基于模态联合仿真寻优法的机床刀具结合部参数辨识方法
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摘要
为保证机床加工时的切削稳定性,获得准确的稳定性叶瓣图(切削速度–切削深度关系图),需要得到机床刀具刀尖点的频率响应函数(FRF)。刀尖在加工时处于旋转状态,无法通过粘贴式传感器直接获取其频率响应函数。针对这一问题,提出了通过准确辨识刀柄结合部间动力学参数来预测刀尖频响。为实现刀柄结合部的动态参数识别,提出了基于模态分析理论的联合仿真寻优法的辨识方法。该方法通过均布弹簧–阻尼单元模拟结合部接触特性,以模态实验测得前2阶模态固有频率及其对应的振幅为目标约束,以结合部间的刚度和阻尼为变量进行有限元分析,采用最小二乘法构建二者的多目标优化函数,并在MATLAB–ANSYS集成环境下建立非线性规划函数寻优任务实现结合部动力学参数的辨识。为了提高辨识效率减少调用有限元分析的次数,采用了样本点构造的方法;为了避免因采样点选取不合理而造成计算量增加,采用了采样区间归一化的处理方式。最后,将优化识别结果通过弹簧单元指令代入有限元模型进行谐响应分析来预测刀尖FRF,对比有限元仿真与模态试验对应测点的频响数据。结果表明,二者的频率响应函数曲线拟合度较高,且前2阶的固有频率误差分别仅为0和0.04%。验证了该方法的可行性,为进一步获得稳定叶瓣图提供支持。
To ensure cutting stability and obtain accurate stability lobes diagram(diagram of cutting speed–cutting depth), need to get the frequency response function(FRF) of the tool nose. The tool tip is in a rotating state during processing, and its frequency response function cannot be directly obtained through the adhesive sensor.Therefore the dynamic parameter identification of the shank structure is the premise for accurate prediction the tool nose's FRF. In order to solve this problem, based on the theory of modal analysis, the method of modal joint optimization simulation was used to identify the dynamic parameter of the joint part. Through the evenly distributed spring damping units to simulate contact characteristics, the modal frequency and amplitude of the modal experiment and finite element analysis were served as the optimized constraints and optimized goals, which were combined with least square method to construct multi-objective optimization function, The nonlinear programming function optimization algorithm was used under MATLAB–ANSYS integration environment to realize the junction parameters identification. By used the method of construct the sample points in order to reduce the number of calls the ANSYS finite element analysis.By used the method of design variable sampling interval normalization process in order to avoid the unreasonable sampling. Brought the optimize recognition results into Ansys model for forecasting tool point FRF. The result showed that the two curves fitting degree of frequency response function are high and the first two order natural frequency of harmonic response analysis error are 0 and 0.04%. The feasibility of this method is verified, which can provide support for further obtaining stable lobe pattern.
To ensure cutting stability and obtain accurate stability lobes diagram(diagram of cutting speed–cutting depth), need to get the frequency response function(FRF) of the tool nose. The tool tip is in a rotating state during processing, and its frequency response function cannot be directly obtained through the adhesive sensor.Therefore the dynamic parameter identification of the shank structure is the premise for accurate prediction the tool nose's FRF. In order to solve this problem, based on the theory of modal analysis, the method of modal joint optimization simulation was used to identify the dynamic parameter of the joint part. Through the evenly distributed spring damping units to simulate contact characteristics, the modal frequency and amplitude of the modal experiment and finite element analysis were served as the optimized constraints and optimized goals, which were combined with least square method to construct multi-objective optimization function, The nonlinear programming function optimization algorithm was used under MATLAB–ANSYS integration environment to realize the junction parameters identification. By used the method of construct the sample points in order to reduce the number of calls the ANSYS finite element analysis.By used the method of design variable sampling interval normalization process in order to avoid the unreasonable sampling. Brought the optimize recognition results into Ansys model for forecasting tool point FRF. The result showed that the two curves fitting degree of frequency response function are high and the first two order natural frequency of harmonic response analysis error are 0 and 0.04%. The feasibility of this method is verified, which can provide support for further obtaining stable lobe pattern.
