A method and system for mechanical and electrical pipeline conflict detection and adjustment based on a BIM model

Abstract

The application provides a kind of mechanical and electrical pipeline conflict detection and adjustment method and system based on BIM model, belongs to the field of mechanical and electrical installation.The technical scheme is: analyzing BIM model to generate component geometric parameters, generate mechanical and electrical pipeline conflict data;According to the mechanical and electrical pipeline conflict data, the conflict type is automatically classified, and the mechanical and electrical pipeline conflict sorting data is calculated;According to the mechanical and electrical pipeline conflict type and the mechanical and electrical pipeline conflict sorting data, the knowledge rule engine is called, and the conflict adjustment strategy is matched;Perform pipeline position adjustment action, update BIM model data synchronously;Record the conflict processing result after adjustment to case base, and update the strategy of knowledge rule engine based on case base data.The beneficial effects of the application are: by constructing the whole process mechanism of conflict detection and adjustment based on BIM model, the automatic and intelligent processing process from identification to adjustment of mechanical and electrical pipeline conflict is realized, the frequency of manual intervention is effectively reduced, and the constructability and collaboration efficiency of BIM model are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of mechanical and electrical installation, and in particular to a mechanical and electrical pipeline conflict detection and adjustment method and system based on a BIM model. BACKGROUND

[0002] With the wide application of building information modeling (BIM) technology in the field of engineering construction, three-dimensional collaborative design based on BIM model has gradually become an important support means for mechanical and electrical design and construction. The BIM model can accurately describe the spatial geometric information, system attributes and installation elevation of the mechanical and electrical pipeline, effectively improving the design quality and construction efficiency. Especially in complex construction projects, the use of BIM technology for spatial coordination and pipeline optimization of mechanical and electrical systems has become an important prerequisite for ensuring the implementability of construction. Therefore, the research on automatic conflict detection and optimization adjustment based on BIM model has gradually become a research hotspot in the field of building informatization and intelligent construction.

[0003] However, the current existing BIM conflict detection technology mainly identifies geometric overlap, lacks quantitative judgment of conflict severity and intelligent generation ability of adjustment strategy. On the one hand, the existing conflict detection method usually stays at the result presentation level, and can only identify whether there is geometric interference or spatial proximity between components, and it is difficult to support comprehensive evaluation of multi-dimensional parameters such as component importance, system combination and adjustment cost, resulting in conflict data redundancy and unclear priority. On the other hand, the conflict adjustment process often relies on manual experience for judgment and operation, lacks strategy driven and self-learning mechanism based on knowledge rules, and cannot realize adaptive migration and continuous optimization of rules in different projects. This leads to the fact that although the mechanical and electrical conflict problems in the BIM model can be identified, they cannot be efficiently handled in a closed loop, which greatly limits the intelligent level of BIM in the aspects of mechanical and electrical deepening design and intelligent adjustment.

[0004] Therefore, there is an urgent need for a complete technical path from conflict detection, type classification, priority scoring, rule matching, automatic execution to knowledge feedback, to realize the intelligent management and dynamic optimization of the whole process of mechanical and electrical pipeline conflict. SUMMARY

[0005] The purpose of the present application is to provide a conflict detection and adjustment whole process mechanism based on BIM model, which realizes the automatic and intelligent processing process of mechanical and electrical pipeline conflict from identification to adjustment. The method can accurately obtain the spatial relationship between components, improve the pertinence of conflict response by combining classification and scoring mechanism, and realize strategy matching and continuous optimization through knowledge rule engine, finally effectively reduce the frequency of manual intervention, and improve the constructability and collaborative efficiency of BIM model.

[0006] The present application is realized by the following measures:

[0007] A mechanical and electrical pipeline conflict detection and adjustment method based on a BIM model, characterized in that it comprises:

[0008] Analyzing a BIM model to generate component geometric parameters, and performing spatial conflict detection between mechanical and electrical pipelines based on the component geometric parameters to generate mechanical and electrical pipeline conflict data;

[0009] According to the mechanical and electrical pipeline conflict data, the conflict types are automatically classified, and the priority scores of each conflict are calculated to generate mechanical and electrical pipeline conflict sorting data;

[0010] According to the mechanical and electrical pipeline conflict type and the mechanical and electrical pipeline conflict sorting data, a knowledge rule engine is called to match predefined rules to generate mechanical and electrical pipeline conflict adjustment strategies;

[0011] According to the recommended adjustment strategy, the pipeline position adjustment action is automatically executed, and the BIM model data is updated synchronously;

[0012] The adjusted conflict processing result is recorded to the case library, and the strategy optimization update of the knowledge rule engine is based on the case library data.

