Processing stage cloud-edge cooperative driving reinforcement model lightweight design platform
The lightweight design platform for steel bar models driven by cloud-edge collaboration has solved the problem of disconnection between tunnel structure steel bar design and processing, achieved efficient data synchronization and multi-user collaboration, improved production efficiency and processing accuracy, and reduced production costs.
Patent Information
- Application Number
- CN202510832984.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-20
- Publication Date
- 2025-10-10
AI Technical Summary
The disconnect between tunnel structure steel bar design and processing leads to data transmission delays, long response times, frequent design changes, large amounts of waste, and high production costs. Existing technologies make it difficult to achieve real-time collaboration and efficient data synchronization.
The lightweight design platform for steel bar models driven by cloud-edge collaboration includes edge modeling, cloud services, data access, lightweight engines and collaborative service modules. It achieves efficient data synchronization and processing accuracy through distributed task scheduling, multi-source data standardization, lightweight processing and multi-user collaborative editing.
Reduce data transmission delays, improve response speed and processing efficiency, ensure processing accuracy, avoid traditional bottleneck problems, achieve efficient multi-user collaboration, and reduce production costs.
Smart Images
Figure CN120764014A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of construction engineering technology, and in particular to a lightweight design platform for steel bar models driven by cloud-edge collaborative driving during the processing stage. Background Art
[0002] The advent of CNC machining of tunnel structural steel bars has automated the transportation of raw steel, processing, welding, and collection of finished products, significantly reducing worker labor intensity and improving production efficiency and processing quality. However, the current design and processing of tunnel structural steel bars are largely disconnected. CNC machining of tunnel structural steel bars still relies on manual input of steel bar information at the design end, which is not only inefficient but also difficult to ensure accuracy.
[0003] Currently, most construction companies still use 2D drawings to guide manufacturing. Design information must undergo multiple manual conversions between BIM models and CNC processing equipment, resulting in high data distortion rates. The BIM model data volume for a single complex node often exceeds hundreds of MB, and loading time on mobile terminals at construction sites can be measured in minutes, making it difficult to meet the needs of real-time collaboration.
[0004] Moreover, the average response time for design changes involving multiple parties across multiple regions is generally more than 24 hours, which often results in frequent rework. In addition, the waste generated due to the disconnection between the model and the actual processing stage greatly increases production costs. To this end, a lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage is proposed. Summary of the Invention
[0005] In order to solve the technical problems existing in the above-mentioned prior art, the present invention provides a lightweight design platform for steel bar models that is collaboratively driven by cloud and edge in the processing stage.
[0006] To solve the above technical problems, the present invention provides the following technical solutions: a lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage, comprising an edge model design module, a cloud service module, a model data access module, a lightweight engine module, a collaborative service module and an application interface module. The edge model design module is electrically connected to the cloud service module. The edge model design module is used for steel bar modeling in an edge network computing environment. The cloud service module is used to establish a distributed task scheduling mechanism, dynamically optimize computing resource allocation, coordinate the nodes responsible for processing high-concurrency modeling requests, balance computing load nodes through dynamic resource scheduling, and process high-concurrency requests.
[0007] The model data access module is electrically connected to the cloud service module, and the model data access module is used for standardized access and semantic fusion of multi-source heterogeneous data;
[0008] The lightweight engine module is electrically connected to the cloud service module, and the lightweight engine module is used to compress the model data volume while ensuring processing accuracy;
[0009] The collaborative service module is electrically connected to the cloud service module, and is used to build a multi-user real-time collaborative editing environment, resolve concurrency conflicts, ensure causal consistency of operations, and achieve efficient data synchronization;
[0010] The application interface module is electrically connected to the cloud service module, and the application interface module is used to realize interface reuse throughout the entire process of design, implementation and material cutting.
[0011] Preferably, the edge model design module includes a parametric modeling module, and the model data formed by the parametric modeling module is stored in the form of structured tuples. The model data is mathematically defined as:
[0012] Medge=(ID, Pgeo, Pprocess, GLOD, Vversion);
[0013] Where D = ProjectID / TypeCode / Hash(L, φ, θ), ProjectID is the 8-bit project code, and the hash value is the SHA-256 digest based on the geometric parameters.
