WO2020051818A1 - 一种面向切削稳定性预报的跨轴跨点模态测试与参数辨识方法 - Google Patents

一种面向切削稳定性预报的跨轴跨点模态测试与参数辨识方法 Download PDF

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WO2020051818A1
WO2020051818A1 PCT/CN2018/105389 CN2018105389W WO2020051818A1 WO 2020051818 A1 WO2020051818 A1 WO 2020051818A1 CN 2018105389 W CN2018105389 W CN 2018105389W WO 2020051818 A1 WO2020051818 A1 WO 2020051818A1
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axis
tool
modal
cross
matrix
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孙玉文
姜尚磊
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Dalian University of Technology
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/09—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool
    • B23Q17/0904—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool before or after machining
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/09—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool
    • B23Q17/0952—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool during machining
    • B23Q17/0971—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool during machining by measuring mechanical vibrations of parts of the machine
    • B23Q17/0976—Detection or control of chatter
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/12—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring vibration

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  • the invention relates to a method for modal testing and parameter identification for cutting stability prediction, and particularly to a method for modal testing and parameter identification for cross-axis and cross-point for cutting stability prediction.
  • the stability prediction of the cutting process is usually achieved by drawing a stability leaflet diagram, that is, the processing parameter domain is divided into three types: stable, flutter and critical stability by the calculated stability leaflet. combination. On this basis, further flutter suppression scheme design and optimization of flutter-free machining parameters can be carried out.
  • This type of method requires the establishment of a time-delayed cutting dynamics equation.
  • the dynamic parameters involved are mainly a modal mass matrix, a modal damping matrix, a modal stiffness matrix, and a modal matrix.
  • a core step in implementing this type of method is how to expand the relevant modal analysis to accurately obtain these dynamic parameter matrices. This step directly determines the prediction accuracy of the stability leaflet map.
  • the existing modal analysis methods for cutting stability prediction mainly include numerical simulation methods based on finite element analysis and experimental testing methods based on hammer hammer.
  • the characteristic is that a single-axis acceleration sensor's response measurement direction is perpendicular to the impact direction of the hammer on the basis of the striking scheme in Reference 1. It is still necessary to install a single-axis acceleration sensor twice. This method actually considers the dynamic characteristics of the coupling of the cutting system across the axis at the point of the tool.
  • the invention patent with application number 201310409076.5 discloses a stability prediction method that considers multi-modal coupling at the point of the blade.
  • the tapping scheme is the same as that in Document 1, but two independent directions (X-direction and Y-direction) are identified respectively.
  • node 1 Not only at the tool tip point (node 1), but also multiple nodes (such as node 2, ..., node q) are tapped along the tool axis in sequence, although the method considers the dynamics of the coupling of the cutting system along the tool axis across the point Characteristics, but ignore the effects of modal coupling across the system.
  • node 2 At present, neither the relevant literature nor the patent considers the dynamic characteristics of the cross-axis coupling and cross-point coupling of the cutting system at the same time; and it is foreseeable that the percussion test that simultaneously considers the cross-axis and cross-point coupling also involves the new system transfer function processing and dynamics. Problems with parameter identification.
  • the present invention provides a method for modal testing and parameter identification of cross-axis and cross-points for cutting stability prediction, so as to obtain a cutting system that considers both cross-axis coupling and cross-point coupling dynamic parameters.
  • this method first installs a miniature three-axis acceleration sensor at the tool tip, and uses a hammer to preset multiple nodes on the tool axis along two horizontal orthogonal Modal percussion experiments across axes and points.
  • the measured transfer functions are grouped according to different measurement axes, and the dynamic parameters (modal mass, damping, stiffness, and formation) are identified for each group of transfer functions.
  • the meshing part between the tool and the workpiece at a given axial depth of cut is divided into multiple cutting layer microelements along the tool axis, and each layer of microelements is assigned a modal formation value identified at the above node by linear interpolation.
  • a parameter matrix assembly process matching the kinetic model is performed.
