure layout model, the overall data volume of the park model can be significantly reduced while effectively avoiding oversimplification of key electromechanical components during the simplification process. This solves the problems of loss of important electromechanical component features and contour distortion caused by traditional methods, and significantly improves the usability of the lightweight park model in operation and maintenance scenarios.

[0015] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0016] Figure 1 This is a flowchart of the lightweight campus model method provided in the embodiments of this application; Figure 2 yes Figure 1 The flowchart of step S104 in the process; Figure 3 yes Figure 1 Another flowchart of step S104 in the process; Figure 4 yes Figure 1 The flowchart of step S105 in the process; Figure 5 yes Figure 1 The flowchart of step S106 in the process; Figure 6 yes Figure 5 The flowchart of step S501 in the process; Figure 7 This is a flowchart of another lightweight campus model method provided in the embodiments of this application; Figure 8 This is a schematic diagram of the lightweight campus model provided in the embodiments of this application; Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0018] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0020] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0021] Based on this, embodiments of this application provide a method and apparatus, electronic device and storage medium for lightweighting a campus model. By identifying the core component features and secondary component features in the initial electromechanical system model, the core component features are retained, and the initial system model is lightweighted based on the secondary component features. Furthermore, the target electromechanical system model with retained core component features is integrated with the building structure layout model, which solves the problems of loss of important electromechanical component features and contour distortion caused by traditional methods, and significantly improves the usability of the lightweight campus model in operation and maintenance scenarios.

[0022] The lightweight method, apparatus, electronic device, and storage medium based on the campus model provided in this application are specifically described through the following embodiments. First, the lightweight method of the campus model in this application is described.

[0023] Figure 1 This is an optional flowchart of the lightweight campus model method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S108.

[0024] Step S101: Obtain the initial park model and model accuracy simplification requirements corresponding to the target park; wherein, the initial park model includes the building structure layout model and the initial electromechanical system model.

[0025] Step S102: Extract spatial layout information from the building structure layout model.

[0026] Step S103: Analyze the component attributes of the initial electromechanical system model to obtain component attribute information.

[0027] Step S104: Based on the model accuracy simplification requirements and spatial layout information, perform component feature discrimination on the component attribute information to extract core component features and secondary component features from the component attribute information.

[0028] Step S105: Based on the features of the core components, the initial electromechanical system model is locked with necessary contour boundaries to obtain fixed contour representation information.

[0029] Step S106: Based on the features of secondary components, the initial electromechanical system model is simplified by secondary contour processing to obtain simplified contour representation information.

[0030] Step S107: The initial electromechanical system model is lightweighted based on the fixed contour representation information and the simplified contour representation information to obtain the target electromechanical system model.

[0031] Step S108: Integrate the building structure layout model and the target electromechanical system model to obtain the target park model.

[0032] Steps S101 to S108 as illustrated in this embodiment firstly involve acquiring an initial campus model containing a building structure layout model and an initial electromechanical system model, and extracting spatial layout information from it. This establishes a spatial relationship between building space and electromechanical equipment, providing a spatial constraint benchmark for subsequent simplification of the electromechanical system. Secondly, by analyzing the component attributes of the initial electromechanical system model and performing component feature discrimination based on model accuracy simplification requirements and spatial layout information, core component features and secondary component features are extracted from the component attribute information. This identifies the core component features in the electromechanical system model, preventing the loss of features of important electromechanical components during the simplification process from the outset, thus solving the problem of traditional methods. The method, which only uses geometric error measurement standards for unified simplification, fails to identify key electromechanical components. Furthermore, it locks the necessary contour boundaries of the initial electromechanical system model based on the features of core components, ensuring the integrity of the geometric features of key electromechanical components. Contour simplification based on secondary component features effectively reduces the data volume of the electromechanical system model. Finally, by integrating the target electromechanical system model that retains the features of core components with the building structure layout model, it can significantly reduce the overall data volume of the park model while effectively avoiding oversimplification of key electromechanical components during the simplification process. This solves the problems of lost features and contour distortion of important electromechanical components caused by traditional methods, significantly improving the usability of the lightweight park model in operation and maintenance scenarios.

[0033] In step S101 of some embodiments, specifically, the initial park model refers to a three-dimensional digital model of the target park, which includes a building structure layout model and an initial electromechanical system model; wherein, the building structure layout model refers to a three-dimensional digital model describing the spatial form and enclosure structure of buildings in the target park, including the geometric data and spatial combination relationships of building components such as walls, floors, roofs, doors, windows, and stairs, to characterize the spatial division, floor distribution and functional area division of the target park; the initial electromechanical system model refers to a three-dimensional digital model describing the layout of building equipment and electromechanical systems in the target park, which may include, but is not limited to, a three-dimensional digital model of all electromechanical equipment, pipes, lines and their physical connection relationships and attribute parameters in the target park.

[0034] For example, if the target park is a science and technology park, the initial park model includes a three-dimensional digital representation of the main building of the science and technology research and development center, the laboratory building, the connecting corridors, and the underground parking garage. It also includes the geometry, size, and spatial location of all building components such as exterior walls, interior partitions, floor slabs, roof steel structures, glass curtain walls, fire doors, and safety staircases. This clearly defines the spatial division and floor distribution of different functional areas such as office areas, laboratories, meeting rooms, equipment rooms, and traffic cores. Furthermore, the initial electromechanical system model includes all electromechanical facilities that maintain the operation of the building. Specifically, it includes variable air volume ventilation ducts and terminal air outlets for laboratories, cleanroom air conditioning units, water supply and drainage networks and fire sprinkler systems on each floor, cable trays and distribution cabinets running through the building, as well as electromechanical components such as elevators, water pumps, and fans. This model not only records the three-dimensional geometry and spatial laying path of electromechanical components, pipes, and lines, but also their physical connection relationships (such as how pipes are connected to equipment interfaces) and attribute parameters (such as pipe material, diameter, design flow rate, equipment model, power, and manufacturer).

[0035] Specifically, the model accuracy simplification requirement refers to a set or more sets of detail levels and their corresponding simplification target parameters that are predefined before lightweight processing, in order to clarify the degree of geometric detail preservation, visual fidelity and data volume limit that the model needs to meet under different park application scenarios.

[0036] For example, if the target area is a hospital campus, the model accuracy simplification requirements defined for this campus may include three levels: LOD (Level of Detail) 300 (medium detail), LOD 350 (high detail), and LOD 400 (fine detail). Among them, the LOD 300 level is suitable for overall hospital overview and emergency command scenarios, and its simplification target parameter can be an overall polygon reduction rate of no less than 70%, but it must retain 100% of the building zoning outlines and the connection logic of the main fire protection pipelines. The LOD 350 level is suitable for department-level operation and maintenance management, and its target parameter can be a polygon reduction rate of no less than 50%, while retaining the identifiable features of key equipment such as all medical gas pipeline interfaces and the outlines of operating room purification units. The LOD 400 level is suitable for maintenance training and simulation between key equipment, and its target parameter may only require a polygon reduction rate of 20%, but it must fully retain micro-geometric features such as the joint structure of surgical shadowless lamps and the details of the socket panels on intensive care equipment.

[0037] Specifically, the 3D model completed during the design phase of the target park can be obtained and exported as a Gltf (GL Transmission Format) model file. From this file, all geometric data, attribute information, and topological relationships related to the building structure and electromechanical system of the target park can be extracted to determine the initial park model.

