Complex structure part machining data management system and application method thereof

Abstract

The invention relates to a complex structure part machining data management system, which establishes a three-layer database of a cutting / grinding foundation, a process foundation and a process, and develops a process knowledge system containing an application enabling tool. According to the system, firstly, machining hierarchical process data knowledge modeling is passed, and a machining data knowledge system is established; on the basis, a key material cutting / grinding basic database, a typical part machining characteristic process database and a part machining process database are constructed; hierarchical processing data bidirectional mapping is carried out, and the data flow direction among the three databases is broken through; and finally, carrying out knowledge-driven rapid programming technology research, integrating a technology knowledge rapid programming template and a programming strategy, realizing rapid programming based on a part technology processing strategy, and carrying out integrated application of physical simulation of a typical part cutting processing technology. The system provides theory, technology and platform support for solving the problems of accumulation, reuse, data generation and the like of complex structure part machining basic data knowledge, and promotes improvement of complex structure part manufacturing capability and technical level.

Description

Technical Field

[0001] The invention relates to a complex structure part machining data management system and an application method thereof. Background Art

[0002] The efficient and precise machining of complex structural parts is not only the core of the country's major strategic needs, but also the frontier field of international engineering science. Its technical complexity, long R&D cycle and huge capital demand make the precision manufacturing of complex parts a top challenge in modern industry, known as the "crown jewel of modern industry". Compared with mechanical manufacturing powers such as Europe and the United States, my country still has a certain gap in the cutting / grinding technology level of difficult-to-process materials. It is mainly reflected in the lack of systematic combing, induction and evaluation of relevant data knowledge, resulting in the immature development and application of enabling tools such as data knowledge reuse reasoning and rapid programming. This directly affects the machining accuracy and consistency of complex structural parts, and then affects the overall performance and reliability of the parts.

[0003] At the same time, the existing domestic processing databases, knowledge bases and process software are mostly independent, without model libraries and algorithm libraries matching the process software, and have poor practicality. In addition, there is a lack of effective process data and knowledge mining and reasoning technology, making it difficult to achieve automatic updating of knowledge, and a lack of self-learning ability for rule knowledge. Once the processing environment changes, the original process data and knowledge cannot guide the decision-making of new process problems well.

[0004] In summary, although certain achievements have been made in the research of databases and process software at home and abroad, further exploration and innovation are still needed to meet the data knowledge management needs of cutting / grinding technology for complex structural parts and difficult-to-process materials. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a complex structure parts machining data management system and an application method thereof in view of the above-mentioned deficiencies in the prior art.

[0006] The technical problem to be solved by the present invention can be achieved by the following technical solutions:

[0007] The present invention is based on a complex structure parts machining data management system, and supports the construction of a complex structure parts machining basic data knowledge system platform through the construction of a mechanical machining hierarchical process data knowledge modeling method and system. In the specific implementation process, three levels of mutually verified databases are constructed, including: a key material cutting / grinding basic processing database, a typical feature process basic database for process preparation, and a cutting / grinding process database for on-site processing. On this basis, the typical feature process basic database for process preparation and the cutting / grinding process database for on-site processing are optimized and selected and used, and application enabling tools such as data mining / generation are developed. After that, by constructing a mechanical machining basic data knowledge system platform, characteristic process parameters, tool types, etc. are recommended as needed, programming strategy optimization is supported, and cutting / grinding fast programming is realized. At the same time, combined with the key material cutting / grinding basic processing database and cutting / grinding physical simulation, the iterative optimization of tool types and process parameters is completed, and finally a program for on-site processing is generated.

[0008] The basic database of cutting / grinding includes data on force, temperature, chip morphology, tool wear, and key indicators of surface integrity during the material cutting / grinding process, such as three-dimensional morphology of the machined surface, microstructure, microhardness, residual stress, etc. The data entry standard is that for the test data obtained through cutting / grinding simulation processing, the cutting / grinding basic database is entered in the format of tool / grinding parameters-workpiece material-process parameters-cutting data. Each entry data should meet the standard of complete information including workpiece material, process parameters, tool / grinding parameters, and cutting data; specific material data include composition, conventional mechanical properties, constitutive parameters, etc., tool data include geometric angles, base materials, coating materials, etc., and processing parameters include cutting / grinding speed, thickness, cooling and lubrication, etc.

