Conflict detection method and device for multi-person operation, storage medium and electronic equipment

Abstract

The application provides a multi-person operation conflict detection method and device, a storage medium and an electronic device, and relates to the field of computer-aided design. The electronic device receives a synchronization request sent by a client; the synchronization request comprises version information of a local model and modification information of the local model; if the versions of the local model and a cloud model are inconsistent, it is determined whether the modification information causes multiple modification conflicts for the same target component; if yes, the conflict degree of the implicit conflicts between the multiple modifications is evaluated. In this way, when it is detected that the versions of the local model and the cloud model are inconsistent, the formal comparison does not stop, but further analysis is performed on whether the modification information causes multiple modification conflicts for the same target component, and the conflict degree of the implicit conflicts therebetween is evaluated, so that effective detection of cross-dimension association implicit conflicts is realized.

Description

Technical Field

[0001] This application relates to the field of computer-aided design, and more specifically, to a conflict detection method, apparatus, storage medium, and electronic device for multi-user operations. Background Technology

[0002] With the advancement of strategies such as intelligent construction, multi-person collaborative 3D model editing systems have become a core supporting technology in fields such as industrial design, Building Information Modeling (BIM), and digital twins. Compared to single-person independent modeling, multi-person collaborative 3D models allow design teams distributed in different spaces (e.g., structural engineers and electrical engineers in mechanical design, and architectural, structural, and MEP professional teams in architectural design) to operate in parallel on the same model carrier, achieving rapid integration and iterative optimization of design concepts through real-time data interaction. Industry research shows that using collaborative editing systems can shorten the 3D model design cycle by 30%-40%. Therefore, in scenarios with stringent requirements for efficiency and accuracy, such as high-precision mechanical manufacturing and ultra-large-scale building projects, its application penetration rate has exceeded 75%.

[0003] While current mainstream multi-user collaborative 3D model editing systems (such as Autodesk BIM 360, BentleyiTwin, and Dassault 3DEXPERIENCE) have achieved basic data synchronization functions, model data conflicts remain a key bottleneck restricting system performance and design quality in multi-user parallel operation scenarios. This is especially true when the model contains massive amounts of geometric data (e.g., millions of triangular facets), multi-dimensional attribute information (material parameters, tolerance levels, assembly constraints), and time-series related data (e.g., current iteration records, editing operation sequences). The probability of conflicts and the difficulty of handling them increase exponentially, directly leading to design rework, data loss, and project delays.

[0004] Research has found that existing conflict detection methods rely solely on version numbers and cannot identify conflicts based on substantive data features. For example, conflict detection often depends on a single mechanism such as "version number comparison" or "timestamp judgment," and can only identify explicit conflicts such as "the same component being modified simultaneously," while failing to identify implicit conflicts involving cross-dimensional relationships. Summary of the Invention

[0005] To overcome at least one deficiency in the prior art, this application provides a conflict detection method, apparatus, storage medium, and electronic device for multi-user operations, comprising:

[0006] Firstly, this application provides a conflict detection method for multi-user operations, the method comprising:

[0007] Receive a synchronization request sent by the client, wherein the synchronization request includes version information of the local model and modification information of the local model;

[0008] If the versions of the local model and the cloud model are inconsistent, then based on the modification information, the target component with multiple modification conflicts is determined.

[0009] If there is an implicit conflict among the various modification conflicts, the degree of conflict of the implicit conflict is evaluated.

[0010] Secondly, this application provides a collision detection device for multi-user operations, the device comprising:

[0011] The synchronization interaction module is used to receive synchronization requests sent by the client, wherein the synchronization request includes version information of the local model and modification information of the local model;

[0012] The conflict identification module is used to determine, based on the modification information, the target component that has multiple modification conflicts if the versions of the local model and the cloud model are inconsistent.

[0013] The conflict analysis module is used to assess the degree of conflict of the implicit conflict if there is an implicit conflict among the multiple modification conflicts.

[0014] Thirdly, this application provides a storage medium storing a computer program that, when executed by a processor, implements the aforementioned conflict detection method for multi-user operations.

[0015] Fourthly, this application provides an electronic device, which includes a processor and a memory. The memory stores a computer program, which, when executed by the processor, implements the aforementioned conflict detection method for multi-user operations.

[0016] Compared with the prior art, this application has the following beneficial effects:

[0017] In the conflict detection method, apparatus, storage medium, and electronic device provided in this application for multi-user operations, the electronic device receives a synchronization request sent by the client. The synchronization request includes version information of the local model and modification information of the local model. If the versions of the local model and the cloud model are inconsistent, it is determined whether the modification information causes multiple modification conflicts for the same target component. If so, the degree of implicit conflict among the multiple modifications is evaluated. Thus, when an inconsistency between the versions of the local model and the cloud model is detected, the process does not stop at formal comparison but further analyzes whether the modification information causes multiple modification conflicts for the same target component and evaluates the degree of implicit conflict, thereby achieving effective detection of implicit conflicts across dimensions. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is one of the flowcharts illustrating a conflict detection method for multi-user operations provided in an embodiment of this application.

[0020] Figure 2 A second schematic flowchart of a conflict detection method for multi-user operations provided in this application embodiment;

[0021] Figure 3 The third flowchart illustrates the conflict detection method for multi-user operations provided in this application embodiment;

[0022] Figure 4 A schematic diagram of the structure of a collision detection device for multi-person operations provided in an embodiment of this application;

[0023] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of this application (hereinafter referred to as "the embodiments") clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0025] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0026] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0027] In the description of this application, it should be noted that the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0028] Based on the above statement, as described in the background section, existing conflict detection relies solely on version numbers and cannot identify substantial data feature conflicts.