[0038] In this implementation, by obtaining an initial park model corresponding to the target park, which includes a building structure layout model and an initial electromechanical system model, a data foundation is provided for subsequent model simplification. The model accuracy simplification requirements corresponding to the target park are also obtained, and the simplification requirements of the park scene are transformed into quantifiable processing parameters. This gives the lightweight processing process clear target constraints and avoids the problems of oversimplification or undersimplification caused by the ambiguity of simplification standards in traditional methods.

[0039] In step S102 of some embodiments, specifically, spatial layout information refers to structured data describing the geometric relationships and functional zoning of building spaces.

[0040] Specifically, the geometric data and semantic attributes of the building structure layout model can be analyzed first to identify and extract basic spatial elements such as floor plan outlines, vertical traffic core locations, structural column grid spacing, and enclosure structure boundaries. Then, based on room function labels or area thresholds, spatial functional zoning can be performed to mark concentrated equipment areas such as power distribution rooms, air conditioning rooms, and weak current rooms. Finally, the topological connection relationship between spatial elements can be established to form spatial layout information describing the hierarchical structure from floor to functional zoning to equipment location.

[0041] For example, the spatial layout information extracted from the architectural structural layout model of its No. 1 computer room building can first determine the planar boundaries of each floor (such as the power area on the first floor, the main computer room area on the second floor, and the office area on the third floor); then, within the main computer room area on the second floor, the spatial range of each independent micro-module computer room, cold aisle, maintenance corridor and precision air conditioning room can be further identified and divided; at the same time, the precise location and vertical penetration range of the core tube (including stairs, elevators and pipe shafts) connecting each floor can be extracted.

[0042] In this embodiment, spatial layout information is extracted from the building structure layout model, and a spatial mapping relationship between the building physical space and the electromechanical system is established, providing a spatial location reference benchmark for subsequent electromechanical component feature identification.

[0043] In step S103 of some embodiments, specifically, the component attribute information refers to a structured dataset that describes the category, specification parameters, geometric representation, spatial orientation, and system connection relationship of electromechanical components. The component attribute information may include component geometric parameters and component usage parameters.

[0044] Specifically, the boundary representation (B-Rep) or 3D mesh data of the initial electromechanical system model can be obtained, and the physical morphological parameters of the electromechanical components (such as component size, centerline, bounding box, feature contour line, etc.) can be obtained based on the boundary representation and 3D mesh data to determine the component geometric parameters; furthermore, the attribute fields that define the functional semantics of the electromechanical components (such as function type, model, material, connection and system, etc.) can be obtained from the attribute set corresponding to the initial electromechanical system model and the design specification to determine the component usage parameters.

[0045] In this embodiment, unstructured model data is transformed into structured component attribute information through component attribute parsing, providing a solid data foundation for subsequent lightweighting decisions regarding the function, performance, and spatial context of electromechanical components.

[0046] Please see Figure 2 In some embodiments, the component attribute information includes component geometric parameters; core component features include core component appearance features; secondary component features include secondary component appearance features; and step S104 may include, but is not limited to, steps S201 to S205.

[0047] Step S201: Obtain the appearance feature discrimination problem, and obtain the component geometric category and component geometric elements of the component geometric parameters based on the appearance feature discrimination problem.

[0048] Step S202: Visually analyze and constrain the geometric elements of the components based on the spatial layout information and the component geometric category to obtain geometric visual constraint information.

[0049] Step S203: Based on the model accuracy simplification requirements and component geometry categories, perform main contour analysis constraints on the component geometric elements to obtain main contour constraint information.

[0050] Step S204: Construct prompts based on geometric visual constraint information and main contour constraint information to obtain component appearance discrimination prompts.

[0051] Step S205: Based on the component appearance discrimination prompts, the pre-trained component feature discrimination model is used to perform appearance feature discrimination on the appearance feature discrimination problem, so as to extract the appearance features of the core component and the appearance features of the secondary component from the component geometric parameters.

[0052] In step S201 of some embodiments, specifically, the appearance feature discrimination problem refers to the question text raised by the user regarding the appearance feature discrimination of electromechanical components, which is used to characterize the requirement information for distinguishing the appearance features of core components and secondary components of electromechanical components.

[0053] Specifically, the component geometry category refers to the morphological category to which the electromechanical component belongs.

[0054] For example, in a smart technology park, the geometric categories of electromechanical system components can be pipes, fittings (such as elbows and tees), valves, fans, water pumps, and distribution boxes, etc.

[0055] Specifically, component geometric elements refer to the set of basic elements that constitute the three-dimensional geometric shape of a component, which may include, but are not limited to, vertices, edges, faces (such as triangular facets), central axes, component outlines, and associated texture coordinates.

[0056] Specifically, the geometric parameters of the components that need to be identified in terms of appearance features can be obtained from the problem of appearance feature identification. Based on the IFC (Industry Foundation Classes) standard, the geometric parameters of the components are analyzed to obtain the geometric category of the components. The data of vertices, edges, triangular faces and component outlines are extracted from the three-dimensional model mesh data in the geometric parameters of the components to determine the geometric elements of the components.

[0057] In step S202 of some embodiments, specifically, geometrical visual constraint information refers to data describing the visual importance of the geometric elements of a component, used to assess the visual salience or degree of exposure required for each geometric element of the component from the viewing angle.

[0058] Specifically, the process begins by establishing a spatial relationship between spatial layout information and component geometric elements. This involves calculating the coordinates of the component's geometric elements within the park space, determining the functional zoning of the component (e.g., public corridors, equipment rooms, pipe shafts, concealed ceiling spaces), and identifying whether it falls within the visible range of personnel activity areas. Then, based on the component's geometric category, visually significant features (e.g., the outline of a fan casing) are identified. Furthermore, a visual constraint level is set by combining spatial location and component geometric category. Typically, key interface areas within the visible range of personnel activity areas are subject to high visual constraints (if original geometric details need to be preserved, it is recommended to retain more than 90% of the triangular facets). Non-interface areas in concealed spaces are subject to low visual constraints (if significant simplification of the component is required, it is recommended to retain less than 30% of the triangular facets). Functionally critical areas in densely populated equipment areas are subject to medium visual constraints (if moderate simplification of the component is required, it is recommended to retain 60% to 80% of the three-facets). This results in a geometric visual constraint information set that includes the visual constraint level identifier for each component's geometric elements, the constraint basis (e.g., the component's geometric category and the functional zoning of the space to which the component belongs), and the recommended proportion of facets to be retained.

[0059] In this implementation, visual resolution constraints are applied to the geometric elements of components based on spatial layout information and component geometric categories. This ensures that subsequent model simplification prioritizes the component parts that will actually be observed in real operation, maintenance, and visitor scenarios, avoiding the waste of computational resources on excessive retention of invisible or secondary visual areas, and making the lightweight results more practical.

[0060] In step S203 of some embodiments, specifically, the main contour constraint information refers to data describing the protection requirements of key contour lines in the geometric elements of the component, used to clearly identify the component contour line information that must be retained under any degree of simplification.

[0061] Specifically, firstly, the LOD level specified in the model accuracy simplification requirements is obtained, along with control parameters related to geometric simplification (such as the maximum deviation threshold of the contour line, the list of key features to be retained, and the minimum number of faces after simplification). Then, the main contour elements of the component are identified according to the component's geometric category (such as the contour of a wind turbine casing). Next, a constraint mapping between the model accuracy requirements and the main contour elements is established. Specifically, high-level simplification accuracy (such as LOD400) requires the retention of the original geometric details of all main contour elements with a contour deviation threshold of 0mm; medium-level simplification accuracy (such as LOD300-350) requires moderate simplification of non-interface main contours while maintaining shape topology with a contour deviation threshold of 5 to 10mm; and low-level simplification accuracy (such as LOD200) requires the abstract shape of the main contour to be identifiable with a contour deviation threshold of 20 to 50mm. This generates main contour constraint information containing the constraint level, contour deviation threshold, and topology preservation requirements for each main contour element.

