CN112729731B - Machine tool sensitive part identification method and device based on dynamic stiffness sensitivity - Google Patents
Machine tool sensitive part identification method and device based on dynamic stiffness sensitivity Download PDFInfo
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Abstract
The invention discloses a method and a device for identifying a sensitive part of a machine tool based on dynamic stiffness sensitivity, belongs to the technical field of machine tool sensitive part identification, and aims to solve the problems of long time consumption, low precision and the like in sensitive part identification in the prior art. The identification method comprises the following steps: step 1, obtaining the r-th order modal shape of the whole machine tool through modal analysis of the whole machine tool
Step 2, according to the dynamic stiffness of the r-th order mode relative to the stiffness KijAnd KmnAnd (3) obtaining the sensitivity of relative rigidity of different measuring points according to the changed proportion, wherein the formula is as follows:
and 3, obtaining dynamic stiffness sensitivity curves of different parts according to the step 2, and further identifying the sensitive parts of the whole machine tool. The method is suitable for identifying the sensitive parts of the whole machine tool.
Description
Technical Field
The invention belongs to the technical field of machine tool sensitive part identification, and particularly relates to a method and a device for identifying a machine tool sensitive part based on dynamic stiffness sensitivity.
Background
With the development of advanced manufacturing technology, the dynamics of machine tools, which have little influence on machining under conventional conditions, have become a major factor hindering the improvement of machine tool performance. The machining parameters can be optimized by analyzing the dynamic characteristics of the machine tool, and the machining quality and efficiency are improved. In addition, for a newly developed machine tool, the weak part needing to be optimized can be determined through dynamic characteristic analysis, and therefore the mechanical performance of the whole machine is improved.
At present, the dynamic characteristic analysis of the complete machine tool mainly comprises a finite element analysis method and an experimental modal analysis method.
The finite element analysis method is mainly used in the initial stage of machine tool design and research, and the dynamic characteristics of the whole machine tool are analyzed by modeling, assembling, meshing and adding constraints on the machine tool and each part, but the method has the defects of complex calculation, long time consumption and low precision. The experimental modal analysis method is used for analyzing the dynamic characteristics of the machine tool on the basis of the frequency response function of the actually measured machine tool. Because the machine tool is a complex system formed by multiple components, the experimental modal analysis method taking the actual machine tool as an analysis object is more reliable. The dynamic parameters obtained by the experimental modal analysis are used as the intermediate information of the machine tool dynamics, the differences of the machine tool space and each part are not combined with the specific application in the machining process of the machine tool, and the dynamic characteristics of the whole machine tool related to the position of the machine tool cannot be directly represented.
Disclosure of Invention
In view of the above analysis, the present invention aims to provide a method and an apparatus for identifying a sensitive component of a machine tool based on dynamic stiffness sensitivity, so as to solve the problems of long time consumption, low precision and the like in the identification of the sensitive component in the prior art.
The purpose of the invention is mainly realized by the following technical scheme:
on one hand, the invention provides a machine tool complete machine sensitive part identification method based on dynamic stiffness sensitivity, which comprises the following steps:
in the formula, Hr(ω) is the frequency response function of order r; kijStiffness of points i to j, KmnStiffness at points m to n;
the vibration mode value of the ith point of the ith dielectric mode is shown;
the mode shape value of the jth point of the ith dielectric mode is shown;
the mode shape value of the mth point of the mth dielectric mode;
the mode shape value of the nth point of the nth dielectric mode is shown;
and 3, obtaining dynamic stiffness sensitivity curves of different parts according to the step 2, and further identifying the sensitive parts of the whole machine tool.
Further, the step 1 comprises:
setting a measuring point;
exciting the machine tool and collecting signals;
and (3) acquiring the kinetic parameters of the machine tool by using an experimental modal analysis method.
Further, the acquired signals include an input force signal and an output vibration signal.
Further, the dynamic parameters include a natural frequency and a mode shape.