[0013] The specific features of the present application also include:

[0014] Analyzing a BIM model to generate component geometric parameters includes:

[0015] Analyzing mechanical and electrical pipeline component data in the BIM model, and extracting component geometric parameters for spatial analysis contained in the mechanical and electrical pipeline component data;

[0016] Through a data interface with the building information model, a data communication connection is established, a preset analysis module is called to read the mechanical and electrical pipeline component data file, the component data is structurally analyzed according to the system type, component type, size parameter and spatial position information, after the structural analysis is completed, the mechanical and electrical pipeline components that meet the spatial analysis conditions are identified, the spatial three-dimensional coordinates, spatial occupied volume and boundary positioning parameters of the mechanical and electrical pipeline components are extracted, and all the extracted information is summarized and output as component geometric parameters.

[0017] Based on the component geometric parameters, spatial conflict detection between mechanical and electrical pipelines is performed to generate mechanical and electrical pipeline conflict data, which includes:

[0018] inputting the component geometry parameters into the space analysis module, constructing a space occupation area model of each electromechanical pipeline component based on the component geometry parameters, and performing pairwise comparison on all the space occupation area models in the space analysis module to detect whether there is a space overlap relationship or a boundary distance less than a preset safety distance threshold, generating electromechanical pipeline conflict instance data when the conflict determination condition is met, and summarizing all the electromechanical pipeline conflict instance data to generate electromechanical pipeline conflict data after the comparison of all the space occupation area models is completed.

[0019] According to the electromechanical pipeline conflict data, the automatic classification of the conflict type includes:

[0020] inputting the electromechanical pipeline conflict data into the conflict classification module, extracting relevant parameters in the conflict instance data by the conflict classification module, and performing conflict type determination logic, the conflict type determination logic determines according to the preset classification rule based on the space overlap state, the component relative boundary position relationship and the component system type in the electromechanical pipeline conflict instance data, and outputs the automatic classification result of the corresponding electromechanical pipeline conflict type after processing all the conflict instance data.

[0021] And calculating the priority score of each conflict to generate electromechanical pipeline conflict sorting data includes: inputting the automatic classification result of the electromechanical pipeline conflict type into the priority score module, extracting the parameter information related to the conflict instance data by the priority score module, generating the priority score of each conflict instance data according to the preset score calculation logic, and sorting according to the score result after the score is completed, and outputting the electromechanical pipeline conflict sorting data.

[0022] According to the electromechanical pipeline conflict type and the electromechanical pipeline conflict sorting data, the knowledge rule engine is called to match the predefined rule to generate the electromechanical pipeline conflict adjustment strategy, which includes: inputting the electromechanical pipeline conflict type and the electromechanical pipeline conflict sorting data into the knowledge rule engine, performing rule matching operation based on the preset rule library by the knowledge rule engine, finding the predefined adjustment rule corresponding to the conflict type and the priority, and triggering the learning module for strategy reasoning when the matching fails, and finally generating the electromechanical pipeline conflict adjustment strategy corresponding to each conflict instance data.

[0023] According to the recommended adjustment strategy, the pipeline position adjustment action is automatically executed, and the BIM model data is updated synchronously, which includes: calling the strategy execution module to analyze the target component and the adjustment parameter based on the conflict adjustment strategy, completing the component position adjustment, and writing the adjusted position parameter into the BIM model through the data interface to realize the synchronous update of the electromechanical pipeline component data.

[0024] Record the adjusted conflict processing result to the case library, and update the strategy optimization of the knowledge rule engine based on the case library data includes:

[0025] The three-dimensional space coordinate parameters before and after the component position adjustment, component identification information, conflict type, conflict priority score value, adjustment time length and artificial intervention record information are extracted by the data recording module, the data is written into the conflict processing case database, and after the accumulated data in the database reaches a preset number, the strategy learning module in the knowledge rule engine is triggered to analyze and learn the recorded data in the database, the pre-defined adjustment rules are updated based on the statistical results, and the strategy optimization update of the knowledge rule engine is completed.

[0026] The beneficial effects of the present application are: the present application realizes the automatic and intelligent processing process of mechanical and electrical pipeline conflict from identification to adjustment by constructing a conflict detection and adjustment full-process mechanism based on BIM model, the method can accurately obtain the spatial relationship between components, the pertinence of conflict response is improved by combining classification and scoring mechanism, and strategy matching and continuous optimization are realized through the knowledge rule engine, finally the frequency of artificial intervention is effectively reduced, and the constructability and collaboration efficiency of BIM model are improved.

