机械工程学报
機械工程學報
궤계공정학보
Journal of Mechanical Engineering
2015年
21期
87-94
,共8页
机床动力学%加工空间%空间统计学%Kriging模型%固有频率
機床動力學%加工空間%空間統計學%Kriging模型%固有頻率
궤상동역학%가공공간%공간통계학%Kriging모형%고유빈솔
machine tools dynamics%manufacturing space%spatial statistics%Kriging model%natural frequency
机床刚度、固有频率等动力学特性随着机床部件位置、姿态在工作空间中的变化而变化.对机床动力学特性的研究不仅需要考虑到机床质量、刚度、阻尼值的大小,还应重视机床加工点的空间位置变化.采用空间统计学方法,以超精密机床固有频率这一关键动力学性能为例,分析机床动力学性能与机床位置姿态之间的数学关系,选取机床动态特性变异函数,建立动力学性能变化预测的Kriging方法模型,研究动力学特性在工作空间中的变化规律以及动力学特性空间信息的表述方法.将所建立的模型与正交多项式方法、径向基神经网络方法、二阶响应面方法等方法建立动力学性能预测分析模型比较,空间统计学Kriging方法所建立的模型R2检验大于0.96,在四种模型建构方式中为精确度最优,能够在完整工作空间中准确地描述机床动力学特性.基于空间统计学的机床动力学特性研究为机床的动力学设计提供了新的设计分析方法及相应的技术支持.
機床剛度、固有頻率等動力學特性隨著機床部件位置、姿態在工作空間中的變化而變化.對機床動力學特性的研究不僅需要攷慮到機床質量、剛度、阻尼值的大小,還應重視機床加工點的空間位置變化.採用空間統計學方法,以超精密機床固有頻率這一關鍵動力學性能為例,分析機床動力學性能與機床位置姿態之間的數學關繫,選取機床動態特性變異函數,建立動力學性能變化預測的Kriging方法模型,研究動力學特性在工作空間中的變化規律以及動力學特性空間信息的錶述方法.將所建立的模型與正交多項式方法、徑嚮基神經網絡方法、二階響應麵方法等方法建立動力學性能預測分析模型比較,空間統計學Kriging方法所建立的模型R2檢驗大于0.96,在四種模型建構方式中為精確度最優,能夠在完整工作空間中準確地描述機床動力學特性.基于空間統計學的機床動力學特性研究為機床的動力學設計提供瞭新的設計分析方法及相應的技術支持.
궤상강도、고유빈솔등동역학특성수착궤상부건위치、자태재공작공간중적변화이변화.대궤상동역학특성적연구불부수요고필도궤상질량、강도、조니치적대소,환응중시궤상가공점적공간위치변화.채용공간통계학방법,이초정밀궤상고유빈솔저일관건동역학성능위례,분석궤상동역학성능여궤상위치자태지간적수학관계,선취궤상동태특성변이함수,건립동역학성능변화예측적Kriging방법모형,연구동역학특성재공작공간중적변화규률이급동역학특성공간신식적표술방법.장소건립적모형여정교다항식방법、경향기신경망락방법、이계향응면방법등방법건립동역학성능예측분석모형비교,공간통계학Kriging방법소건립적모형R2검험대우0.96,재사충모형건구방식중위정학도최우,능구재완정공작공간중준학지묘술궤상동역학특성.기우공간통계학적궤상동역학특성연구위궤상적동역학설계제공료신적설계분석방법급상응적기술지지.
The dynamic characteristics of machine tools, such as stiffness and natural frequency vary with the changing of position and posture of the machine components in working space. Not only the mass, stiffness, damping ratios should be considered during the research of the dynamic characteristics of machine tools, the spatial position change of machining point should also be paid more attention. Spatial statistical method is adopted, and the machine tool's natural frequency is taken as the critical dynamic characteristic, thus the mathematical relation between the machine tool's dynamic characteristics and its position and posture is analyzed. The machine tool's dynamic performance variation function is selected, and the Kriging method model to predict dynamic characters is established, then the prediction of the changing rules of machine tool's dynamic characteristics is realized. The established model is compared with the dynamic characteristics predication models established by using orthogonal polynomial method, the RBF neural network method and the second order response surface method, and result shows that theR-Squared value of the model using spatial statics Kriging method is 0.96, which is the optimum in the four models, thus it can accurately describe the machine tool's dynamic characteristics in complete working space. The research of machine tools dynamics based on spatial statistics provides a new design and analyze method and technical support for the dynamic design of the ultra-precision machine tools.