WO2023272836A1 - 一种基于加工知识的数控工艺设计及优化方法 - Google Patents

一种基于加工知识的数控工艺设计及优化方法 Download PDF

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WO2023272836A1
WO2023272836A1 PCT/CN2021/108407 CN2021108407W WO2023272836A1 WO 2023272836 A1 WO2023272836 A1 WO 2023272836A1 CN 2021108407 W CN2021108407 W CN 2021108407W WO 2023272836 A1 WO2023272836 A1 WO 2023272836A1
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processing
data
knowledge
feature
numerical control
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French (fr)
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牟文平
隋少春
高鑫
彭雨
王鹏程
李仁政
罗耀辉
唐李
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成都飞机工业（集团）有限责任公司
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/4097—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by using design data to control NC machines, e.g. CAD/CAM
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/35—Nc in input of data, input till input file format
    • G05B2219/35012—Cad cam
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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  • the invention relates to the technical field of numerical control process design, in particular to a numerical control process design and optimization method based on machining knowledge.
  • the NC machining process is the link connecting the part design model and the final product, and directly affects the final processing quality of the part.
  • the parts of the above products show a trend of becoming more complex and high-precision, and the processing difficulty is significantly increased, which puts forward higher requirements for CNC processing technology.
  • the existing process design method mainly adopts the computer-aided manufacturing mode of "human-computer interaction and human-oriented", which relies heavily on manual experience, low efficiency, and poor quality stability, which has seriously affected the development cycle of parts.
  • the process preparation of large frame parts of an aircraft The cycle is as long as 45 days, the human-computer interaction exceeds 200,000 times, and the ratio of process preparation time to CNC machining time is as long as 10:1.
  • the process knowledge cannot be accumulated and inherited under the existing process preparation mode, which has seriously restricted the improvement of the CNC process level.
  • an integrated process solution is urgently needed to realize the accumulation and reuse of process knowledge.
  • the existing public NC process design methods mainly include cutting parameter optimization, machining trajectory optimization, process decision-making based on knowledge base, etc., which can improve the level of NC process design to a certain extent, but have not realized the process closed-loop control in the NC process design stage. And the data connection for the whole process of product processing cannot effectively improve the level of CNC process design.
  • the present invention provides a numerical control process design and optimization method based on processing knowledge, so as to realize the process closed-loop control in the numerical control process design stage and the data connection oriented to the whole process of product processing, and effectively improve the level of numerical control process design .
  • the present invention adopts the following technical solutions:
  • a numerical control process design and optimization method based on processing knowledge comprising the following steps:
  • Step 1 Construct a processing knowledge data model with processing characteristics as the carrier, take the processing data flow as the main line, and orderly integrate programming, post-processing, cutting simulation, processing process monitoring and detection, and processing result detection to determine different storage data type, and store data in each link;
  • Step 2 Obtain the features to be processed from the parts, and based on the feature similarity evaluation method, obtain the similar feature set with the features to be processed from the constructed processing knowledge data model;
  • Step 3 Aiming at the historical processing effects of similar feature sets, based on the evaluation results of historical processing effects, and based on the entropy weight method, the comprehensive evaluation value of historical processing effects of similar features is obtained;
  • Step 4 Obtain the feature with the best comprehensive evaluation of historical processing effect and its corresponding process plan from the similar feature set, and use this process plan as the process plan of the feature to be processed;
  • Step 5 In the NC process design stage, based on software integration and processing data integration, the cutting simulation results are fed back to the programming stage as the basis for process optimization to realize closed-loop control in the process design stage;
  • Step 6 In the CNC machining stage of the part, the processing state monitoring and detection data is obtained during the processing, and the processing result detection data is obtained after processing;
  • Step 7 Store the processing state monitoring and detection data, processing result detection data and process design data in the processing knowledge data model as the basis for subsequent NC process optimization.
  • the processing features include feature type, feature geometric structure, feature geometric size, feature machining accuracy, feature material properties and positional relationship between features, and the feature types include grooves, ribs, holes and contours.
  • the data types in the processing knowledge data model include blank size, clamping scheme, processing procedure, processing step, processing machine tool, processing tool, processing feature, and cutting strategy , Tool advance and retreat mode and cutting parameters;
  • the data types in the processing knowledge data model include processing procedures, processing steps and NC programs.
  • the NC programs include NC codes, feature numbers, processing operation numbers, and processing process monitoring and detection instructions.
  • Processing process monitoring and detection instructions include probe detection trigger instructions and intermediate state monitoring trigger instructions;
  • the data types in the machining knowledge data model include cutting simulation files, NC programs, and simulation results.
  • the simulation results include abnormal information of parts machining undercut, overcut, and collision, machining simulation time information, and machining simulation.
  • Cutting volume change information
  • the data types of the process knowledge data model include NC program, machine tool power monitoring data, cutting vibration monitoring data, probe detection data in the middle state of the processing process and ultrasonic thickness measurement data in the middle state;
  • the data types in the processing knowledge data model include processing features, processing result detection program, feature shape and position tolerance detection data, feature size detection data and surface quality detection data.
  • the feature similarity evaluation method is: obtain the similarity between different features according to the evaluation index, and then obtain the feature set whose similarity with the feature to be processed is higher than the expected value;
  • the evaluation index includes feature type, material, Dimensions, structure, processing accuracy, processing machine tools and tools used.
  • the historical processing effect evaluation takes processing features and their corresponding processing technology as evaluation objects, including processing state evaluation and processing result evaluation, and the processing technology corresponding to processing features includes feature processing tooling strategy, cutting parameters , feature processing sequence, and processing resource information of machine tools and tools.
