BIM model optimization processing system for water conservancy projects based on lightweight and component integration

Abstract

The present invention relates to the technical field of building information management, and specifically to a water conservancy project BIM model optimization processing system based on lightweight and component integration. The graph structure construction module maps the geometric shape and spatial relationship of the component into nodes and edges based on the component data of the BIM model, integrates the parameter information of the pipeline and supporting structure sub-projects in the water conservancy project, establishes the topological relationship between the nodes, and generates a graph structure model. The present invention maps the component data in the water conservancy project BIM model into a graph structure, and conducts a detailed analysis of the geometric shape and spatial relationship to form a topological relationship between the nodes and the edges. This data structure conversion makes the stress distribution analysis of the water flow path and the supporting structure more intuitive and efficient, thereby optimizing the design and performance of the entire system. By screening key component groups, optimizing these groups, eliminating redundant connections, and integrating structural units with similar functions, the accuracy and application efficiency of the model are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of building information management, and in particular to a hydraulic engineering BIM model optimization processing system based on lightweight and component integration. Background Art

[0002] The field of building information management realizes data integration and management of the entire life cycle of a building by establishing a virtual building information model. BIM not only contains the three-dimensional geometric information of the building, but also covers information such as time, cost, materials and construction progress, thereby providing support for various stages such as design, construction, operation and maintenance. This technical field is committed to improving the collaborative efficiency of construction projects, reducing design errors, optimizing construction processes, and realizing digital and intelligent management of construction projects.

[0003] Among them, the water conservancy project BIM model optimization processing system is a BIM application system developed for water conservancy projects. The system aims to optimize the BIM model of water conservancy projects to improve the accuracy and application efficiency of the model. By integrating the data and parameters unique to water conservancy projects, the design and information management process of the BIM model is optimized to provide data support and decision-making basis for each stage of water conservancy project planning, design, construction and management. The application scope of the system includes water conservancy projects such as dams, levees, irrigation systems, and water treatment facilities, realizing the information and intelligent management of the entire life cycle of water conservancy projects.

[0004] Traditional BIM systems focus on model construction and basic management, but do not provide in-depth analysis of complex spatial relationships and structural stress, which results in the inability to accurately locate structural defects or safety hazards during the project implementation phase. In addition, in large-scale water conservancy projects, it is difficult for system models to identify and optimize key components, resulting in redundant designs and waste of resources, increasing project costs and maintenance difficulties. This can easily lead to project delays, increased safety risks, and higher maintenance costs in the later stages. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings existing in the prior art and propose a water conservancy project BIM model optimization processing system based on lightweight and component integration.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a water conservancy project BIM model optimization processing system based on lightweight and component integration, the system comprising: a graph structure construction module maps the geometric form and spatial relationship of the components into nodes and edges based on the component data of the BIM model, integrates the parameter information of the pipeline and supporting structure sub-projects in the water conservancy project, establishes the topological relationship between the nodes, and generates a graph structure model;

[0007] The component relationship analysis module analyzes the stress distribution and water flow path of the pipeline connection and the supporting structure based on the graph structure model, selects the key component groups, and obtains the associated component group information;

[0008] The node optimization module deletes redundant connection nodes and merges structural units with similar functions based on the associated component group information, adjusts the layout of the supporting structure and optimizes the fluidity of the pipeline network, and generates an optimized component diagram;

[0009] The problem location module is based on the optimized component diagram, combined with the design drawings of key components in the water conservancy project and the BIM model, to calibrate the locations of pipeline leakage and structural deformation safety hazards and generate problem component location information;

[0010] The path calculation module calculates the shortest path between the pipeline and the supporting structure based on the location information of the problem component, the spatial distance between the components, and the structural load parameters, evaluates the construction feasibility and maintenance convenience of the path, and generates the shortest path information;

[0011] The component attachment module analyzes the historical maintenance records and the functional characteristics of the components according to the shortest path information, recommends other components associated with the problem type, locates the matching components on the BIM model, and generates intelligent attachment results.

[0012] The present invention has improvements in that the graph structure model includes geometric morphology mapping of node topological structure, spatial relationship connection between components, integrated pipeline and support structure parameter information, the associated component group information includes screened key component nodes, association relationship based on stress distribution, and connection information of water flow path, the optimized component diagram includes simplified node layout, merged structural units, and re-optimized pipeline network, the problem component position information includes determined pipeline leakage point coordinates, structural deformation location, and key hidden danger calibration information, the shortest path information includes the arrangement order of path nodes, the optimal distance between nodes, and the distribution information of structural loads, and the intelligent hanging result includes automatically matched associated components, positions in the BIM model, and association descriptions between components.