[0029] For example, in the collaborative design of large bridge structures, multiple engineers often need to simultaneously modify the same component in different dimensions. While one structural engineer adjusts the geometry of the main beam to optimize its load-bearing performance, another materials engineer changes the steel grade of the main beam to control construction costs. These two operations affect different data attributes of the model—one involving changes to geometric parameters, the other updating material properties. Since they do not overlap at the data storage level, current mainstream collaborative systems typically do not trigger any warnings when conflicts are detected based solely on version numbers or timestamps. However, this seemingly compatible merging can harbor serious safety hazards. When a reduction in cross-sectional width and a downgrading of high-strength steel occur simultaneously, the overall load-bearing capacity of the component will significantly decrease, even falling below the safety threshold required by national design codes.

[0030] It should be noted that the defects in the solutions in the prior art are the result of practice and careful research. Therefore, the discovery process of the above problems and the solutions proposed by the embodiments of this application in the following text should be regarded as contributions to this application in the process of invention and creation, and should not be understood as technical content known to those skilled in the art.

[0031] Based on the discovery of the above-mentioned technical problems, this embodiment provides a conflict detection method for multi-user operations. For example... Figure 1 As shown, the method includes:

[0032] S1 receives synchronization requests sent by the client.

[0033] The synchronization request includes the version information of the local model and the modification information of the local model.

[0034] S2, if the versions of the local model and the cloud model are inconsistent, then the target component with multiple modification conflicts is determined based on the modification information.

[0035] S3. If there is an implicit conflict among multiple modification conflicts, then assess the degree of conflict of the implicit conflict.

[0036] Thus, when inconsistencies are detected between the local model and the cloud model, the process does not stop at formal comparison, but further analyzes whether the modification information causes multiple modification conflicts for the same target component and assesses the degree of implicit conflict, thereby achieving effective detection of implicit conflicts in cross-dimensional associations.

[0037] It should be understood that, in this embodiment, the electronic device implementing the multi-user conflict detection method can be any computing device with data processing and network communication capabilities. Specifically, the electronic device includes, but is not limited to, desktop computers, laptops, workstations, industrial control computers, cloud computing servers, edge computing gateways, or high-performance graphics processing unit (GPU) servers. In practical applications, the client is typically a terminal device used by designers, such as a personal computer or mobile terminal running 3D modeling software; while the server can be deployed in a local data center or cloud platform, employing multi-core processors and large-capacity memory to support high-concurrency data comparison and conflict detection operations.

[0038] To make the solution provided in this embodiment clearer, a server is used as the electronic device for implementing the method below, and in conjunction with... Figure 1 Each step of the method is described in detail. However, it should be understood that the operations in the flowchart may not be implemented in sequence, and steps without logical contextual relationships may be reversed in order or performed simultaneously. Furthermore, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowchart, or remove one or more operations from the flowchart. See also... Figure 1 As shown, the method includes:

[0039] S1 receives synchronization requests sent by the client.

[0040] The synchronization request includes the version information of the local model and the modification information of the local model.

[0041] Research has found that existing conflict detection methods mainly rely on a full comparison of client-side and server-side data, which means that even if modifications are made, the entire file still needs to be transmitted, resulting in problems such as high bandwidth consumption and response delays.

[0042] Therefore, in this embodiment, the synchronization request does not simply submit the entire local model. Instead, the client pre-generates and sends a lightweight data packet containing version information and modification information of the local model. The version information of the local model serves as the basis for version consistency judgment and mainly includes the client's unique identifier (client_id), the client's local version number (local_version), the server version number used in the last synchronization (server_version), and the model's unique identifier (model_id). This information collectively constitutes the basic traceability data in the synchronization request, enabling the server to quickly determine whether the current client is editing based on the latest server baseline version, thereby deciding whether conflict detection needs to be performed subsequently.

[0043] Building upon this, modifications to the local model are organized and transmitted using a difference vector (Dv). In this embodiment, the difference vector (Dv), serving as the core data carrier for synchronization between the client and server, can be represented in a nested JSON format, specifically divided into two parts: base information (BaseInfo) and difference data (DiffData). The difference data (DiffData) lists all modified components in array form, with each modification corresponding to a difference item (DiffItem), which includes the modified component ID (element_id), element type (element_type), modification type (modify_type), and specific modification content (diff_content). Modification types can be further categorized into geometric changes, attribute changes, topological changes, additions, or deletions, ensuring the server can recognize editing operations across different dimensions. Furthermore, each modification can be accompanied by a local modification timestamp (modify_timestamp) to aid in time series analysis and conflict determination.

[0044] For example, the difference vector can be represented as:

[0045] {

[0046] "BaseInfo": {

[0047] "client_id": "client_001", / / Client identifier

[0048] "local_version": 5, / / Client local version number (Vc)

[0049] "server_version": 3, / / The server version (Vs) the client last synchronized with

[0050] "model_id": "bridge_beam_01" / / Model identifier (e.g., bridge main beam model)

[0051] },

[0052] "DiffData": [ / / List of difference data, each element corresponds to a modification item]

[0053] {

[0054] "element_id": "beam_203", / / Modified component ID (main beam number 203)

[0055] "element_type": "structural_beam", / / Element type (structural beam)

[0056] "modify_type": "attribute", / / Modification type: attribute change (materials are attributes)

[0057] "diff_content": {

[0058] "attr_key": "material", / / Attribute to be changed: material

[0059] "old_val": { / / Old material parameters in the baseline model (Ms)

[0060] "type": "steel",

[0061] "grade": "Q355", / / Steel grade: Q355 (yield strength 355MPa)

[0062] Density: 7850 kg / m³

[0063] },

[0064] "new_val": { / / New material parameters modified by the client

[0065] "type": "steel",

[0066] "grade": "Q235", / / Change to Q235 (yield strength 235MPa)

[0067] "density": 7850

[0068] }

[0069] },

[0070] "modify_timestamp": "2025-10-10T09:30:00Z" / / Modify time

[0071] }, ]

[0073] }

[0074] In practical applications, after a user completes local editing, the client automatically compares the local edited version model (Mc) with the baseline version model (Ms) from the last synchronization. By combining fast hash comparison with fine-grained difference extraction technology, it accurately identifies the changed components and their modification details, and then encapsulates them into a difference vector (Dv) of the aforementioned structure. Finally, this difference vector (Dv), along with the version number of the local model, is submitted to the server as part of the synchronization request.