[0062] In step S204 of some embodiments, specifically, the component appearance discrimination prompt refers to text information containing descriptions of component geometric elements, constraints, and discrimination task definitions, which is used to instruct the component feature discrimination model to identify the standardized input of core component appearance features and secondary component appearance features.

[0063] Specifically, the process first extracts spatial location descriptions, visual constraint levels, and suggested facet ratios for retaining component geometric elements from geometric visual constraint information. Then, it extracts functional importance descriptions, contour constraint levels, and contour deviation thresholds for main contour elements from main contour constraint information. Next, it performs information fusion according to a predefined prompt template, which typically includes a component identity description section (e.g., category, location, system affiliation), geometric element fields (e.g., element type and constraints), a discrimination task definition section (e.g., core feature judgment criteria and secondary feature judgment criteria), and an output format specification section (e.g., feature label definitions and confidence requirements). Finally, it generates structured component appearance discrimination prompts, describing the component geometric elements and their constraints in natural language, providing standardized input for the pre-trained model.

[0064] In step S205 of some embodiments, specifically, the pre-trained component feature discrimination model refers to a trained large language model, such as a model based on the Transformer architecture.

[0065] Specifically, the appearance features of core components refer to the set of appearance features that need to be retained in the target area to support functions such as equipment identification, connection operation, and spatial positioning; the appearance features of secondary components refer to the set of appearance features that need to be geometrically simplified without affecting the core functions of the components.

[0066] Specifically, the component appearance discrimination prompts are first input into a pre-trained component feature discrimination model for parsing. This yields the component identity, list of geometric elements, and feature discrimination intent from the prompts. Embedded or related electromechanical system domain knowledge (such as electromechanical equipment standard drawings and operation and maintenance procedures) is then invoked for auxiliary reasoning to output the feature classification results of the component's geometric elements (i.e., core component appearance features or secondary component appearance features, and confidence scores). Finally, high-confidence discrimination results are filtered based on a preset confidence threshold (e.g., 0.8) to determine the final core component appearance features (including component geometric element index, retention requirements, and confidence scores) and secondary component appearance features (including component geometric element index, simplification permission, and confidence scores).

[0067] For example, in a smart park application scenario, the problem of identifying appearance features is as follows: For cooling water pipes, since some straight pipe sections are obscured, the shape of the flange connection surfaces at both ends is a key contour defining the connection function. From the perspective of ensuring that the pipeline connection relationship is identifiable, please determine which of the pipe component geometric elements are core component appearance features and which are secondary component appearance features. The component feature discrimination model can be used to identify the pipe routing outline and the shape of the connection nodes as core component appearance features based on the component appearance discrimination prompts, while the surface texture of the straight pipe section obscured in the middle of the pipe and the chamfer of the flange bolt holes are identified as secondary component appearance features.

[0068] Through steps S201 to S205, by clearly defining the appearance features to identify the task objective and integrating spatial visual constraints and precision main contour constraints to construct prompts, the knowledge reasoning ability of the pre-trained model is used to achieve accurate and intelligent classification of the appearance features of electromechanical components. This effectively solves the problem of traditional methods that rely solely on geometric error measurement standards for unified simplification and are difficult to identify key electromechanical parts.

[0069] Please see Figure 3 In some embodiments, the component attribute information includes component usage parameters; core component features include core component usage features; secondary component features include secondary component usage features; and step S104 may also include, but is not limited to, steps S301 to S305.

[0070] Step S301: Obtain the purpose feature discrimination problem, and obtain the component function category of the component purpose parameters based on the purpose feature discrimination problem.

[0071] Step S302: Based on the component function category and spatial layout information, redundant parameter identification constraints are performed on the component purpose parameters to obtain redundant component parameter constraint information.

[0072] Step S303: Based on the component function category and model accuracy simplification requirements, perform main function analysis constraints on the component usage parameters to obtain the main component function constraint information.

[0073] Step S304: Construct prompts based on redundant component parameter constraint information and main component functional constraint information to obtain component usage discrimination prompts.

[0074] Step S305: Based on the component use discrimination prompt, the component feature discrimination model performs use feature discrimination on the number of use feature discrimination questions to extract core component use features and secondary component use features from the component use parameters.

[0075] In step S301 of some embodiments, specifically, the purpose feature discrimination problem refers to the question text raised by the user regarding the purpose feature discrimination of electromechanical components, which is used to characterize the demand information for distinguishing the core component purpose features and secondary component purpose features of electromechanical components; the component function category refers to the type classification of components according to the functional attributes of electromechanical systems, which is used to characterize the functional role undertaken by the component in the park's electromechanical system.

[0076] For example, in the operation and maintenance scenario of a smart hospital park, the functional categories of electromechanical system components can be life support equipment (such as ventilators and medical gas terminals), core protection equipment (such as operating room purification air conditioning units), and security and fire protection equipment (such as fire pumps and emergency lighting).

[0077] Specifically, the component usage parameters for demand-based usage characteristic determination can be obtained from the usage characteristic determination problem, and the component usage parameters can be functionally analyzed based on the electromechanical system functional classification standards (such as the functional zoning of HVAC systems and the functional hierarchy of water supply and drainage systems) to obtain the component functional category.

[0078] In step S302 of some embodiments, specifically, redundant component parameter constraint information refers to data describing irrelevant or duplicate data that can be removed from the component usage parameters, used to identify redundant attribute information unrelated to park operation and maintenance, duplicated component instances, and unnecessary construction process parameters.

[0079] Specifically, based on spatial layout information, components hidden inside the initial electromechanical system model that do not need to be displayed in operation and maintenance visualization, as well as non-visual attribute information such as construction process parameters (e.g., temporary support structure data used for positioning during construction, construction reserved opening dimensions, etc.), can be identified. Based on component function categories, duplicate geometric data can be identified (e.g., multiple pipes of the same specification are repeatedly defined in the model), forming redundant component parameter constraint information that includes a list of redundant component types, a list of redundant parameter fields, and redundant data location identifiers.

[0080] In step S303 of some embodiments, specifically, the main component functional constraint information refers to the data that describes the key functional data that needs to be retained in the component's purpose parameters, and is used to clearly identify the core functional parameters, key connection relationships and other necessary attributes that support the operation of the electromechanical system.

[0081] Specifically, the model obtains the LOD level specified in the simplified model accuracy requirements and its corresponding business scenarios (such as emergency command, daily operation and maintenance, and space planning). Then, it identifies the core functional elements of the electromechanical components according to their functional categories. Furthermore, it establishes a constraint mapping between the model accuracy requirements and the core functional elements. Specifically, high-level simplified accuracy (such as LOD400, used for simulation training) requires retaining the complete functional data chain and all key attributes of the electromechanical components; medium-level simplified accuracy (such as LOD350, used for operation and maintenance management) requires retaining the core functional parameters and main interface relationships of the electromechanical components; low-level simplified accuracy (such as LOD200, used for space planning) only requires retaining the most basic functional type identifier and space occupancy relationship. Finally, it generates backbone component functional constraint information containing the core functional elements of nuclear power components, corresponding constraint levels, and data retention requirements (such as complete retention, partial retention of key fields, or retention of only type identifiers).

[0082] In step S304 of some embodiments, specifically, the component use discrimination prompt refers to text information containing a description of the component use parameters, constraints, and a discrimination task definition, which is used to instruct the component feature discrimination model to identify the core component use features and secondary component use features as standardized input.