[0013] The present invention is improved in that the graph structure building module includes:

[0014] The node creation submodule analyzes the geometric information and physical properties of the components based on the component data of the BIM model, converts them into basic nodes of the graph structure, and defines and identifies the attributes of the nodes to establish the basic nodes of the components;

[0015] The spatial mapping submodule analyzes the relative position and connection relationship of the component in the three-dimensional space based on the component basic nodes, connects the nodes into edges of the graph structure, and adjusts the spatial position and connection relationship to obtain the component spatial structure;

[0016] The topological integration submodule performs topological integration of pipelines and supporting structures in water conservancy projects based on the component spatial structure, optimizes the hierarchy and correlation of the topological structure by integrating the parameter information and node connection relationship of the subprojects, and generates a graph structure model.

[0017] The present invention is improved in that the component relationship analysis module includes:

[0018] The function evaluation submodule evaluates the functional role and interdependence of the components in the overall structure based on the graph structure model, identifies the relationship between key functional nodes and secondary nodes, and obtains functional relationship data;

[0019] The stress distribution analysis submodule analyzes the stress transfer and load distribution of the component under working condition based on the functional relationship data, identifies the core stress area and stress nodes, and obtains stress distribution information;

[0020] Based on the stress distribution information, the component screening submodule screens components that play a key role in the water flow path and the supporting structure, identifies nodes that affect the stability of the overall supporting structure, and generates associated component group information.

[0021] The present invention is improved in that the node optimization module comprises:

[0022] The redundant node deletion submodule screens and verifies redundant nodes in the graph structure based on the associated component group information, deletes duplicate nodes by analyzing the connection and functional duplication between nodes, and obtains a simplified node structure;

[0023] The functional unit merging submodule identifies the association between structural units and nodes with similar functions based on the simplified node structure through a hierarchical clustering algorithm, merges the nodes and uniformly adjusts the node attributes to generate a merged node structure;

[0024] The structural layout adjustment submodule adjusts the support structure layout and the pipeline network based on the merged node structure, reconfigures the node connection sequence and layout structure, and generates an optimized component diagram.

[0025] The present invention is improved in that the hierarchical clustering algorithm is according to the formula:

[0026]

[0027] Calculate the similarity index between nodes ;

[0028] in, represents the exponential function, which is used to convert the similarity measure into a non-negative number. Is a node and nodes The functional difference measure between Is a weight factor used to adjust the integration of components The impact on the overall similarity measure is obtained through data analysis or expert experience according to the current situation. It is a node based on lightweight and component integration. and The integration measure between is a scaling parameter that adjusts the effect of distance, either based on the distribution of the data or empirically.

[0029] The present invention is improved in that the problem location module includes:

[0030] The design drawing comparison submodule analyzes the design drawings of key components in the water conservancy project based on the optimized component drawings, compares the component layout in the design drawings with the structure in the BIM model, automatically identifies the differences and potential problems between the design structure and the current structure, and marks and records the differences to obtain the drawing comparison results;

[0031] The component mapping submodule corresponds and matches the key nodes in the design drawings with the positions in the BIM model based on the drawing comparison results, calibrates the spatial positions of the components in the BIM model, and generates component mapping information;

[0032] The hidden danger calibration submodule identifies and calibrates the safety hidden dangers of pipeline leakage and structural deformation based on the component mapping information, determines the location and type of hidden dangers by combining the field data with the design comparison results, and generates the location information of the problem components.

[0033] The present invention is improved in that the path calculation module comprises:

[0034] The path evaluation submodule analyzes the connection mode between components and the potential feasibility of the path based on the location information of the problem components, selects the path options that meet the requirements, and performs initial path evaluation and marking to obtain initial path information;

[0035] The spatial distance calculation submodule measures the spatial distance between component nodes based on the initial path information, calculates the total length of each path, and sorts and screens the path distances to generate a spatial distance result;

[0036] The load parameter integration submodule analyzes the load parameters of the path based on the spatial distance results and refers to the structural load, construction convenience and maintenance requirements to generate the shortest path information.

[0037] The present invention is improved in that the component mounting module comprises:

[0038] The historical record analysis submodule extracts and analyzes historical maintenance records based on the shortest path information and uses the Bayesian reasoning method. By collecting historical maintenance data and component information associated with the problem type, it identifies component characteristics that match the current problem and obtains historical analysis results.

