Intelligent manufacturing control system and method for precise part machining

Abstract

The invention provides an intelligent manufacturing control system and method for precision part machining, and the method comprises the steps: extracting the geometric entity information of a to-be-machined part from the three-dimensional CAD model data of the to-be-machined part, and constructing a topological association graph of the to-be-machined part according to the geometric entity information; all machining feature partition surfaces in the topological association graph are extracted based on machining navigation parameters of the topological structure of the to-be-machined part, and a topological cooperation path of the to-be-machined part is recognized according to the contact relation between the machining feature surfaces in all the machining feature partition surfaces and the datum plane; according to an association surface set associated with the topology cooperation path in the topology association graph, combining edge concavity and convexity codes of the to-be-processed part to construct processing constraint features; and the to-be-machined part is machined on the basis of a tool movement path generated by the machining constraint features. According to the technical scheme provided by the invention, the topological incidence relation between the surfaces of the precision part can be identified, and the generated tool path is prevented from generating machining conflicts in the machining process.

Description

Technical Field

[0001] The present application relates to the field of intelligent manufacturing control technology. More specifically, the present application relates to an intelligent manufacturing control system and method for precision parts processing. Background Art

[0002] In today's rapidly developing science and technology, the manufacturing industry is undergoing profound changes. In the early days, it moved from manual manufacturing to automated manufacturing, relying on automated control systems to achieve process, mechanical and electronic automation. However, with the expansion of industrial production scale and the increase in complexity, traditional automated control has become insufficient, and intelligent manufacturing control has emerged. Intelligent manufacturing control integrates cutting-edge technologies such as artificial intelligence, big data, the Internet of Things, and cloud computing to provide modern manufacturing with efficient and intelligent solutions, becoming the core force for improving productivity and competitiveness.

[0003] In the precision parts processing control in the existing intelligent manufacturing control, the various operations, steps and part shape and size information required for processing precision parts are pre-compiled into a CNC processing program with code, and transmitted to the CNC system through the input device. After the CNC system decodes the program, it calculates the control instructions for each cycle and distributes them to the drive circuit of each motion axis. The drive motor drives the axis to move, thereby processing precision parts that meet high-precision requirements. However, in the precision parts processing control process, precision parts usually have multiple faces. Traditional processing methods only perform processing feature recognition based on geometric models, and fail to identify the topological relationship between the faces of the parts, resulting in processing conflicts when the generated tool path is processed in the feature intersection area. Therefore, how to identify the topological relationship between the faces of precision parts and avoid processing conflicts in the generated tool path during processing has become a difficult problem faced by the industry. Summary of the Invention

[0004] The present application provides an intelligent manufacturing control system and method for precision parts processing, which can identify the topological relationship between the surfaces of precision parts and avoid processing conflicts in the generated tool path during the processing.

[0005] In a first aspect, the present application provides an intelligent manufacturing control method for precision parts processing, comprising the following steps:

[0006] Obtain 3D CAD model data of parts to be processed;

[0007] Extracting geometric entity information of the parts to be processed from the three-dimensional CAD model data, and constructing a topological association diagram of the parts to be processed according to the attribute status of each geometric element in the geometric entity information;

[0008] Based on the processing navigation parameters of the topological structure of the part to be processed, the topological association graph is deeply traversed to obtain all processing feature partition surfaces, and then the topological collaborative path between the surfaces when processing the part to be processed is identified according to the contact relationship between the processing feature surfaces and the reference surface in each processing feature partition surface;

[0009] Determining a set of associated surfaces associated with the topological collaborative path in the topological association graph, and then constructing a processing constraint feature of the component to be processed based on associated surfaces constrained by the processing technology in the associated surface set and edge concavity coding of the component to be processed;

[0010] A tool motion path of the component to be processed is generated based on the processing constraint feature, and the tool motion path is used to control the tool to process the component to be processed.

[0011] In some embodiments, extracting geometric entity information of the part to be processed from the 3D CAD model data specifically includes:

[0012] Parsing the three-dimensional CAD model data to obtain geometric definition units constituting the part to be processed;

[0013] Extracting a set of geometric elements including faces, edges, and vertices based on the geometric definition unit;

[0014] Identifying the size, normal, and curvature attribute states of each geometric element in the geometric element set to form a geometric attribute description;

[0015] The geometric attribute description is associated with the geometric element set to generate geometric entity information of the part to be processed.