  • the evaluation of the state of the processing process refers to the evaluation of the state of the processing process when the processing features are processed by a certain process.
  • the evaluation indicators include tool vibration during the processing process, machine tool power signal changes, size changes in the intermediate state, and deformation of parts during processing. , Tool wear and abnormalities in the machining process.
  • the processing result evaluation refers to the evaluation of the processing results after the processing features are processed by a certain process
  • the evaluation indicators include processing time, final processing dimensional accuracy of features, surface processing quality, feature deformation and processing cost.
  • software integration refers to the effective integration of programming, post-processing and cutting simulation using CAM software as a platform in the part numerical control process design stage.
  • processing data integration includes process data integration and processing process data integration; where process data integration refers to the realization of characteristic Processing requirements, process steps, processing procedures, and simulation result data are transferred at each stage of the process design of programming, post-processing, and cutting simulation; processing process data integration refers to the realization of processing procedures, processing procedures,
  • process information of each processing step, the monitoring and testing data of the processing process and the testing data of the processing results are transmitted at each stage of the whole process of processing, and the monitoring and testing data of the processing process are fed back to the process design stage.
  • programming refers to the new compilation and optimization of processing procedures based on processing knowledge and processing process data, including process plan formulation, processing sequence planning, cutting parameter optimization and tool cutting strategy decision-making, and the implementation of the programming Standardized programming mode, including machining program naming, auxiliary geometry creation, part model, blank and tooling structure tree setting, the pre-program generated after the programming includes machining features and operation process information.
  • the post-processing refers to generating an NC program corresponding to the processing machine tool according to the pre-program, retaining processing features in the NC program, operating various process information, and adding a processing process monitoring detection trigger instruction to the NC program based on the processing requirements of the part .
  • the cutting simulation refers to the simulation verification of the cutting trajectory, and by integrating the processing experience and knowledge, the rationality of the use of the tool holder, the setting of the cutting amount, and the order of the working steps are checked, and the cutting simulation results are output and fed back to programming part.
  • the monitoring and detection of the machining process means that during the machining process, when the NC program runs to the monitoring and detection trigger command, the machining process monitoring program is activated, the machine tool power and cutting vibration monitoring data are obtained during the machining process, and the probe program is triggered to realize the intermediate state On-machine inspection and ultrasonic thickness measurement, and establish the relationship between processing data and NC program.
  • the detection of processing results means that after the processing of the part is completed, the final processing size, shape and position tolerance and surface quality of the part are measured according to the measurement program, and the relationship between the measurement data and the processing characteristics of the part is established.
  • the present invention can orderly integrate various links such as programming, post-processing, cutting simulation, processing process monitoring and detection, and processing result detection, so as to realize the effective accumulation of knowledge in the whole cycle of product processing, and based on the evaluation results of historical processing effects, it can realize Processing knowledge is reused to form a process closed-loop control oriented to the whole process of product processing, and to complete the design and optimization of NC process, thereby effectively avoiding the recurrence of historical processing quality problems, significantly improving the level of NC process design, and providing efficient and stable NC for intelligent processing. Process scheme.
  • the present invention feeds back the cutting simulation results as the basis for process optimization to the programming stage.
  • results and other data are transmitted in each stage of process design such as programming, post-processing, cutting simulation, etc., to achieve the purpose of closed-loop control in the stage of CNC process design;
  • the processing data is integrated into hierarchical process data integration and processing process data integration, and process data integration It can realize the transfer of data such as feature processing requirements, process steps, processing procedures, and simulation results in the process design stages of programming, post-processing, and cutting simulation, so as to achieve the purpose of closed-loop control in the NC process design stage;
  • process data integration It can realize the transmission of processing program, processing procedure, process information of processing steps, processing process monitoring and testing data and processing result testing data in each stage of the whole process of processing, and feed back the processing monitoring and testing data to the process design stage, so as to provide a solid
  • Fig. 1 is the schematic flow chart of a kind of numerical control process design and optimization method based on machining knowledge provided by the present invention
  • Fig. 2 is a schematic diagram of the process closed-loop control process for the whole process of product processing in the present invention
  • Figure 3 is a schematic diagram of the processing characteristics of a typical part.
  • this embodiment provides a numerical control process design and optimization method based on machining knowledge, including the following steps:
  • Step 1 Construct a processing knowledge data model with processing characteristics as the carrier, take the processing data flow as the main line, and orderly integrate programming, post-processing, cutting simulation, processing process monitoring and detection, and processing result detection to determine different storage data type, and store data in each link;
  • Step 2 Obtain the features to be processed from the parts, and based on the feature similarity evaluation method, obtain the similar feature set with the features to be processed from the constructed processing knowledge data model;
  • Step 3 Aiming at the historical processing effects of similar feature sets, based on the evaluation results of historical processing effects, and based on the entropy weight method, the comprehensive evaluation value of historical processing effects of similar features is obtained;
  • Step 4 Obtain the feature with the best comprehensive evaluation of historical processing effect and its corresponding process plan from the similar feature set, and use this process plan as the process plan of the feature to be processed;
  • Step 5 In the NC process design stage, based on software integration and processing data integration, the cutting simulation results are fed back to the programming stage as the basis for process optimization to realize closed-loop control in the process design stage;
  • Step 6 In the CNC machining stage of the part, the processing state monitoring and detection data is obtained during the processing, and the processing result detection data is obtained after processing;
  • Step 7 Store the processing state monitoring and detection data, processing result detection data and process design data in the processing knowledge data model as the basis for subsequent NC process optimization.