[0039] The component matching submodule compares the problem type with the functional characteristics of the associated components based on the historical analysis results, selects key components, and generates component matching information;

[0040] The BIM positioning submodule marks the matched components in the BIM model based on the component matching information and generates intelligent mounting results.

[0041] The present invention is improved in that the Bayesian reasoning method is according to the formula:

[0042]

[0043] The posterior probability of a component under a given problem type ;

[0044] in, It is in the component Simplified structure and resource optimization Type of problem encountered The conditional probability of and Respectively represent the new parameters of optimized structural simplification and resource allocation, In structural simplification Under the condition of The probability of occurrence, It is a simplified structure The probability of occurrence, It is resource optimization The probability of Is the type of question The total probability of occurrence.

[0045] Compared with the prior art, the advantages and positive effects of the present invention are:

[0046] In the present invention, by mapping the component data in the BIM model of the water conservancy project into a graph structure, a detailed analysis of the geometric form and spatial relationship is performed to form a topological relationship between nodes and edges. This data structure conversion makes the stress distribution analysis of the water flow path and the supporting structure more intuitive and efficient, thereby optimizing the design and performance of the entire system. By screening key component groups and optimizing these groups, eliminating redundant connections, and integrating structural units with similar functions, the accuracy and application efficiency of the model are improved. In addition, through intelligent hanging technology, the problem components can be accurately located, which improves the convenience of maintenance and management. The feasibility of construction and maintenance is further ensured by calculating the shortest path. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 The module diagram of the water conservancy project BIM model optimization processing system based on lightweight and component integration is proposed for the present invention;

[0048] Figure 2 The system framework diagram of the water conservancy project BIM model optimization processing system based on lightweight and component integration is proposed for the present invention;

[0049] Figure 3 A schematic diagram of a graph structure building module of the present invention;

[0050] Figure 4 is a schematic diagram of a component relationship analysis module of the present invention;

[0051] Figure 5 It is a schematic diagram of the node optimization module of the present invention;

[0052] Figure 6 A schematic diagram of a problem location module of the present invention;

[0053] Figure 7 is a schematic diagram of a path calculation module of the present invention;

[0054] Figure 8 It is a schematic diagram of the component mounting module of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0056] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating positions or positional relationships, are based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0057] See also Figure 1 ,The present invention provides a technical solution: a water conservancy project BIM model optimization processing system based on lightweight and component integration, the system includes: a graph structure construction module maps the geometric form and spatial relationship of the components into nodes and edges based on the component data of the BIM model, integrates the parameter information of the pipeline and supporting structure sub-projects in the water conservancy project, establishes the topological relationship between the nodes, and generates a graph structure model;

[0058] The component relationship analysis module analyzes the stress distribution and water flow path of pipeline connections and supporting structures based on the graph structure model, selects key component groups, and obtains the information of related component groups;

[0059] The node optimization module deletes redundant connection nodes and merges structural units with similar functions based on the information of associated component groups, adjusts the layout of the supporting structure and optimizes the fluidity of the pipeline network to generate an optimized component diagram;

[0060] The problem location module is based on the optimized component diagram, combined with the design drawings of key components in the water conservancy project and the BIM model, to calibrate the location of pipeline leakage and structural deformation safety hazards and generate the location information of the problem components;

[0061] The path calculation module calculates the shortest path between the pipeline and the supporting structure based on the location information of the problem component, the spatial distance between components, and the structural load parameters, evaluates the construction feasibility and maintenance convenience of the path, and generates the shortest path information;

[0062] The component attachment module analyzes the historical maintenance records and the functional characteristics of the components based on the shortest path information, recommends other components associated with the problem type, locates the matching components on the BIM model, and generates intelligent attachment results.

[0063] The graph structure model includes the geometric morphology mapping of the node topology, the spatial relationship connection between components, and the integrated pipeline and supporting structure parameter information. The associated component group information includes the selected key component nodes, the association relationship based on stress distribution, and the connection information of the water flow path. The optimized component diagram includes the simplified node layout, the merged structural units, and the re-optimized pipeline network. The problem component location information includes the determined coordinates of the pipeline leakage point, the location of the structural deformation, and the calibration information of the key hidden dangers. The shortest path information includes the arrangement order of the path nodes, the optimal distance between nodes, and the distribution information of the structural load. The intelligent hanging results include the automatically matched associated components, the positions in the BIM model, and the association descriptions between components.