[0016] In some embodiments, constructing a topological association graph of the to-be-processed component based on the attribute states of each geometric element in the geometric entity information specifically includes:

[0017] Extracting the connection relationship and spatial attributes of each geometric element in the geometric entity information;

[0018] Generate a mapping table of geometric connection nodes and edges based on the connection relationship and the spatial attributes;

[0019] Establishing a directed connection relationship between geometric connection nodes according to the mapping table of geometric connection nodes and edges combined with the attribute status of each geometric element;

[0020] The geometric connection nodes with the directed connection relationship are organized into a graph structure to obtain a topological association graph of the parts to be processed.

[0021] In some embodiments, the topology association graph is deeply traversed based on the processing navigation parameters of the topological structure of the component to be processed to obtain all processing feature partition surfaces, specifically including:

[0022] Set the processing navigation parameters including processing direction, feed path, and processing priority according to the topological structure of the parts to be processed;

[0023] Taking a preset starting node in the topological association graph as an entry, a depth-first traversal operation is performed according to the processing direction in the processing navigation parameter;

[0024] During the traversal process, the geometric connection path that meets the processing conditions is screened out based on the processing priority and feed path;

[0025] The geometric surfaces constituting the continuous processing units are extracted along the geometric connection path as processing feature partition surfaces, and all processing feature partition surfaces are obtained.

[0026] In some embodiments, identifying the topological collaborative path between the surfaces when processing the component to be processed based on the contact relationship between the processing feature surface and the reference surface in each processing feature partition surface specifically includes:

[0027] Extracting the machining feature surface and the corresponding reference surface in each machining feature partition surface;

[0028] For each machining feature partition surface, determine the contact relationship between the machining feature surface and the reference surface;

[0029] Extracting a boundary connection sequence between the machining feature surface and the reference surface according to the contact relationship;

[0030] A topological collaborative path between faces when processing the component to be processed is constructed through the boundary connection sequence.

[0031] In some embodiments, determining the set of associated faces associated with the topological collaborative path in the topological association graph specifically includes:

[0032] Mapping the topology collaborative path into the topology association graph to obtain a collaborative path mapping graph;

[0033] Surfaces adjacent to the topological collaborative path are extracted from the collaborative path map as associated surfaces associated with the topological collaborative path, thereby obtaining an associated surface set associated with the topological collaborative path in the topological association map.

[0034] In some embodiments, 3D CAD model data of the component to be processed is extracted from a 3D CAD model file.

[0035] In a second aspect, the present application provides an intelligent manufacturing control system for precision parts processing, which is used to execute an intelligent manufacturing control method for precision parts processing, including:

[0036] An acquisition module is used to obtain the 3D CAD model data of the parts to be processed;

[0037] a processing module, configured to extract geometric entity information of the parts to be processed from the three-dimensional CAD model data, and construct a topological association graph of the parts to be processed according to the attribute states of each geometric element in the geometric entity information;

[0038] The processing module is further configured to perform a deep traversal of the topological association graph based on the processing navigation parameters of the topological structure of the component to be processed, obtain all processing feature partition surfaces, and then identify the topological collaborative path between the surfaces when processing the component to be processed based on the contact relationship between the processing feature surfaces and the reference surface in each processing feature partition surface;

[0039] The processing module is further configured to determine a set of associated surfaces associated with the topological collaborative path in the topological association graph, and then construct a processing constraint feature of the component to be processed based on the associated surfaces constrained by the processing technology in the set of associated surfaces in combination with the edge concavity and convexity coding of the component to be processed;

[0040] An execution module is used to generate a tool motion path for the part to be processed based on the processing constraint feature, and control the tool motion path to process the part to be processed

[0041] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores code, and the processor is configured to obtain the code and execute the above-mentioned intelligent manufacturing control method for precision parts processing.

[0042] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned intelligent manufacturing control method for precision parts processing.

[0043] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0044] In the intelligent manufacturing control system and method for precision parts processing provided by the present application, first, three-dimensional CAD model data of the part to be processed is obtained; secondly, geometric entity information of the part to be processed is extracted from the three-dimensional CAD model data, and a topological association graph of the part to be processed is constructed according to the attribute status of each geometric element in the geometric entity information; further, the topological association graph is deeply traversed based on the processing navigation parameters of the topological structure of the part to be processed to obtain all processing feature partition surfaces, and then the topological collaborative path between the surfaces when processing the part to be processed is identified according to the contact relationship between the processing feature surface and the reference surface in each processing feature partition surface; then, the associated surface set associated with the topological collaborative path in the topological association graph is determined, and then the processing constraint features of the part to be processed are constructed according to the associated surfaces constrained by the processing process in the associated surface set combined with the edge convexity coding of the part to be processed; finally, the tool motion path of the part to be processed is generated based on the processing constraint features, and the tool motion path controls the tool to process the part to be processed.