  • the processing knowledge data model uses processing characteristics as the carrier to realize the storage of processing knowledge, and through the orderly integration of programming, post-processing, cutting simulation, processing process monitoring and detection, processing result detection and other links, product processing can be realized
  • the effective accumulation of full-cycle knowledge, and based on the evaluation results of historical processing effects, can realize the reuse of processing knowledge (ie step 2 to step 4), form a process closed-loop control oriented to the whole process of product processing, and complete the design and optimization of NC process, so as to effectively avoid
  • the repeated occurrence of historical processing quality problems can significantly improve the level of CNC process design and provide efficient and stable CNC process solutions for intelligent processing.
  • the processing features include feature types, feature geometric structures, feature geometric dimensions, feature machining accuracy, feature material properties, and positional relationships between features.
  • the feature types include grooves, ribs, holes, and contours.
  • step 1 the data types stored in the processing knowledge data model are different for different links, so in step 1:
  • the data types in the processing knowledge data model include blank size, clamping scheme, processing procedure, processing step, processing machine tool, processing tool, processing feature, cutting strategy, cutting method, cutting parameter, etc. Process information and processing feature information;
  • the data types in the processing knowledge data model include processing procedures, processing steps, and NC programs.
  • Number, processing operation number, processing process monitoring and detection instructions the feature number format is "feature type + feature number", for example, the feature of No. 1 slot is “Pocket+0001", the feature of No. 1 rib is “Rib+0001", and the feature of No. 1 hole
  • the feature is "Hole+0001”
  • the format of the processing operation number is "processing procedure + processing step + operation type + operation number", for example, the third face milling operation in 15 process 03 step is "Process15+Step03+FaceMilling+0003 ”
  • process monitoring and detection instructions include probe detection trigger instructions, intermediate state monitoring trigger instructions, etc.;
  • the data types in the machining knowledge data model include cutting simulation files, NC programs, and simulation results.
  • the simulation results include abnormal information of parts machining undercut, overcut, and collision, machining simulation time information, and machining simulation.
  • Cutting volume change information and the above information is associated with the processing code in the NC program;
  • the data types of the processing knowledge data model include NC programs, machine tool power monitoring data, cutting vibration monitoring data, probe detection data in the middle state of the processing process, and ultrasonic thickness measurement data in the middle state; the above data are the same as those in the NC
  • the processing code in the program is associated, so that the monitoring data of the processing process can be matched with the process information, which is convenient for subsequent process optimization and analysis;
  • the data types in the processing knowledge data model include processing features, processing result detection programs, feature shape and position tolerance detection data, feature size detection data and surface quality detection data, and also include the above data and processing features. connection relation.
  • the feature similarity evaluation method is: obtain the similarity between different features according to the evaluation index, and then obtain the feature set whose similarity with the feature to be processed is higher than the expected value;
  • the evaluation index includes feature type, material, Dimensions, structure, processing accuracy, processing machine tools and tools used.
  • step three the evaluation of historical processing effects takes processing features and their corresponding processing technology as the evaluation object, including processing state evaluation and processing result evaluation. , feature processing sequence, and processing resource information of machine tools and cutting tools; among them,
  • the state evaluation of the processing process refers to the evaluation of the state of the processing process when the processing characteristics are processed by a certain process.
  • the evaluation indicators include the vibration of the tool during the processing process, the change of the power signal of the machine tool, the change of the size of the intermediate state, the deformation of the part during processing, and the wear of the tool. and abnormal conditions in the processing process; determine the evaluation factors of different evaluation indicators according to the degree of influence of the evaluation indicators on the final processing quality, cost, and efficiency of the feature, and obtain the evaluation value of the processing state through the weighting method;
  • the evaluation of processing results refers to the evaluation of the processing results after the processing features are processed by a certain process.
  • the evaluation indicators include processing time, final processing dimension accuracy of features, surface processing quality, feature deformation and processing cost;
  • the degree of importance determines the corresponding evaluation factor, and the evaluation value of the processing result can be obtained through the weighting method.
  • the comprehensive evaluation value of the processing process and processing result is based on the evaluation of the state of the processing process and the evaluation of the processing result, based on the entropy weight method to determine the state of the processing process and the influencing factors of the processing result, and then comprehensively calculate.
  • step five software integration refers to the effective integration of programming, post-processing and cutting simulation using CAM software as a platform in the stage of part NC process design.
  • the specific meaning of software integration in the process design stage is that after the program is compiled, the post-processing system is automatically invoked in the CAM environment to generate an NC program that matches the processing machine tool, and according to the part processing procedure and work step setting information, automatically generate Cutting simulation environment including parts, blanks, tooling, machine tools, and cutting tools.
  • the cutting simulation results will be fed back to the programming stage as the basis for process optimization, so that data such as feature processing requirements, process steps, processing programs, and simulation results can be integrated into the program.
  • the transmission of each stage of process design such as compilation, post-processing, and cutting simulation achieves the purpose of closed-loop control in the stage of CNC process design.
  • processing data integration includes process data integration and processing process data integration; wherein,
  • Process data integration refers to the realization of feature processing requirements, process steps, processing procedures, simulation results and other data in the process of programming, post-processing, The transfer of each stage of the process design of cutting simulation, so as to achieve the purpose of closed-loop control in the stage of CNC process design;
  • Processing process data integration refers to the transmission of processing program, processing procedure, process information of processing steps, processing process monitoring and detection data and processing result detection data at each stage of the whole processing process with processing characteristics as the carrier, and integrates processing process monitoring and detection The data is fed back to the process design stage, thus providing data support for NC process design and optimization.