  • a dynamic parameter matrix including cross-axis coupling and cross-point coupling is obtained.
  • Step 1 Install the milling cutter in the shank, clamp the shank to the machine tool spindle, and establish the tool coordinate system: the coordinate origin is the center of the free end of the tool, the X axis is the feed direction of the tool, and the Y axis is the surface to be processed. In the vertical direction (downward milling vertical surface outwards, down milling vertical surface inward), the Z axis is the direction of the tool axis away from the free end of the tool.
  • Step 2 from the free end of the tool, mark q nodes to be tapped along the tool axis at a certain distance, install a miniature three-axis acceleration sensor at the node of the tool tip, and then at each node from X and Y two horizontal positive A hammer strike was performed in the direction of intersection, and all transfer functions of the spindle-toolholder-milling tool system were measured at each node.
  • Step 3 In the transfer function measured in step 2, remove all the transfer functions measured by the Z-axis of the acceleration sensor, and then divide the remaining transfer functions into different ones based on the X-axis or Y-axis measurement of the acceleration sensor. Two sets of transfer functions. They are labeled ⁇ FRF x ⁇ and ⁇ FRF y ⁇ .
  • step 4 the kinetic parameter identification is performed on the transfer function sets ⁇ FRF x ⁇ and ⁇ FRF y ⁇ obtained in step 3.
  • the natural frequency is ⁇ nx, 1 , ⁇ nx, 2 , ..., ⁇ nx, m ;
  • damping ratio is ⁇ x, 1 , ⁇ x, 2 , ..., ⁇ x, m ;
  • the formation matrix is among them
  • the dimension is 2q ⁇ 1, which is the j-th formation vector corresponding to the main vibration direction in the X direction.
  • Step 5 Divide the meshing part between the tool and the workpiece at a given axial cutting depth a p into p cutting layer microelements along the cutter axis direction, and according to the relative position of the center of each layer microelement and the above-mentioned percussion node These cutting layer microelements are assigned the modal formation values identified by step 4 by linear interpolation.
  • Step 6 Assemble different types of dynamic parameters according to different modal orders into a modal mass matrix, a modal damping matrix, a modal stiffness matrix, and a modal matrix that match the system dynamic model.
  • the modal mass matrix is
  • the modal damping matrix is
  • the modal stiffness matrix is
  • the modal formation matrix is:
  • the dimension is 2p ⁇ 1, which is the j-th order formation vector whose main vibration direction is X direction or Y direction corresponding to each cutting layer.
  • the beneficial effect of the present invention firstly installs a three-axis acceleration sensor at the tool tip, and performs a cross-axis and cross-point modal in two horizontally orthogonal directions at a plurality of nodes preset on the tool axis by a force hammer. Tap to group the measured transfer functions according to different measurement axes, and identify the dynamic parameters (modal mass, damping, stiffness, and formation) for each group of transfer functions. Then, the meshing part between the tool and the workpiece at a given axial depth of cut is divided into multiple cutting layer microelements along the tool axis, and each layer of microelements is assigned a modal formation value identified at the above node by linear interpolation.
  • FIG. 1 is a schematic diagram of a cross-axis and cross-point modal test according to the present invention.
  • A represents the hammer striking in the X direction;
  • (b) represents the hammer striking in the Y direction.
  • FIG. 2 is a set of transfer functions of a process system according to the present invention, which is divided according to X-axis and Y-axis response measurements of a three-axis acceleration sensor.
  • this method first installs a miniature three-axis acceleration sensor at the tip of a knife, and uses a force hammer to preset multiple nodes on the knife axis orthogonally along two levels, respectively.
  • modal percussion experiments are performed across axes and points.
  • the measured transfer functions are grouped according to different measurement axes, and the dynamic parameters (modal mass, damping, stiffness, and formation) are identified for each group of transfer functions.
  • the meshing part between the tool and the workpiece at a given axial depth of cut is divided into multiple cutting layer microelements along the tool axis, and each layer of microelements is assigned a modal formation value identified at the above node by linear interpolation.