[0009] The basic database of cutting / grinding processes includes 15 typical structures and their process features, such as center holes, transition fillets, stiffeners, thin-walled rings, bosses, grooves, holes, mounting edges, and webs. Parametric modeling is performed using typical geometric features, which also include information such as processing technology, to form a geometric feature model that meets the requirements of data exchange. Artificial neural network technology is used to construct a cross-correlation between processing tool parameters, performance, part structural features, and material properties, forming an intelligent correlation network between processing requirements and processing tool data sets, and realizing intelligent sorting and recommendation of part geometric feature processing methods and tools.

[0010] The process database collects data such as cutting force / heat, tool wear, processing efficiency, processing accuracy, surface quality, etc. during on-site processing, and combines part materials (brand, heat treatment status), blank form, typical structural characteristics, process route, processing stage, datum selection, allowance allocation, and process data to establish the collection strategy and specifications for on-site processing data of three types of typical parts; by clustering the working condition data, the distribution characteristics and laws of process data of typical parts under different process conditions are obtained; deep learning algorithms are developed, and process data knowledge prediction models are developed. The effective processing data of the first type of parts are: cutting force / heat, tool wear, processing efficiency, processing accuracy, surface quality, processing deformation, chatter, and surface integrity. The processing quality and efficiency data of the second type of parts are: cutting force / heat, tool wear, processing efficiency, processing accuracy, surface quality, processing deformation, chatter. The processing quality and efficiency data of the third type of parts are: cutting force / heat, tool wear, processing efficiency, processing accuracy, surface quality, and surface integrity; the process data-processing quality and efficiency evaluation specifications are formed, and the process strategy and cutting parameter range that match the evaluation requirements are established.

[0011] The present invention is based on an application method of a complex structure parts machining data management system, comprising:

[0012] On the basis of the three established databases, data of each process in parts manufacturing, process knowledge, tooling and equipment data are collected, and iterative optimization and integrated application of hierarchical databases and enabling tools are carried out to open up data transmission between various software such as databases, rapid programming, and physical simulation.

[0013] The product application chain is divided into objects, and the connotation of process chain and technology chain is used as the specific content. CNC programming templates for typical geometric structure features are formulated. Based on the identification of geometric features and parameter information, tool / grinding tool types, processing parameters and programming strategies are recommended, and rapid CNC machining programming and processing plan design of typical structural features are carried out.

[0014] Construct physical simulation environment for typical parts, typical structure processing models, and tool models; carry out physical simulation of CNC programs, processing plans, and processing squares based on typical material cutting performance data; and formulate CNC program simulation evaluation and optimization plans.

[0015] The beneficial effects and advantages of the present invention are:

[0016] The present invention breaks through the hierarchical data knowledge modeling technology, constructs a hierarchical process knowledge system, and realizes effective organization and management of knowledge; through the analysis of key material cutting / grinding tests, the mapping relationship between process parameters and surface quality is established to form cutting / grinding test specifications; then through typical parts processing feature process modeling and process performance evaluation and other technologies, the process data processing and storage specifications of the features are established; then the process data of typical parts are collected to form an evaluation method for field data; finally, through the storage / mining / evolution and reasoning technology of processing process data, the two-way mapping between data is realized, and a three-layer database of cutting / grinding foundation, cutting / grinding process, and process is established; through the cutting / grinding basic database and CNC programming template, the tool / grinding tool type, processing parameters and programming strategy corresponding to the feature are recommended to realize the rapid programming of typical structures and physical simulation verification. The present invention develops a typical parts machining data management system and its application method in view of the current problems of huge complex structure parts data knowledge, complex association rules, process strategies and parameters relying on experience knowledge, and conservative selection. It realizes the optimization of the whole process of complex parts manufacturing, shortens the process design cycle, reduces the process design cost, and thus achieves the goal of comprehensively improving the process design capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a design idea diagram for designing software for the present invention.