[0045] It can be seen that the present application identifies the topological association relationship between the various faces of precision parts to avoid processing conflicts in the generated tool path during the processing; first, the 3D CAD model data of the parts to be processed is obtained to provide a computable geometric and process data basis for subsequent processing; secondly, the geometric entity information of the parts to be processed is extracted from the 3D CAD model data, and the topological association graph of the parts to be processed is constructed based on the attribute status of each geometric element in the geometric entity information. The geometric information in the CAD model data can be converted into executable intelligent processing logic to realize automatic reasoning from design form to processing sequence; further, all processing feature partition surfaces are extracted from the topological association graph based on the processing navigation parameters of the topological structure of the parts to be processed, and then the topological collaborative path between the faces when processing the parts to be processed is identified according to the contact relationship between the processing feature faces and the reference plane in each processing feature partition surface, so as to intelligently integrate the topological association relationship between the faces of the identified components and the multi-process process constraints, and the discrete processing features are converted into the topological association graph. The feature partitions (such as reference planes) are dynamically connected in series to form a globally optimal tool motion chain, thereby significantly improving the overall processing efficiency and eliminating the conflict risk between processes while ensuring the single feature processing accuracy; then, the set of associated surfaces associated with the topological collaborative path in the topological association graph is determined, and then the processing constraint features of the parts to be processed are constructed based on the associated surfaces constrained by the processing technology in the associated surface set combined with the edge convexity coding of the parts to be processed, so as to integrate the geometric characteristics of the parts (such as edge convexity, thin-wall structure) and process requirements (such as surface accuracy, cutting force limitation) to construct quantifiable and executable digital process rules, so as to dynamically avoid interference risks and optimize cutting parameters during intelligent processing; finally, the tool motion path of the parts to be processed is generated based on the processing constraint features, and the tool motion path controls the tool to process the parts to be processed; in summary, the technical solution provided by the present application can identify the topological association relationship between the surfaces of precision parts, and avoid processing conflicts in the generated tool path during the processing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is an exemplary flow chart of an intelligent manufacturing control method for precision parts processing according to some embodiments of the present application;

[0047] Figure 2 is an exemplary flow chart for determining geometric entity information according to some embodiments of the present application;

[0048] Figure 3 This is a schematic diagram of the structure of an intelligent manufacturing control system for precision parts processing according to some embodiments of the present application;

[0049] Figure 4It is a structural diagram of a computer device for implementing an intelligent manufacturing control method for precision parts processing according to some embodiments of the present application. DETAILED DESCRIPTION

[0050] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0051] refer to Figure 1 , which is an exemplary flow chart of an intelligent manufacturing control method for precision parts processing according to some embodiments of the present application, and mainly includes the following steps:

[0052] In step S101 , three-dimensional CAD model data of a component to be processed is obtained.

[0053] In specific implementation, the 3D CAD model data of the parts to be processed is extracted from the 3D CAD model file. The 3D CAD model file refers to a digital 3D entity file generated by computer-aided design (CAD) software. It accurately describes the structural characteristics, dimensional tolerances and assembly relationships of precision parts through mathematically expressed geometric shapes, and contains topological connection information (the correlation between points, edges, and faces) and manufacturing properties (materials, surface roughness, etc.), providing a computable geometric and process data basis for subsequent processing.

[0054] It should be noted that the three-dimensional CAD model data in this application refers to a structured data set generated by a computer-aided design (CAD) system that accurately describes the geometry and manufacturing characteristics of the parts to be processed in a digital manner.

[0055] In step S102, geometric entity information of the part to be processed is extracted from the three-dimensional CAD model data, and a topological association graph of the part to be processed is constructed according to the attribute status of each geometric element in the geometric entity information.

[0056] In some embodiments, reference Figure 2 As shown in FIG. 1 , this figure is an exemplary flow chart for determining geometric entity information according to some embodiments of the present application. In this embodiment, the geometric entity information of the to-be-processed parts can be extracted from the 3D CAD model data by using the following steps:

[0057] In step S1021, the three-dimensional CAD model data is parsed to obtain geometric definition units constituting the part to be processed;

[0058] In step S1022, a set of geometric elements including faces, edges, and vertices is extracted based on the geometric definition unit;

[0059] In step S1023, the size, normal, and curvature attribute states of each geometric element in the geometric element set are identified to form a geometric attribute description;

[0060] In step S1024, the geometric attribute description is associated with the geometric element set to generate geometric entity information of the part to be processed.