[0027] By analyzing the BIM model component data and extracting geometric parameters, accurate modeling of the spatial relationship of mechanical and electrical pipelines is realized, which lays a data foundation for subsequent conflict identification, and a differentiated processing mechanism is constructed through conflict classification and priority scoring, which significantly improves the efficiency of conflict management; by calling the knowledge rule engine to match the strategy, intelligent adjustment for component types and system combinations is realized; further, by automatically executing the adjustment operation and updating the BIM model, the real-time consistency of design data is ensured; finally, by recording the adjustment behavior to benefit the rule library, dynamic optimization and self-adaptive evolution of the strategy are realized, thereby constructing a closed-loop, intelligent and efficient BIM conflict detection and adjustment system. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 The present application provides a kind of based on BIM model's mechanical and electrical pipeline conflict detection and adjustment method overall flow chart of embodiment. DETAILED DESCRIPTION

[0029] To clearly illustrate the technical features of the present scheme, the present scheme will be described below through specific embodiments.

[0030] Example 1

[0031] Reference Figure 1 ,

[0032] Step 1, analyze BIM model to generate component geometric parameters, and perform spatial conflict detection between mechanical and electrical pipelines based on component geometric parameters to generate mechanical and electrical pipeline conflict data;

[0033] Specifically, it includes: analyzing the mechanical and electrical pipeline component data in the BIM model, and extracting the component geometric parameters for spatial analysis contained in the mechanical and electrical pipeline component data;

[0034] By establishing a data communication connection with the data interface of the building information model, a preset analysis module is called to read the mechanical and electrical pipeline component data file, the component data is structurally analyzed according to the system type, component type, size parameter and spatial position information, after the structural analysis is completed, the mechanical and electrical pipeline components meeting the spatial analysis conditions are identified, the spatial three-dimensional coordinates, spatial occupation volume and boundary positioning parameters of the mechanical and electrical pipeline components are extracted, and all the extracted information is output as component geometric parameters.

[0035] Specifically, by establishing a data communication connection with the data interface of the building information model, a preset analysis module is called to read the mechanical and electrical pipeline component data file, the component data is structurally analyzed according to the system type, component type, size parameter and spatial position information, after the structural analysis is completed, the mechanical and electrical pipeline components meeting the spatial analysis conditions are identified, the spatial three-dimensional coordinates, spatial occupation volume, boundary positioning parameters and system type field of the mechanical and electrical pipeline components are extracted, and all the extracted information is output as component geometric parameters.

[0036] Specifically, first, a data communication connection is established with the data interface of the building information model, the data interface is an application programming interface (API) for accessing BIM model component data, such as Revit API based on Autodesk Revit platform, IFC standard interface or custom Web service interface, the data communication connection is established in the form of plug-in embedding or local program calling, a preset analysis module is called to obtain mechanical and electrical pipeline component related data; the analysis module includes a component identification submodule, an attribute extraction submodule, a field mapping submodule, a format standardization submodule and a data export submodule, which can automatically identify the mechanical and electrical system components from the BIM model file and extract their associated attribute data.

[0037] The analysis step includes: calling the component identification submodule to identify and filter the component data of the mechanical and electrical system in the model, the system type includes but is not limited to: heating and ventilation system (HVAC), water supply and drainage system, electrical system, fire fighting system, etc.; the component type includes air pipe, bridge, spray pipe, distribution box, drainage vertical pipe, etc.; after identification, the system type, component type, component number, size parameter, installation elevation, spatial position and other fields are extracted in turn, and field standardization processing (including unit conversion and semantic mapping) is performed, and stored uniformly in the component attribute data table.

[0038] The system then traverses the component attribute data table and performs a filter according to the following spatial analysis conditions: a. Components marked as not participating in conflict checking (ClashDetection = false); b. Any dimension of the component geometry is less than a set spatial minimum threshold (e.g. 50mm); c. The component type belongs to a non-physical class (e.g. placeholder, marker); d. The component system category is a predefined excluded system; e. The component is set to "skip detection" in user configuration.

[0039] After filtering, the spatial three-dimensional coordinates of the remaining components (representing the position of the component in the BIM global coordinate system), the spatial occupancy volume (calculated based on the component geometry model), the boundary positioning parameters (the minimum and maximum boundary points of the component hexahedral AABB), and the system type field of the component are stored uniformly in the component geometry parameter data table. The following standardization processing is also performed:

[0040] Coordinate system conversion: convert the local coordinate system to the BIM global coordinate system;

[0041] Geometric integrity check: determine whether there are missing fields, illegal dimensions, etc.

[0042] After that, the component geometry parameters are input into the spatial analysis module, and based on the component geometry parameters, the spatial occupancy area models of each mechanical and electrical pipeline component are constructed, and all spatial occupancy area models are compared in the spatial analysis module. The existence of spatial overlap relationship or boundary distance less than the preset safety distance threshold is detected, and when the conflict determination condition is met, the mechanical and electrical pipeline conflict instance data is generated, and after all the spatial occupancy area models are compared, all the mechanical and electrical pipeline conflict instance data is summarized to generate the mechanical and electrical pipeline conflict data.