[0075] Based on the above explanation of synchronization requests, we will continue with... Figure 1 Step S1 will be explained as follows:

[0076] S2, if the versions of the local model and the cloud model are inconsistent, then the target component with multiple modification conflicts is determined based on the modification information.

[0077] This can be understood as follows: by comparing the modification types of the specific modification behaviors of the same component in the local model and the cloud model, the above steps identify target components with multiple modification conflicts, namely those concurrent changes that do not overlap directly on the surface but are related in engineering.

[0078] In practice, when the server receives a synchronization request from the client, it first retrieves the version information of the local model contained within and compares it with the version number of the current cloud model. If the versions of the local model and the cloud model are found to be inconsistent, it indicates that the server-side model has been updated by other users since the client's last synchronization. In this case, further analysis is needed to determine if there are any potential modification conflicts. Therefore, based on the modification information, the server locates all modified components involved in this synchronization request and filters out target components with multiple modification conflicts.

[0079] To address this, the server can extract the modifications that occurred in both the local and cloud models and categorize them according to preset modification types. These modification types include, but are not limited to, geometric changes, attribute changes, topology changes, additions, and deletions. Subsequently, the server compares the modification types of the same component in the two versions; if it finds that different types of modifications have occurred in the local and cloud versions, it determines that the component is a target component with multiple modification conflicts.

[0080] For example, suppose a component is named "beam_203". The client-submitted modification information records that a property change was performed on this component, specifically adjusting the material grade from Q355 to Q235. However, the server detects that in the current cloud model, this component has been geometrically modified by another user, specifically changing its cross-sectional height from 2.0m to 1.8m. Although these two modifications do not directly overlap at the data level (they do not modify the same field), they both affect the same structural component and thus impact its load-bearing capacity. Therefore, they are classified as target components with multiple modification conflicts.

[0081] Therefore, by comparing the modification types of the same component in the local and cloud versions, we can identify concurrent modification behaviors imposed by different users on different dimensions, so as to assess whether there are implicit conflicts.

[0082] Based on the above explanation of various modification conflicts, the following will address... Figure 1 Step S2 will be explained as follows:

[0083] S3. If there is an implicit conflict among multiple modification conflicts, then assess the degree of conflict of the implicit conflict.

[0084] It should be understood that in actual engineering design scenarios, when multiple people work together, there may be harmful hidden conflicts, which means that different users make different types of modifications to the same target component but there are interrelationships. These modifications may seem independent at the data level, but may cause serious performance degradation or violation of specifications in engineering.

[0085] For example, user A changes the material of a load-bearing beam from high-strength steel Q355 to low-strength steel Q235, while user B reduces its cross-sectional width at the same time. These two operations are attribute changes and geometric changes, respectively. If only compared by type, they might be considered indirect conflicts and allowed to be merged. However, in reality, the decrease in material strength combined with the reduction in cross-section could cause the beam's load-bearing capacity to fall far below the design safety threshold, posing a serious safety hazard. Because such problems do not manifest as data overlay, existing mechanisms are highly susceptible to overlooking them.

[0086] Therefore, in this embodiment, the server can determine whether an implicit conflict exists by judging whether there is a linkage relationship among multiple modification conflicts. A linkage relationship refers to the inherent dependence of certain types of modifications in terms of physics, mechanics, or design logic, where combined changes can lead to consequences far more severe than a single modification. In view of this, this embodiment provides the following optional implementation methods for step S3:

[0087] S3-1 identifies multiple linked conflicts from various modification conflicts.

[0088] Specifically, during the collaborative editing of 3D models by multiple users, when the server determines that there are multiple modification conflicts between the local model and the cloud model for the same target component, it does not stop at the level of data difference comparison, but further analyzes whether these modifications are related in terms of function or performance.

[0089] For example, the mechanical load-bearing capacity of a structural beam is determined by its material strength and geometric cross-section. If the client modifies the material grade of the component (e.g., from Q355 steel to Q235), and the cloud version simultaneously adjusts its cross-sectional width or height, these two changes, although occurring in different attribute fields, constitute a linkage in engineering, meaning that their combined effect directly impacts the actual safety performance of the component. Therefore, the server needs to identify multiple linkage conflicts from various modification conflicts. Here, the linkage relationship refers to the technical association where multiple modification items have a synergistic effect.

[0090] Based on the above explanation of the linkage conflict, step S3 also includes:

[0091] S3-2, obtain the design constraints or engineering specifications corresponding to various linkage conflicts.

[0092] Based on this, the server retrieves the design constraints or engineering specifications corresponding to various linkage conflicts as a basis for judging whether the consequences of the modification are acceptable. Here, design constraints or engineering specifications refer to technical standard documents widely adopted in specific industry fields, which clearly stipulate the minimum requirements that various components must meet in terms of material selection, dimensional tolerances, and connection methods. For example, the national standard GB / T 1591-2018 specifies the mechanical property classification of low-alloy steel for structures, while GB50205-2020 sets the allowable deviation range for the processing and installation of steel structure components. The server establishes a benchmark rule set for assessing the impact of modifications by retrieving relevant clauses that match the current target component type.

[0093] Based on the design constraints or engineering specifications obtained above, step S3 further includes:

[0094] S3-3 calculates the performance degradation index or the degree of violation of technical standards under design constraints or engineering specifications for multiple linkage conflicts.

[0095] In this implementation, the server can reconstruct the key parameters before and after the modification based on the original state of the target component in the cloud model (i.e., baseline version Ms) and its modifications in the local model (recorded in the DiffData field of the difference vector Dv), and substitute them into relevant engineering formulas for performance simulation. Taking material change as an example, the performance degradation index can be calculated using the following expression:

[0096]

[0097] in, This indicates the original performance parameters of the component in the baseline version (e.g., load capacity of 100kN). This indicates the new performance parameters (e.g., 60kN) recalculated based on the modified material model from the client. Similarly, for structural changes caused by geometric alterations, the actual deviation can be calculated using methods such as least squares fit deviation or bounding box overlap rate, and the degree of violation can be determined by combining this with the allowable deviation value specified in the standard.