  • programming refers to the new editing and optimization of machining programs based on machining knowledge and process data, including process plan formulation, machining sequence planning, cutting parameter optimization, and cutting tool strategy decision-making;
  • Software integration open up process data flow, program compilation implements standardized programming mode, including machining program naming, auxiliary geometry creation, part model, blank and tooling structure tree setting, the pre-program generated after programming contains processing features, and operates each process information.
  • post-processing refers to generating the NC program corresponding to the processing machine tool according to the pre-program, retaining the processing characteristics and operating various process information in the NC program, so as to realize the association of subsequent processing data with processing characteristics and operations, and facilitate processing abnormalities.
  • the traceability of the situation realizes the rapid positioning of the processing program of the abnormal part; and based on the processing requirements of the part, the processing process monitoring detection trigger instruction is added to the NC program, so as to realize the monitoring of the intermediate state of the critical part.
  • cutting simulation refers to the simulation verification of the cutting trajectory, and also checks the rationality of the use of the tool holder, the setting of the cutting amount, and the order of the working steps by integrating the processing experience and knowledge, and outputs the cutting simulation results, which are fed back to programming part.
  • the monitoring and detection of the machining process means that during the machining process, when the NC program runs to the monitoring and detection trigger command, the machining process monitoring program is activated, the machine tool power and cutting vibration monitoring data are obtained during the machining process, and the probe program is triggered to realize the intermediate state On-machine detection and ultrasonic thickness measurement, and establish the relationship between processing data and NC program, so as to realize on-machine detection and ultrasonic thickness measurement in the intermediate state.
  • the monitoring and detection data is stored in In the machining knowledge data model, data support is provided for NC process design and optimization.
  • the processing result inspection refers to the measurement of the final processing size, shape and position tolerance and surface quality of the part according to the measurement program after the part is processed, and the establishment of the relationship between the measurement data and the processing characteristics of the part. Based on the relationship between the above measurement data and the processing characteristics of the part, the processing result detection data is stored in the processing knowledge data model to provide data support for NC process design and optimization.