[0043] Specifically, the system inputs the component geometry parameters into the spatial analysis module. The module uses the AABB (Axis-Aligned Bounding Box) algorithm to construct an envelope box spatial model for each component. After modeling is completed, the system selects components one by one as "current detection components", and performs spatial conflict judgment on all components except itself. The judgment logic includes:

[0044] Spatial overlap determination logic: if the AABB of two components overlaps in X, Y, and Z directions, it is considered to have "geometric overlap conflict";

[0045] Boundary distance determination logic: if the AABBs do not overlap, but the nearest boundary distance is less than the set safety distance threshold (e.g. 50mm), it is considered to constitute a "boundary proximity conflict".

[0046] For each pair of component combinations that have any of the above types of conflicts, the system generates an electromechanical pipeline conflict instance data in real time, the structure of which includes:

[0047] Component unique identifier;

[0048] Three-dimensional coordinates;

[0049] Conflict type (overlap / proximity);

[0050] Conflict area description (such as spatial overlap area volume, boundary minimum distance);

[0051] Intersection angle between component pairs (calculated from the angle between the component axes);

[0052] Spatial relative position relationship (such as up / down, cross / parallel, etc.);

[0053] System type to which it belongs.

[0054] After the system completes all traversals, the conflict instance data is integrated into a structured output to form an electromechanical pipeline conflict dataset. This dataset will serve as the standard input for subsequent conflict classification and priority scoring, ensuring traceability, structural consistency, and business-related integrity of subsequent calculation parameters.

[0055] Step 2, automatically classify the conflict types according to the electromechanical pipeline conflict data, and calculate the priority scores of each conflict to generate electromechanical pipeline conflict sorting data;

[0056] It includes: inputting electromechanical pipeline conflict data into the conflict classification module, extracting relevant parameters from conflict instance data by the conflict classification module, and executing conflict type determination logic. The conflict type determination logic is based on the spatial overlap state, the relative boundary position relationship of the components, and the system type to which the components belong. According to the preset classification rules, the determination operation is performed, and the automatic classification results of the corresponding electromechanical pipeline conflict types are output after all conflict instance data processing is completed.

[0057] Specifically, first, batch input electromechanical pipeline conflict data into the conflict classification module. The conflict classification module is composed of a parameter extraction submodule, a classification rule engine, and a classification result output unit.

[0058] This module calls the parameter extraction submodule to extract the following key parameters from each conflict instance data: spatial overlap area volume , boundary minimum distance , system combination type of conflict component pairs , intersection angle , and spatial relative position relationship (such as whether it is on the same layer, whether there is a height offset, etc.).

[0059] Subsequently, the classification rule engine executes conflict type determination logic based on the built-in rule dictionary table. The rule dictionary table is constructed by integrating engineering specifications, industry experience and statistical modeling of actual projects, and contains various conflict determination conditions and corresponding labels.

[0060] Examples of common rules are as follows:

[0061] like ,and If it belongs to the backbone system, it is classified as "high-risk backbone conflict";

[0062] like ,but and This is then classified as "border adjacency conflict".

[0063] like If the components intersect at different elevation planes, it is a "typical vertical intersection conflict".

[0064] During the classification process, the system compares conflict parameters with preset rules in turn. If a match is found, the corresponding classification label is output; if no match is found, the classification label is entered into the "to be identified" pool for subsequent manual labeling.

[0065] All category labels are ultimately appended to each conflict instance data, and the unified output is "Automatic classification result of electromechanical pipeline conflict type".

[0066] Next, the automatic classification results of the electromechanical pipeline conflict types are input into the priority scoring module. The priority scoring module extracts the parameter information related to the conflict instance data, generates a priority score for each conflict instance data according to the preset scoring calculation logic, and sorts the data according to the scoring results after the scoring is completed, outputting the electromechanical pipeline conflict sorting data.

[0067] Specifically, the system will automatically input the classification results into the priority scoring module;

[0068] This module consists of a scoring parameter extraction unit, a weight configuration engine, a scoring calculation engine, and a sorting output unit.

[0069] The priority scoring module first extracts the following parameters:

[0070] Volume of spatial overlapping region (unit );

[0071] Minimum spacing of boundaries (unit );

[0072] Importance level of the system to which the component belongs The system level mapping table is obtained (e.g., fire protection = 5, electrical = 4, heating and ventilation = 3, water supply and drainage = 2, and weak current = 1).

[0073] Predicted adjustment cost score According to the component size, position accessibility and cross complexity estimation (e.g., the adjustment cost of large-diameter air pipe in the ceiling is significantly higher than that of the ground wiring bridge).