  • a parameter matrix assembly process matching the kinetic model is performed.
  • a dynamic parameter matrix including cross-axis coupling and cross-point coupling is obtained.
  • Step 1 Install the milling cutter in the tool holder, clamp the tool holder to the machine tool spindle, and establish the tool coordinate system: the origin of the coordinate is the center of the free end of the tool, the X axis is the feed direction of the tool, and the Y axis is the In the vertical direction (downward milling vertical surface outwards, down milling vertical surface inward), the Z axis is the direction of the tool axis away from the free end of the tool.
  • Step 2 from the free end of the tool, mark q nodes to be tapped along the tool axis at a certain distance.
  • Step 3 In the transfer function measured in step 2, remove all the transfer functions measured by the Z-axis of the acceleration sensor, and then divide the remaining transfer functions into different ones based on the X-axis or Y-axis measurement of the acceleration sensor.
  • the two sets of transfer function sets, as shown in Figure 2, are labeled ⁇ FRF x ⁇ and ⁇ FRF y ⁇ .
  • step 4 the kinetic parameter identification is performed on the transfer function sets ⁇ FRF x ⁇ and ⁇ FRF y ⁇ obtained in step 3.
  • the natural frequency is ⁇ nx, 1 , ⁇ nx, 2 , ..., ⁇ nx, m ;
  • damping ratio is ⁇ x, 1 , ⁇ x, 2 , ..., ⁇ x, m ;
  • the formation matrix is among them
  • the dimension is 2q ⁇ 1, which is the j-th formation vector corresponding to the main vibration direction in the X direction.
  • Step 5 Divide the meshing part between the tool and the workpiece at a given axial cutting depth a p into p cutting layer microelements along the cutter axis direction, and according to the relative position of the center of each layer microelement and the above-mentioned percussion node These cutting layer microelements are assigned the modal formation displacement values identified in step 4 by linear interpolation.