[0083] Specifically, firstly, the redundant component type description, redundant parameter fields, and data location identifiers are obtained from the redundant component parameter constraint information; then, the main function parameter description, key connection relationships, and operation and maintenance attribute requirements are obtained from the main component functional constraint information; finally, information is fused according to a predefined prompt template, which typically includes a component identity description section (such as function category, system affiliation, service area, etc.), purpose parameter fields (such as parameter type and constraint conditions), a judgment task definition section (such as core purpose feature judgment criteria and secondary purpose feature judgment criteria), and an output format specification section (such as feature label definition and confidence requirements) to generate component purpose judgment prompts.

[0084] In step S305 of some embodiments, specifically, the core component usage characteristics refer to the set of functional characteristics that need to be retained in the target park to support functions such as electromechanical system operation monitoring, equipment maintenance management, and fault diagnosis and analysis; the secondary component usage characteristics refer to the set of usage characteristics that can be removed from data or simplified by parameterization without affecting the above-mentioned core functions.

[0085] Specifically, the component usage discrimination prompt is first input into a pre-trained component feature discrimination model for parsing. This process yields the component identity, usage parameter list, and feature discrimination intent from the prompt. Embedded or related electromechanical system domain knowledge (such as electromechanical equipment standard drawings, operation and maintenance procedures, and system operating principles) is then invoked for auxiliary reasoning to output the feature classification results of the component usage parameters (i.e., core component usage features or secondary component usage features, and confidence scores). Finally, high-confidence discrimination results are filtered based on a preset confidence threshold (e.g., 0.8) to determine the final core component usage features (including usage parameter index, retention requirements, and confidence scores) and secondary component usage features (including usage parameter index, simplification permit, and confidence scores).

[0086] Through steps S301 to S305, the redundancy cleaning requirements and core function retention requirements can be transformed into executable intelligent discrimination tasks. By using the component feature discrimination model, the business value of the component's purpose is automatically classified, which upgrades the lightweight decision from simple geometric deletion to a simplified task based on business logic. This fundamentally solves the problem of mistakenly deleting key electromechanical components or retaining invalid and redundant components, ensuring that the effectiveness of the business function information carried by the components in the initial electromechanical system model reaches the optimal level during lightweighting.

[0087] Please see Figure 4 In some embodiments, step S105 may include, but is not limited to, steps S401 to S404: Step S401: Perform geometric boundary analysis on the core component features to obtain the component boundary line features.

[0088] Step S402: Vertex sampling is performed on the component boundary line to obtain the boundary triangle vertices.

[0089] Step S403: Obtain the vertex coordinates of the boundary triangle vertices, and lock the boundary triangle vertices based on the vertex coordinates to obtain the locked vertices.

[0090] Step S404: Determine the fixed contour representation information based on the locked vertices.

[0091] In step S401 of some embodiments, specifically, the component boundary line feature refers to the feature data set describing the geometric properties of the component's outer contour line and key structural lines.

[0092] Specifically, a geometric analysis engine (such as B-Rep geometric representation) can be used to traverse the boundary elements corresponding to the core component features and detect the number of adjacent faces of the boundary. Edges that belong to only a single face are marked as boundary edges. At the same time, the dihedral curvature of each edge is calculated, and edges with curvature exceeding a preset curvature threshold (such as 45 degrees) are marked as feature edges. Continuous boundary edges and feature edges are connected to form closed or open edge loops to obtain the component boundary line features.

[0093] In step S402 of some embodiments, specifically, the boundary triangle vertex refers to the set of three-dimensional coordinate points located on the boundary line, and the boundary triangle vertex is the basic element constituting the geometric representation of the boundary line.

[0094] Specifically, the sampling strategy can be determined based on the boundary line type and geometric parameters in the component boundary line features. For straight line segments, equidistant sampling is used, while for curved segments, curvature adaptive sampling (higher sampling density where curvature is large and lower sampling density where curvature is small) is used. Then, the sampling point positions are calculated on the boundary line according to the sampling strategy. Specifically, for circular contour lines, the sampling point coordinates are calculated by dividing the angle equally, and for spiral lines, the sampling point coordinates are calculated by the arc length parameter. Next, the geometric attributes at the sampling points are extracted, including the three-dimensional coordinates of the sampling point, the tangent direction at the sampling point, and the normal relationship between the sampling point and the adjacent surface. Finally, an index mapping relationship between the sampling points and the original boundary lines is established, recording the boundary line identifier to which each sampling point belongs, its sequential position in the boundary line, and the topological connection relationship between adjacent sampling points, forming a boundary triangle vertex data set.

[0095] For example, taking the stainless steel process pipeline in a pharmaceutical workshop in a certain industrial park as an example, for the core component feature of the reducing elbow DN150×DN100, its boundary line includes the circular outline of the large end (circumference 471mm), the circular outline of the small end (circumference 314mm), and the spiral transition curve connecting the two ends (length 280mm). When sampling the vertices, 24 points are sampled at a 20mm interval for the large end, 21 points are sampled at a 15mm interval for the small end, and 36 points are sampled according to the curvature adaptive sampling of the spiral section, finally obtaining 81 boundary triangle vertices. These vertices retain the precise roundness of the interface at both ends of the reducing elbow and the curvature characteristics of the middle transition section.

[0096] In this implementation, the boundary triangle vertices are obtained by sampling the component boundary lines, transforming the continuous boundary line geometric representation into discrete lockable vertex units, providing the smallest operable geometric element for subsequent coordinate locking. At the same time, the curvature adaptive sampling strategy ensures the sampling accuracy of key curve parts.

[0097] In step S403 of some embodiments, specifically, vertex coordinates refer to coordinate data describing the position of the boundary triangle vertex in three-dimensional space; locking vertices refers to applying a protection mark to the boundary triangle vertex so that it cannot be edited, deleted or moved during subsequent lightweighting processes.

[0098] Specifically, the vertex index corresponding to the boundary triangle vertex is located based on the vertex coordinates, and the state of the corresponding boundary triangle vertex is marked as locked based on the vertex index. The locking mark is then bound to the vertex coordinates and topological association data of the boundary triangle vertex to ensure that the locked state is continuously inherited in all subsequent geometric operations (such as edge folding, vertex merging, and mesh smoothing). This ensures that the spatial position of the triangle vertex is not moved or deleted during the simplification process.

[0099] In step S404 of some embodiments, specifically, the fixed contour representation information refers to the component contour dataset generated after boundary locking processing, which maintains the original geometric accuracy. The fixed contour representation information includes the locked vertices, the vertex coordinates corresponding to the locked vertices, the boundary lines to which the locked vertices belong, and the core component features associated with the locked vertices.

[0100] Through steps S401 to S404, explicit marking and physical protection of key contour boundaries are achieved, ensuring that the core component features maintain geometric integrity in subsequent lightweighting processes. This avoids the problem that key contours are easily altered by global algorithm optimization during simplification, leading to distortion of key contours. This significantly improves the lightweighting accuracy of the subsequent park model, thereby enhancing the usability of the lightweighted park model.

[0101] Please see Figure 5 In some embodiments, step S106 may include, but is not limited to, steps S501 to S503: Step S501: If the secondary component feature is the appearance feature of the secondary component, then the geometric elements of the component in the initial electromechanical system model are geometrically simplified according to the appearance feature of the secondary component to obtain simplified appearance contour representation information.

[0102] Step S502: If the secondary component feature is the secondary component purpose feature, then the initial electromechanical system model is simplified based on the secondary component purpose feature to obtain simplified component outline representation information.