Abstract

一种基于加工知识的数控工艺设计及优化方法，其包括以加工特征为载体构建加工知识数据模型，有序集成程序编制、后置处理、切削仿真、加工过程监测检测、加工结果检测各环节，确定不同的存储数据类型，并进行各环节数据的存储。数控工艺设计及优化方法打通产品加工全流程数据流，实现产品加工全周期知识的有效积累，且通过建立加工知识同零件特征的关联关系，构建数控工艺基础数据模型，基于历史加工效果评价结果，实现加工知识重用，形成面向产品加工全流程的工艺闭环控制，完成数控工艺设计及优化，有效避免历史加工质量问题的重复发生，可显著提升数控工艺设计水平，为智能加工提供高效、稳定的数控工艺方案。

Description

一种基于加工知识的数控工艺设计及优化方法 技术领域
本发明涉及数控工艺设计技术领域，具体涉及一种基于加工知识的数控工艺设计及优化方法。
背景技术
数控加工工艺是连接零件设计模型与最终产品的纽带，直接影响零件的最终加工质量。在航空、航天、船舶等领域，随着飞机、火箭、舰船等产品性能提升，上述产品零件呈现复杂化、高精度化发展趋势，加工难度显著提升，对数控加工工艺提出了更高的要求。在上述领域多品种、小批量生产模式下，无法通过持续迭代优化方式获取高效稳定的工艺方案，且加工过程不可预测，因而对数控工艺设计水平提出了更高的要求。
现有工艺设计方法主要采用“人机交互、以人为主”的计算机辅助制造模式，严重依赖人工经验、效率低、质量稳定性差，已严重影响零件研制周期，如某飞机大型框类零件工艺准备周期长达45天，人机交互超过20万次，工艺准备时间与数控加工时间之比长达10:1。现有工艺准备模式下工艺知识无法积累和继承，已严重制约数控工艺水平的提升。为提升数控工艺技术水平，迫切需要一种集成工艺解决方案，实现工艺知识的积累和重用。
现有公开的数控工艺设计方法主要包括切削参数优化、加工轨迹优化、基于知识库的工艺决策等方向，可在一定程度上提高数控工艺设计水平，但并未实现数控工艺设计阶段的工艺闭环控制及面向产品加工全流程的数据贯通，不能有效提升数控工艺设计水平。
发明内容
针对现有技术中的缺陷，本发明提供一种基于加工知识的数控工艺设计及优化方法，以实现数控工艺设计阶段的工艺闭环控制及面向产品加工全流程的数据贯通，有效提升数控工艺设计水平。
为解决上述的技术问题，本发明采用以下技术方案：
一种基于加工知识的数控工艺设计及优化方法，包括以下步骤：
步骤一：以加工特征为载体构建加工知识数据模型，以加工数据流为主线，有序集成程序编制、后置处理、切削仿真、加工过程监测检测、加工结果检测各环节，确定不同的存储数据类型，并进行各环节数据的存储；
步骤二：从零件上获取待加工特征，并基于特征相似度评价方法，从构建的加工知识数据模型中得到同待加工特征的相似特征集；
步骤三：针对相似特征集的历史加工效果，基于历史加工效果评价结果，并基于熵权法得到相似特征历史加工效果的综合评价值；
步骤四：从相似特征集中得到历史加工效果综合评价最优的特征及其对应的工艺方案，以此工艺方案作为待加工特征的工艺方案；
步骤五：在数控工艺设计阶段，基于软件集成和加工数据集成，将切削仿真结果作为工艺优化的依据反馈至程序编制阶段，实现工艺设计阶段的闭环控制；
步骤六：在零件的数控加工阶段，加工过程中获取加工过程状态监测检测数据，加工后获取加工结果检测数据；
步骤七：将加工过程状态监测检测数据、加工结果检测数据及工艺设计各环节的数据将存储到加工知识数据模型中，作为后续数控工艺优化的依据。
优选地，在步骤一中，加工特征包括特征类型、特征几何结构、特征几何尺寸、特征加工精度、特征材料属性和特征间位置关系各信息，所述特征类型包括槽、筋、孔和轮廓。
优选地，在步骤一中，在程序编制的环节中，加工知识数据模型中的数据类型包括毛坯尺寸、装夹方案、加工工序、加工工步、加工机床、加工刀具、 加工特征、走刀策略、进退刀方式和切削参数；
在后置处理的环节中，加工知识数据模型中的数据类型包括加工工序、加工工步和NC程序，所述NC程序包括NC代码、特征编号、加工操作编号、加工过程监测检测指令，所述加工过程监测检测指令包括探头检测触发指令、中间状态监测触发指令；
在切削仿真的环节中，加工知识数据模型中的数据类型包括切削仿真文件、NC程序和仿真结果，其中仿真结果包含零件加工欠切、过切、碰撞各异常信息、加工仿真时间信息以及加工仿真切削体积变化信息；
在加工过程监测检测的环节中，加工知识数据模型的数据类型包括NC程序、机床功率监测数据、切削振动监测数据、加工过程中间状态测头检测数据和中间状态超声测厚数据；
在加工结果检测的环节中，加工知识数据模型中的数据类型包括加工特征、加工结果检测程序、特征形位公差检测数据、特征尺寸检测数据和表面质量检测数据。
优选地，在步骤二中，特征相似度评价方法为：依据评价指标得到不同特征之间的相似度，进而获取同待加工特征相似度高于期望值的特征集；评价指标包括特征类型、材料、尺寸、结构、加工精度、使用的加工机床及刀具。
优选地，在步骤三中，历史加工效果评价以加工特征及其对应的加工工艺作为评价对象，包括加工过程状态评价和加工结果评价，加工特征对应的加工工艺包括特征加工走刀策略、切削参数、特征加工顺序以及机床、刀具各加工资源信息。
优选地，加工过程状态评价是指加工特征采用某种工艺加工时，对加工过程状态好坏的评价，其评价指标包括加工过程刀具振动、机床功率信号变化、中间状态尺寸变动、零件加工过程变形、刀具磨损和加工过程异常情况。
优选地，加工结果评价是指加工特征采用某种工艺加工后，对加工结果好坏的评价，其评价指标包括加工时间、特征最终加工尺寸精度、表面加工质量、 特征变形量和加工成本。
优选地，在步骤五中，软件集成是指在零件数控工艺设计阶段，以CAM软件为平台，实现程序编制、后置处理及切削仿真的有效集成。