  • Step 6 Assemble different types of dynamic parameters according to different modal orders into a modal mass matrix, a modal damping matrix, a modal stiffness matrix, and a modal matrix that match the system dynamic model.
  • the modal mass matrix is
  • the modal damping matrix is
  • the modal stiffness matrix is
  • the modal formation matrix is
  • the main vibration direction is Xiangdi Cutting layer First-order mode Formation displacement in the direction.

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
  • Numerical Control (AREA)

Abstract

一种面向切削稳定性预报的跨轴跨点模态测试与参数辨识方法，首先将一个三轴加速度传感器安装于刀尖，通过力锤在刀轴上预设的多个节点处分别沿两个水平正交的方向进行跨轴跨点模态敲击，将测量的传递函数按照不同测轴进行分组，对每组传递函数分别进行动力学参数辨识；再将给定轴向切深下刀具与工件之间的啮合部分沿刀轴划分成多个切削层微元，对每一层微元通过线性插值分配在上述节点处辨识的模态阵型值，并连同其它动力学参数进行与动力学模型相匹配的参数矩阵拼装处理；最后可获得包含跨轴跨点模态耦合效应的动力学参数矩阵。该方法中加速度传感器只需一次安装。该方法用于提升现有切削稳定性预报方法的精度。

Description

一种面向切削稳定性预报的跨轴跨点模态测试与参数辨识方法 技术领域
本发明涉及一种面向切削稳定性预报的模态测试与参数辨识方法，具体涉及一种面向切削稳定性预报的跨轴跨点模态测试与参数辨识方法。
背景技术
对切削过程进行稳定性预报有利于改善零件加工质量、提高材料去除率、减缓刀具磨损，还能避免由于剧烈振动损坏机床主轴，现已逐渐成为自动化、智能化加工的一个重要考量。目前，对切削过程进行稳定性预报通常采用绘制稳定性叶瓣图的方法来实现，即：通过计算得出的稳定性叶瓣将加工参数域划分成稳定、颤振和临界稳定的三类不同组合。在此基础上可展开进一步的颤振抑制方案设计和无颤振加工参数优化。
这类方法需要建立延时的切削动力学方程，涉及的动力学参数主要有模态质量矩阵、模态阻尼矩阵、模态刚度矩阵和模态阵型矩阵。实现这类方法的一个核心步骤在于如何展开相关模态分析从而准确获得这些动力学参数矩阵，这个步骤直接决定了稳定性叶瓣图的预报精度。通过检索相关文献与专利，可以发现存在的面向切削稳定性预报的模态分析方法主要有基于有限元分析的数值仿真方法和基于力锤敲击的实验测试方法。基于有限元分析的数值仿真方法一般需要对结构进行精密的网格划分，这带来了计算效率方面的损失；同时需要准确地建立、设置和输入待测结构的几何模型、边界条件和材料参数，这使得计算精度也难以保障。
另一方面，基于力锤敲击的实验测试方法，由于具有建模简便、计算精度高和数据处理快等优点，得到了较为广泛的研究与应用。这类方法的相关文献与专利主要集中在刀尖点动力学参数的获取上。文献1“B.P.Mann,K.A.Young, T.L.Schmitz,D.N.Dilley,Simultaneous Stability and Surface Location Error Predictions in Milling,Journal of Manufacturing Science and Engineering.127(2005)446.”给出了一种铣削稳定性预报方法，如图1(a)所示，该方法在刀尖点处(节点1)建立系统阵型归一的动力学方程，通过力锤分别敲击刀具的1X和1Y方向，并保持单轴加速度传感器的响应测量方向与敲击方向始终一致，需要两次安装单轴加速度传感器，可获得系统在刀尖点处相互独立的系统动力学参数。文献2“X.J.Zhang,C.H.Xiong,Y.Ding,M.J.Feng,Y.L.Xiong,Milling stability analysis with simultaneously considering the structural mode coupling effect and regenerative effect,International Journal of Machine Tools and Manufacture.53(2012)127–140.”