[0098] S3-4, based on performance degradation indicators or violation levels, determines the degree of implicit conflict.

[0099] In this implementation, the server can normalize the aforementioned calculation results into a quantified value between 0 and 1 to characterize the overall risk level brought about by the group of linked modifications. For example, when the carrying capacity decreases beyond the specification limit, the conflict level approaches 1; if there is a slight deviation but it is still within the safety margin, a lower value is taken. Thus, compared to a simple judgment of whether there is a conflict, this embodiment quantifies it as how severe the conflict is.

[0100] This can be understood as follows: by introducing engineering design logic as a conflict assessment framework, the above steps transform the interconnected changes of multiple independent modifications at the physical performance level into quantifiable compliance indicators, thereby achieving objective and accurate identification and severity assessment of implicit conflicts.

[0101] The study also found that in multi-user collaborative 3D model editing scenarios, the same target component may be modified by different users from multiple dimensions within a short period of time. For example, one person changes material properties, another adjusts geometric dimensions, and a third changes assembly relationships. Existing conflict detection mechanisms typically treat these modifications as independent events, lacking the comprehensive assessment capability of the coupled effects between multiple types of conflicts, resulting in an inaccurate reflection of the overall conflict severity. Therefore, if... Figure 2 As shown, the conflict detection method for multi-user operations provided in this embodiment further includes:

[0102] S4 retrieves the conflict level of various modification conflicts.

[0103] In this implementation, the various modification conflicts include material conflicts, geometric conflicts, and topological conflicts. The degree of these conflicts includes the first degree of material conflict, the second degree of geometric conflict, and the third degree of topological conflict.

[0104] As an optional implementation, the server can obtain the first material used by the target component in the cloud model and the second material used by the target component in the local model; obtain the degree of change in material properties between the first material and the second material; and map the degree of change to a first conflict level between 0 and 1.

[0105] This can be understood as follows: by transforming changes in material properties into quantifiable performance deviation indicators, the above steps achieve an objective assessment of the severity of material conflicts.

[0106] Specifically, in conflict detection methods for multi-user operations, after identifying material modification behavior of the same target component, the server needs to further determine whether the modification constitutes a substantial conflict and express its degree of impact using a uniform scale.

[0107] In practical applications, the server first obtains the primary material used by the target component in the cloud model and the secondary material used by the target component in the local model. The primary material refers to the original material parameters of the component in the server-side baseline version model (Ms), for example, the steel grade is Q355 with a density of 7.85 g / cm³. The secondary material is the new material setting for the component in the client-side local edit version model (Mc), for example, changing it to Q235 steel. This material information typically includes fields such as type, grade, and physical properties, and is stored in the model attribute library in structured data form.

[0108] To achieve efficient comparison, the server employs a fast hash comparison algorithm, concatenating material parameters into a standardized string (such as "steel_Q355_7850") and calculating its SHA-256 hash value. If the material hash values ​​of the same target component are inconsistent between the cloud and local storage, a material difference is determined, and the component is marked as a material conflict.

[0109] Based on this, the server maps the degree of change to a first level of conflict, ranging from 0 to 1. This mapping process is calculated according to a preset formula:

[0110]

[0111] in, The first conflict level represents the quantified result of the material conflict; the new value refers to the key performance parameter value corresponding to the second material (e.g., the yield strength of Q235 steel is 235 MPa), and the baseline value refers to the original performance parameter value corresponding to the first material (e.g., the yield strength of Q355 steel is 355 MPa). The calculated ratio reflects the relative deviation; if it exceeds 1.0, it is truncated to 1.0 to ensure that the output value is always within the [0,1] range.

[0112] As an optional implementation, the server also obtains the first bounding box of the target component in the cloud model and the second bounding box in the local model; if the overlap rate between the first bounding box and the second bounding box is less than the overlap threshold, the geometric deviation between the target component in the cloud model and the local model is obtained; the geometric deviation is mapped to a second conflict level between 0 and 1.

[0113] Specifically, when obtaining the geometric deviation between the target component in the cloud model and the local model, the server can extract the first feature point set of the target component in the cloud model and the second feature point set in the local model, wherein the first feature point set and the second feature point set come from the same position of the target component; the first feature point set and the second feature point set are registered, and the average deviation between the first feature point set and the second feature point set is calculated based on the registration result; the average deviation is used as the geometric deviation.

[0114] This can be understood as follows: by constructing a two-level detection mechanism of "rapid screening + accurate verification", the above steps achieve high-precision quantitative assessment of geometric conflicts while ensuring computational efficiency.

[0115] Specifically, when the server identifies that the same target component has geometric modifications in both the cloud model and the local model, it is necessary to further determine whether the changes constitute a substantial deviation and output a comparable second degree of conflict on a unified scale.

[0116] In practical applications, the server first obtains the first bounding box of the target component in the cloud model and the second bounding box in the local model. The first bounding box refers to the axis-aligned bounding box (AABB) of the component in the server-side baseline version model (Ms), representing its original spatial extent. The second bounding box is the new spatial boundary of the corresponding component in the client-side local edit version model (Mc), generated based on the modified geometric parameters. Both are lightweight spatial representation structures, facilitating rapid comparison.

[0117] Based on this, the server calculates the overlap rate between the first and second bounding boxes. This overlap rate can be calculated using the Intersection over Union (IoU) ratio, which is the ratio of the intersection volume to the union volume of the two bounding boxes. If the overlap rate is less than a preset overlap threshold (e.g., 90%), it is determined that the size or position change is significant and marked as a "suspected geometric conflict," thus triggering a secondary verification process. Conversely, if the overlap rate is higher than the threshold, the geometric change is considered minor and does not constitute a significant conflict, requiring no further analysis.