[0064] See also Figure 2 and Figure 3 , the graph structure building modules include:

[0065] The node creation submodule is based on the component data of the BIM model, analyzes the geometric information and physical properties of the component, converts it into the basic nodes of the graph structure, and defines and identifies the attributes of the node. The process of establishing the basic node of the component is as follows;

[0066] Analyze the geometric information and physical properties of each component. The length of the component obtained by analysis ,width ,high , and physical properties such as density Used for node attribute definition. These dimensional data are converted to the relative size of the nodes in the graph through a standardized formula to ensure that the proportions of each node are accurate. The formula is as follows: , Indicates the relative standardized size of a component. , ,and It is the maximum value in each dimension and is used to ensure that the size ratios of different components are consistent.

[0067] The spatial mapping submodule analyzes the relative position and connection relationship of components in three-dimensional space based on the basic nodes of components, connects the nodes into edges of the graph structure, and adjusts the spatial position and connection relationship. The process of obtaining the spatial structure of components is as follows;

[0068] Based on the basic information of the nodes, the relative position and connection relationship of the components in the three-dimensional space are analyzed. By calculating the Euclidean distance between two nodes Implementation, determine how to connect these nodes in the graph. The distance calculation formula is: , represents the spatial distance between nodes, and is the coordinate of the node in space. Distance is the basis of edges in the graph and is used to build physical connections between nodes.

[0069] The topological integration submodule performs topological integration of pipelines and supporting structures in water conservancy projects based on the spatial structure of components. By integrating the parameter information and node connection relationship of subprojects, the hierarchy and relevance of the topological structure are optimized, and the process of generating a graph structure model is as follows;

[0070] By integrating the existing node connection information, the topological structure of pipelines and supporting structures in water conservancy projects is optimized. The weighted graph algorithm used takes into account the distance and physical properties (such as density) between nodes to calculate the weight of the connection. The weight calculation formula is: , represents the weight of the connection, and and It is a coefficient adjusted according to system requirements or design parameters to control the impact of distance and node density. These coefficients help optimize connection priority and overall structural layout, generating a more structured graph model.

[0071] See also Figure 2 and Figure 4 , the component relationship analysis module includes:

[0072] The function evaluation submodule is based on the graph structure model, evaluates the functional role and interdependence of components in the overall structure, identifies the relationship between key functional nodes and secondary nodes, and obtains the function relationship data in the following process;

[0073] By constructing a feature impact matrix , expressing key functional nodes With secondary nodes The specific calculation formula of this matrix is ​​as follows: , Representation Node For Node The functional influence of It is a slave node To Node The number of paths, is the maximum number of paths between any two nodes in the graph. This method helps identify and quantify the functional relationships between nodes, thereby obtaining functional relationship data.

[0074] The stress distribution analysis submodule analyzes the stress transfer and load distribution of components under working conditions based on functional relationship data, identifies core stress areas and stress nodes, and obtains stress distribution information in the following process:

[0075] Based on the above functional relationship data, the stress transfer and load distribution of the components under working conditions are further analyzed. The transfer between the core stress area and the nodes is calculated by the following formula: , Is a node The stress value, Representation and Node The stress values ​​of other directly connected nodes, and is the aforementioned functional influence matrix, which is used to describe the stress transfer efficiency between nodes. This formula describes the dynamic distribution of stress between nodes through cumulative calculation, which helps to identify the core stress area and stress nodes.

[0076] The component screening submodule, based on stress distribution information, screens the components that play a key role in the water flow path and the supporting structure, identifies the nodes that affect the stability of the overall supporting structure, and generates the associated component group information in the following process:

[0077] Based on the stress distribution information, select the components that play a key role in the water flow path and supporting structure. The score is obtained by comprehensively considering the function and stress influence of the node, and the calculation formula is as follows: , Representation Node The critical rating of is an adjustment factor to balance the effects of stress and function. is the stress value at the node, is the functional importance of the node. The value of is adjusted based on system design or empirical estimation to ensure that the scoring system reflects both stress and functional importance.

[0078] See also Figure 2 and Figure 5 , the node optimization module includes:

[0079] The redundant node deletion submodule screens and verifies redundant nodes in the graph structure based on the associated component group information, and deletes duplicate nodes by analyzing the connection and functional duplication between nodes. The process of obtaining a simplified node structure is as follows;

[0080] Screen and verify redundant nodes in the graph structure based on the associated component group information. By analyzing the connection strength between nodes and functional similarity , determine the redundancy of the node. Define the node redundancy evaluation index As follows, it is used to evaluate the possibility of node deletion: , Representation Node Redundancy index of Is a node With Node The strength of the connection between Is a node and This formula determines the redundancy of nodes by accumulating the connection strength and functional similarity between nodes, and thus decides whether to delete them to simplify the graph structure.