[0074] The scoring calculation engine adopts the following preset logic:

[0075]

[0076] wherein, is a user-configurable weight coefficient (default value: 0.3, 0.25, 0.25, 0.2), indicates normalization processing to avoid bias caused by inconsistent dimensions.

[0077] After completing the priority scoring of all conflict instances, the scoring module sorts the scoring values in descending order, with higher scores indicating higher urgency of processing. The system maps the conflict instances and corresponding scoring results to generate a sorted list, which is output as "mechanical and electrical pipeline conflict sorting data" for subsequent rule engine calls.

[0078] Step 3, according to the mechanical and electrical pipeline conflict type and the mechanical and electrical pipeline conflict sorting data, call the knowledge rule engine to match the predefined rules to generate the mechanical and electrical pipeline conflict adjustment strategy;

[0079] The mechanical and electrical pipeline conflict type and the mechanical and electrical pipeline conflict sorting data are input into the knowledge rule engine, which performs rule matching operations based on the preset rule library, finds the predefined adjustment rules corresponding to the conflict type and priority, and triggers the learning module for strategy reasoning when the matching fails, finally generates the mechanical and electrical pipeline conflict adjustment strategy corresponding to each conflict instance data.

[0080] Specifically, the output "automatic classification result of mechanical and electrical pipeline conflict type" and "mechanical and electrical pipeline conflict sorting data" are input into the knowledge rule engine;

[0081] The knowledge rule engine includes a rule library module, a rule matching execution module, and a learning reasoning module, and its core logic flow is as follows:

[0082] I. Rule matching process The knowledge rule engine first sorts the conflict instance data according to the priority score P in descending order, and selects each conflict instance data as the processing target. For each conflict instance, the system extracts the following parameters in turn:

[0083] - Space overlap volume ;

[0084] - Minimum distance of boundary ;

[0085] - System type pair of components ;

[0086] - Cross angle between component pairs ;

[0087] - Spatial relative position relationship (such as "up / down", "same layer", etc.);

[0088] - System importance level ;

[0089] - Component adjustment cost score ;

[0090] Subsequently, the above parameters are compared with the rule conditions in the rule base at the field level, and the rule matching uses the following mathematical expression:

[0091]

[0092] wherein, represents the score value of the th conflict instance, is its conflict parameter set, is the condition parameter set of the rule , and a successful match outputs the corresponding adjustment strategy.

[0093] II. Preset rule base structure

[0094] The rule base relied on by the knowledge rule engine is generated in advance by project experience, standard specifications, and expert knowledge training, and is stored in the form of a structured dictionary table. Each rule contains fields such as scoring range, conflict type judgment condition, system combination and spatial relationship restriction, corresponding adjustment strategy, etc.

[0095] For example:

[0096] {

[0097] "rule_id": "R_007",

[0098] "type": "boundary adjacent conflict",

[0099] "P_range": [0.7, 0.85],

[0100] "condition": {

[0101] "Vc_max": 10000,

[0102] "dmin_max": 15,

[0103] "theta_range": [80, 100],

[0104] "importance_diff": true

[0105] },

[0106] "strategy": "Perform translational avoidance on the component with the larger boundary spacing".

[0107] }

[0108] The system determines the hit rule based on the score P and the conflict parameter range, and outputs the corresponding strategy in real time;

[0109] To ensure system adaptability and rule selection transparency, the matching relationship between scoring ranges and rules is shown in the table below:

[0110]

[0111] For example, if a conflict instance has a score of P=0.88, its component type is "intersection of duct and main sprinkler pipe", and the angle of intersection is... The boundary spacing is 10mm, which is considered a high-importance combination (ductwork). Spraying The system will prioritize matching high-risk overlapping rules: Judgment condition hit:

[0112]

[0113] Strategy selection: Keep the main sprinkler duct unchanged, and implement bypass or elevation of the air duct. The system will automatically adjust the elevation and generate path suggestions.

[0114] III. Inference Module Triggering Mechanism: If no explicit rule is matched (i.e., RuleMatch(i) = 0), the engine automatically calls the learning inference module. This module constructs a feature similarity network based on conflict-adjustment pairs (Dj, Sj) from historical projects, and calculates the inference weights as follows:

[0115]

[0116] in, Historical Cases With the current conflict The rule-based similarity score is calculated using sim(), which is a Euclidean or cosine similarity function. For the current instance One conflict feature parameter, For parameter weights.

[0117] The similarity threshold is defined as:

[0118]

[0119] That is, when the system determines that the current conflict instance has sufficient structural similarity with the historical case, automatically inherits the adjustment strategy of the historical case and records the reasoning path of this time, for subsequent updating of the rule base.