[0061] In specific implementation, first, the existing data parser can be used to parse the 3D CAD model data to decompose the 3D CAD model data into geometric definition units of planes, cylinders or free-form surfaces, and the geometric definition units represent the mathematical elements that constitute the model of the part to be processed; secondly, a topological traversal algorithm (such as breadth-first search) is used to extract the faces, edges and vertices in the geometric definition units and combine them into a set of geometric elements; then, the geometric calculation module is called to identify the size, normal, and curvature of each geometric element in the geometric element set and combine them into a geometric attribute description; finally, a bidirectional index relationship is established between the geometric attribute description and the corresponding geometric element in the geometric element set through a hash mapping table, so as to generate geometric entity information of the part to be processed that contains complete topological connections and geometric characteristics.

[0062] It should be noted that the geometric entity information in this application represents a structured data set extracted from three-dimensional CAD model data that fully describes the geometric features and topological relationships of parts.

[0063] In some embodiments, constructing a topological association graph of a component to be processed based on the attribute states of each geometric element in the geometric entity information can be achieved by the following steps, namely:

[0064] Extracting the connection relationship and spatial attributes of each geometric element in the geometric entity information;

[0065] Generate a mapping table of geometric connection nodes and edges based on the connection relationship and the spatial attributes;

[0066] Establishing a directed connection relationship between geometric connection nodes according to the mapping table of geometric connection nodes and edges combined with the attribute status of each geometric element;

[0067] The geometric connection nodes with the directed connection relationship are organized into a graph structure to obtain a topological association graph of the parts to be processed.

[0068] In the specific implementation, the connection relationship (such as the connection relationship between faces and the connection relationship between edges and vertices) and spatial attributes (such as the relative positions of faces, vertices and edges) of each geometric element in the geometric entity information are extracted through the data processing tool Python; secondly, each geometric element is represented as a graph node, and the connection relationship is used as the edge between the graph nodes, and the corresponding spatial attributes are used as the weight of the edge to generate a mapping table of geometric connection nodes and edges; then, the attribute status of each geometric element is obtained (such as the priority processing order), and the edges in the mapping relationship table are added with directionality according to the processing order based on the attribute status of each geometric element, so as to form a directed connection relationship between the geometric connection nodes; the geometric connection nodes with the directed connection relationship are organized into a graph structure to obtain a topological association graph of the parts to be processed.

[0069] It should be noted that, in this embodiment, spatial attributes refer to the position parameters of geometric elements in three-dimensional space; in this embodiment, directed connection relationships refer to directional connection relationships between geometric elements, which are used to reflect the processing sequence and geometric constraint relationships; in this application, the topological association graph represents the spatial connection graph between the geometric elements of the parts to be processed, which is used to represent the spatial connection relationship, process constraints and processing sequence dependencies between the geometric elements (such as faces, edges, vertices) of the parts to be processed. Its core is to structure the processing features and manufacturing logic of geometric entities through the composition of nodes and directed edges. By determining the topological association graph, the intelligent manufacturing system can convert the geometric information of the CAD model into executable intelligent processing logic, and realize automatic reasoning from "design form" to "processing sequence"; in this embodiment, the geometric connection node refers to the graph node used to represent the machinable geometric feature unit in the topological association graph.

[0070] In step S103, the topological association graph is deeply traversed based on the processing navigation parameters of the topological structure of the part to be processed to obtain all the processing feature partition surfaces, and then the topological collaborative path between the surfaces when processing the part to be processed is identified according to the contact relationship between the processing feature surfaces and the reference surface in each processing feature partition surface.

[0071] In some embodiments, the topology association graph is deeply traversed based on the processing navigation parameters of the topological structure of the component to be processed to obtain all processing feature partition surfaces, which can be achieved by the following steps, namely:

[0072] Set the processing navigation parameters including processing direction, feed path, and processing priority according to the topological structure of the parts to be processed;

[0073] Taking a preset starting node in the topological association graph as an entry, a depth-first traversal operation is performed according to the processing direction in the processing navigation parameter;

[0074] During the traversal process, the geometric connection path that meets the processing conditions is screened out based on the processing priority and feed path;

[0075] The geometric surfaces constituting the continuous processing units are extracted along the geometric connection path as processing feature partition surfaces, and all processing feature partition surfaces are obtained.