[0081] Based on the simplified node structure, the functional unit merging submodule uses a hierarchical clustering algorithm to identify the relationship between structural units and nodes with similar functions, merge nodes and make unified adjustments to node attributes. The process of generating the merged node structure is as follows;

[0082] A hierarchical clustering algorithm is used to identify the relationship between structural units and nodes with similar functions based on the simplified node structure, and the nodes are merged.

[0083] The hierarchical clustering algorithm follows the formula:

[0084]

[0085] Calculate the similarity index between nodes ;

[0086] in, Is a node and nodes The similarity index between them is used to measure the functional proximity of two nodes. The higher the result, the more similar the functions of the two nodes are. represents an exponential function, which is used to convert the measure of similarity into a non-negative number for easy processing and interpretation. Is a node and nodes The functional difference measure between nodes is usually calculated based on the functional attributes of the nodes, such as the Euclidean distance. Is a weight factor used to adjust the integration of components The impact of the total similarity measurement is obtained through data analysis or expert experience according to the actual situation. It is a node based on lightweight and component integration. and The integration metric between them is an indicator to measure the integration of two nodes in the entire water conservancy project BIM model. is a scaling parameter that adjusts the effect of distance and ensures that the dynamic range of the similarity index is appropriate. It is usually adjusted based on the distribution of the data or through experience.

[0087] The calculation process is as follows:

[0088] For the formula:

[0089] Representation Node and Relative differences in component integration. is a coefficient used to adjust The weight of influence in the overall similarity index.

[0090] Assume that each node has a set of properties related to the integration of the component, including but not limited to weight, volume, number of connection points, etc. A simple metric can be used, such as the weighted difference of these properties between two nodes to calculate :

[0091]

[0092] in, and The nodes are and In Properties The value on is the weight of the attribute.

[0093] Similarity metrics merged into hierarchical clustering

[0094] By Incorporating similarity metrics into the calculation allows for a more comprehensive assessment of the similarity between nodes, not just based on their functional attributes, but also on their consistency or difference in terms of engineering component integration. This helps to cluster nodes more accurately, especially in engineering projects where lightweighting and integration are particularly important.

[0095] Putting all the pieces together, we get the final formula:

[0096] With this improvement, the formula not only takes into account the functional differences of the nodes, but also integrates their similarities or differences in structure and integration, so that the clustering results are more in line with actual engineering needs. The ultimate goal of this approach is to optimize engineering design, improve the efficiency and practicality of the model, and reduce unnecessary costs and complexity.

[0097] The structural layout adjustment submodule adjusts the support structure layout and pipeline network based on the merged node structure, reconfigures the node connection sequence and layout structure, and generates the optimized component diagram in the following process:

[0098] Based on the merged node structure, the support structure layout and pipeline network are adjusted. Use the layout optimization index To measure the efficiency of the reconfigured node connection order and layout structure: , It is the optimization index of the overall structural layout; Is a node and The connection weight between them; Is a node and This indicator is used to optimize the spatial configuration and connection efficiency of nodes, ensuring that the adjusted structural layout is more reasonable and effective.

[0099] See also Figure 2 and Figure 6 ,The problem location module includes:

[0100] The design drawing comparison submodule analyzes the design drawings of key components in the water conservancy project based on the optimized component drawings, compares the component layout in the design drawings with the structure in the BIM model, automatically identifies the differences and potential problems between the design structure and the current structure, and marks and records the differences. The process of obtaining the drawing comparison results is as follows;

[0101] The comparison between the design drawings of key components and the BIM model structure is performed by calculating the difference vector. Assume that the position vector of each key component in the design drawing is , the position vector of the corresponding component in the BIM model is , the difference vector Calculated by the following formula: , Represents the modulus of a vector, i.e. the straight-line distance between two points, and is used to calculate the direct spatial difference between the position in the design drawing and the position in the BIM model. It is a component in the design drawing The position vector of It is a component in the BIM model The actual position vector, is the position vector and The difference vector between .

[0102] Based on the drawing comparison results, the component mapping submodule corresponds and matches the key nodes in the design drawings with the positions in the BIM model, calibrates the spatial positions of the components in the BIM model, and generates the component mapping information in the following process:

[0103] Using the drawing comparison results, the key nodes in the design drawings are matched with the positions in the BIM model. The accuracy of the mapping is calculated by the difference vector The modulus length and threshold setting If , then the match is considered successful, otherwise the match fails. Quantification: , is a scaling parameter that adjusts the mapping sensitivity, which is used to control the sensitivity of the mapping accuracy to the matching results. is the threshold set to determine the difference vector Is it within the acceptable range? is a scaling parameter used to adjust the effect of distance differences during the mapping process. It is the mapping efficiency, which quantifies the accuracy with which the locations in the design drawings match the locations in the BIM model.