[0103] Step S503: Integrate the simplified appearance contour representation information and the simplified component contour representation information to obtain the simplified contour representation information.

[0104] Please see Figure 6 In some embodiments, the initial electromechanical system model consists of multiple target meshes, and each target mesh consists of multiple target triangular facets. Step S501 may include, but is not limited to, steps S601 to S604.

[0105] Step S601: According to the preset initial simplification strategy, perform triangular edge folding processing on the target triangular facet in the target mesh corresponding to each component feature to obtain the initial simplified triangular facet.

[0106] In step S602, during the triangular edge folding process, the appearance error of each target mesh is accumulated based on the initial simplified triangular facet and the target triangular facet to obtain the cumulative appearance error value.

[0107] Step S603: Adjust the initial simplification strategy according to the preset simplified appearance error constraints and the cumulative appearance error value to obtain the target simplification strategy.

[0108] Step S604: The initial simplified triangular facet is simplified and updated according to the target simplification strategy to obtain the target simplified triangular facet, and the target simplified triangular facet is integrated to obtain the simplified appearance contour representation information.

[0109] In step S601 of some embodiments, specifically, the initial simplification strategy refers to the control logic that simplifies the initial electromechanical system model, which is used to guide the edge folding process of the triangular facets.

[0110] For example, for the simplification of pipelines, the initial simplification strategy can be to adjust the priority of edge folding in stages (such as protecting the linearity of the pipeline axis). When the deviation is close to the threshold, the folding priority of "edges that affect the linearity of the pipeline axis" is reduced, and "non-functional and non-appearance edges" are folded first to avoid the appearance deformation caused by the bending of the axis.

[0111] Specifically, the initial simplified triangular facets refer to the intermediate set of triangular facets formed after edge folding, which has a reduced number of facets but has not yet undergone appearance error verification.

[0112] Specifically, the target mesh corresponding to the appearance features of the secondary components can be obtained according to the preset initial simplification strategy, and the edge folding priority of the target triangle facets contained in the target mesh can be determined. According to the edge folding priority, one edge in the target triangle facet is shrunk to one endpoint and the degenerate facet is deleted to update the mesh topology and obtain the initial simplified triangle facets.

[0113] For example, taking a park operation and maintenance scenario as an example, in the mobile inspection application of the smart park operation and maintenance platform, maintenance personnel need to quickly check the pipeline route in the chiller room to locate the fault point, but do not need to pay attention to the texture details of the surface insulation layer. At this time, triangular edge folding is performed on the appearance features of the insulation layer of DN300 chilled water pipe. Its original target mesh contains 6,000 target triangular facets (such as describing the embossed texture of the aluminum outer sheath). After preliminary edge folding, 3,000 initial simplified triangular facets are obtained. The surface of the insulation layer tends to be smooth, but further verification is needed to see if it affects the pipe diameter identification and route judgment.

[0114] Taking the "chilled water main pipeline" of an energy station in a certain park as an example, the target mesh of its straight pipe section contains 4,000 target triangular faces. The preset simplification strategy sets the initial target ratio to 40%. The improved edge folding algorithm prioritizes the processing of the flat areas of the straight pipe section. After 2,400 effective folds, 1,600 initial simplified triangular faces are obtained. At the same time, the original face density is retained at the bends to ensure the direction recognition, thus achieving preliminary geometric simplification and rendering performance optimization.

[0115] In step S602 of some embodiments, specifically, the cumulative appearance error value refers to the deviation of the projected area between the initial simplified triangular facet and the target triangular facet in the target viewpoint, which is used to characterize the degree of appearance shape deviation introduced by the simplification operation.

[0116] Specifically, after each triangular edge folding process, the deviation of the projected area between the initial simplified triangular facet and the initial electromechanical system model under the target view is calculated and determined as the cumulative appearance error value.

[0117] For example, for a pipe component, the pipe is orthogonally projected from the target viewpoint (e.g., the frontal view) to project the vertices of the relevant target triangular facets of the pipe component onto the frontal view plane, ignoring the vertical coordinates, and the area of ​​each projected triangular facet is calculated. The total projected area is obtained by summing the projected areas of all triangular facets, and the total projected area is compared with the total projected area of ​​the initial electromechanical system model under the same viewpoint. The absolute difference is calculated, and this difference is the local appearance error generated by this folding. All local appearance errors are summed to determine the cumulative appearance error value of the target mesh.

[0118] Furthermore, for any projected triangular facet, the facet may include the coordinates of a first vertex (x1y1), a second vertex (x2y2), and a third vertex (x3y3). The first vertex coordinates and the second vertex coordinates are multiplied by difference to obtain a first difference product value (i.e., the difference between x1y2 and x2y1). The second vertex coordinates and the third vertex coordinates are multiplied by difference to obtain a second difference product value (i.e., the difference between x2y3 and x3y2). The first vertex coordinates and the third vertex coordinates are multiplied by difference to obtain a third difference product value (i.e., the difference between x3y1 and x1y3). The first difference product value, the second difference product value, and the third difference product value are summed to obtain a sum of difference products. Half of the sum of difference products value is determined as the area of ​​the projected triangular facet.

[0119] In step S603 of some embodiments, specifically, the simplified appearance error constraint condition refers to the visually perceptible threshold that limits the degree of appearance deviation introduced by the simplification operation, which is determined based on the actual application scenario.

[0120] For example, in a park operation and maintenance scenario, the visually perceptible threshold can be 0.1% to 0.5% of the overall size of the initial electromechanical system model.

[0121] Specifically, the target simplification strategy refers to the control logic that, after constraint verification and adjustment, can achieve the maximum degree of simplification within the allowable error range.

[0122] Specifically, when the cumulative value of appearance error approaches the visually perceptible threshold, it indicates that the current simplification intensity may cause visually perceptible distortion, immediately triggering a strategy adjustment. This adjustment does not simply stop simplification, but rather enables different target simplification strategies based on the type of electromechanical component and the source of error.

[0123] For example, for pipe components, if the deviation mainly originates from axial bending, a graded edge folding priority adjustment strategy is activated to reduce the folding priority of edges that affect the linearity of the pipe axis, prioritizing the folding of edges with less impact on the overall shape. If the deviation originates from cross-sectional deformation, since the pipe's appearance depends on the consistency of the circular cross-section, a cross-sectional shape constraint strengthening strategy is activated, adding dual constraints on cross-sectional diameter deviation and roundness error to avoid cross-sectional deformation caused by simplification. If the deviation originates from pipe elbows, tees, or other connection parts, a local patch subdivision compensation strategy can be activated to pause edge folding at the connection part or even reverse subdivide the local patch to compensate for shape details and maintain the curvature continuity of the connection part.

[0124] In this embodiment, the initial simplification strategy is adjusted according to the simplified appearance error constraints and the cumulative appearance error value. This can transform the simplification process from being executed with fixed parameters to adaptive optimization based on scenario requirements. This upgrades the simplification process from focusing only on geometric errors (such as the distance between triangle vertices) to the overall visual fidelity of the initial electromechanical system model, avoiding the problem that a single strategy cannot cope with complex geometric distortions.

[0125] In step S604 of some embodiments, specifically, the target simplified triangular facet refers to the set of final state triangular facets that meet the simplified appearance error constraints after being processed by the target simplification strategy.

[0126] Specifically, simplified appearance contour representation information refers to the geometric data that fully describes the lightweight appearance features of secondary components after integrating all target simplified triangular facets.