引文
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[11]Wang Zhonghou,Yuan Keke,Li Gang.Optimization identification for dynamic characteristic parameters of sliding joints based on response surface methodology[J].China Mechanical Engineering,2016,27(5):622-626.[汪中厚,袁可可,李刚.基于响应面法的滑动结合面动态特性参数优化识别[J].中国机械工程,2016,27(5):622-626.]
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[13]廖伯瑜,周新民,尹志宏.现代机械动力学及其工程应用[M].北京:机械工业出版社,2003:235-250.
[2]Wang Bo,Sui Wei,Tai Xingyu,et al.Effect of interface on dynamic characteristics of spindle system[J].Journal of Vibration and Shock,2011,30(10):231-235.[汪博,孙伟,太兴宇,等.主轴系统结合面对主轴系统动力学特性的影响分析[J].振动与冲击,2011,30(10):231-235.]
[3]Ertürk A,?zgüven H N,Budak E.Analytical modeling of spindle-tool dynamics on machine tools using Timoshenko beam model and receptance coupling for the prediction of tool point FRF[J].International Journal of Machine Tools&Manufacture,2006,46(15):1901-1912.
[4]Tony L S,Kevin P,Dongki W,et al.Shrink fit tool holder connection stiffness/damping modeling for frequency response prediction in milling[J].International Journal of Machine Tools and Manufacture,2007,47(9):1368-1380.
[5]?z?ahin O,Ertürk A,?zgüven H N.et al.A closed-form approach for identification of dynamical contact parameters in spindle-holder-tool assemblies[J].International Journal of Machine Tools&Manufacture,2009,49(1):25-35.
[6]Chen Jian,Wang Guicheng,Tiang Lian.Model and parameter identification of hohlschaftkegel shrink toolholder-tool joint part[J].Journal of Shanghai Jiaotong University,2016,50(7):1005-1010.[陈建,王贵成,田良,等.高速中空热装刀柄-刀具结合部的建模与参数辨识[J].上海交通大学学报,2016,50(7):1005-1010.]
[7]Chen Jian,Wang Guicheng,Tian Liang.Dynamic property analysis of hsk spindle-toolholder system based on joint part[J].China Mechanical Engineering,2016,27(3):296-301.[陈建,王贵成,田良,等.基于结合部的HSK主轴-刀柄系统动态特性分析[J].中国机械工程,2016,27(3):296-301.]
[8]Namazi M,Altintas Y,Abe T,et al.Modeling and identification of tool holder-spindle interface dynamics[J].International Journal of Machine Tools&Manufacture,2007,47(9):1333-1341.
[9]Dong Guanhua,Yin Qin,Liu Yun.A study on the identification of joints dynamic stiffness based on modal analysis[J].Journal of Vibration&Shock,2017,36(20):125-131.[董冠华,殷勤,刘蕴,等.基于模态分析理论的结合部动刚度辨识[J].振动与冲击,2017,36(20):125-131.]
[10]Sun Mingnan,Mi Liang,Gan Jing.An optimum identification method of dynamic characteristic parameters of guideway joint on a NC machine tool[J].Journal of Sichuan University(Engineering Science Edition),2012,44(3):217-223.[孙明楠,米良,干静,等.数控机床导轨结合部动态特性参数优化识别方法研究[J].四川大学学报(工程科学版),2012,44(3):217-223.]
[11]Wang Zhonghou,Yuan Keke,Li Gang.Optimization identification for dynamic characteristic parameters of sliding joints based on response surface methodology[J].China Mechanical Engineering,2016,27(5):622-626.[汪中厚,袁可可,李刚.基于响应面法的滑动结合面动态特性参数优化识别[J].中国机械工程,2016,27(5):622-626.]
[12]Lou Jianglei,Tang Jinyuan.A method of equivalent stiffness identification for bearing joint of a gearbox based on CAE/CAT/CAO[J].Journal of Vibration&Shock,2014,33(23):81-86.[楼江雷,唐进元.基于CAE/CAT/CAO的齿轮箱轴承结合部等效刚度识别方法[J].振动与冲击,2014,33(23):81-86.]
[13]廖伯瑜,周新民,尹志宏.现代机械动力学及其工程应用[M].北京:机械工业出版社,2003:235-250.