[0018] Figure 2 This is the process ontology knowledge model architecture diagram of the present invention.

[0019] Figure 3 Schematic diagram of the neural network operation for classifying process data of the present invention.

[0020] Figure 4 This is a diagram of the hierarchical database architecture of the present invention.

[0021] Figure 5 It is a structural diagram of process knowledge contained in the database of the present invention.

[0022] Figure 6 A workflow diagram quickly compiled for the program of the present invention. DETAILED DESCRIPTION

[0023] The present invention will be further described below in conjunction with the accompanying drawings.

[0024] The present invention is based on a complex structure parts machining data management system and its application method. The main research ideas are as follows: Figure 1 As shown, the software framework mainly includes 6 modules: process knowledge modeling, cutting / grinding basic database, process basic database, process database, rapid programming and physical simulation.

[0025] Focusing on the machining of typical parts of key materials of complex structural parts, research on ontology-based machining process data knowledge modeling, hierarchical machining process data classification technology, etc., to form a method for knowledge modeling of hierarchical machining process data; Figure 2 It expresses a separate process ontology partial knowledge model. Each module ontology library contains the corresponding class hierarchy and instances, and the attribute library is constructed separately. Instances refer to specific objects or events, while attributes are used to characterize the characteristics or traits of these objects or events. By clarifying and constraining the associations between each module ontology library or instance, the consistency and integrity of knowledge can be maintained. On this basis, we can build a comprehensive process ontology knowledge architecture, which uses a hierarchical structure to organize and manage process-related knowledge, making the acquisition, expression and application of knowledge easier and more efficient.

[0026] Implementing precise process data classification strategies, this project introduces a hierarchical machining data classification technology to meet the process data classification needs of typical parts. Its core framework is as follows: Figure 3 Display. First, an intelligent neural network classification system is constructed based on the classification coding rules. This system takes the core features of the parts as the input starting point. These features are processed through a deep processing layer - the hidden layer, which focuses on parsing key feature parameters such as the degree of surface curvature, aperture size, groove depth, and hole depth. Then, the system output layer will classify the process data into specific process categories such as cutting or grinding based on the results of the previous processing. Through the interactive interface between people and the system, users can train and optimize the classification system so that it can automatically and efficiently classify the process data of parts.

[0027] In terms of data storage, data storage is divided into three levels: cutting / grinding basic data layer, process basic data layer, and process data layer. Figure 4 shown.

[0028] The basic data layer for machining mainly stores basic data such as tool coating, cutting edge geometry, constitutive equation, cutting force, temperature, chip load, stress, etc. in cutting, as well as basic data such as the organizational structure, abrasive type, binder type, porosity, grinding force, temperature, stress-strain, etc. of abrasive tools (mainly bonded abrasive grinding wheels) in grinding. The basic process data layer adds process information such as tool parameters, process methods, tool-workpiece contact relationship, etc. on the basis of the basic data layer for machining. The process data layer stores process system information such as tool-spindle subsystem information, workpiece-fixture subsystem information, processing environment information, CNC system information, system equipment response information, etc., as shown in the following figure. Figure 5 shown.

[0029] The testing and acquisition of basic machining data is the basis for accumulating the basic cutting / grinding database. This layer of database mainly obtains basic cutting / grinding data through the most basic orthogonal cutting / grinding: materials, micro-geometric information, tool materials, processing forms, ambient temperature, cooling lubrication, processing parameters, and force, temperature, chips, and tool damage information collected by experimental equipment. The cutting / grinding database management supports users to query, add, modify and delete basic cutting / grinding data, and provides one-click data import and export functions (supporting data formats such as excel or csv).

[0030] The second layer is the process base database, which includes the cutting / grinding process data for machining certain part features. The main stored data include: tool type, tool type, machining method, machining process, cooling and lubrication, machining parameters, part features, and information such as force, temperature, chips, and tool damage collected by experimental equipment. The process base database management supports users to query, add, modify and delete basic process base data, and provides one-click data import and export functions (supporting data formats such as excel or csv).