[0076] In the specific implementation, first, the standard processing specifications of the part to be processed are read from the process database through the data processing tool Python, and the processing navigation parameters of the processing direction, feed path and processing priority are automatically generated by combining the geometric properties (such as normal vector, curvature) and process constraints (such as surface roughness requirements) of each geometric connection node in the topological association graph; secondly, the starting node marked in the topological association graph is used as the entry, and a depth-first traversal operation is performed according to the processing direction in the processing navigation parameters. Specifically, all adjacent geometric connection nodes of the current geometric connection node are accessed in a recursive manner, and the adjacent geometric connection node with the smallest angle between the normal vector and the tool axis is selected as the next search node according to the processing direction until all geometric connection nodes are searched; then, during the traversal process, the geometric connection path that meets the processing conditions is selected according to the processing priority and the feed path, that is, the geometric connection nodes with no conflicting processing priorities and continuous feed paths are sequentially obtained, and the connection path of all the obtained geometric connection nodes is used as the geometric connection path that meets the processing conditions; finally, the geometric surfaces constituting the continuous processing units are extracted along the geometric connection path as the processing feature partition surfaces, and all the processing feature partition surfaces are obtained.

[0077] It should be noted that the processing navigation parameters in this application refer to the key process control variables used to guide tool path planning and processing sequence optimization. Its essence is to quantify manufacturing experience, geometric constraints and processing goals into computable decision rules; in this embodiment, the geometric connection path represents the optimal node access path screened out in the topological association graph, which is used to convert discrete processing feature surfaces into continuously executable tool motion trajectories; in this application, the processing feature partition surface represents the geometric surface with similar processing attributes in the topological association graph. By determining the processing feature partition surface, the processing task of complex parts is decomposed into multiple continuous geometric surface units with consistent process attributes (such as tool type, cutting parameters, processing sequence), thereby optimizing tool path planning, reducing the number of processing interruptions, improving process execution efficiency, and ensuring the continuity and quality control of the processing process, avoiding tool interference and redundant operations.

[0078] In some embodiments, identifying the topological collaborative path between the surfaces when processing the component to be processed based on the contact relationship between the processing feature surface and the reference surface in each processing feature partition surface can be achieved by the following steps, namely:

[0079] Extracting the machining feature surface and the corresponding reference surface in each machining feature partition surface;

[0080] For each machining feature partition surface, determine the contact relationship between the machining feature surface and the reference surface;

[0081] Extracting a boundary connection sequence between the machining feature surface and the reference surface according to the contact relationship;

[0082] A topological collaborative path between faces when processing the component to be processed is constructed through the boundary connection sequence.

[0083] In the specific implementation, first, the machining feature surface (i.e., the feature surface used for actual machining in the machining feature partition surface) and the corresponding reference surface (i.e., the feature surface connected to the machining feature surface) contained in each machining feature partition surface are extracted by the existing geometric topology analysis method, and there is a common edge relationship between the machining feature surface and the corresponding reference surface, and the machining feature surface and the reference surface are combined into a pair relationship set of the machining feature surface and the reference surface; secondly, the intersection relationship between the machining feature surface and the reference surface is determined, that is: the intersection line between the machining feature surface and the reference surface is extracted by the existing boundary representation method, and the intersection relationship between the machining feature surface and the reference surface is described by the intersection line; then, the boundary connection sequence between the machining feature surface and the reference surface is extracted according to the intersection relationship, that is: the intersection line corresponding to the intersection relationship is discretized and sampled, and the sampling points that the tool cannot reach are removed, and then all the retained sampling points are combined into a boundary connection sequence according to the processing order; finally, the sampling points in the boundary connection sequence are connected according to the processing order to obtain the topological collaborative path between the surfaces when the parts to be processed are processed.

[0084] It should be noted that, in this embodiment, the machining feature surface represents a geometric surface with clear machining requirements on the component to be machined. These feature surfaces usually have a positioning or machining sequence dependency relationship with the reference plane, which is used to guide tool path planning and adaptive matching of cutting parameters; in this embodiment, the reference plane represents a geometric reference plane used to constrain the machining feature surface during component machining; in this embodiment, the contact relationship represents the spatial interaction state between the machining feature surface and the reference plane, specifically describing the contact form, connection method and topological continuity between the two on the geometric boundary; in this embodiment, the boundary connection sequence represents a set of ordered discrete points extracted on the contact boundary between the machining feature surface and the reference plane; in this application, the topological collaborative path represents the trajectory of cross-region collaborative machining. By determining the topological collaborative path, the topological association relationship between the surfaces of the components and the multi-process constraints are intelligently integrated and identified, and the discrete machining feature partitions (such as the reference plane) are dynamically connected in series to form a globally optimal tool motion chain, thereby significantly improving the overall machining efficiency and eliminating the risk of conflict between processes while ensuring the single feature machining accuracy.

[0085] In step S104, a set of associated faces associated with the topological collaborative path in the topological association graph is determined, and then the processing constraint features of the part to be processed are constructed based on the associated faces constrained by the processing technology in the associated face set combined with the edge concavity coding of the part to be processed.