[0127] For example, for curved duct components in smart technology parks, relatively dense facets can be retained in the high curvature areas of the component to accurately represent the shape changes, while the number of facets can be significantly reduced in the flat low curvature areas. At the same time, combined with simplified appearance error constraints, the entire curved surface transition is ensured to be smooth and visually consistent with the original curved surface.

[0128] Through steps S601 to S604, the general appearance can be simplified and transformed into a precise optimization for park operation and maintenance business scenarios, making the lightweight appearance of the electromechanical system model available for operation and maintenance business applications.

[0129] In step S502 of some embodiments, specifically, the simplified component outline representation information refers to the set of simplified component outline data in the initial electromechanical system model.

[0130] Specifically, the initial electromechanical system model is simplified based on the usage characteristics of secondary components to obtain simplified component outline representation information. This can include: identifying target simplified components in the initial electromechanical system model based on the usage characteristics of secondary components; wherein, target simplified components include functionally redundant components and adjacent components with the same attributes; if the target simplified component includes functionally redundant components, the corresponding functionally redundant component parameters are obtained, and the functionally redundant components and their parameters are removed to obtain simplified data of functionally redundant components; if the target simplified component includes standard components with the same attributes, the standard components with the same attributes are merged to obtain aggregated component outline simplified data; and the aggregated component outline simplified data and the functionally redundant component simplified data are integrated to obtain simplified component outline representation information.

[0131] Furthermore, redundant functional components refer to components with repetitive or temporary functional definitions, which may include standard components that are completely functionally repetitive and follow uniform specifications and parameters, as well as temporary components that serve the construction and design phases; redundant functional component parameters refer to the non-visual attribute information corresponding to redundant functional components; adjacent components with the same attributes refer to adjacent components of the same type and material in the initial electromechanical system model.

[0132] For example, in the operation and maintenance scenario of a smart hospital park, temporary support frames and their parameters (such as material, shape, and size) serving the construction and design phases of medical ventilation duct components are removed. For multiple valve components and their corresponding valve parameters that are functionally identical and of the same specifications, valve parameterization instances are obtained from a pre-built component parameterization template library to perform instantiation and reference replacement on the valves, replacing the original valve models. Only the valve type parameters (such as valve diameter and pressure rating) and spatial coordinate information, and other core parameters relevant to the operation and maintenance scenario, are retained. Among these, the valve parameterization instance is obtained by retaining only one valve parameter content and valve model from multiple valves.

[0133] For example, in the operation and maintenance scenario of a smart hospital park, for straight pipe sections consisting of continuous adjacent straight pipes of the same material in a medical ventilation duct system, the adjacent straight pipe models can be merged into a whole through geometric appearance simplification operations to eliminate unnecessary splicing surfaces.

[0134] In this embodiment, the initial electromechanical system model is simplified based on the usage characteristics of secondary components to obtain simplified component outline representation information. This allows for the removal of functionally redundant component models and component-related information based on the usage characteristics of secondary components. This not only reduces the number of components in the initial electromechanical system model but also lowers the face number cardinality of the model, thus improving the simplification efficiency of the initial electromechanical system model, while ensuring the core functional component characteristics in the park operation and maintenance application scenario.

[0135] In step S503 of some embodiments, simplified contour representation information refers to a data set that fully describes the simplified features of secondary components after integrating simplified appearance contour representation information and simplified component contour representation information, and serves as a model component parallel to fixed contour representation information.

[0136] Specifically, a data index is established for simplified appearance contour representation information and simplified component contour representation information, so as to associate and map the component identifier, the electromechanical system type to which the component belongs (such as HVAC, electrical, water supply and drainage, etc.) with the spatial region to which the component belongs, so as to obtain simplified contour representation information.

[0137] Through steps S501 to S503, while retaining the accurate outlines of core functional components and key operation and maintenance parameters, secondary outlines such as redundant appearances, redundant functions, and standard components can be simplified. This reduces the data size of the electromechanical system model while maintaining the information integrity and query availability of the electromechanical system model in actual operation and maintenance tasks such as equipment identification, status monitoring, or capacity planning. It achieves a balance between lightweight effect and operation and maintenance practicality, which helps to improve the availability of subsequent lightweight park models.

[0138] In step S107 of some embodiments, specifically, the target electromechanical system model refers to the lightweight electromechanical system model.

[0139] For example, for the electromechanical system of a hospital campus, fixed contour representation information (such as interfaces of key equipment in the operating room, main pipe connections, etc.) is fused with simplified contour representation information (such as parametric geometry or simplified target mesh of branch pipes and terminal equipment on each floor). Specifically, the spatial positions of fixed and simplified contour representation information are registered in the global coordinate system of the electromechanical system model. Three-way transition patches are generated at the connection between the DN350 main pipe (i.e., the core component, retaining the original surface details) and the DN100 branch pipe (i.e., the secondary component, parametric cylinder). The attribute data is integrated to identify the electromechanical system affiliation and pipe diameter parameters of the simplified branch pipe. The final output is a target electromechanical system model with a size of 25% of the original electromechanical system model and retaining the complete geometric details of the key equipment interfaces.

[0140] In this embodiment, the initial electromechanical system model is lightweighted based on fixed contour representation information and simplified contour representation information, which effectively avoids the oversimplification of key parts of the electromechanical system during the simplification process. This solves the problems of loss of features and contour distortion of important electromechanical components caused by traditional methods, and significantly improves the usability of the lightweight campus model in operation and maintenance scenarios.

[0141] Please see Figure 7 In some embodiments, the park model lightweighting method may also include, but is not limited to, steps S701 to S704: Step S701: Perform boundary appearance defect detection on the target electromechanical system model to obtain boundary appearance defect data.

[0142] Step S702: Obtain the initial boundary data corresponding to the boundary appearance defect data from the initial electromechanical system model, and calculate the defect deviation based on the boundary appearance defect data and the initial boundary data to obtain the boundary defect deviation data. Step S703: Generate the vertices of the repair triangle based on the boundary defect deviation data.

[0143] Step S704: Fill the boundary appearance defects with triangular patches according to the vertices of the repair triangle to obtain the repaired electromechanical system model, and determine the repaired electromechanical system model as the target electromechanical system model.

[0144] In step S701 of some embodiments, specifically, boundary appearance defect data refers to data representation describing the location and type of boundary appearance defects.

[0145] For example, a lightweight chilled water pipe model may have jagged edges at the interface between the equipment casing and the pipe. In this case, the position coordinates, line segment length and curvature change degree of the jagged edge are determined as boundary appearance defect data.

[0146] Specifically, since the target electromechanical system model after lightweighting may have visually sensitive areas at the equipment shell or pipe interface, the unit normal vectors of the two triangular faces corresponding to any triangular edge in the triangular mesh data of the target electromechanical system model can be calculated separately. The dot product of the unit normal vectors is then performed to obtain the cosine value of the angle between the two triangular faces, i.e., the dihedral angle. If the dihedral angle is greater than a preset angle threshold (e.g., 30 degrees), the edge is identified as a visually sensitive edge. Continuous visually sensitive edges form visually sensitive areas (e.g., jagged edges at the equipment shell outline or pipe interface connection). The jagged edges at the equipment shell outline or pipe interface connection and the spatial coordinates of the area where the jagged edges are located are determined as boundary appearance defect data.

[0147] In step S702 of some embodiments, specifically, the initial boundary data refers to the original geometric data corresponding to the boundary appearance defect area extracted from the initial electromechanical system model, which includes complete contour curves and surface details.

[0148] Specifically, boundary defect deviation data refers to the quantitative indicators and repair accuracy requirements of the geometric deviation of boundary defects by comparing the boundary appearance defect data with the initial boundary data, including measures such as edge contour deviation value and subdivision density level.