[0120] Four, strategy result output

[0121] After the knowledge rule engine completes rule matching and strategy generation for all conflict instances, a structured strategy set is uniformly output:

[0122] Each record includes: conflict instance number, matching rule number or reasoning path, strategy content description (which component to adjust, how to adjust), execution priority.

[0123] The final output result will be directly input to the mechanical and electrical pipeline automatic adjustment module to form an executable adjustment suggestion sequence.

[0124] Step 4, automatically execute pipeline position adjustment actions according to the recommended adjustment strategy, and update the BIM model data synchronously;

[0125] Call the strategy execution module to parse the target component and adjustment parameters based on the conflict adjustment strategy, complete the component position adjustment, and write the adjusted position parameters into the BIM model through the data interface to realize the synchronous update of the mechanical and electrical pipeline component data.

[0126] The strategy execution module is the core functional module in the present application that transitions from "rule output" to "physical change". Its main function is to execute specific position adjustment actions on the corresponding conflict components in the BIM model based on the mechanical and electrical pipeline conflict adjustment strategy generated by the knowledge rule engine in step 3, and complete the BIM data synchronous update;

[0127] The strategy execution module first receives the structured strategy set output from the knowledge rule engine, which specifically includes:

[0128] - Conflict instance number (consistent with the component geometric parameter table and conflict data set in step 1);

[0129] - Matching rule number or reasoning path number (from the rule base matching or reasoning module in step 3);

[0130] - Strategy content (such as "move component A" and "lift component B");

[0131] - Adjustment direction vector and adjustment distance scalar ;

[0132] - Execution priority (based on the score value P in step 2 in descending order);

[0133] - Adjustment mode identification (such as "translation", "rotation", "rearrangement", etc.).

[0134] The strategy execution module executes tasks in descending order of priority P value through an internal task scheduler, ensuring that high-risk conflicts with high-risk scores (such as ) are handled first, forming an adjustment task queue.

[0135] BIM component positioning and original parameter extraction: for each task in the queue, the module first calls the data interface consistent with step 1 to locate the target component, extracts the original spatial three-dimensional coordinates , component system type, geometric size, and current installation elevation information, ensuring that all operations are performed in a unified spatial coordinate system, compatible with the AABB space analysis and coordinate conversion logic in step 1.

[0136] Target position calculation and parameter judgment: combined with the adjustment vector and adjustment distance , the module performs the following calculations:

[0137]

[0138] 、 : respectively represent the three-dimensional coordinates of the component before and after adjustment;

[0139] Subsequently, the vector distance function is called to determine whether to trigger the data write-back operation:

[0140]

[0141] If (where is the default tolerance, 1mm), then enter the update phase; otherwise, it is determined that no adjustment is needed. This judgment is linked with the rule accuracy control mechanism in step 3, effectively avoiding false triggering and ensuring that the strategy execution has boundary judgment ability.

[0142] Position update and BIM synchronization: when the target position is determined to be valid, the module updates the to the geometric parameter field of the corresponding component in the BIM model through the interface write-back, completes the model data synchronization, and the updated data will be stored in the component geometric parameter table (consistent with the format in step 1), ensuring the integrity of subsequent review, backtracking, and re-adjustment.

[0143] Through the above process, the policy execution module realizes the full-process mapping from the rule layer to the component layer, successfully maps the extraction results of the component geometric parameters in step 1, the quantitative ranking of the priority scoring model in step 2, and the structured output of the rule and policy reasoning mechanism in step 3 to the measurable, traceable and executable component adjustment behavior in step 4, builds a complete and closed-loop conflict processing link, and embodies the innovation and engineering adaptability of the application in the direction of BIM intelligent adjustment.

[0144] Step 5, record the adjusted conflict processing results to the case library, and update the strategy of the knowledge rule engine based on the case library data;

[0145] Through the data recording module, the three-dimensional space coordinate parameters before and after the component position adjustment, the component identification information, the conflict type, the conflict priority score value, the adjustment time and the manual intervention record information are extracted, and the data is written into the conflict processing case database. When the accumulated data in the database reaches a preset number, the strategy learning module in the knowledge rule engine is triggered to analyze and learn the recorded data in the database, and the pre-defined adjustment rules are updated based on the statistical results to complete the strategy optimization update of the knowledge rule engine.