[0014] Pgeo = (L, φ, θ, R, Ccurve), defines the total length L, diameter φ, bending angle θ, bending radius R, and bending section control point Ccurve of the steel bar;
[0015] The optimal processing path BendOrder under the process constraints of welding type WeldType, sleeve specification SleeveSpec and bending order.
[0016] Preferably, the distributed task scheduling mechanism of the cloud service module adopts a mixed integer linear programming algorithm, and the objective function is to minimize the weighted sum of global task completion time and resource cost:
[0017]
[0018] Where T j is the task time of node j, C j is the resource cost, α and β are weight factors, w ij is the task weight, c j The computing power of the node.
[0019] Preferably, the data standardization output of the model data access module is a multidimensional tuple structure:
[0020]
[0021] The components are defined as follows: ID = ProjectID / / Hash (G ∪ A), ProjectID is a 12-digit project code;
[0022] G = (Type, BREP, glTF, CSG), defines the geometry type and boundary representation, lightweight mesh, and constructive solid geometry expressions;
[0023] A=[Design×Process], which includes the mapping between design attributes and process attributes
[0024] Preferably, the process-constrained QEM simplified algorithm introduces a bending radius deviation penalty term into the edge folding cost function;
[0025] Parametric compression, converting reinforcement geometry into constructive solid geometry representation:
[0026] Straight bars are described as:
[0027] The bending reinforcement is described as In the formula is the translation operator, is a Boolean union operation.
[0028] Preferably, the collaborative service module resolves multi-user concurrency conflicts through an operation conversion algorithm and a vector clock protocol, and the conflict resolution rules are formalized as follows:
[0029]
[0030] Where VC is the vector clock, which records the operation timing of each replica;
[0031] Preferably, the response model of the application interface module is based on the uniform resource description framework and the polymorphic interface mapping rule:
[0032]
[0033] Where RDF = (ID, Geometry, Material), MQC is the quality inspection rule set, and Pprocess contains processing parameters.
[0034] Preferably, the data flow transmission steps of the platform are as follows: the edge model design module receives user input and generates preliminary steel bar model data, the model data is transmitted to the cloud service module, the cloud service module performs data standardization, cleaning and analysis, the lightweight engine module optimizes the data and compresses the data volume, the collaborative service module performs multi-user real-time collaborative editing, and the application interface module transmits the optimized data to the design, implementation and cutting links;
[0035] Preferably, the compression target of the lightweight engine module satisfies:
[0036] Size(Glight)≤0.05·Size(Graw);
[0037] Where Graw is the original geometric data volume, and Glight is the lightweight data volume.
[0038] Preferably, the model data access module supports automatic parsing of the BIM format, and performs geometric integrity verification and process compliance review through a rule engine, including mandatory specification verification of the bending radius R≥2.5φ.
[0039] Compared with the prior art, the beneficial effects of the present invention are:
[0040] 1. The present invention sets up a cloud-edge collaboratively driven architecture, distributes the steel bar model design, data transmission and processing between the edge and the cloud, fully utilizes the rapid response capability of edge computing and the powerful computing resources of the cloud, realizes efficient lightweight design of steel bar models, reduces data transmission delay and computing burden, and improves the system's response speed and processing efficiency.
[0041] 2. This invention utilizes multi-layered data standardization, lightweight processing, and collaborative mechanisms to ensure unified processing and semantic fusion of heterogeneous data from diverse sources. A lightweight engine reduces model data volume and ensures processing accuracy. Furthermore, multi-user real-time collaborative editing and optimized cloud-based task scheduling enable efficient collaboration among multiple designers and devices, avoiding the bottlenecks inherent in traditional single-node processing and effectively improving work efficiency and data synchronization capabilities. BRIEF DESCRIPTION OF THE DRAWINGS
[0042] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION
[0043] The present invention will be further described below with reference to the accompanying drawings and embodiments, with respect to the above and other technical features and advantages of the present invention. However, the following embodiments are merely preferred embodiments of the present invention and are not exhaustive.