考虑了刀尖点动力学参数的模态耦合效应，其特点是，在文献1的敲击方案基础上补充了单轴加速度传感器的响应测量方向与力锤敲击方向相垂直的敲击实验，依然需要两次安装单轴加速度传感器，该方法实际上考虑了切削系统在刀尖点处跨轴耦合的动力学特性。申请专利号为201310409076.5的发明专利公开了一种考虑刀尖点处多模态耦合的稳定性预报方法，敲击方案与文献1相同，但分别辨识了两个独立方向(X向和Y向)的多阶模态，对处于同一模态阶的动力学参数进行匹配并绘制出相应的稳定性叶瓣，将不同模态阶所确定的叶瓣下缘连接而成的包络线作为最终的稳定性叶瓣。上述文献与专利的共同特点是均假设切削系统的动力学行为发生在刀尖点处，即忽略了切削系统沿刀具轴向变化的动力学特性，这在较大的轴向切削条件下，往往不能满足系统动力学模型的精度要求，从而导致所预报的稳定性叶瓣图在某些转速范围内存在一定程度上的失真。文献3“C.Eksioglu,Z.M.Kilic,Y.Altintas,Discrete-Time Prediction of Chatter Stability,Cutting Forces,and Surface Location Errors in Flexible Milling Systems,Journal of Manufacturing Science and  Engineering.134(2012)61006.”给出了一个刀具与工件多点接触的动力学模型，其特点为：如图1(a)所示，加速度传感器安装于刀尖点，测量方向保证始终与敲击方向平行，但进行力锤敲击不仅在刀尖点处(节点1)执行，还要依次沿刀具轴线敲击多个节点(如节点2，…，节点q)，尽管该方法考虑了切削系统沿刀轴跨点耦合的动力学特性，但却忽略了系统跨轴模态耦合的影响。目前相关文献与专利均未同时考虑切削系统跨轴耦合和跨点耦合的动力学特性；且可预见，同步考虑跨轴和跨点耦合的敲击测试还涉及新的系统传递函数处理与动力学参数辨识的问题。
发明内容
针对现有技术的不足，本发明提供了一种面向切削稳定性预报的跨轴跨点模态测试与参数辨识方法，以获得切削系统同时考虑跨轴耦合和跨点耦合的动力学参数。如图1(a)和(b)所示，该方法首先将一个微型三轴加速度传感器安装于刀尖，通过力锤在刀轴上预设的多个节点处分别沿两个水平正交的方向进行跨轴和跨点的模态敲击实验。将测量的传递函数按照不同测轴进行分组，对每组传递函数分别进行动力学参数(模态质量、阻尼、刚度和阵型)辨识。再将给定轴向切深下刀具与工件之间的啮合部分沿刀轴划分成多个切削层微元，对每一层微元通过线性插值分配在上述节点处辨识的模态阵型值，并连同其它动力学参数进行与动力学模型相匹配的参数矩阵拼装处理。最后可获得包含跨轴耦合和跨点耦合的动力学参数矩阵。以侧铣过程为例，采用的具体步骤为：
步骤①、将铣刀安装于刀柄中，刀柄装夹到机床主轴上，建立刀具坐标系：坐标原点为刀具自由端的中心，X轴为刀具的进给方向，Y轴为待加工表面的垂直方向(顺铣垂直表面向外，逆铣垂直表面向里)，Z轴为远离刀具自由端的刀具轴线方向。
步骤②、从刀具自由端开始按一定间距沿刀具轴线标记q个待敲击节点，将一个微型三轴加速度传感器安装于刀尖节点，然后在每个节点处分别从X和Y两个水平正交的方向上进行力锤敲击，测得主轴-刀柄-铣刀系统在每个节点处所有传递函数。
步骤③、在步骤②所测量的传递函数中，剔除所有由加速度传感器Z轴测得的传递函数，然后将剩余的传递函数根据振动响应是由加速度传感器的X轴或Y轴测量划分成不同的两组传递函数集合。分别标记为{FRF x}和{FRF y}。
步骤④、对步骤③得到的传递函数集合{FRF x}和{FRF y}分别进行动力学参数辨识，基于{FRF x}辨识的前m阶动力学参数结果：自然频率为ω nx,1，ω nx,2，…，ω nx,m；阻尼比为ξ x,1，ξ x,2，…，ξ x,m；阵型矩阵为
Figure PCTCN2018105389-appb-000001
Figure PCTCN2018105389-appb-000002
其中
Figure PCTCN2018105389-appb-000003
的维数为2q×1，是主振动方向为X向对应每一敲击节点的第j阶阵型向量。基于{FRF y}辨识的前m阶动力学参数结果：自然频率为ω ny,1，ω ny,2，…，ω ny,m；阻尼比为ξ y,1，ξ y,2，…，ξ y,m；阵型矩阵为
Figure PCTCN2018105389-appb-000004