[0149] Specifically, based on the visually sensitive area identifiers and spatial coordinates in the boundary appearance defect data, the corresponding original contour area is located in the initial electromechanical system model. The complete initial boundary data of this area is extracted (which may include the original contour curve parameters, surface curvature distribution, and normal vector information). The jagged edge vertices in the boundary appearance defect data are matched with the initial boundary data for contour registration and error calculation. The geometric deviation between corresponding sampling points (such as the projection distance perpendicular to the original contour) is calculated. The maximum deviation value and the average deviation value are statistically analyzed. Based on the degree of deviation, the required subdivision density level for repair is determined (e.g., deviation greater than 5mm corresponds to high-density subdivision, deviation between 2 and 5mm corresponds to medium-density subdivision, and deviation less than 2mm corresponds to low-density subdivision) to determine the boundary defect deviation data.

[0150] In step S703 of some embodiments, specifically, the repair triangle vertex refers to a new triangle vertex generated along the defect edge corresponding to the boundary appearance defect data. This vertex is located inside the defect edge or connected to the irregular boundary and is the basic geometric element constituting the repair patch. This vertex is used to repair the visually sensitive area.

[0151] For example, in the repair of cooling water pipe models, the plate heat exchanger interface has a jagged edge due to lightweighting. The repair triangle vertex is a dynamically generated repair triangle vertex along the edge according to the high density subdivision level, in order to reconstruct a smooth transition surface consistent with the original contour.

[0152] Specifically, repair triangle vertices can be generated on the jagged edges based on the defect edge range, subdivision density level, and original contour curvature information in the boundary defect deviation data.

[0153] For example, for jagged points with boundary defect deviation data greater than 5mm, which are identified as severely distorted areas, three repair triangle vertices can be generated between the jagged point and its adjacent original triangle vertices. For jagged points with boundary defect deviation data between 2mm and 5mm, which are identified as moderately distorted areas, one to two repair triangle vertices can be generated between the jagged point and its adjacent original triangle vertices, and the position of the vertex can be determined by a quadratic interpolation algorithm. For jagged points with boundary defect deviation data less than 2mm, since the visual impact of the jagged point is close to the human eye's recognition limit, no repair triangle vertex can be generated or only one repair triangle vertex can be generated to avoid unnecessary increase in the number of faces.

[0154] In step S704 of some embodiments, specifically, repairing the electromechanical system model refers to an electromechanical system model whose boundary appearance defects have been repaired and which is compatible with the surrounding triangular mesh.

[0155] For example, in the model of the air conditioning electromechanical system of a hospital, if the shell interface of the combined air conditioning unit has jagged edges after being lightweighted, a new triangular mesh can be constructed by repairing the vertices of the triangles and the original edge vertices. The fusion verification ensures that the normal information of the new mesh matches the surrounding original meshes. The repaired electromechanical system model is the complete unit model after filling, which can be directly used for subsequent equipment inspection and maintenance simulation.

[0156] For example, the generated repair triangle vertices can be connected to their adjacent original triangle vertices using the Delaunay triangulation mesh generation algorithm to form new, denser, and smoother triangular facets. A fusion check is then performed on the new triangular facets to verify the overall appearance consistency (e.g., whether the deviation from the original component outline is less than the low-density subdivision (e.g., 2mm)). The verified new triangular facets are then integrated into the triangular mesh data of the target electromechanical system model, replacing the original jagged edge regions, to obtain the repaired electromechanical system model. This repaired electromechanical system model is then used as the final target electromechanical system model.

[0157] Through steps S701 to S704, local geometric defects that are difficult to completely avoid in visually sensitive areas during the lightweighting process can be accurately repaired, providing reliable technical support for the digital delivery and visualization application of electromechanical systems in smart parks, effectively avoiding maintenance interference caused by visual defects in the appearance of electromechanical system models, and significantly improving the usability of lightweight park models.

[0158] In step S108 of some embodiments, specifically, the target park model refers to a complete park information simulation model that includes the lightweight building structure and the target electromechanical system.

[0159] Specifically, firstly, a spatial reference relationship is established between the building structure layout model and the target electromechanical system model. Typically, the coordinate system of the building structure model is used as the reference, and the spatial coordinates of the target electromechanical system model are transformed as necessary to achieve registration. Then, the data organization methods of the two types of models are unified, including hierarchical structure (such as by floor or by electromechanical system) and attribute field naming conventions. Finally, a comprehensive model containing complete building space information and lightweight electromechanical equipment information is generated.

[0160] In this embodiment, by integrating the building structure layout model and the target electromechanical system model, a target park model is obtained. This model can improve the lightweighting of the park while supporting park operation and maintenance management to perform business operations such as spatial visualization, equipment positioning, and maintenance path planning, significantly improving the usability of the lightweight park model in operation and maintenance business scenarios.

[0161] The proposed lightweight campus model method first obtains an initial campus model containing a building structure layout model and an initial electromechanical system model, and extracts spatial layout information from it. This establishes spatial location relationships between building spaces and electromechanical equipment, providing a spatial constraint benchmark for subsequent electromechanical system simplification. Second, by analyzing the component attributes of the initial electromechanical system model and performing component feature discrimination based on model accuracy simplification requirements and spatial layout information, core component features and secondary component features are extracted from the component attribute information. This method identifies the core component features in the electromechanical system model, thus preventing the loss of features of important electromechanical components during the simplification process from the outset, and solving the problem of traditional methods relying solely on... The problem of difficulty in identifying key electromechanical components due to the unification and simplification of geometric error measurement standards is addressed. Furthermore, necessary contour boundary locking is performed on the initial electromechanical system model based on the features of core components, ensuring the integrity of the geometric features of key electromechanical components. Contour simplification based on the features of secondary components effectively reduces the data volume of the electromechanical system model. Finally, by integrating the target electromechanical system model that retains the features of core components with the building structure layout model, the overall data volume of the park model can be significantly reduced while effectively avoiding oversimplification of key electromechanical components during the simplification process. This solves the problems of loss of important electromechanical component features and contour distortion caused by traditional methods, and significantly improves the usability of the lightweight park model in operation and maintenance scenarios.

[0162] Please see Figure 8 This application also provides a lightweighting device for a park model, which can implement the above-mentioned lightweighting method for a park model, including: The park model and simplified requirements acquisition module allows users to obtain an initial park model and simplified model accuracy requirements corresponding to the target park; the initial park model includes a building structure layout model and an initial electromechanical system model. The layout information extraction module is used to extract spatial layout information from the building structure layout model; The component attribute parsing module is used to parse the component attributes of the initial electromechanical system model and obtain the component attribute information. The component feature discrimination module is used to perform component feature discrimination on component attribute information based on the model accuracy simplification requirements and spatial layout information, so as to extract core component features and secondary component features from the component attribute information; The contour boundary locking module is used to lock the necessary contour boundaries of the initial electromechanical system model based on the features of the core components, so as to obtain fixed contour representation information. The secondary contour simplification processing module is used to simplify the secondary contour of the initial electromechanical system model based on the features of secondary components, and obtain simplified contour representation information. The lightweight processing module is used to perform lightweight processing on the initial electromechanical system model based on fixed contour representation information and simplified contour representation information to obtain the target electromechanical system model. The model integration module is used to integrate the building structure layout model and the target electromechanical system model to obtain the target park model.

[0163] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the campus model lightweighting method as described in any one of the embodiments of the first aspect of this application.