[0118] Under conditions of suspected geometric conflict, the server obtains the geometric deviations of the target component between the cloud model and the local model. To this end, the server extracts a first set of feature points of the target component in the cloud model and a second set of feature points in the local model. These feature point sets are derived from the same geometric locations of the component, such as the four corner points of a cross section, the endpoints of an axis, or key control points, ensuring spatial correspondence in the comparison.

[0119] The server registers the first and second feature point sets. For example, it can use the Iterative Closest Point (ICP) algorithm to achieve optimal spatial alignment of the two point cloud data sets through iterative optimization. Based on the registration results, the server calculates the average deviation between the first and second feature point sets. This value reflects the degree of change in the overall geometry of the component. For example, a 100mm offset in the width direction of the target component beam_203 is a specific geometric deviation.

[0120] Finally, the server uses the average deviation as the geometric deviation and maps it to a second degree of conflict, ranging from 0 to 1. This mapping process is based on the following formula:

[0121]

[0122] in, This indicates the second degree of conflict, i.e., the quantification result of geometric conflict; the actual deviation refers to the average deviation value calculated after ICP registration (e.g., 0.1m); the allowable deviation refers to the tolerance limit set according to industry standards or design specifications (e.g., ±0.01m). When the actual deviation exceeds the allowable deviation, the ratio is greater than 1, and is ultimately taken as 1.0, indicating serious deviation; if it does not exceed the limit, a value between 0 and 1 is output proportionally.

[0123] As an optional implementation, the server also obtains the first topological adjacency matrix of the target component in the cloud model and the second topological adjacency matrix in the local model; obtains the connection change number based on the first topological adjacency matrix and the second topological adjacency matrix; and maps the connection change number to a third conflict level between 0 and 1.

[0124] This can be understood as follows: when it is determined that multiple users are collaboratively editing the same target component, a conflict at the topology level is triggered. The degree of conflict is quantified by constructing and comparing the topological relationships before and after the model state changes.

[0125] During this process, the server obtains the first topological adjacency matrix of the target component in the cloud model and the second topological adjacency matrix in the local model. The first topological adjacency matrix here refers to the set of connection relationships between components in the baseline version model (i.e., the cloud model) currently maintained by the server, where each matrix element indicates whether there is an assembly or connection relationship between two components.

[0126] For example, if [beam_203][col_105]=1 in the matrix, it means that the beam component numbered beam_203 and the column component numbered col_105 have a physical connection or logical association in the cloud model.

[0127] The second topological adjacency matrix refers to the set of topological relationships formed by the corresponding target components in the client's local edit version model. Its structure and meaning are the same as the first topological adjacency matrix, but it reflects the connection status after the user modifies it locally.

[0128] The server compares each item in the two adjacency matrices, counting the total number of connections whose values ​​have changed. This identifies which previously connected components have been disconnected, or which previously unconnected components have been newly connected. Each such difference is counted as a change in connection, thus forming a quantitative indicator representing the scale of the topology change.

[0129] Finally, the server maps the connection change count to a third level of collision, ranging from 0 to 1. This mapping process uses the following mathematical expression:

[0130]

[0131] In the formula, The third degree of conflict is indicated by the connectivity change number, which refers to the number of changes in connectivity relationships obtained from the aforementioned comparison; the baseline connectivity number refers to the number of original connectivity relationships of the target component in the baseline model (i.e., the cloud model), used as a normalization reference benchmark to ensure that the conflict degree value falls within the range (0,1). The larger the proportion of connectivity change, the closer the third degree of conflict is to 1, indicating a more severe topological conflict.

[0132] For example, suppose the target component beam_203 was originally connected to 5 other components in the cloud model (i.e., baseline connectivity = 5), while in the local model, 2 original connections were deleted and no other connections were added. Substituting into the formula, we get: |2| / 5 = 0.4, so the topology conflict level is 0.4.

[0133] Based on the first, second, and third levels of conflict obtained above, please refer to... Figure 2 The method also includes:

[0134] S5 weights and merges the conflict levels of multiple modification conflicts to obtain the overall conflict level of the target component.

[0135] This can be understood as follows: by quantifying and integrating the severity of different types of conflicts, a unified comprehensive evaluation index is constructed, thereby achieving a holistic judgment on the impact of multi-dimensional modifications on the same target component.

[0136] Specifically, in multi-user conflict detection methods, when the server identifies multiple types of conflicts, including material conflicts, geometric conflicts, and topological conflicts, for a target component, it is necessary to further evaluate the severity level of each of these conflicts and integrate them into an operational comprehensive conflict level.

[0137] In practical applications, the server first acquires the first degree of material conflict, the second degree of geometric conflict, and the third degree of topological conflict. These conflict degree values ​​are all quantitative values ​​between 0 and 1, representing the severity of the corresponding type of conflict. Among them, the first degree of conflict reflects the degree of performance deviation caused by changes in material properties (e.g., the percentage decrease in strength), the second degree of conflict reflects the degree to which geometrical changes exceed design tolerances, and the third degree of conflict characterizes the impact of the disruption of topological connectivity (e.g., the loss of critical support connections).

[0138] Based on this, if the target component has only a single type of conflict, the degree of conflict is directly used as its comprehensive conflict degree; however, if two or three types of conflicts occur simultaneously, for example, user A modifies the component material, user B adjusts the geometric dimensions, and the assembly relationship of the component in the cloud version is also updated, then a weighted average method is used to calculate the first conflict degree, the second conflict degree, and the third conflict degree to generate the comprehensive conflict degree of the first target component.