[0086] In some embodiments, determining the set of associated faces associated with the topological collaborative path in the topological association graph may be implemented by the following steps, namely:

[0087] Mapping the topology collaborative path into the topology association graph to obtain a collaborative path mapping graph;

[0088] Surfaces adjacent to the topological collaborative path are extracted from the collaborative path map as associated surfaces associated with the topological collaborative path, thereby obtaining an associated surface set associated with the topological collaborative path in the topological association map.

[0089] In the specific implementation, first, the topological collaborative path is mapped into the topological association graph through the image processing tool OpenCV to obtain a collaborative path mapping graph; then, the faces adjacent to the topological collaborative path are extracted from the collaborative path mapping graph as associated faces associated with the topological collaborative path, and then a set of associated faces associated with the topological collaborative path in the topological association graph is obtained.

[0090] It should be noted that, in this embodiment, the collaborative path mapping diagram represents the diagram obtained by mapping the topological collaborative path into the topological association diagram; in this application, the association face set represents a combination of multiple association faces, and the association faces represent faces adjacent to the topological collaborative path. By determining the association face set, the interference features of the precision parts to be processed can be effectively identified.

[0091] In some embodiments, the following steps may be used to construct the processing constraint features of the part to be processed based on the associated surfaces constrained by the processing technology in the associated surface set and the edge concavity and convexity coding of the part to be processed, namely:

[0092] Extracting associated surfaces constrained by the machining process from the associated surface set;

[0093] Obtain edge concave-convexity code of the part to be processed;

[0094] Associating the edge concavity and convexity code with each associated surface constrained by the processing technology to form a processing constraint description with a concave-convex structure expression;

[0095] Construct the machining constraint features of the parts to be machined according to all machining restriction descriptions.

[0096] In a specific implementation, first, the process compliance index (such as the Gaussian curvature of the surface) of each associated surface in the associated surface set is calculated using an existing geometric analysis engine, and the associated surfaces whose process compliance index exceeds the threshold are screened out as associated surfaces subject to processing constraints. Secondly, the edge convexity code of the part to be processed is obtained based on the edge tracking algorithm of the existing chain code (i.e., the convex edge is coded as +1, the concave edge is coded as -1, and the straight line is 0). Then, the edge convexity code is associated with each associated surface subject to processing constraints to form a processing constraint description with a concave-convex structure expression. That is, the edge convexity code is embedded in the process attribute set of the associated surface subject to processing constraints using the image processing tool OpenCV to form a processing descriptor containing geometric structure constraints (for example, "the feed rate needs to be reduced for the concave edge connection surface"). Finally, the processing constraint features of the part to be processed are constructed based on all the processing constraint descriptions. That is, all the processing descriptors are integrated and an existing logical reasoning engine (such as a rule engine) is applied to generate a multi-level constraint network, and this multi-level constraint network is used as the processing constraint features of the part to be processed.

[0097] It should be noted that, in this embodiment, the edge convexity coding represents a digital label that quantitatively characterizes the geometric features of the component boundary. Its core is to convert the topological characteristics of the edge (such as convexity, concaveness or flatness) into a machine-recognizable discrete parameter sequence, so as to accurately express the contact mechanical characteristics of the tool-workpiece in the processing constraint modeling, and provide a structured geometric basis for intelligent process decision-making; in this embodiment, the processing constraint description represents structured data that formally expresses the interaction relationship between geometric features and process constraints in the processing process; in this application, the processing constraint feature represents the feature of the processing constraint on the component to be processed. The purpose of determining the processing constraint feature is to systematically integrate the geometric characteristics of the component (such as edge convexity, thin-wall structure) and process requirements (such as surface accuracy, cutting force limitation) to construct quantifiable and executable digital process rules, so as to dynamically avoid interference risks, optimize cutting parameters, and ensure the consistency of processing quality during the intelligent processing process.

[0098] In step S105 , a tool motion path of the component to be processed is generated based on the processing constraint feature, and the tool motion path is used to control the tool to process the component to be processed.

[0099] In some embodiments, generating a tool motion path for the component to be processed based on the processing constraint features, and controlling the tool to process the component to be processed by the tool motion path can be achieved by the following steps, namely:

[0100] Extracting the optimal feed direction and optimal obstacle avoidance strategy of the tool in the machining area according to the machining constraint characteristics;

[0101] Generate a tool motion path for the part to be processed according to the feed direction and the obstacle avoidance strategy;

[0102] The tool is driven to process the workpiece step by step according to the tool movement path.