优选地，在步骤五中，加工数据集成包括工艺数据集成和加工过程数据集成；其中工艺数据集成是指在零件数控工艺设计阶段，以集成软件为平台，以加工知识数据模型为载体，实现特征加工要求、工序工步、加工程序、仿真结果数据在程序编制、后置处理、切削仿真的工艺设计各阶段的传递；加工过程数据集成是指以加工特征为载体，实现加工程序、加工工序、加工工步各工艺信息、加工过程监测检测数据及加工结果检测数据在加工全流程各阶段的传递，将加工过程监测检测数据反馈至工艺设计阶段。
优选地，程序编制是指以加工知识和加工过程数据为基础，实现加工程序的新编和优化，包括工艺方案制定、加工顺序规划、切削参数优选和走刀策略决策，且所述程序编制实施标准化编程模式，包括加工程序命名、辅助几何创建、零件模型、毛坯和工装结构树设置，所述程序编制后生成的前置程序中包含加工特征、操作各工艺信息。
优选地，后置处理是指依据前置程序生成加工机床对应的NC程序，在NC程序中保留加工特征、操作各工艺信息，并基于零件加工要求，在NC程序中添加加工过程监测检测触发指令。
优选地，切削仿真是指对切削轨迹进行仿真验证，还通过融入加工经验和知识，对刀具刀套使用、切削量设置、工步设置顺序的合理性进行检查，并输出切削仿真结果，反馈至程序编制环节。
优选地，加工过程监测检测是指在加工过程中，当NC程序运行到监测检测触发指令时，激活加工过程监测程序，获取加工过程机床功率和切削振动监测数据，并触发探头程序，实现中间状态在机检测及超声测厚，并建立加工过程数据同NC程序的关联关系。
优选地，加工结果检测是指零件加工完成后，依据测量程序对零件最终加 工尺寸、形位公差和表面质量进行测量，并建立测量数据同零件加工特征的关联关系。
本发明的有益效果体现在：
1、本发明可有序集成程序编制、后置处理、切削仿真、加工过程监测检测、加工结果检测等各环节，实现产品加工全周期知识的有效积累，并基于历史加工效果评价结果，可实现加工知识重用，形成面向产品加工全流程的工艺闭环控制，完成数控工艺设计及优化，从而有效避免历史加工质量问题的重复发生，可显著提升数控工艺设计水平，为智能加工提供高效、稳定的数控工艺方案。
2、本发明在数控工艺设计阶段，基于软件集成和加工数据集成，将切削仿真结果作为工艺优化的依据反馈至程序编制阶段，通过软件集成可实现特征加工要求、工序工步、加工程序、仿真结果等数据在程序编制、后置处理、切削仿真等工艺设计各阶段的传递，达到数控工艺设计阶段闭环控制的目的；同时将加工数据集成分层工艺数据集成和加工过程数据集成，工艺数据集成可实现特征加工要求、工序工步、加工程序、仿真结果等数据在程序编制、后置处理、切削仿真的工艺设计各阶段的传递，从而达到数控工艺设计阶段闭环控制的目的；加工过程数据集成可实现加工程序、加工工序、加工工步各工艺信息、加工过程监测检测数据及加工结果检测数据在加工全流程各阶段的传递，将加工过程监测检测数据反馈至工艺设计阶段，从而为数控工艺设计及优化提供数据支撑，通过软件集成和加工数据集成的协同作用，为实现数控工艺设计阶段闭环控制和数控工艺设计及优化提供有力支撑。
附图说明
为了更清楚地说明本发明具体实施方式或现有技术中的技术方案，下面将对具体实施方式或现有技术描述中所需要使用的附图作简单地介绍。在所有附图中，类似的元件或部分一般由类似的附图标记标识。附图中，各元件或部分 并不一定按照实际的比例绘制。
图1为本发明提供的一种基于加工知识的数控工艺设计及优化方法的流程示意图；
图2为本发明面向产品加工全流程的工艺闭环控制流程示意图；
图3为典型零件加工特征示意图。
具体实施方式
为使本发明实施例的目的、技术方案和优点更加清楚，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。通常在此处附图中描述和示出的本发明实施例的组件可以以各种不同的配置来布置和设计。
因此，以下对在附图中提供的本发明的实施例的详细描述并非旨在限制要求保护的本发明的范围，而是仅仅表示本发明的选定实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
应注意到：相似的标号和字母在下面的附图中表示类似项，因此，一旦某一项在一个附图中被定义，则在随后的附图中不需要对其进行进一步定义和解释。
实施例
如图1-3所示，本实施例提供一种基于加工知识的数控工艺设计及优化方法，包括以下步骤：
步骤一：以加工特征为载体构建加工知识数据模型，以加工数据流为主线，有序集成程序编制、后置处理、切削仿真、加工过程监测检测、加工结果检测各环节，确定不同的存储数据类型，并进行各环节数据的存储；
步骤二：从零件上获取待加工特征，并基于特征相似度评价方法，从构建的加工知识数据模型中得到同待加工特征的相似特征集；
步骤三：针对相似特征集的历史加工效果，基于历史加工效果评价结果，并基于熵权法得到相似特征历史加工效果的综合评价值；
步骤四：从相似特征集中得到历史加工效果综合评价最优的特征及其对应的工艺方案，以此工艺方案作为待加工特征的工艺方案；
步骤五：在数控工艺设计阶段，基于软件集成和加工数据集成，将切削仿真结果作为工艺优化的依据反馈至程序编制阶段，实现工艺设计阶段的闭环控制；
步骤六：在零件的数控加工阶段，加工过程中获取加工过程状态监测检测数据，加工后获取加工结果检测数据；
步骤七：将加工过程状态监测检测数据、加工结果检测数据及工艺设计各环节的数据将存储到加工知识数据模型中，作为后续数控工艺优化的依据。
本实施例中，加工知识数据模型以加工特征为载体实现加工知识的存储，通过有序集成程序编制、后置处理、切削仿真、加工过程监测检测、加工结果检测等各环节，可实现产品加工全周期知识的有效积累，并基于历史加工效果评价结果，可实现加工知识重用(即步骤二至步骤四)，形成面向产品加工全流程的工艺闭环控制，完成数控工艺设计及优化，从而有效避免历史加工质量问题的重复发生，可显著提升数控工艺设计水平，为智能加工提供高效、稳定的数控工艺方案。
具体地，在步骤一中，加工特征包括特征类型、特征几何结构、特征几何尺寸、特征加工精度、特征材料属性和特征间位置关系各信息，所述特征类型包括槽、筋、孔和轮廓。
具体地，为更好地存储产品加工全周期不同阶段的数据信息，针对不同环节，加工知识数据模型中存储的数据类型存在差异，因此在步骤一中：
在程序编制的环节中，加工知识数据模型中的数据类型包括毛坯尺寸、装夹方案、加工工序、加工工步、加工机床、加工刀具、加工特征、走刀策略、进退刀方式和切削参数等工艺信息及加工特征信息；