[0139] By default, material conflicts are weighted at 0.4, structural geometry conflicts at 0.4, and topological conflicts at 0.2. Therefore, the overall conflict level... The calculation formula is as follows:

[0140]

[0141] In the formula, Indicates the first degree of conflict (material conflict). Indicates the second level of conflict (geometric conflict). Indicates the third level of conflict (topological conflict); , , These are their corresponding weight coefficients. It should be noted that this weighting configuration reflects that in most engineering scenarios, material and geometric parameters play a decisive role in component performance, while topological relationships are generally more stable, and although their changes are important, they occur less frequently; therefore, they are assigned slightly lower weights. Of course, in practical applications, the above weights can be adjusted adaptively.

[0142] Therefore, after the server completes the analysis of the discrepancy data submitted by the client, it may obtain multiple modification conflicts and their corresponding conflict degrees, thereby generating conflict description information C containing multiple conflict items. Each item corresponds to a target component and its conflict degree value in different dimensions. Specifically, this includes the first conflict degree, which characterizes the change in material properties; the second conflict degree, which is calculated through bounding box overlap rate screening and feature point set registration; the third conflict degree, which is obtained by normalization based on the change number of the topological adjacency matrix; and the conflict degree of implicit conflicts. The final conflict description information C is essentially a structured encapsulation of these sub-conflict degrees, which can be used to determine whether to trigger further manual intervention mechanisms.

[0143] In practice, if the conflict level of all elements in the conflict description information C is 0, it indicates that no substantial differences have been detected at the material, geometry, or topology level. That is, the modification between the client's local edit version model Mc and the server's baseline version model Ms belongs to a non-overlapping area or a compatibility change (for example, user A modifies the component color attribute, and user B modifies the dimension parameters of another independent component). In this case, no manual intervention is required. The server can directly update Ms to Mc and upgrade the version number to Vc to achieve efficient and silent synchronization.

[0144] However, if the conflict description information C ≠ 0, meaning that at least one target component has a conflict level greater than zero in any dimension, it indicates that the modification of that component has caused potential design conflicts across users. For example, if a beam component has its steel grade changed in the local model (resulting in a first conflict level > 0), and its cross-sectional width is also adjusted with a deviation exceeding the allowable tolerance (resulting in a second conflict level > 0), the server can still identify this implicit conflict risk under multiple overlapping dimensions, even if other users have not directly manipulated the same parameter. In this case, the server will not automatically perform a merging operation, but will return the complete conflict description information C to the requesting client as a signal input requiring manual review.

[0145] The client receives the conflict description information C and extracts the specific details of each conflict. Since the vector itself already contains the conflict type, a comparison of values ​​before and after modification, and the corresponding conflict severity value, the server can generate intuitive visual prompts. For example, it can highlight the target component with material or geometric conflicts in the 3D view and display detailed information such as "Client modified value is 50mm, server current value is 60mm" in a pop-up window, thus prompting the user to select a handling strategy.

[0146] Strategy 1: Retain the server-side version;

[0147] Strategy 2: Retain the client version (the conflicting parts need to be modified later).

[0148] If the user selects strategy 1, the client updates the content of conflicting elements in the local model to the corresponding content on the server-side Ms, ensuring consistency between the local model and the server, and synchronization is complete. If the user selects strategy 2, the client prompts "There is an incompatible conflict. Please modify the conflicting parts and resynchronize." After the user completes the modifications, a new synchronization request is submitted.

[0149] In addition, such as Figure 3 As shown, compared to prompting the user to select a processing strategy, in another optional implementation, the conflict detection method for multi-user operations further includes:

[0150] S6 generates conflict description information.

[0151] The conflict description information includes the degree of conflict for various modification conflicts and the degree of conflict for implicit conflicts.

[0152] S7, call the pre-trained conflict decision model to process the conflict description information and obtain the synchronization strategy for the synchronization request;

[0153] S8 executes the synchronization strategy.

[0154] This can be understood as follows: the above steps construct a mapping relationship between structured conflict information and intelligent decision-making capabilities through a conflict decision-making model, thereby enabling the automatic generation of processing strategies adapted to the current collaborative situation based on multi-dimensional conflict assessment results, thus realizing the transformation from passive alarm to autonomous decision-making.

[0155] Specifically, in the conflict detection method for multi-user operations, after the server completes the calculation of the conflict severity of various modification conflicts and implicit conflicts, it enters the stage of generating conflict description information. This conflict description information is structured text, which records various conflict severity values ​​from previous steps, including but not limited to the first conflict severity of material conflicts, the second conflict severity of geometric conflicts, and the third conflict severity of topological conflicts. It can also further integrate contextual information such as conflict element identifiers, modification timestamps, and user roles.

[0156] In this way, the various conflict indicators are organized in a specific format and output as a conflict description that can be processed by external models. Therefore, this conflict description not only reflects the existence of conflict, but also carries the distribution of conflict types and severity levels.

[0157] Based on this, the server calls a pre-trained conflict decision model to process the conflict description information in order to obtain a synchronization strategy for the synchronization request. The pre-trained conflict decision model here can be a machine learning model with engineering semantic understanding capabilities, which can be a Large Language Model (LLM) or a domain-specific model specifically designed for collaborative design scenarios.

[0158] It should be understood that during training, this model learned from a large amount of design specification text, historical edit logs, expert handling cases, and industry standard documents, enabling it to identify the modification intentions of users with different professional backgrounds and judge the rationality of modifications in conjunction with technical constraints. In practical applications, the server converts the structured fields in the conflict description information into natural language prompts, such as:

[0159] “Component beam_203 currently uses Q355 steel on the server side, but the client side proposes to change it to Q235, resulting in a 40% decrease in load-bearing capacity; at the same time, the cross-sectional width is adjusted from 1.2m to 1.1m, exceeding the allowable range of GB50205-2020 by 10 times. This modification comes from the mechanical and electrical engineering discipline, while the baseline version was confirmed by the structural engineering discipline. Please assess whether it is permissible to retain the client-side modification.”

[0160] After receiving the prompt, the conflict decision model performs reasoning and analysis based on its inherent knowledge system and outputs recommended synchronization strategies, such as "suggest rejecting client modifications", "suggest accepting but requiring investigation", or "automatic merging".