[0103] In the specific implementation, first, the geometric constraints (such as edge convexity coding) and process parameter library (such as cutting parameter table) in the processing constraint features are parsed by the data processing tool Python, and the existing vector analysis method is used to calculate the optimal feed direction of the tool in the processing area (such as moving the tool in the direction of maximum curvature). At the same time, based on the existing space occupancy detection algorithm (such as octree collision detection), the optimal obstacle avoidance strategy of the tool in the processing area is generated; secondly, the feed direction and the obstacle avoidance strategy are used as constraints for path planning, and the tool motion path of the part to be processed is generated according to the isoparametric method in the parameterized path planning algorithm; then, the tool is driven to perform step-by-step processing on the part to be processed according to the tool motion path to complete the processing of the part to be processed.

[0104] In addition, in another aspect of the present application, in some embodiments, the present application provides an intelligent manufacturing control system for precision parts processing, referring to Figure 3 , which is a schematic diagram of the structure of an intelligent manufacturing control system for precision parts processing according to some embodiments of the present application. The intelligent manufacturing control system for precision parts processing includes: an acquisition module 201, a processing module 202, and an execution module 203, which are described as follows:

[0105] Acquisition module 201, in this application, acquisition module 201 is mainly used to obtain the three-dimensional CAD model data of the parts to be processed;

[0106] Processing module 202, in this application, is mainly used to extract geometric entity information of the parts to be processed from the three-dimensional CAD model data, and construct a topological association diagram of the parts to be processed based on the attribute status of each geometric element in the geometric entity information;

[0107] The processing module 202 is further configured to perform a deep traversal of the topological association graph based on the processing navigation parameters of the topological structure of the component to be processed, obtain all processing feature partition surfaces, and then identify the topological collaborative path between the surfaces when processing the component to be processed based on the contact relationship between the processing feature surfaces and the reference surface in each processing feature partition surface;

[0108] In addition, the processing module 202 is further configured to determine a set of associated surfaces associated with the topological collaborative path in the topological association graph, and then construct a processing constraint feature of the component to be processed based on the associated surfaces constrained by the processing technology in the associated surface set and the edge concavity and convexity coding of the component to be processed;

[0109] The execution module 203 in this application is mainly used to generate a tool motion path for the component to be processed based on the processing constraint feature, and control the tool to process the component to be processed by the tool motion path.

[0110] In addition, the present application also provides a computer device, which includes a memory and a processor, the memory storing a code, and the processor being configured to obtain the code and execute the above-mentioned intelligent manufacturing control method for precision parts processing.

[0111] In some embodiments, reference Figure 4 , which is a schematic diagram of the structure of a computer device for implementing an intelligent manufacturing control method for precision parts processing according to some embodiments of the present application. The intelligent manufacturing control method for precision parts processing in the above embodiment can be achieved by Figure 4 The computer device shown in FIG3 is implemented as shown in FIG3 , which includes at least one processor 301 , a communication bus 302 , a memory 303 and at least one communication interface 304 .

[0112] The processor 301 can be a general-purpose central processing unit (CPU), or an application-specific integrated circuit (ASIC) or one or more components for controlling the execution of the intelligent manufacturing control method for precision parts processing in this application.

[0113] The communication bus 302 may be used to transmit information between the aforementioned components.

[0114] Memory 303 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, a random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer. Memory 303 may be independent and connected to processor 301 via communication bus 302. Memory 303 may also be integrated with processor 301.

[0115] Memory 303 is used to store program code for executing the solution of the present application, and is controlled by processor 301 for execution. Processor 301 is used to execute the program code stored in memory 303. The program code may include one or more software modules. The determination of the intelligent manufacturing control method for precision parts processing in the above embodiment can be implemented by processor 301 and one or more software modules in the program code in memory 303.

[0116] The communication interface 304 uses any device such as a transceiver to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0117] In a specific implementation, as an example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor herein may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0118] The aforementioned computer device can be a general-purpose computer device or a dedicated computer device. In a specific implementation, the computer device can be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of this application do not limit the type of computer device.

[0119] In addition, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned intelligent manufacturing control method for precision parts processing.

[0120] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0121] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. An intelligent manufacturing control method for precision parts processing, characterized in that: The steps include: Obtain 3D CAD model data of parts to be processed; Extracting geometric entity information of the parts to be processed from the three-dimensional CAD model data, and constructing a topological association diagram of the parts to be processed according to the attribute status of each geometric element in the geometric entity information; The topological association graph is deeply traversed based on the machining navigation parameters of the topological structure of the part to be machined to obtain all machining feature partition surfaces, and then the topological collaborative paths between the surfaces when machining the part to be machined are identified based on the contact relationship between the machining feature surfaces and the reference surface in each machining feature partition surface; Determining a set of associated surfaces associated with the topological collaborative path in the topological association graph, and then constructing a processing constraint feature of the component to be processed based on associated surfaces constrained by the processing technology in the associated surface set and edge concavity coding of the component to be processed; A tool motion path of the component to be processed is generated based on the processing constraint feature, and the tool motion path is used to control the tool to process the component to be processed.