[0164] Fourthly, embodiments of this application provide a computer-readable storage medium storing a program that is executed by a processor to implement the campus model lightweighting method as described in any of the embodiments of the first aspect of this application.

[0165] Please see Figure 9 , Figure 9 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the campus model lightweighting method of the embodiments of this application. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between the various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0166] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described campus model lightweighting method.

[0167] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0168] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0169] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0170] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0171] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0172] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0173] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0174] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0175] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0176] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0177] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0178] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A lightweight method for campus models, characterized in that, The method includes: Obtain the initial park model corresponding to the target park and the model accuracy simplification requirements; wherein, the initial park model includes a building structure layout model and an initial electromechanical system model; Extract spatial layout information from the building structure layout model; The component attribute information is obtained by parsing the initial electromechanical system model. Based on the model accuracy simplification requirements and the spatial layout information, the component attribute information is subjected to component feature discrimination in order to extract core component features and secondary component features from the component attribute information; Based on the features of the core components, the initial electromechanical system model is locked with necessary contour boundaries to obtain fixed contour representation information; Based on the features of the secondary components, the initial electromechanical system model is simplified by performing secondary contour simplification processing to obtain simplified contour representation information; The initial electromechanical system model is lightweighted based on the fixed contour representation information and the simplified contour representation information to obtain the target electromechanical system model. By integrating the building structure layout model and the target electromechanical system model, the target park model is obtained.

2. The method according to claim 1, characterized in that, The component attribute information includes the component's geometric parameters; the core component features include the core component's appearance features. The secondary component features include the appearance features of the secondary component; The step of performing component feature discrimination on the component attribute information based on the model accuracy simplification requirements and the spatial layout information, in order to extract core component features and secondary component features from the component attribute information, includes: Obtain the appearance feature discrimination problem, and based on the appearance feature discrimination problem, obtain the component geometric category and component geometric elements of the component geometric parameters; Based on the spatial layout information and the component geometric category, the geometric elements of the component are visually analyzed and constrained to obtain geometric visual constraint information; Based on the model accuracy simplification requirements and the component geometry category, the main contour analysis constraint is performed on the component geometry elements to obtain the main contour constraint information; Based on the geometric visual constraint information and the main contour constraint information, prompts are constructed to obtain component appearance discrimination prompts; Based on the component appearance discrimination prompts, a pre-trained component feature discrimination model is used to perform appearance feature discrimination on the appearance feature discrimination problem, so as to extract the appearance features of the core component and the appearance features of the secondary component from the component geometric parameters.

3. The method according to claim 2, characterized in that, The component attribute information includes component usage parameters; the core component features include core component usage features; The secondary component features include the secondary component's usage features; The step of performing component feature discrimination on the component attribute information based on the model accuracy simplification requirements and the spatial layout information, in order to extract core component features and secondary component features from the component attribute information, includes: Obtain the usage feature discrimination problem, and obtain the component function category of the component usage parameters based on the usage feature discrimination problem; Based on the functional category of the component and the spatial layout information, redundant parameter identification constraints are performed on the component's purpose parameters to obtain redundant component parameter constraint information; Based on the functional category of the component and the model accuracy simplification requirements, the main functional constraints of the component's usage parameters are analyzed and constrained to obtain the main component functional constraint information. Based on the redundant component parameter constraint information and the main component functional constraint information, prompts are constructed to obtain component usage discrimination prompts. Based on the component usage discrimination prompt, the component feature discrimination model is instructed to perform usage feature discrimination on the number of usage feature discrimination questions, so as to extract the core component usage features and the secondary component usage features from the component usage parameters.

4. The method according to claim 3, characterized in that, The process of simplifying the initial electromechanical system model based on the secondary component features to obtain simplified contour representation information includes: If the secondary component feature is the appearance feature of the secondary component, then the initial electromechanical system model is geometrically simplified based on the appearance feature of the secondary component to obtain simplified appearance contour representation information; If the secondary component feature is the secondary component usage feature, then the initial electromechanical system model is simplified based on the secondary component usage feature to obtain simplified component outline characterization information; The simplified appearance contour representation information and the simplified component contour representation information are integrated to obtain the simplified contour representation information.

5. The method according to claim 4, characterized in that, The initial electromechanical system model consists of multiple target meshes, and each target mesh consists of multiple target triangular facets; The step of performing a geometric simplification operation on the initial electromechanical system model based on the appearance features of the secondary components to obtain simplified appearance contour representation information includes: According to the preset initial simplification strategy, the target triangle facet in the target mesh corresponding to each of the secondary component features is subjected to triangle edge folding processing to obtain the initial simplified triangle facet; During the triangular edge folding process, the appearance error of each target mesh is accumulated based on the initial simplified triangular facet and the target triangular facet to obtain the appearance error accumulation value. The initial simplification strategy is adjusted according to the preset simplified appearance error constraints and the cumulative appearance error value to obtain the target simplification strategy; The initial simplified triangular facet is simplified and updated according to the target simplification strategy to obtain the target simplified triangular facet, and the target simplified triangular facet is integrated to obtain the simplified appearance contour representation information.

6. The method according to claim 1, characterized in that, The step of locking the necessary contour boundaries of the initial electromechanical system model based on the features of the core components to obtain fixed contour representation information includes: Geometric boundary analysis is performed on the core component features to obtain the component boundary line features; Vertex sampling is performed on the boundary lines of the component to obtain the vertices of the boundary triangle; Obtain the vertex coordinates of the boundary triangle vertices, and lock the boundary triangle vertices based on the vertex coordinates to obtain the locked vertices; The fixed contour representation information is determined based on the locked vertices.

7. The method according to claim 6, characterized in that, After performing lightweight processing on the initial electromechanical system model based on the fixed contour representation information and the simplified contour representation information to obtain the target electromechanical system model, the method further includes: Boundary appearance defect detection is performed on the target electromechanical system model to obtain boundary appearance defect data; The initial boundary data corresponding to the boundary appearance defect data is obtained from the initial electromechanical system model, and the defect deviation is calculated based on the boundary appearance defect data and the initial boundary data to obtain the boundary defect deviation data. Generate repair triangle vertices based on the boundary defect deviation data; The boundary appearance defects are filled with triangular patches based on the vertices of the repair triangle to obtain the repaired electromechanical system model, and the repaired electromechanical system model is determined as the target electromechanical system model.

8. A lightweight device for a park model, characterized in that, include: The park model and simplified requirements acquisition module allows users to obtain an initial park model and simplified model accuracy requirements corresponding to the target park; wherein, the initial park model includes a building structure layout model and an initial electromechanical system model; The layout information extraction module is used to extract spatial layout information from the building structure layout model. The component attribute parsing module is used to parse the component attributes of the initial electromechanical system model to obtain component attribute information. The component feature discrimination module is used to perform component feature discrimination on the component attribute information according to the model accuracy simplification requirements and the spatial layout information, so as to extract core component features and secondary component features from the component attribute information; The contour boundary locking module is used to perform necessary contour boundary locking on the initial electromechanical system model based on the features of the core components, so as to obtain fixed contour representation information. The secondary contour simplification processing module is used to perform secondary contour simplification processing on the initial electromechanical system model based on the features of the secondary components to obtain simplified contour representation information; The lightweight processing module is used to perform lightweight processing on the initial electromechanical system model based on the fixed contour representation information and the simplified contour representation information to obtain the target electromechanical system model. The model integration module is used to integrate the building structure layout model and the target electromechanical system model to obtain the target park model.

9. An electronic device, characterized in that, include: The system includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the campus model lightweighting method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a program that is executed by a processor to implement the campus model lightweighting method as described in any one of claims 1 to 7.

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