其中
Figure PCTCN2018105389-appb-000005
的维数为2q×1，是主振动方向为Y向对应每一敲击节点的第j阶阵型向量。
步骤⑤、沿刀轴方向将给定轴向切深a p下刀具与工件之间的啮合部分划分成p个切削层微元，根据每一层微元的中心与上述敲击节点的相对位置通过线性插值对这些切削层微元分配由步骤④辨识的模态阵型值。
步骤⑥、将不同类别动力学参数按照不同模态阶次拼装成与系统动力学模型相匹配的模态质量矩阵、模态阻尼矩阵、模态刚度矩阵和模态阵型矩阵。拼装后得到：
模态质量矩阵为
Figure PCTCN2018105389-appb-000006
模态阻尼矩阵为
Figure PCTCN2018105389-appb-000007
Figure PCTCN2018105389-appb-000008
模态刚度矩阵为
Figure PCTCN2018105389-appb-000009
模态阵型矩阵为：
Figure PCTCN2018105389-appb-000010
其中：
Figure PCTCN2018105389-appb-000011
的维数为2p×1，是主振动方向为X向或Y向对应每一切削层的第j阶阵型向量。
本发明的有益效果：该方法首先将一个三轴加速度传感器安装于刀尖，通过力锤在刀轴上预设的多个节点处分别沿两个水平正交的方向进行跨轴跨点模态敲击，将测量的传递函数按照不同测轴进行分组，对每组传递函数分别进行动力学参数(模态质量、阻尼、刚度和阵型)辨识。再将给定轴向切深下刀具 与工件之间的啮合部分沿刀轴划分成多个切削层微元，对每一层微元通过线性插值分配在上述节点处辨识的模态阵型值，并连同其它动力学参数进行与动力学模型相匹配的参数矩阵拼装处理。最后可获得包含跨轴跨点模态耦合效应的动力学参数矩阵。该方法可显著提高现有切削稳定性预报方法的精度，获得更加准确的稳定性叶瓣图，且加速度传感器只需一次安装。
附图说明
图1是本发明的跨轴跨点模态测试示意图，(a)代表力锤沿X方向敲击；(b)代表力锤沿Y方向敲击。
图2是本发明的根据三轴加速度传感器X轴和Y轴响应测量划分的工艺系统传递函数集合。
具体实施方式
下面结合附图和技术方案，详细说明本发明的具体实施。如图1(a)和1(b)所示，该方法首先将一个微型三轴加速度传感器安装于刀尖，通过力锤在刀轴上预设的多个节点处分别沿两个水平正交的方向(X向和Y向)进行跨轴和跨点的模态敲击实验。将测量的传递函数按照不同测轴进行分组，对每组传递函数分别进行动力学参数(模态质量、阻尼、刚度和阵型)辨识。再将给定轴向切深下刀具与工件之间的啮合部分沿刀轴划分成多个切削层微元，对每一层微元通过线性插值分配在上述节点处辨识的模态阵型值，并连同其它动力学参数进行与动力学模型相匹配的参数矩阵拼装处理。最后可获得包含跨轴耦合和跨点耦合的动力学参数矩阵。以侧铣过程为例，采用的具体步骤为：
步骤①、将铣刀安装于刀柄中，刀柄装夹到机床主轴上，建立刀具坐标系：坐标原点为刀具自由端的中心，X轴为刀具的进给方向，Y轴为待加工表面的垂直方向(顺铣垂直表面向外，逆铣垂直表面向里)，Z轴为远离刀具自由端的 刀具轴线方向。
步骤②、从刀具自由端开始按一定间距沿刀具轴线标记q个待敲击节点，如图1所示，将一个微型三轴加速度传感器安装于刀尖节点，然后在每个节点处分别从X和Y两个水平正交的方向上进行力锤敲击，测得主轴-刀柄-铣刀系统在每个节点处所有传递函数。
步骤③、在步骤②所测量的传递函数中，剔除所有由加速度传感器Z轴测得的传递函数，然后将剩余的传递函数根据振动响应是由加速度传感器的X轴或Y轴测量划分成不同的两组传递函数集合，如图2所示，分别标记为{FRF x}和{FRF y}。
步骤④、对步骤③得到的传递函数集合{FRF x}和{FRF y}分别进行动力学参数辨识，基于{FRF x}辨识的前m阶动力学参数结果：自然频率为ω nx,1，ω nx,2，…，ω nx,m；阻尼比为ξ x,1，ξ x,2，…，ξ x,m；阵型矩阵为
Figure PCTCN2018105389-appb-000012
Figure PCTCN2018105389-appb-000013
其中
Figure PCTCN2018105389-appb-000014
的维数为2q×1，是主振动方向为X向对应每一敲击节点的第j阶阵型向量。基于{FRF y}辨识的前m阶动力学参数结果：自然频率为ω ny,1，ω ny,2，…，ω ny,m；阻尼比为ξ y,1，ξ y,2，…，ξ y,m；阵型矩阵为
Figure PCTCN2018105389-appb-000015
其中
Figure PCTCN2018105389-appb-000016