[0104] The hidden danger calibration submodule identifies and calibrates the safety hazards of pipeline leakage and structural deformation based on the component mapping information. By combining the field data with the design comparison results, the hidden danger location and type are determined, and the process of generating the location information of the problem component is as follows;

[0105] Based on the component mapping information, the hidden danger identification submodule identifies and identifies safety hazards. Based on mapping efficiency The assessed component safety risk value is calculated as follows: , is the risk weight, which is used to adjust the impact of mapping efficiency on security risk assessment. is the risk weight parameter used to map the efficiency Adjust the security risk assessment results. Based on mapping efficiency The component safety risk value is used to evaluate the potential safety hazards of each component.

[0106] See also Figure 2 and Figure 7 , the path calculation module includes:

[0107] The path assessment submodule analyzes the connection mode between components and the potential feasibility of the path based on the location information of the problem components, selects the path options that meet the requirements, and performs initial path assessment and marking. The process of obtaining the initial path information is as follows;

[0108] Based on the position information of the problem components, the potential feasibility of the connection mode and path between components is analyzed. Assume that the position vector of each component is , and the position vector of the component connected to it is The initial feasibility of the path Calculated by: , is a scaling parameter that adjusts distance sensitivity and is used to control the impact of distance on path feasibility. It is The position vector of the component is with Position vectors of directly connected components, is a scaling parameter that adjusts the effect of distance on path feasibility.

[0109] The spatial distance calculation submodule measures the spatial distance between component nodes based on the initial path information, calculates the total length of each path, and sorts and screens the path distances. The process of generating the spatial distance results is as follows;

[0110] Based on the initial path information, this submodule determines the spatial distance between component nodes and calculates the total length of each path. Let the sum of the distances of the nodes on the path be : , Represents the total number of components on the path. Used to sort and filter the path distance to obtain the spatial distance result. is the total number of components on the path, It is The total length of the paths.

[0111] The load parameter integration submodule analyzes the load parameters of the path based on the spatial distance results, referring to the structural load, construction convenience and maintenance requirements, and generates the shortest path information in the following process:

[0112] Based on the spatial distance results, this submodule analyzes the load parameters of the path with reference to the structural load, construction convenience and maintenance requirements. The calculation of is as follows: , is the weight parameter of the path length, It is The maintenance difficulty coefficient of the component, is the structural load value of the component, is the weight parameter of the path length, It is The maintenance difficulty coefficient of the component, It is Structural load value of the component.

[0113] See also Figure 2 and Figure 8 , the component mounting module includes:

[0114] The historical record analysis submodule extracts and analyzes historical maintenance records based on the shortest path information and uses the Bayesian reasoning method. It collects historical maintenance data and component information associated with the problem type and identifies component characteristics that match the current problem. The process of obtaining historical analysis results is as follows:

[0115] Historical maintenance records are extracted and analyzed based on the shortest path information through Bayesian reasoning.

[0116] Bayesian inference method follows the formula:

[0117]

[0118] The posterior probability of a component under a given problem type ;

[0119] in, It is in the component Existence and consideration of certain structural simplifications and resource optimization Type of problem encountered The conditional probability of and Respectively represent the new parameters of optimized structural simplification and resource allocation, Considering structural simplification Under the condition of The probability of occurrence indicates the influence of structural simplification on component selection. It is a simplified structure Probability of occurrence, which characterizes how often a specific simplification measure is applied in a project, It is resource optimization The probability of implementing specific resource optimization measures in the project, Is the type of question The total probability of occurrence is the statistical probability of the frequency of occurrence of the problem type in the entire analysis.

[0120] The calculation process is as follows:

[0121] Collect relevant historical maintenance data, structural simplification measures and resource optimization records.

[0122] Using historical data to estimate structural simplification and resource optimization Probability and This can be done by statistically analyzing how often these measures have been applied in historical projects.

[0123] estimate , that is, in a specific component When there is a problem, consider the type of problem encountered when simplifying the structure and optimizing resources This usually involves machine learning models or statistical analysis, where the models are trained and adjusted based on the corresponding event frequencies in historical data.

[0124] Use the Bayesian formula to combine the collected probabilities for calculation:

[0125] here Indicates that the structure is simplified Under the condition of The probability of occurrence may need to be based on Evaluate the impact of component utilization, e.g. by analyzing Resulting in changes in component selection.

