基于FFSM的数控机床加工状态建模方法
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摘要
为描述数控机床加工过程中的刀具状态,提出一种基于模糊有限状态机的建模方法。由该方法建立的模型通过"状态叠加"机制定量刻画了刀具的临界属性,从而预测刀具未来状态。围绕建模步骤、模型参数优化和预测方法进行了详细讨论,定性分析了状态转换规则及输入变量,设计了一种基于遗传算法的模型参数定量优化方法,并揭示了当刀具分别处于稳态与临界态时的预测原理。实验表明,在一定预测步长内,其预测误差小于低阶线性自回归模型,同时该模型具有连续预测刀具状态的能力。
To synchronize the processing states from a Computer Numerical Control(CNC)machine entity to its counterpart,a modelling method based on Fuzzy Finite State Machine(FFSM)was proposed.The model established by this method was able to quantify the critical attributes of the tool through "state superposition" mechanism for predicting its future states based on prior knowledge.A detailed discussion on modelling steps,parameter optimization and prediction mechanism was expounded,which analyzed the state transition rules and input variables qualitatively,designed a quantitative optimization method based on genetic algorithm for model parameters and revealed the prediction mechanism of tools in steady and critical states respectively.The experiment results showed that the prediction errors of the proposed model was less than the errors of the low-order Linear Autoregressive Model(LAM)within a certain prediction steps,and that the model had the ability to predict machine state continuously.
To synchronize the processing states from a Computer Numerical Control(CNC)machine entity to its counterpart,a modelling method based on Fuzzy Finite State Machine(FFSM)was proposed.The model established by this method was able to quantify the critical attributes of the tool through "state superposition" mechanism for predicting its future states based on prior knowledge.A detailed discussion on modelling steps,parameter optimization and prediction mechanism was expounded,which analyzed the state transition rules and input variables qualitatively,designed a quantitative optimization method based on genetic algorithm for model parameters and revealed the prediction mechanism of tools in steady and critical states respectively.The experiment results showed that the prediction errors of the proposed model was less than the errors of the low-order Linear Autoregressive Model(LAM)within a certain prediction steps,and that the model had the ability to predict machine state continuously.
引文
[1]ALAM K M,SADDIK A E.C2PS:a digital twin architecture reference model for the cloud-based cyber-physical systems[J].IEEE Access,2017,5:2050-2062.DOI:10.1109/AC-CESS.2017.2657006.
[2]GU Yan,CHENG Huanchong,WANG Zhen,et al.Design and implementation of 3D monitoring system based on OPCUA[J].Journal of System Simulation,2017,29(11):2767-2773(in Chinese).[顾岩,程奂翀,王震,等.基于OPCUA的3D实时监控系统设计与实现[J].系统仿真学报,2017,29(11):2767-2773.]
[3]YANG Cheng,LIU Tao,CHEN Niannian,et al.Monitoring system design and realization for 3Ddigital factories[J].Control and Instruments in Chemical Industry,2012,39:108:111(in Chinese).[杨程,刘涛,陈念年,等.3D数字工厂监控系统的设计与实现[J].化工自动化及仪表,2012,39(1):108-111.]
[4]CAI Y,STARLY B,COHEN P,et al.Sensor data and information fusion to construct digital-twins virtual machine tools for cyber-physical manufacturing[J].Procedia Manufacturing,2017,10:1031-1042.
[5]SCHLUSE M,PRIGGEMEYER M,ATORF L,et al.Experimentable digital twins-streamlining simulation-based systems engineering for Industry 4.0[J].IEEE Transactions on Industrial Informatics,2018,14(4):1722-1731.
[6]MORENO A,VELEZ G,ARDANZA A,et al.Virtualisation process of a sheet metal punching machine within the Industry4.0vision[J].International Journal on Interactive Design&Manufacturing,2016,11(2):1-9.
[7]TAO Fei,ZHANG Meng,CHENG Jiangfeng,et al.Digital twin workshop:a new paradigm for future workshop[J].Computer Integrated Manufacturing Systems,2017,23(1):1-9(in Chinese).[陶飞,张萌,程江峰,等.数字孪生车间---一种未来车间运行新模式[J].计算机集成制造系统,2017,23(1):1-9.]
[8]TAO F,ZHANG M.Digital twin shop-floor:a new shopfloor paradigm towards smart manufacturing[J].IEEE Access,2017,5:20418-20427.DOI:10.1109/ACCESS.2017.2756069.
[9]ZHOU Xingshe,YANG Yalie,YANG Gang.Modeling methods for dynamic behaviors of cyber-physical system[J].Chinese Journal of Computers,2014,37(6):1411-1423(in Chinese).[周兴社,杨亚磊,杨刚.信息-物理融合系统动态行为模型构建方法[J].计算机学报,2014,37(6):1411-1423.]
[10]ZHANG Jianning.Modeling and verifying of CPS component service composition based on hybrid automa[D].Suzhou:Soochow University,2014(in Chinese).[张建宁.基于混成自动机的CPS构件服务组合建模与验证[D].苏州:苏州大学,2014.]