[0044] Example:
[0045] like Figure 1As shown, the present invention provides a lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage, including an edge model design module, a cloud service module, a model data access module, a lightweight engine module, a collaborative service module and an application interface module. The edge model design module is electrically connected to the cloud service module. The edge model design module is used for steel bar modeling in an edge network computing environment. The cloud service module is used to establish a distributed task scheduling mechanism, dynamically optimize computing resource allocation, coordinate each node responsible for processing high-concurrency modeling requests, balance computing load nodes through dynamic resource scheduling, and process high-concurrency requests;
[0046] The model data access module is electrically connected to the cloud service module, and the model data access module is used for standardized access and semantic fusion of multi-source heterogeneous data;
[0047] The lightweight engine module is electrically connected to the cloud service module, and the lightweight engine module is used to compress the model data volume while ensuring processing accuracy;
[0048] The collaborative service module is electrically connected to the cloud service module, and is used to build a multi-user real-time collaborative editing environment, resolve concurrency conflicts, ensure causal consistency of operations, and achieve efficient data synchronization;
[0049] The application interface module is electrically connected to the cloud service module, and the application interface module is used to realize interface reuse throughout the entire process of design, implementation and material cutting.
[0050] The edge model design module includes a parametric modeling module. The model data formed by the parametric modeling module is stored in the form of structured tuples. The mathematical definition of the model data is:
[0051] Medge=(ID, Pgeo, Pprocess, GLOD, Vversion);
[0052] Where D = ProjectID / TypeCode / Hash(L, φ, θ), ProjectID is the 8-bit project code, and the hash value is the SHA-256 digest based on the geometric parameters.
[0053] Pgeo = (L, φ, θ, R, Ccurve), defines the total length L, diameter φ, bending angle θ, bending radius R, and bending section control point Ccurve of the steel bar;
[0054] The optimal processing path BendOrder under the process constraints of welding type WeldType, sleeve specification SleeveSpec and bending order.
[0055] The distributed task scheduling mechanism of the cloud service module adopts a mixed integer linear programming algorithm, and the objective function is to minimize the weighted sum of global task completion time and resource cost:
[0056]
[0057] Where T j is the task time of node j, C j is the resource cost, α and β are weight factors, w ij is the task weight, c j The computing power of the node.
[0058] The data standardization output of the model data access module is a multidimensional tuple structure:
[0059]
[0060] The components are defined as follows: ID = ProjectID / / Hash (G ∪ A), ProjectID is a 12-digit project code;
[0061] G = (Type, BREP, glTF, CSG), defines the geometry type and boundary representation, lightweight mesh, and constructive solid geometry expressions;
[0062] A=[Design×Process], which includes the mapping between design attributes and process attributes
[0063] The process-constrained QEM simplification algorithm introduces a bending radius deviation penalty term into the edge folding cost function;
[0064] Parametric compression, converting reinforcement geometry into constructive solid geometry representation:
[0065] Straight bars are described as:
[0066] The bending reinforcement is described as In the formula is the translation operator, is a Boolean union operation.
[0067] The collaborative service module resolves multi-user concurrent conflicts through the operation conversion algorithm and vector clock protocol. The conflict resolution rules are formalized as follows:
[0068]
[0069] Where VC is the vector clock, which records the operation timing of each replica;
[0070] The response model of the application interface module is based on the uniform resource description framework and the polymorphic interface mapping rules:
[0071]
[0072] Where RDF = (ID, Geometry, Material), MQC is the quality inspection rule set, and Pprocess contains processing parameters.
[0073] The platform's data flow transmission steps are as follows: the edge model design module receives user input and generates preliminary steel bar model data. The model data is transmitted to the cloud service module. The cloud service module performs data standardization, cleaning and analysis. The lightweight engine module optimizes the data and compresses the data volume. The collaborative service module performs multi-user real-time collaborative editing. The application interface module transmits the optimized data to the design, implementation and cutting links.
[0074] The compression target of the lightweight engine module meets the following requirements:
[0075] Size(Glight)≤0.05·Size(Graw);
[0076] Where Graw is the original geometric data volume, and Glight is the lightweight data volume.
[0077] The model data access module supports automatic parsing of BIM formats and performs geometric integrity verification and process compliance review through a rule engine, including mandatory specification verification of bending radius R ≥ 2.5φ.
[0078] The above description is merely a preferred embodiment of the present invention and is intended to be illustrative rather than restrictive of the present invention. Those skilled in the art will appreciate that many changes, modifications, and even equivalents may be made to the present invention within the spirit and scope of the claims, all of which fall within the scope of protection of the present invention.