[0126] Combining all the estimated probability parameters, the final posterior probability is calculated by plugging the actual values ​​into the Bayesian formula .

[0127] Assume that historical data shows that when simplifying the structure and resource optimization In the project, a component When encountering problem types The probability of is higher than that of projects that have not made these optimizations. In this case, will be adjusted to a higher value based on these data. and Estimates can be made based on how often these measures are implemented.

[0128] The resulting posterior probability It can help project managers more accurately identify components that may need attention under specific optimization measures. This can not only improve the pertinence of maintenance and repair, but also optimize resource allocation and risk management, and ultimately improve the overall execution efficiency and success rate of the project.

[0129] The component matching submodule compares the problem type with the functional characteristics of the associated components based on the historical analysis results, selects key components, and generates component matching information in the following process:

[0130] Based on the information obtained from the historical record analysis submodule , this submodule further analyzes and matches the functional characteristics of the components. Each component There is a feature rating , taking into account factors such as its physical properties, historical maintenance frequency, etc. Comprehensive matching score of components Calculated by the following formula: , and is a weight parameter that adjusts the historical probability and the importance of functional characteristics. The components with the highest scores are selected based on the values ​​of and are used as key components for subsequent operations.

[0131] The BIM positioning submodule marks the matched components in the BIM model based on the component matching information, and the process of generating the intelligent attachment result is as follows;

[0132] After confirming the key components, this module will mark these components in the BIM model for intelligent connection. The connection process is based on the comprehensive score. Reaching or exceeding a predetermined threshold The BIM model not only shows the location of components, but also provides intuitive information about their importance and potential maintenance needs.

[0133] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. The water conservancy project BIM model optimization processing system based on lightweight and component integration is characterized by: The system comprises: The graph structure construction module maps the geometric shape and spatial relationship of the components into nodes and edges based on the component data of the BIM model, integrates the parameter information of the pipeline and supporting structure sub-projects in the water conservancy project, establishes the topological relationship between the nodes, and generates a graph structure model; The component relationship analysis module analyzes the stress distribution and water flow path of the pipeline connection and the supporting structure based on the graph structure model, selects the key component groups, and obtains the associated component group information; The node optimization module deletes redundant connection nodes and merges structural units with similar functions based on the associated component group information, adjusts the layout of the supporting structure and optimizes the fluidity of the pipeline network, and generates an optimized component diagram; The problem location module is based on the optimized component diagram, combined with the design drawings of key components in the water conservancy project and the BIM model, to calibrate the locations of pipeline leakage and structural deformation safety hazards and generate problem component location information; The path calculation module calculates the shortest path between the pipeline and the supporting structure based on the location information of the problem component, the spatial distance between the components, and the structural load parameters, evaluates the construction feasibility and maintenance convenience of the path, and generates the shortest path information; The component attachment module analyzes the historical maintenance records and the functional characteristics of the components according to the shortest path information, recommends other components associated with the problem type, locates the matching components on the BIM model, and generates intelligent attachment results.

2. The water conservancy project BIM model optimization processing system based on lightweight and component integration according to claim 1 is characterized by: The graph structure model includes the geometric morphology mapping of the node topological structure, the spatial relationship connection between components, and the integrated pipeline and support structure parameter information. The associated component group information includes the selected key component nodes, the association relationship based on stress distribution, and the connection information of the water flow path. The optimized component diagram includes the simplified node layout, the merged structural units, and the re-optimized pipeline network. The problem component location information includes the determined pipeline leakage point coordinates, the location of the structural deformation, and the calibration information of the key hidden dangers. The shortest path information includes the arrangement order of the path nodes, the optimal distance between the nodes, and the distribution information of the structural load. The intelligent hanging result includes the automatically matched associated components, the position in the BIM model, and the association description between the components.

3. The water conservancy project BIM model optimization processing system based on lightweight and component integration according to claim 1 is characterized in that: The graph structure building module includes: The node creation submodule analyzes the geometric information and physical properties of the components based on the component data of the BIM model, converts them into basic nodes of the graph structure, and defines and identifies the attributes of the nodes to establish the basic nodes of the components; The spatial mapping submodule analyzes the relative position and connection relationship of the component in the three-dimensional space based on the component basic nodes, connects the nodes into edges of the graph structure, and adjusts the spatial position and connection relationship to obtain the component spatial structure; The topological integration submodule performs topological integration of pipelines and supporting structures in water conservancy projects based on the component spatial structure, optimizes the hierarchy and correlation of the topological structure by integrating the parameter information and node connection relationship of the subprojects, and generates a graph structure model.