2. The method according to claim 1, wherein Extracting geometric entity information of the parts to be processed from the 3D CAD model data specifically includes: Parsing the three-dimensional CAD model data to obtain geometric definition units constituting the part to be processed; Extracting a set of geometric elements including faces, edges, and vertices based on the geometric definition unit; Identifying the size, normal, and curvature attribute states of each geometric element in the geometric element set to form a geometric attribute description; The geometric attribute description is associated with the geometric element set to generate geometric entity information of the part to be processed.

3. The method according to claim 1, wherein Constructing a topological association diagram of the parts to be processed according to the attribute states of each geometric element in the geometric entity information specifically includes: Extracting the connection relationship and spatial attributes of each geometric element in the geometric entity information; Generate a mapping table of geometric connection nodes and edges based on the connection relationship and the spatial attributes; Establishing a directed connection relationship between geometric connection nodes according to the mapping table of geometric connection nodes and edges combined with the attribute status of each geometric element; The geometric connection nodes with the directed connection relationship are organized into a graph structure to obtain a topological association graph of the parts to be processed.

4. The method according to claim 1, wherein The topological association graph is deeply traversed based on the processing navigation parameters of the topological structure of the parts to be processed, and all processing feature partition surfaces are obtained, including: Set the processing navigation parameters including processing direction, feed path, and processing priority according to the topological structure of the parts to be processed; Taking a preset starting node in the topological association graph as an entry, a depth-first traversal operation is performed according to the processing direction in the processing navigation parameter; During the traversal process, the geometric connection path that meets the processing conditions is screened out based on the processing priority and feed path; The geometric surfaces constituting the continuous processing units are extracted along the geometric connection path as processing feature partition surfaces, and all processing feature partition surfaces are obtained.

5. The method according to claim 1, wherein Based on the contact relationship between the machining feature surface and the reference surface in each machining feature partition surface, the topological collaborative path between the surfaces when machining the parts to be machined is identified, specifically including: Extracting the machining feature surface and the corresponding reference surface in each machining feature partition surface; For each machining feature partition surface, determine the contact relationship between the machining feature surface and the reference surface; Extracting a boundary connection sequence between the machining feature surface and the reference surface according to the contact relationship; A topological collaborative path between faces when processing the component to be processed is constructed through the boundary connection sequence.

6. The method according to claim 1, wherein Determining a set of associated faces associated with the topological collaborative path in the topological association graph specifically includes: Mapping the topology collaborative path into the topology association graph to obtain a collaborative path mapping graph; Surfaces adjacent to the topological collaborative path are extracted from the collaborative path map as associated surfaces associated with the topological collaborative path, thereby obtaining an associated surface set associated with the topological collaborative path in the topological association map.

7. The method according to claim 1, wherein Extract the 3D CAD model data of the parts to be processed from the 3D CAD model file.

8. An intelligent manufacturing control system for precision parts processing, used to execute the intelligent manufacturing control method for precision parts processing according to any one of claims 1 to 7, characterized in that: include: An acquisition module is used to obtain the 3D CAD model data of the parts to be processed; a processing module, configured to extract geometric entity information of the parts to be processed from the three-dimensional CAD model data, and construct a topological association graph of the parts to be processed according to the attribute states of each geometric element in the geometric entity information; The processing module is further configured to perform a deep traversal of the topological association graph based on the processing navigation parameters of the topological structure of the component to be processed, obtain all processing feature partition surfaces, and then identify the topological collaborative path between the surfaces when processing the component to be processed based on the contact relationship between the processing feature surfaces and the reference surface in each processing feature partition surface; The processing module is further configured to determine a set of associated surfaces associated with the topological collaborative path in the topological association graph, and then construct a processing constraint feature of the component to be processed based on the associated surfaces constrained by the processing technology in the set of associated surfaces in combination with the edge concavity and convexity coding of the component to be processed; An execution module is used to generate a tool motion path for the component to be processed based on the processing constraint feature, and control the tool to process the component to be processed by the tool motion path.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores code, and the processor is configured to obtain the code and execute the intelligent manufacturing control method for precision parts processing as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the intelligent manufacturing control method for precision parts processing as described in any one of claims 1 to 7 is implemented.

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