Claims
1. A lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage, including an edge model design module, a cloud service module, a model data access module, a lightweight engine module, a collaborative service module and an application interface module, characterized in that: The edge model design module is electrically connected to the cloud service module. The edge model design module is used for steel bar modeling in the edge network computing environment. The cloud service module is used to establish a distributed task scheduling mechanism, dynamically optimize computing resource allocation, coordinate the nodes responsible for processing high-concurrency modeling requests, balance computing load nodes through dynamic resource scheduling, and process high-concurrency requests; The model data access module is electrically connected to the cloud service module, and the model data access module is used for standardized access and semantic fusion of multi-source heterogeneous data; The lightweight engine module is electrically connected to the cloud service module, and the lightweight engine module is used to compress the model data volume while ensuring processing accuracy; The collaborative service module is electrically connected to the cloud service module, and is used to build a multi-user real-time collaborative editing environment, resolve concurrency conflicts, ensure causal consistency of operations, and achieve efficient data synchronization; The application interface module is electrically connected to the cloud service module, and the application interface module is used to realize interface reuse throughout the entire process of design, implementation and material cutting.
2. A lightweight steel model design platform driven by cloud-edge collaboration in the processing stage according to claim 1, characterized in that: The edge model design module includes a parametric modeling module. The model data formed by the parametric modeling module is stored in the form of structured tuples. The mathematical definition of the model data is: Medge=(ID, Pgeo, Pprocess, GLOD, Vversion); Where D = ProjectID / TypeCode / Hash(L, φ, θ), ProjectID is the 8-bit project code, and the hash value is the SHA-256 digest based on the geometric parameters. Pgeo = (L, φ, θ, R, Ccurve), defines the total length L, diameter φ, bending angle θ, bending radius R, and bending section control point Ccurve of the steel bar; The optimal processing path BendOrder under the process constraints of welding type WeldType, sleeve specification SleeveSpec and bending order.
3. The lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage according to claim 1 is characterized in that: The distributed task scheduling mechanism of the cloud service module adopts a mixed integer linear programming algorithm, and the objective function is to minimize the weighted sum of global task completion time and resource cost: Where T j is the task time of node j, C j is the resource cost, α and β are weight factors, w ij is the task weight, c j The computing power of the node.
4. The lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage according to claim 1 is characterized in that: The data standardization output of the model data access module is a multidimensional tuple structure: The components are defined as follows: ID = ProjectID / / Hash (G ∪ A), ProjectID is a 12-digit project code; G = (Type, BREP, glTF, CSG), defines the geometry type and boundary representation, lightweight mesh, and constructive solid geometry expressions; A = [Design × Process], which includes the mapping between design attributes and process attributes.
5. The lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage according to claim 1 is characterized in that: The process-constrained QEM simplification algorithm introduces a bending radius deviation penalty term into the edge folding cost function; Parametric compression, converting reinforcement geometry into constructive solid geometry representation: Straight bars are described as: The bending reinforcement is described as In the formula is the translation operator, is a Boolean union operation.
6. The lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage according to claim 1 is characterized in that: The collaborative service module resolves multi-user concurrent conflicts through the operation conversion algorithm and vector clock protocol. The conflict resolution rules are formalized as follows: Where VC is the vector clock, which records the operation timing of each replica.
7. The lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage according to claim 1 is characterized in that: The response model of the application interface module is based on the uniform resource description framework and the polymorphic interface mapping rules: Where RDF = (ID, Geometry, Material), MQC is the quality inspection rule set, and Pprocess contains processing parameters.
8. The lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage according to claim 1 is characterized in that: The data flow transmission steps of the platform are as follows: the edge model design module receives user input and generates preliminary steel bar model data. The model data is transmitted to the cloud service module. The cloud service module performs data standardization, cleaning and analysis. The lightweight engine module optimizes the data and compresses the data volume. The collaborative service module performs real-time collaborative editing by multiple users. The application interface module transmits the optimized data to the design, implementation and cutting links.
9. The lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage according to claim 1, characterized in that: The compression target of the lightweight engine module meets the following requirements: Size(Glight)≤0.05·Size(Graw); Where Graw is the original geometric data volume, and Glight is the lightweight data volume.
10. The lightweight design platform for steel bar models driven by cloud-edge collaboration in the processing stage according to claim 1, characterized in that: The model data access module supports automatic parsing of BIM formats and performs geometric integrity verification and process compliance review through a rule engine, including mandatory specification verification of bending radius R ≥ 2.5φ.