在后置处理的环节中，加工知识数据模型中的数据类型包括加工工序、加工工步和NC程序，为实现不同环节中数据信息的关联对应，NC程序中除包含NC代码外，还包括特征编号、加工操作编号、加工过程监测检测指令；特征编号格式为“特征类型+特征序号”，如1号槽特征为“Pocket+0001”，1号筋特征为“Rib+0001”，1号孔特征为“Hole+0001”；加工操作编号格式为“加工工序+加工工步+操作类型+操作序号”，如15工序03工步中第3个铣面操作为“Process15+Step03+FaceMilling+0003”；加工过程监测检测指令包括探头检测触发指令、中间状态监测触发指令等；
在切削仿真的环节中，加工知识数据模型中的数据类型包括切削仿真文件、NC程序和仿真结果，其中仿真结果包含零件加工欠切、过切、碰撞各异常信息、加工仿真时间信息以及加工仿真切削体积变化信息，且上述信息同NC程序中的加工代码相关联；
在加工过程监测检测的环节中，加工知识数据模型的数据类型包括NC程序、机床功率监测数据、切削振动监测数据、加工过程中间状态测头检测数据和中间状态超声测厚数据；上述数据同NC程序中的加工代码相关联，使加工过程监测数据同工艺信息相匹配，便于后续进行工艺优化和分析；
在加工结果检测的环节中，加工知识数据模型中的数据类型包括加工特征、加工结果检测程序、特征形位公差检测数据、特征尺寸检测数据和表面质量检测数据，还包括上述数据同加工特征的关联关系。
具体地，在步骤二中，特征相似度评价方法为：依据评价指标得到不同特征之间的相似度，进而获取同待加工特征相似度高于期望值的特征集；评价指标包括特征类型、材料、尺寸、结构、加工精度、使用的加工机床及刀具。
具体地，在步骤三中，历史加工效果评价以加工特征及其对应的加工工艺作为评价对象，包括加工过程状态评价和加工结果评价，加工特征对应的加工工艺包括特征加工走刀策略、切削参数、特征加工顺序以及机床、刀具各加工资源信息；其中，
加工过程状态评价是指加工特征采用某种工艺加工时，对加工过程状态好坏的评价，其评价指标包括加工过程刀具振动、机床功率信号变化、中间状态尺寸变动、零件加工过程变形、刀具磨损和加工过程异常情况；依据评价指标对特征最终加工质量、成本、效率的影响程度确定不同评价指标的评价因子，通过加权法即可获取加工过程状态的评价值；
加工结果评价是指加工特征采用某种工艺加工后，对加工结果好坏的评价，其评价指标包括加工时间、特征最终加工尺寸精度、表面加工质量、特征变形量和加工成本；依据评价指标的重要程度确定对应的评价因子，通过加权法即可获取加工结果的评价值。
需要说明的是，加工过程及加工结果综合评价值是在加工过程状态评价及加工结果评价的基础上，基于熵权法确定加工过程状态、加工结果影响因子，进而综合计算得到的。
具体地，在步骤五中，软件集成是指在零件数控工艺设计阶段，以CAM软件为平台，实现程序编制、后置处理及切削仿真的有效集成。
工艺设计阶段各软件集成的具体含义是程序编制完成后，在CAM环境下，自动调用后置处理系统，生成同加工机床匹配的NC程序，并依据零件加工工序及工步设置信息，自动生成包含零件、毛坯、工装、机床、刀具在内的切削仿真环境，同时切削仿真结果将被作为工艺优化依据反馈至程序编制阶段，实现特征加工要求、工序工步、加工程序、仿真结果等数据在程序编制、后置处理、切削仿真等工艺设计各阶段的传递，达到数控工艺设计阶段闭环控制的目的。
具体地，在步骤五中，加工数据集成包括工艺数据集成和加工过程数据集成；其中，
工艺数据集成是指在零件数控工艺设计阶段，以集成软件为平台，以加工知识数据模型为载体，实现特征加工要求、工序工步、加工程序、仿真结果等数据在程序编制、后置处理、切削仿真的工艺设计各阶段的传递，从而达到数 控工艺设计阶段闭环控制的目的；
加工过程数据集成是指以加工特征为载体，实现加工程序、加工工序、加工工步各工艺信息、加工过程监测检测数据及加工结果检测数据在加工全流程各阶段的传递，将加工过程监测检测数据反馈至工艺设计阶段，从而为数控工艺设计及优化提供数据支撑。
具体地，程序编制是指以加工知识和加工过程数据为基础，实现加工程序的新编和优化，包括工艺方案制定、加工顺序规划、切削参数优选和走刀策略决策；为实现工艺设计阶段的软件集成，打通工艺数据流，程序编制实施标准化编程模式，包括加工程序命名、辅助几何创建、零件模型、毛坯和工装结构树设置，程序编制后生成的前置程序中包含加工特征、操作各工艺信息。
具体地，后置处理是指依据前置程序生成加工机床对应的NC程序，在NC程序中保留加工特征、操作各工艺信息，从而实现后续加工过程数据同加工特征、操作的关联，便于加工异常情况的追溯，实现异常部位加工程序的快速定位；并基于零件加工要求，在NC程序中添加加工过程监测检测触发指令，从而实现对关重部位中间状态的监控。
具体地，切削仿真是指对切削轨迹进行仿真验证，还通过融入加工经验和知识，对刀具刀套使用、切削量设置、工步设置顺序的合理性进行检查，并输出切削仿真结果，反馈至程序编制环节。
具体地，加工过程监测检测是指在加工过程中，当NC程序运行到监测检测触发指令时，激活加工过程监测程序，获取加工过程机床功率和切削振动监测数据，并触发探头程序，实现中间状态在机检测及超声测厚，并建立加工过程数据同NC程序的关联关系，从而实现中间状态在机检测及超声测厚，基于上述加工过程数据同NC程序的关联关系，将监测检测数据存储到加工知识数据模型中，为数控工艺设计及优化提供数据支撑。
具体地，加工结果检测是指零件加工完成后，依据测量程序对零件最终加工尺寸、形位公差和表面质量进行测量，并建立测量数据同零件加工特征的关 联关系。基于上述测量数据同零件加工特征的关联关系，将加工结果检测数据存储到加工知识数据模型中，为数控工艺设计及优化提供数据支撑。
最后应说明的是：以上各实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述各实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范围，其均应涵盖在本发明的权利要求和说明书的范围当中。

Claims (14)

  1. 一种基于加工知识的数控工艺设计及优化方法，其特征在于，包括以下步骤：
    步骤一：以加工特征为载体构建加工知识数据模型，以加工数据流为主线，有序集成程序编制、后置处理、切削仿真、加工过程监测检测、加工结果检测各环节，确定不同的存储数据类型，并进行各环节数据的存储；
    步骤二：从零件上获取待加工特征，并基于特征相似度评价方法，从构建的加工知识数据模型中得到同待加工特征的相似特征集；
    步骤三：针对相似特征集的历史加工效果，基于历史加工效果评价结果，并基于熵权法得到相似特征历史加工效果的综合评价值；
    步骤四：从相似特征集中得到历史加工效果综合评价最优的特征及其对应的工艺方案，以此工艺方案作为待加工特征的工艺方案；