[11]MENCAR C,LUCARELLI M,CASTIELLO C,et al.Design of strong fuzzy partitions from cuts[C]//Proceedings of the 8th Conference of the European Society for Fuzzy Logic and Technology.Cook Country,Ill.,USA:Atlantis Press,2014:424-431.
[12]ALSINA C,FRANK M J,SCHWEIZER B.Associative functions:triangular norms and copulas[M].Toh Tuck Lin,Singapore:World Scientific,2006.
[13]LU Xiaohu.Research and application on key technology of network platform for open CNC system[D].Shenyang:University of Chinese Academy of Sciences,Shenyang Institute of Computing Technology,2015(in Chinese).[陆小虎.开放式数控系统网络化平台关键技术研究与应用[D].沈阳:中国科学院研究生院,沈阳计算技术研究所,2015.]
[14]TENLLADO C,SETOAIN J,PRIETO M,et al.Parallel implementation of the 2D discrete wavelet transform on fraphics processing units:filter bank versus lifting[J].IEEETransactions on Parallel&Distributed Systems,2008,19(3):299-310.
[15]VAN DER LAAN W J,JALBA A C,ROERDINK J B T M.Accelerating wavelet lifting on graphics hardware using CU-DA[J].IEEE Transactions on Parallel&Distributed Systems,2011,22(1):132-146.
[2]GU Yan,CHENG Huanchong,WANG Zhen,et al.Design and implementation of 3D monitoring system based on OPCUA[J].Journal of System Simulation,2017,29(11):2767-2773(in Chinese).[顾岩,程奂翀,王震,等.基于OPCUA的3D实时监控系统设计与实现[J].系统仿真学报,2017,29(11):2767-2773.]
[3]YANG Cheng,LIU Tao,CHEN Niannian,et al.Monitoring system design and realization for 3Ddigital factories[J].Control and Instruments in Chemical Industry,2012,39:108:111(in Chinese).[杨程,刘涛,陈念年,等.3D数字工厂监控系统的设计与实现[J].化工自动化及仪表,2012,39(1):108-111.]
[4]CAI Y,STARLY B,COHEN P,et al.Sensor data and information fusion to construct digital-twins virtual machine tools for cyber-physical manufacturing[J].Procedia Manufacturing,2017,10:1031-1042.
[5]SCHLUSE M,PRIGGEMEYER M,ATORF L,et al.Experimentable digital twins-streamlining simulation-based systems engineering for Industry 4.0[J].IEEE Transactions on Industrial Informatics,2018,14(4):1722-1731.
[6]MORENO A,VELEZ G,ARDANZA A,et al.Virtualisation process of a sheet metal punching machine within the Industry4.0vision[J].International Journal on Interactive Design&Manufacturing,2016,11(2):1-9.
[7]TAO Fei,ZHANG Meng,CHENG Jiangfeng,et al.Digital twin workshop:a new paradigm for future workshop[J].Computer Integrated Manufacturing Systems,2017,23(1):1-9(in Chinese).[陶飞,张萌,程江峰,等.数字孪生车间---一种未来车间运行新模式[J].计算机集成制造系统,2017,23(1):1-9.]
[8]TAO F,ZHANG M.Digital twin shop-floor:a new shopfloor paradigm towards smart manufacturing[J].IEEE Access,2017,5:20418-20427.DOI:10.1109/ACCESS.2017.2756069.
[9]ZHOU Xingshe,YANG Yalie,YANG Gang.Modeling methods for dynamic behaviors of cyber-physical system[J].Chinese Journal of Computers,2014,37(6):1411-1423(in Chinese).[周兴社,杨亚磊,杨刚.信息-物理融合系统动态行为模型构建方法[J].计算机学报,2014,37(6):1411-1423.]
[10]ZHANG Jianning.Modeling and verifying of CPS component service composition based on hybrid automa[D].Suzhou:Soochow University,2014(in Chinese).[张建宁.基于混成自动机的CPS构件服务组合建模与验证[D].苏州:苏州大学,2014.]
[11]MENCAR C,LUCARELLI M,CASTIELLO C,et al.Design of strong fuzzy partitions from cuts[C]//Proceedings of the 8th Conference of the European Society for Fuzzy Logic and Technology.Cook Country,Ill.,USA:Atlantis Press,2014:424-431.
[12]ALSINA C,FRANK M J,SCHWEIZER B.Associative functions:triangular norms and copulas[M].Toh Tuck Lin,Singapore:World Scientific,2006.
[13]LU Xiaohu.Research and application on key technology of network platform for open CNC system[D].Shenyang:University of Chinese Academy of Sciences,Shenyang Institute of Computing Technology,2015(in Chinese).[陆小虎.开放式数控系统网络化平台关键技术研究与应用[D].沈阳:中国科学院研究生院,沈阳计算技术研究所,2015.]
[14]TENLLADO C,SETOAIN J,PRIETO M,et al.Parallel implementation of the 2D discrete wavelet transform on fraphics processing units:filter bank versus lifting[J].IEEETransactions on Parallel&Distributed Systems,2008,19(3):299-310.
[15]VAN DER LAAN W J,JALBA A C,ROERDINK J B T M.Accelerating wavelet lifting on graphics hardware using CU-DA[J].IEEE Transactions on Parallel&Distributed Systems,2011,22(1):132-146.