[0031] The third layer is the process database, which includes the process information of machining the entire part structure. The main stored data include: machine tool information, machine tool control system information, clamping method, machining method, machining process, cooling and lubrication, cutting / grinding parameters, part features, and force, temperature, tool wear and surface integrity information collected by experimental equipment. The process database management supports users to query, add, modify and delete basic process data, and provides one-click data import and export functions (supports data formats such as excel or csv).

[0032] Through the above-mentioned hierarchical architecture design, strong data and knowledge support is provided for the establishment of the machining process model, which can not only realize the effective management and utilization of historical process data, but also provide strong support for process optimization.

[0033] Integrated applications around fast programming modules such as Figure 6 As shown in the figure, this module supports users to search for process parameter data in the database. Users can retrieve complete relevant resource data by inputting material data, feature data, and equipment data, and then retrieve matching process parameter information from the process basic database and process database; ensuring the efficiency of retrieval and recording log-related information of the retrieval process. Among the input parameters, the material selection parameter supports search, and after selection, the material details and pictures are displayed for users to choose; the equipment selection displays the equipment picture, name and main parameters, and supports multiple equipment selection; the real-time feedback mechanism indicates whether the filled data is normal or incorrect, and the status button indicates.

[0034] The cutting force model prediction function of the model is supported. The processing data management system can calculate the preliminary optimal cutting parameters (such as tool type, cutting speed, feed rate, etc.) based on the material information and optimization algorithm input by the user. At the same time, the user can manually adjust some parameters according to their own experience and needs, and view and adjust them through the corresponding controls on the user interface. Finally, the processing route and optimal cutting parameters that meet the characteristics of the part are generated, and a report containing the calculation process and results is generated. All adjustment history and preference settings are recorded by the system for subsequent analysis and optimization.

[0035] In the integrated application around the physical simulation module, the material data retrieval function is supported, the material type and processing method information input by the user is received, and the necessary preprocessing and verification are performed. After that, data extraction is performed to extract the material data that matches the input information from the material basic database, ensure that the extracted data is accurate and complete, and convert the extracted material data into the format required for physical simulation. By preprocessing the material information and processing method input by the user, selecting the required simulation algorithm and model, and outputting visual reports and simulation reports, the user can customize the report name and file location. All historical simulation records and single simulation detailed data are recorded by the system for subsequent reference and analysis.

[0036] The present invention integrates and develops a comprehensive system of various types of knowledge in the field of mechanical processing. On the basis of mechanical processing process knowledge modeling, a three-layer database system of cutting / grinding basic data layer, process basic data layer and process data layer is constructed, and two-way mapping and data conversion between data layers are realized, so that users can easily access the required data. The present invention further enables decision-making, process optimization and technological innovation in the field of mechanical processing. It not only covers the basic knowledge system of mechanical processing, such as processing theory, process parameters, material properties, etc., but also deeply integrates cutting-edge knowledge resources such as advanced manufacturing concepts, innovative process means and rich case databases. Relying on this comprehensive knowledge platform, users can easily query, retrieve, deeply analyze and flexibly apply knowledge, thereby significantly improving the operating efficiency and finished product quality of mechanical processing. The present invention has far-reaching strategic value for supporting the high-performance manufacturing needs of complex structural parts, building a common data knowledge platform system serving the entire industry, and promoting the manufacturing technology of complex structural parts to a higher level, and has a strong driving effect on the overall progress of the industry.

Claims

1. A complex structure parts machining data management system and its application method, characterized by: The construction and application method of the data knowledge platform includes the following steps: Carry out hierarchical process data knowledge modeling for cutting / grinding, establish a machining data knowledge system, and form standard specifications and guidelines for process data evaluation, digital storage and application; Based on the basic information such as force, temperature, tool wear form and mechanism during the cutting / grinding process of key materials, determine the type of applicable tools or abrasives, the constitutive parameters of key materials for cutting / grinding, etc., and form a basic database for cutting / grinding; Carry out typical feature process modeling, process testing and performance optimization research to obtain optimized process data for common key features of typical parts and form a feature process basic database; then combine the relationship between part structure-processing position, process optimization and other contents, visualize them into specific cases of typical parts and form a part process database.