[0161] The server executes a synchronization strategy, which means implementing the operation instructions output by the model. If the recommended strategy is to retain the server-side version, the server maintains the current model state and notifies the client to update the corresponding local parts; if the recommended strategy is to retain the client-side version, the server writes the modifications submitted by the client into the cloud model, completing the data update; if the recommended strategy is to initiate a review process, the server marks the conflict as pending manual handling and triggers a collaborative investigation notification mechanism.

[0162] Therefore, this embodiment, by introducing an intelligent decision-making mechanism based on a conflict decision-making model, transforms the conflict handling method from the traditional "human-led" to "server-led". This significantly reduces the cost of manual intervention for high-frequency, low-risk conflicts and improves the level of automation in multi-person collaborative operations, while ensuring the safety of key design parameters.

[0163] Based on the same inventive concept as the conflict detection method for multi-user operations provided in this embodiment, this embodiment also provides a conflict detection device for multi-user operations. This device includes at least one software functional module that can be stored in a memory or embedded in an electronic device. The processor in the electronic device executes the executable module stored in the memory. For example, the software functional module and computer program included in this device. Please refer to... Figure 4 Functionally, the device may include:

[0164] The synchronization interaction module 11 is used to receive synchronization requests sent by the client, wherein the synchronization request includes version information of the local model and modification information of the local model.

[0165] The conflict identification module 12 is used to identify the target component that has multiple modification conflicts if the versions of the local model and the cloud model are inconsistent, based on the modification information.

[0166] The conflict analysis module 13 is used to assess the degree of conflict of implicit conflicts if there are implicit conflicts among multiple modification conflicts.

[0167] In this embodiment, the synchronous interaction module 11 is used to implement Figure 1 In step S1, the conflict identification module 12 is used to implement Figure 1 In step S2, the conflict analysis module 13 is used to implement Figure 1 Step S3 in the above process. Therefore, for a detailed description of each of the above modules, please refer to the specific implementation method of the corresponding step.

[0168] Optionally, the conflict analysis module 13 is also specifically used for:

[0169] Identify multiple interconnected conflicts from a variety of modification conflicts;

[0170] Obtain the design constraints or engineering specifications corresponding to various linkage conflicts;

[0171] Calculate the performance degradation index or the degree of violation of technical standards under design constraints or engineering specifications for multiple linkage conflicts;

[0172] The degree of implicit conflict is determined based on performance degradation indicators or the degree of violation.

[0173] Optionally, the conflict analysis module 13 is also used for:

[0174] Obtain the conflict level of various modification conflicts;

[0175] The conflict levels of various modification conflicts are weighted and integrated to obtain the overall conflict level of the target component.

[0176] Optionally, the conflict analysis module 13 is also used for:

[0177] Generate conflict description information, which includes the conflict degree of various modification conflicts and the conflict degree of implicit conflicts;

[0178] The pre-trained conflict decision model is invoked to process the conflict description information and obtain a synchronization strategy for the synchronization request.

[0179] Implement the synchronization strategy.

[0180] Optionally, the conflict levels of various modification conflicts include the first level of conflict in material conflicts, and the conflict analysis module 13 is also specifically used for:

[0181] Obtain the first material used by the target component in the cloud model and the second material used by the target component in the local model;

[0182] To determine the degree of change in material properties between the first material and the second material;

[0183] The degree of change is mapped to a first degree of conflict, which is between 0 and 1.

[0184] Optionally, the conflict levels of various modification conflicts include a second level of conflict based on geometric conflict, and the conflict analysis module 13 is also specifically used for:

[0185] Obtain the first bounding box of the target component in the cloud model and the second bounding box in the local model;

[0186] If the overlap rate between the first bounding box and the second bounding box is less than the overlap threshold, then the geometric deviation between the target component in the cloud model and the local model is obtained.

[0187] The geometric deviation is mapped to a second degree of conflict between 0 and 1.

[0188] Optionally, the conflict analysis module 13 is also specifically used for:

[0189] Extract the first feature point set of the target component in the cloud model and the second feature point set in the local model, wherein the first feature point set and the second feature point set come from the same location of the target component;

[0190] The first feature point set and the second feature point set are registered, and the average deviation between the first feature point set and the second feature point set is calculated based on the registration result.

[0191] The average deviation is used as the geometric deviation.

[0192] Optionally, the conflict levels of various modification conflicts include the third level of topological conflict, and the conflict analysis module 13 is also specifically used for:

[0193] Obtain the first topological adjacency matrix of the target component in the cloud model and the second topological adjacency matrix in the local model;

[0194] Based on the first and second topological adjacency matrices, the number of connection changes is obtained;

[0195] The number of connection variations is mapped to a third level of conflict, ranging from 0 to 1.

[0196] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0197] It should also be understood that if the above embodiments are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0198] Therefore, this embodiment also provides a storage medium, which is a computer-readable storage medium. This storage medium stores a computer program, which, when executed by a processor, implements the conflict detection method for multi-user operations provided in this embodiment. The storage medium can be any medium capable of storing program code, such as a USB flash drive, external hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0199] This embodiment provides an electronic device for implementing a collision detection method for multi-user operations. Please refer to... Figure 5 The electronic device may include a processor 22 and a memory 21. The memory 21 stores a computer program, and the processor reads and executes the computer program corresponding to the above-described embodiments in the memory 21 to implement the conflict detection method for multi-user operations provided in this embodiment.

[0200] See also Figure 5 The electronic device also includes a communication unit 23. The memory 21, processor 22 and communication unit 23 are electrically connected to each other directly or indirectly through system bus 24 to realize data transmission or interaction.

[0201] The memory 21 can be an information recording device based on any electronic, magnetic, optical, or other physical principles, used to record execution instructions, data, etc. In some embodiments, the memory 21 can be, but is not limited to, volatile memory, non-volatile memory, memory drive, etc.

[0202] In some embodiments, the volatile memory may be random access memory (RAM); in some embodiments, the non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, etc.; in some embodiments, the storage drive may be a disk drive, solid-state drive, any type of storage disk (such as optical disc, DVD, etc.), or similar storage media, or a combination thereof.