4. The water conservancy project BIM model optimization processing system based on lightweight and component integration according to claim 1 is characterized in that: The component relationship analysis module includes: The function evaluation submodule evaluates the functional role and interdependence of the components in the overall structure based on the graph structure model, identifies the relationship between key functional nodes and secondary nodes, and obtains functional relationship data; The stress distribution analysis submodule analyzes the stress transfer and load distribution of the component under working condition based on the functional relationship data, identifies the core stress area and stress nodes, and obtains stress distribution information; Based on the stress distribution information, the component screening submodule screens components that play a key role in the water flow path and the supporting structure, identifies nodes that affect the stability of the overall supporting structure, and generates associated component group information.

5. The water conservancy project BIM model optimization processing system based on lightweight and component integration according to claim 1 is characterized in that: The node optimization module includes: The redundant node deletion submodule screens and verifies redundant nodes in the graph structure based on the associated component group information, deletes duplicate nodes by analyzing the connection and functional duplication between nodes, and obtains a simplified node structure; The functional unit merging submodule identifies the association between structural units and nodes with similar functions based on the simplified node structure through a hierarchical clustering algorithm, merges the nodes and uniformly adjusts the node attributes to generate a merged node structure; The structural layout adjustment submodule adjusts the support structure layout and the pipeline network based on the merged node structure, reconfigures the node connection sequence and layout structure, and generates an optimized component diagram.

6. The water conservancy project BIM model optimization processing system based on lightweight and component integration according to claim 5 is characterized in that: The hierarchical clustering algorithm follows the formula: Calculate the similarity index between nodes ; in, represents the exponential function, which is used to convert the similarity measure into a non-negative number. Is a node and nodes The functional difference measure between Is a weight factor used to adjust the integration of components The impact on the overall similarity measure is obtained through data analysis or expert experience according to the current situation. It is a node based on lightweight and component integration. and The integration measure between is a scaling parameter that adjusts the effect of distance, either based on the distribution of the data or empirically.

7. The water conservancy project BIM model optimization processing system based on lightweight and component integration according to claim 1 is characterized by: The problem locating module includes: The design drawing comparison submodule analyzes the design drawings of key components in the water conservancy project based on the optimized component drawings, compares the component layout in the design drawings with the structure in the BIM model, automatically identifies the differences and potential problems between the design structure and the current structure, and marks and records the differences to obtain the drawing comparison results; The component mapping submodule corresponds and matches the key nodes in the design drawings with the positions in the BIM model based on the drawing comparison results, calibrates the spatial positions of the components in the BIM model, and generates component mapping information; The hidden danger calibration submodule identifies and calibrates the safety hidden dangers of pipeline leakage and structural deformation based on the component mapping information, determines the location and type of hidden dangers by combining the field data with the design comparison results, and generates the location information of the problem components.

8. The water conservancy project BIM model optimization processing system based on lightweight and component integration according to claim 1 is characterized by: The path calculation module includes: The path evaluation submodule analyzes the connection mode between components and the potential feasibility of the path based on the location information of the problem components, selects the path options that meet the requirements, and performs initial path evaluation and marking to obtain initial path information; The spatial distance calculation submodule measures the spatial distance between component nodes based on the initial path information, calculates the total length of each path, and sorts and screens the path distances to generate a spatial distance result; The load parameter integration submodule analyzes the load parameters of the path based on the spatial distance results and refers to the structural load, construction convenience and maintenance requirements to generate the shortest path information.

9. The water conservancy project BIM model optimization processing system based on lightweight and component integration according to claim 1 is characterized in that: The component mounting module comprises: The historical record analysis submodule extracts and analyzes historical maintenance records based on the shortest path information and uses the Bayesian reasoning method. By collecting historical maintenance data and component information associated with the problem type, it identifies component characteristics that match the current problem and obtains historical analysis results. The component matching submodule compares the problem type with the functional characteristics of the associated components based on the historical analysis results, selects key components, and generates component matching information; The BIM positioning submodule marks the matched components in the BIM model based on the component matching information and generates intelligent mounting results.

10. The water conservancy project BIM model optimization processing system based on lightweight and component integration according to claim 9 is characterized in that: The Bayesian inference method is according to the formula: The posterior probability of a component under a given problem type ; in, It is in the component Simplified structure and resource optimization Type of problem encountered The conditional probability of and Respectively represent the new parameters of optimized structural simplification and resource allocation, In structural simplification Under the condition of The probability of occurrence, It is a simplified structure The probability of occurrence, It is resource optimization The probability of Is the type of question The total probability of occurrence.

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