[0146] Specifically, first, the component position adjustment recording mechanism introduced in step 5 extracts three-dimensional coordinate parameters before and after the component position adjustment , component unique identification, conflict type label (such as "geometric overlap conflict", "boundary proximity conflict", etc.), conflict priority score value P, adjustment time and manual intervention, etc. through the data recording module, and writes these data into the conflict processing case database to provide detailed and structured training samples for subsequent rule optimization;

[0147] Secondly, this step clearly sets the data-driven trigger mechanism: when the number of valid conflict adjustment cases recorded in the database exceeds a preset threshold (such as 100), the system automatically calls the strategy learning module in the knowledge rule engine to enter the case-based rule reconstruction phase;

[0148] The strategy learning module takes the mapping relationship between the conflict feature parameter set (such as ) and the adjustment result as the analysis core combined with the typical feature vector-result pair mode in machine learning to train new adjustment rules or modify the applicable boundaries and trigger conditions of the original rules;

[0149] The optimization update mechanism has the following outstanding advantages in the inventive concept: on the one hand, it solves the core defect of traditional rule-based BIM conflict processing systems that "rules are static and not updated with the environment", and improves the adaptability of the system to diversified engineering scenarios;

[0150] On the other hand, by retaining the artificial intervention information field, it can be identified which conflict types or scoring intervals are difficult to fully automatically execute the strategy, thereby making fine adjustments to the "automatic / semi-automatic" boundary strategy in rule design.

[0151] In the application effect level, this step can significantly improve the coverage and accuracy of the rule base in the knowledge rule engine, especially in the context of new building structure, complex mechanical and electrical system intersection or frequent change of construction optimization, by continuously introducing actual feedback, avoiding mismatch problems in strategy execution, and building a BIM conflict processing intelligent system driven by data optimization.

[0152] Embodiment 2

[0153] A BIM model-based mechanical and electrical pipeline conflict detection and adjustment method system, characterized in that it comprises:

[0154] The component analysis module: analyze the BIM model to generate component geometric parameters, and perform spatial conflict detection between mechanical and electrical pipelines based on the component geometric parameters to generate mechanical and electrical pipeline conflict data;

[0155] The conflict classification module: automatically classifies the conflict types according to the mechanical and electrical pipeline conflict data, and calculates the priority score of each conflict to generate mechanical and electrical pipeline conflict sorting data;

[0156] The adjustment strategy module: calls the knowledge rule engine according to the mechanical and electrical pipeline conflict type and the mechanical and electrical pipeline conflict sorting data, matches the predefined rules to generate mechanical and electrical pipeline conflict adjustment strategies;

[0157] The action execution module: automatically executes the pipeline position adjustment action according to the recommended adjustment strategy, and synchronously updates the BIM model data;

[0158] The rule updating module: records the adjusted conflict processing results to the case library, and optimizes and updates the knowledge rule engine strategy based on the case library data.

[0159] The technical features not described in the application can be realized by or using the prior art, which will not be repeated here. Of course, the above description is not a limitation of the application, and the application is not limited to the above examples. Changes, modifications, additions or replacements made by ordinary skilled in the art within the scope of the application should also be within the protection scope of the application.

Claims

1. A method for mechanical and electrical pipeline conflict detection and adjustment based on a BIM model, characterized in that, The method comprises the following steps: Resolving BIM model to generate component geometric parameters, performing spatial conflict detection between mechanical and electrical pipelines based on component geometric parameters to generate mechanical and electrical pipeline conflict data; According to the mechanical and electrical pipeline conflict data, the conflict type is automatically classified, and the priority score of each conflict is calculated to generate mechanical and electrical pipeline conflict sorting data; According to the mechanical and electrical pipeline conflict type and the mechanical and electrical pipeline conflict sorting data, the knowledge rule engine is called, the pre-defined rule is matched, and the mechanical and electrical pipeline conflict adjustment strategy is generated; According to the recommended adjustment strategy, the pipeline position adjustment action is automatically executed, and the BIM model data is updated synchronously; The adjusted conflict processing result is recorded to the case library, and the strategy optimization update of the knowledge rule engine is carried out based on the case library data.

2. The BIM model-based electromechanical pipeline conflict detection and adjustment method according to claim 1, characterized in that, Resolving BIM model to generate component geometric parameters comprises: Resolving the mechanical and electrical pipeline component data in the BIM model, extracting the component geometric parameters contained in the mechanical and electrical pipeline component data for spatial analysis; Through the data interface of the building information model, the data communication connection is established, the pre-set analysis module is called to read the mechanical and electrical pipeline component data file, the component data is structurally analyzed according to the system type, component type, size parameter and spatial position information, after the structural analysis is completed, the mechanical and electrical pipeline components meeting the spatial analysis conditions are identified, the spatial three-dimensional coordinates, spatial occupation volume and boundary positioning parameters of the mechanical and electrical pipeline components are extracted, and all the extracted information is output as component geometric parameters.