2. Conduct integrated application research on data optimization between hierarchical databases and enabling tools, and typical geometric feature processing data mapping functions. Conduct research on process knowledge-driven rapid programming technology, integrate process knowledge rapid programming templates and strategies, realize rapid programming based on part process processing strategies, and conduct physical simulation verification of typical part cutting processes.

3. A complex structure parts machining data management system and its application method according to claim 1, characterized in that: Aiming at the cutting / grinding process test data of key materials, characteristic structures, and typical parts, the neural network method is used to realize the classification of mechanical processing hierarchical process data knowledge, and the data knowledge hybrid drive method is used to establish the mechanical processing hierarchical process model; on this basis, the typical processing characteristics and working conditions are sorted out, and unified data collection, processing and data extraction specifications are formulated. On the basis of building the process data knowledge modeling method and system, standard specifications and guidelines for the digital storage and application of process data are formed.

4. A complex structure parts machining data management system and its application method according to claim 1, characterized in that: Focusing on the basic cutting / grinding tests of key materials, the influence of cutting / grinding parameters on force, temperature, microstructure and micromechanical state of the machined surface, and the influence mechanism of cutting interface force-heat coupling on tool wear are obtained. According to the storage standards, the material composition and mechanical performance parameters, micro-geometric information of the cutting edge, tool material and coating, processing form, ambient temperature, cooling and lubrication, cutting / grinding speed and thickness, force, temperature, chip graphics, three-dimensional morphology, surface organization, residual stress, surface hardness, cutting edge damage or wear form and other information experimental data collected by the test equipment are stored in the database to provide support for the selection of the basic process parameter range of material cutting / grinding and the determination of the process parameter domain in the forward process design.

5. The complex structure parts machining data management system and its application method according to claim 1, characterized in that: For typical complex structural parts, the typical structures and their process characteristics are classified and analyzed from 15 aspects, including center holes, transition fillets, stiffeners, thin-walled rings, bosses, grooves, holes, mounting edges, and webs. Parametric modeling and analysis of typical structural characteristics are carried out, and a processing technology model oriented to structural characteristics is established. Feature-based processing technology performance evaluation and optimization research is carried out, and a processing technology database of typical features of complex structural parts is developed; Focusing on the needs of process data collection, analysis, evaluation, optimization and application at the part level, we study the collection methods of on-site processing data, develop and compile collection templates, collect and compile existing basic process data, detect and collect characteristic process data, form data knowledge warehousing specifications, and establish a typical part process database; formulate corresponding data processing and warehousing specifications, and organically combine process knowledge acquisition, artificial intelligence reasoning and database systems to make the database operation process transparent to users and simplify user operations.

6. The complex structure parts machining data management system and its application method according to claim 1, characterized in that: Conduct research on rapid programming and physical simulation driven by process knowledge; users can use NC programming template tools to recommend tool / grinding tool types, processing parameters and programming strategies for cutting / grinding features through the cutting / grinding basic knowledge base and enabling tools, and conduct rapid NC machining programming and machining plan design for typical structural features; specifically, by inputting material data, feature data, and equipment data, complete relevant resource data can be retrieved, and then matching process parameter information can be retrieved from the process basic database and process database; based on the material information input by the user and the optimization algorithm, preliminary optimal cutting parameters (such as tool type, cutting speed, feed rate, etc.) are calculated, and users can manually adjust some parameters according to their own experience and needs, and view and adjust them through the corresponding controls on the user interface; by constructing a typical part physical simulation environment, a typical structure machining model, and a tool model, physical simulation verification of NC programs, machining plans, and machining processes is carried out based on typical material cutting performance data to verify the process feasibility of process machining data.

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