的维数为2q×1，是主振动方向为Y向对应每一敲击节点的第j阶阵型向量。Ψ x和Ψ y可分别表达为
Figure PCTCN2018105389-appb-000017
Figure PCTCN2018105389-appb-000018
其中：u d,c,α,β,(d＝x或y,c＝x或y,α＝1,2,…,q,β＝1,2…,m)代表主振动方向为d向第α个敲击节点第β阶模态c方向的阵型位移。
步骤⑤、沿刀轴方向将给定轴向切深a p下刀具与工件之间的啮合部分划分成p个切削层微元，根据每一层微元的中心与上述敲击节点的相对位置通过线性插值对这些切削层微元分配由步骤④辨识的模态阵型位移值。
步骤⑥、将不同类别动力学参数按照不同模态阶次拼装成与系统动力学模型相匹配的模态质量矩阵、模态阻尼矩阵、模态刚度矩阵和模态阵型矩阵。拼装后得到：
模态质量矩阵为
Figure PCTCN2018105389-appb-000019
模态阻尼矩阵为
Figure PCTCN2018105389-appb-000020
Figure PCTCN2018105389-appb-000021
模态刚度矩阵为
Figure PCTCN2018105389-appb-000022
模态阵型矩阵为
Figure PCTCN2018105389-appb-000023
其中：
Figure PCTCN2018105389-appb-000024
Figure PCTCN2018105389-appb-000025
或
Figure PCTCN2018105389-appb-000026
或
Figure PCTCN2018105389-appb-000027
代表主振动方向为
Figure PCTCN2018105389-appb-000028
向第
Figure PCTCN2018105389-appb-000029
个切削层第
Figure PCTCN2018105389-appb-000030
阶模态
Figure PCTCN2018105389-appb-000031
方向的阵型位移。

Claims (1)

  1. 一种面向切削稳定性预报的跨轴跨点模态测试与参数辨识方法，其特征在于，步骤如下：
    步骤①、将铣刀安装于刀柄中，刀柄装夹到机床主轴上，建立刀具坐标系：坐标原点为刀具自由端的中心，X轴为刀具的进给方向，Y轴为待加工表面的垂直方向，顺铣垂直表面向外，逆铣垂直表面向里，Z轴为远离刀具自由端的刀具轴线方向；
    步骤②、从刀具自由端开始按一定间距沿刀具轴线标记q个待敲击节点，将一个微型三轴加速度传感器安装于刀尖节点，然后在每个待敲击节点处分别从X和Y两个水平正交的方向上进行力锤敲击，测得主轴-刀柄-铣刀系统在每个待敲击节点处所有传递函数；
    步骤③、在步骤②所测量的传递函数中，剔除所有由加速度传感器Z轴测得的传递函数，然后将剩余的传递函数根据振动响应是由加速度传感器的X轴或Y轴测量划分成不同的两组传递函数集合，分别标记为{FRF x}和{FRF y}；
    步骤④、对步骤③得到的传递函数集合{FRF x}和{FRF y}分别进行动力学参数辨识，基于{FRF x}辨识的前m阶动力学参数结果：自然频率为ω nx,1，ω nx,2，…，ω nx,m；阻尼比为ξ x,1，ξ x,2，…，ξ x,m；阵型矩阵为
    Figure PCTCN2018105389-appb-100001
    Figure PCTCN2018105389-appb-100002
    其中
    Figure PCTCN2018105389-appb-100003
    j＝1,2,…,m的维数为2q×1，是主振动方向为X向对应每一敲击节点的第j阶阵型向量；基于{FRF y}辨识的前m阶动力学参数结果：自然频率为ω ny,1，ω ny,2，…，ω ny,m；阻尼比为ξ y,1，ξ y,2，…，ξ y,m；阵型矩阵为
    Figure PCTCN2018105389-appb-100004
    其中
    Figure PCTCN2018105389-appb-100005
    j＝1,2,…,m的维数为2q×1，是主振动方向为Y向对应每一敲击节点的第j阶阵型向量；
    步骤⑤、沿刀轴方向将给定轴向切深a p下刀具与工件之间的啮合部分划分成p个切削层微元，根据每一层微元的中心与上述敲击节点的相对位置通过线 性插值对这些切削层微元分配由步骤④辨识的模态阵型值；
    步骤⑥、将不同类别动力学参数按照不同模态阶次拼装成与系统动力学模型相匹配的模态质量矩阵、模态阻尼矩阵、模态刚度矩阵和模态阵型矩阵；拼装后得到：