3. The BIM model-based electromechanical pipeline conflict detection and adjustment method according to claim 2, characterized in that, Based on the component geometric parameters, the spatial conflict detection between mechanical and electrical pipelines is carried out to generate mechanical and electrical pipeline conflict data, which comprises: The component geometric parameters are input into the spatial analysis module, the spatial occupation area model of each mechanical and electrical pipeline component is constructed based on the component geometric parameters, and all the spatial occupation area models are compared in the spatial analysis module, whether there is a spatial overlap relationship or the boundary distance is less than the pre-set safety distance threshold is detected, when the conflict judgment condition is met, the mechanical and electrical pipeline conflict instance data is generated, and after the comparison of all the spatial occupation area models is completed, all the mechanical and electrical pipeline conflict instance data is summarized to generate the mechanical and electrical pipeline conflict data.

4. The BIM model-based electromechanical pipeline conflict detection and adjustment method according to claim 3, characterized in that, According to the mechanical and electrical pipeline conflict data, the conflict type is automatically classified, which comprises: The mechanical and electrical pipeline conflict data is input into the conflict classification module, the related parameters in the conflict instance data are extracted by the conflict classification module, and the conflict type judgment logic is executed, the conflict type judgment logic is based on the spatial overlap state, the component relative boundary position relationship and the component system type in the mechanical and electrical pipeline conflict instance data, the judgment operation is executed according to the pre-set classification rule, and the automatic classification result of the mechanical and electrical pipeline conflict type is output after the processing of all the conflict instance data is completed.

5. The BIM model-based electromechanical pipeline conflict detection and adjustment method according to claim 4, characterized in that, And calculate the priority score of each conflict to generate mechanical and electrical pipeline conflict sorting data, which comprises: input the automatic classification result of the mechanical and electrical pipeline conflict type into the priority score module, extract the parameter information related to the conflict instance data by the priority score module, generate the priority score of each conflict instance data according to the pre-set score calculation logic, and sort according to the score result after the score is completed, output the mechanical and electrical pipeline conflict sorting data.

6. The BIM model-based electromechanical pipeline conflict detection and adjustment method according to claim 5, characterized in that, The knowledge rule engine is called according to the mechanical and electrical pipeline conflict type and the mechanical and electrical pipeline conflict sorting data, a predefined rule is matched to generate a mechanical and electrical pipeline conflict adjustment strategy, including: inputting the mechanical and electrical pipeline conflict type and the mechanical and electrical pipeline conflict sorting data into the knowledge rule engine, performing a rule matching operation based on a preset rule library by the knowledge rule engine, finding a predefined adjustment rule corresponding to the conflict type and the priority, and triggering a learning module to perform strategy reasoning when the matching fails, and finally generating a mechanical and electrical pipeline conflict adjustment strategy corresponding to each conflict instance data.

7. The BIM model-based electromechanical pipeline conflict detection and adjustment method according to claim 6, characterized in that, The pipeline position adjustment action is automatically executed according to the recommended adjustment strategy, and the BIM model data is synchronously updated, including: calling the strategy execution module to analyze the target component and the adjustment parameter based on the conflict adjustment strategy, completing the component position adjustment, and writing the adjusted position parameter into the BIM model through the data interface to realize the synchronous update of the mechanical and electrical pipeline component data.

8. The BIM model-based electromechanical pipeline conflict detection and adjustment method according to claim 7, characterized in that, The adjusted conflict processing result is recorded to the case library, and the strategy optimization update of the knowledge rule engine is performed based on the case library data, including: The three-dimensional space coordinate parameters before and after the component position adjustment, the component identification information, the conflict type, the conflict priority score value, the adjustment time length and the artificial intervention record information are extracted through the data recording module, the data is written into the conflict processing case database, and when the accumulated data in the database reaches a preset number, the strategy learning module in the knowledge rule engine is triggered to analyze and learn the recorded data in the database, the predefined adjustment rule is updated based on the statistical result, and the strategy optimization update of the knowledge rule engine is completed.

9. A system for BIM model based mechanical and electrical piping conflict detection and adjustment method employing the method of any one of claims 1-8, wherein, Including: The component analysis module: analyzing the BIM model to generate component geometric parameters, and performing spatial conflict detection between mechanical and electrical pipelines based on the component geometric parameters to generate mechanical and electrical pipeline conflict data; The conflict classification module: automatically classifying the conflict type according to the mechanical and electrical pipeline conflict data, and calculating the priority score of each conflict to generate mechanical and electrical pipeline conflict sorting data; The adjustment strategy module: calling the knowledge rule engine according to the mechanical and electrical pipeline conflict type and the mechanical and electrical pipeline conflict sorting data, matching the predefined rule to generate the mechanical and electrical pipeline conflict adjustment strategy; The action execution module: automatically executing the pipeline position adjustment action according to the recommended adjustment strategy, and synchronously updating the BIM model data; The rule update module: recording the adjusted conflict processing result to the case library, and performing the strategy optimization update of the knowledge rule engine based on the case library data.

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