[0203] The communication unit 23 is used to send and receive data over a network. In some embodiments, the network may include a wired network, a wireless network, a fiber optic network, a telecommunications network, an intranet, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a public switched telephone network (PSTN), a Bluetooth network, a ZigBee network, or a near field communication (NFC) network, or any combination thereof. In some embodiments, the network may include one or more network access points. For example, the network may include wired or wireless network access points, such as base stations and / or network switching nodes, through which one or more components of the service request processing system can connect to the network to exchange data and / or information.

[0204] The processor 22 may be an integrated circuit chip with signal processing capabilities, and may include one or more processing cores (e.g., a single-core processor or a multi-core processor). By way of example only, the processor described above may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), an Application Specific Instruction-set Processor (ASIP), a Graphics Processing Unit (GPU), a Physics Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a microcontroller unit, a Reduced Instruction Set Computing (RISC) computer, or a microprocessor, or any combination thereof.

[0205] Understandable. Figure 5 The structure shown is for illustrative purposes only. Electronic devices may also have more advanced features. Figure 5 Showing more or fewer components, or having with Figure 5 The different configurations shown. Figure 5 The components shown can be implemented using hardware, software, or a combination thereof.

[0206] It should be understood that the apparatus and methods disclosed in the above embodiments can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0207] The above descriptions are merely various embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A conflict detection method for multi-user operations, characterized in that, The method includes: Receive a synchronization request sent by the client, wherein the synchronization request includes version information of the local model and modification information of the local model; If the versions of the local model and the cloud model are inconsistent, then based on the modification information, the target component with multiple modification conflicts is determined. If there is an implicit conflict among the multiple modification conflicts, then multiple linked conflicts that are interconnected are identified from the multiple modification conflicts, wherein the multiple linked conflicts are characterized by mutual correlation in function or performance. Obtain the design constraints or engineering specifications corresponding to the various linkage conflicts mentioned above; Calculate the performance degradation index or the degree of violation of technical standards of the various linkage conflicts under the design constraints or engineering specifications; The degree of conflict of the implicit conflict is obtained based on the performance degradation index or the degree of violation; Obtain the degree of conflict of the various modification conflicts; Generate conflict description information, wherein the conflict description information includes the conflict degree of the various modification conflicts and the conflict degree of the implicit conflicts; The conflict description information is processed by calling a pre-trained conflict decision model to obtain a synchronization strategy for the synchronization request. The pre-trained conflict decision model is a large language model with engineering semantic understanding capabilities. Execute the synchronization strategy.

2. The conflict detection method for multi-user operations according to claim 1, characterized in that, The degree of conflict among the various modification conflicts includes the first degree of conflict of material conflicts. Obtaining the degree of conflict among the various modification conflicts includes: Obtain the first material used by the target component in the cloud model and the second material used by the target component in the local model; To determine the degree of change in material properties between the first material and the second material; The degree of change is mapped to a first degree of conflict between 0 and 1.

3. The conflict detection method for multi-user operations according to claim 1, characterized in that, The conflict degree of the various modification conflicts includes a second conflict degree of geometric conflict. Obtaining the conflict degree of the various modification conflicts includes: Obtain the first bounding box of the target component in the cloud model and the second bounding box in the local model; If the overlap rate between the first bounding box and the second bounding box is less than the overlap threshold, then the geometric deviation of the target component between the cloud model and the local model is obtained; The geometric deviation is mapped to a second degree of conflict between 0 and 1.

4. The conflict detection method for multi-person operations according to claim 3, characterized in that, Obtaining the geometric deviation of the target component between the cloud model and the local model includes: Extract a first set of feature points of the target component in the cloud model and a second set of feature points in the local model, wherein the first set of feature points and the second set of feature points come from the same location of the target component; The first feature point set and the second feature point set are registered, and the average deviation between the first feature point set and the second feature point set is calculated based on the registration result. The average deviation is taken as the geometric deviation.

5. The conflict detection method for multi-person operations according to claim 1, characterized in that, The conflict degree of the various modification conflicts includes the third conflict degree of the topology conflict. Obtaining the conflict degree of the various modification conflicts includes: Obtain the first topological adjacency matrix of the target component in the cloud model and the second topological adjacency matrix in the local model; Based on the first topological adjacency matrix and the second topological adjacency matrix, the number of connection changes is obtained; The number of connection changes is mapped to a third level of conflict between 0 and 1.

6. A collision detection device for multi-person operation, characterized in that, The device includes: The synchronization interaction module is used to receive synchronization requests sent by the client, wherein the synchronization request includes version information of the local model and modification information of the local model; The conflict identification module is used to determine, based on the modification information, the target component that has multiple modification conflicts if the versions of the local model and the cloud model are inconsistent. The conflict analysis module is used to identify multiple linked conflicts that are interconnected if there are implicit conflicts among the multiple modification conflicts. The multiple linked conflicts are characterized by mutual correlation in function or performance. Obtain the design constraints or engineering specifications corresponding to the various linkage conflicts mentioned above; Calculate the performance degradation index or the degree of violation of technical standards of the various linkage conflicts under the design constraints or engineering specifications; The degree of conflict of the implicit conflict is obtained based on the performance degradation index or the degree of violation; The conflict analysis module is further configured to: obtain the conflict degree of the various modification conflicts; generate conflict description information, wherein the conflict description information includes the conflict degree of the various modification conflicts and the conflict degree of the implicit conflict; call a pre-trained conflict decision model to process the conflict description information to obtain a synchronization strategy for the synchronization request; and execute the synchronization strategy, wherein the pre-trained conflict decision model is a large language model with engineering semantic understanding capabilities.

7. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the conflict detection method for multi-user operations as described in any one of claims 1-5.

8. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing a computer program, which, when executed by the processor, implements the conflict detection method for multi-user operations as described in any one of claims 1-5.

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