    模态质量矩阵为
    Figure PCTCN2018105389-appb-100006
    模态阻尼矩阵为
    Figure PCTCN2018105389-appb-100007
    Figure PCTCN2018105389-appb-100008
    模态刚度矩阵为
    Figure PCTCN2018105389-appb-100009
    模态阵型矩阵：
    Figure PCTCN2018105389-appb-100010
    其中：
    Figure PCTCN2018105389-appb-100011
    的维数为2p×1，是主振动方向为X向或Y向对应每一切削层的第j阶阵型向量，其中j＝1,2,…,m；d＝x或y。
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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CN113609611B (zh) * 2021-07-26 2024-04-09 西安交通大学 基于单元非线性技术的弱刚性零件表面位置误差预测方法
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102554326A (zh) * 2012-02-17 2012-07-11 上海交通大学 一种基于叶轮叶片动态刚度的铣削精加工方法
CN103559550A (zh) * 2013-09-09 2014-02-05 西北工业大学 多模态耦合下的铣削稳定域预测方法
CN107423502A (zh) * 2017-07-20 2017-12-01 西安交通大学 基于铣刀螺旋角和弯曲效应的铣削优化方法及优化系统
CN107457609A (zh) * 2017-08-25 2017-12-12 西安交通大学 基于刚度变化的铣削颤振抑制方法及铣削颤振优化系统
CN108958167A (zh) * 2018-09-13 2018-12-07 大连理工大学 一种面向切削稳定性预报的跨轴跨点模态测试与参数辨识方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102554326A (zh) * 2012-02-17 2012-07-11 上海交通大学 一种基于叶轮叶片动态刚度的铣削精加工方法
CN103559550A (zh) * 2013-09-09 2014-02-05 西北工业大学 多模态耦合下的铣削稳定域预测方法
CN107423502A (zh) * 2017-07-20 2017-12-01 西安交通大学 基于铣刀螺旋角和弯曲效应的铣削优化方法及优化系统
CN107457609A (zh) * 2017-08-25 2017-12-12 西安交通大学 基于刚度变化的铣削颤振抑制方法及铣削颤振优化系统
CN108958167A (zh) * 2018-09-13 2018-12-07 大连理工大学 一种面向切削稳定性预报的跨轴跨点模态测试与参数辨识方法

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112935865A (zh) * 2021-01-29 2021-06-11 华中科技大学 一种提高薄壁零件加工稳定性的方法及支撑装置
CN113609611B (zh) * 2021-07-26 2024-04-09 西安交通大学 基于单元非线性技术的弱刚性零件表面位置误差预测方法
CN114117727A (zh) * 2021-10-11 2022-03-01 沈阳航空航天大学 一种航空金属材料加工过程中材料去除率的预测方法
CN114462156A (zh) * 2021-12-28 2022-05-10 中国北方发动机研究所(天津) 随动气浮支撑的基于壳理论的薄壁筒镜像切削建模方法
CN114682836A (zh) * 2022-05-07 2022-07-01 南京航空航天大学 微细铣削系统的刀具模态测量实验辅助装置
CN114682836B (zh) * 2022-05-07 2023-06-30 南京航空航天大学 微细铣削系统的刀具模态测量实验辅助装置
CN120610512A (zh) * 2025-08-12 2025-09-09 中国科学院工程热物理研究所 一种基于知识图谱与大模型的机床动态特性感知与智能加工控制方法及系统

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