    步骤五：在数控工艺设计阶段，基于软件集成和加工数据集成，将切削仿真结果作为工艺优化的依据反馈至程序编制阶段，实现工艺设计阶段的闭环控制；
    步骤六：在零件的数控加工阶段，加工过程中获取加工过程状态监测检测数据，加工后获取加工结果检测数据；
    步骤七：将加工过程状态监测检测数据、加工结果检测数据及工艺设计各环节的数据将存储到加工知识数据模型中，作为后续数控工艺优化的依据。
  2. 根据权利要求1所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，在所述步骤一中，所述加工特征包括特征类型、特征几何结构、特征几何尺寸、特征加工精度、特征材料属性和特征间位置关系各信息，所述特征类型包括槽、筋、孔和轮廓。
  3. 根据权利要求1或2所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，在所述步骤一中，在所述程序编制的环节中，加工知识数据模型中的数据类型包括毛坯尺寸、装夹方案、加工工序、加工工步、加工机床、 加工刀具、加工特征、走刀策略、进退刀方式和切削参数；
    在所述后置处理的环节中，加工知识数据模型中的数据类型包括加工工序、加工工步和NC程序，所述NC程序包括NC代码、特征编号、加工操作编号、加工过程监测检测指令，所述加工过程监测检测指令包括探头检测触发指令、中间状态监测触发指令；
    在所述切削仿真的环节中，加工知识数据模型中的数据类型包括切削仿真文件、NC程序和仿真结果，其中仿真结果包含零件加工欠切、过切、碰撞各异常信息、加工仿真时间信息以及加工仿真切削体积变化信息；
    在所述加工过程监测检测的环节中，加工知识数据模型的数据类型包括NC程序、机床功率监测数据、切削振动监测数据、加工过程中间状态测头检测数据和中间状态超声测厚数据；
    在所述加工结果检测的环节中，加工知识数据模型中的数据类型包括加工特征、加工结果检测程序、特征形位公差检测数据、特征尺寸检测数据和表面质量检测数据。
  4. 根据权利要求1所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，在所述步骤二中，所述特征相似度评价方法为：
    依据评价指标得到不同特征之间的相似度，进而获取同待加工特征相似度高于期望值的特征集；
    所述评价指标包括特征类型、材料、尺寸、结构、加工精度、使用的加工机床及刀具。
  5. 根据权利要求1或2所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，在所述步骤三中，所述历史加工效果评价以加工特征及其对应的加工工艺作为评价对象，包括加工过程状态评价和加工结果评价，所述加工特征对应的加工工艺包括特征加工走刀策略、切削参数、特征加工顺序以及机床、刀具各加工资源信息。
  6. 根据权利要求5所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，所述加工过程状态评价是指加工特征采用某种工艺加工时，对加工过程状态好坏的评价，其评价指标包括加工过程刀具振动、机床功率信号变化、中间状态尺寸变动、零件加工过程变形、刀具磨损和加工过程异常情况。
  7. 根据权利要求6所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，所述加工结果评价是指加工特征采用某种工艺加工后，对加工结果好坏的评价，其评价指标包括加工时间、特征最终加工尺寸精度、表面加工质量、特征变形量和加工成本。
  8. 根据权利要求1所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，在所述步骤五中，所述软件集成是指在零件数控工艺设计阶段，以CAM软件为平台，实现程序编制、后置处理及切削仿真的有效集成。
  9. 根据权利要求8所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，在所述步骤五中，所述加工数据集成包括工艺数据集成和加工过程数据集成；其中，
    所述工艺数据集成是指在零件数控工艺设计阶段，以集成软件为平台，以加工知识数据模型为载体，实现特征加工要求、工序工步、加工程序、仿真结果数据在程序编制、后置处理、切削仿真的工艺设计各阶段的传递；
    所述加工过程数据集成是指以加工特征为载体，实现加工程序、加工工序、加工工步各工艺信息、加工过程监测检测数据及加工结果检测数据在加工全流程各阶段的传递，将加工过程监测检测数据反馈至工艺设计阶段。
  10. 根据权利要求9所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，所述程序编制是指以加工知识和加工过程数据为基础，实现加工程序的新编和优化，包括工艺方案制定、加工顺序规划、切削参数优选和走刀策略决策，且所述程序编制实施标准化编程模式，包括加工程序命名、辅助几何创建、零件模型、毛坯和工装结构树设置，所述程序编制后生成的前置程序中包含加工特征、操作各工艺信息。
  11. 根据权利要求10所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，所述后置处理是指依据前置程序生成加工机床对应的NC程序，在NC程序中保留加工特征、操作各工艺信息，并基于零件加工要求，在NC程序中添加加工过程监测检测触发指令。
  12. 根据权利要求11所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，所述切削仿真是指对切削轨迹进行仿真验证，还通过融入加工经验和知识，对刀具刀套使用、切削量设置、工步设置顺序的合理性进行检查，并输出切削仿真结果，反馈至程序编制环节。
  13. 根据权利要求12所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，所述加工过程监测检测是指在加工过程中，当NC程序运行到监测检测触发指令时，激活加工过程监测程序，获取加工过程机床功率和切削振动监测数据，并触发探头程序，实现中间状态在机检测及超声测厚，并建立加工过程数据同NC程序的关联关系。
  14. 根据权利要求13所述的一种基于加工知识的数控工艺设计及优化方法，其特征在于，所述加工结果检测是指零件加工完成后，依据测量程序对零件最终加工尺寸、形位公差和表面质量进行测量，并建立测量数据同零件加工特征的关联关系。
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