Furthermore, each part is provided with 1-30 measuring points.
Furthermore, 33 measuring points are arranged on a main shaft, a swing head, a ram, a cross beam and a tool handle of the planomiller.
Furthermore, the main shaft is provided with 7 measuring points, the swing head is provided with 11 measuring points, the ram is provided with 10 measuring points, the cross beam is provided with 4 measuring points, the tool shank is provided with 1 measuring point, and the measuring points on the tool shank are set as reference points.
Further, the machine tool is excited as follows: the machine tool is excited by the force hammer, a knocking point is selected as a measuring point on the tool handle, the knocking direction is the X direction, the X direction is the left movement direction of the cross beam, and the sampling frequency is 4096 Hz.
Further, excitation is carried out on the machine tool for multiple times, vibration response signals of multiple experiments are collected, and an average value is obtained.
On the other hand, the invention also provides a device for identifying the sensitive parts of the complete machine tool based on the dynamic stiffness sensitivity, and the identification method is adopted;
the device comprises an excitation device, an acceleration sensor, data acquisition equipment and data processing equipment;
the excitation device is used for exciting the whole machine tool;
the acceleration sensors are arranged on each part of the whole machine tool of the sensitive part to be identified, and each acceleration sensor is a measuring point;
the data acquisition equipment is used for acquiring signals detected by each acceleration sensor;
the data processing equipment is used for processing the signals acquired by the data acquisition equipment to determine kinetic parameters.
Further, the signals detected by the acceleration sensor comprise force signals input by the excitation device and vibration signals output by the excitation device; the data acquisition equipment is used for acquiring a force signal and a vibration signal;
further, the data processing equipment is used for calculating a frequency response function according to the collected force signals and vibration signals, identifying dynamic parameters according to the frequency response function, analyzing each order of mode, determining each order of mode vibration mode, and then determining the dynamic stiffness relative to the stiffness K according to the order r of the mode dynamic stiffnessijAnd KmnAnd the sensitivity of relative rigidity of different measuring points is obtained according to the changed proportion.
Further, if the peak value of the dynamic stiffness sensitivity of one part of the whole machine tool is higher than the peak values of the dynamic stiffness sensitivity of other parts, the part is determined as the sensitive part of the whole machine tool.
Compared with the prior art, the invention can at least realize one of the following technical effects:
(1) according to the formula of the dynamic stiffness sensitivity, the method only needs to obtain the corresponding vibration mode value when determining the dynamic stiffness sensitivity of a certain position, avoids the difficulty of solving the physical mass of the machine tool, and is more convenient to operate.
(2) In the identification method, the algorithm has small calculation amount and low time consumption. And because physical mass does not need to be obtained, all parts of the machine tool do not need to be regarded as equal in mass, and sensitive parts are identified more accurately.
(3) Compared with the modes of frequency response function, amplitude contrast and the like, the dynamic stiffness sensitivity of the invention has more reliable judgment of the sensitive part.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
FIG. 1 is a simplified schematic diagram of machine tool components;
FIG. 2 is a schematic diagram of a simulation system;
FIG. 3 is a schematic diagram of dynamic stiffness sensitivity of the case A in a simulation verification process;
FIG. 4 is a schematic diagram of dynamic stiffness sensitivity for case B during a simulation verification process;
FIG. 5 is a schematic view showing the arrangement of measuring points in example 1;
FIG. 6 is a steady state diagram of the experimental modal analysis of example 1;
FIG. 7 is a graphical representation of the sensitivity of the dynamic stiffness of example 1.
Reference numerals:
1-upright column; 2-a main spindle box; 3-X workbench; 4-Y stage; 5-a machine base; 6-a main shaft; 7-swinging the head; 8-ram; 9-a cross beam; 10-a knife handle; 11-frequency response function; 12-modal index function.
Detailed Description
The following is a detailed description of a method for identifying sensitive parts of a machine tool based on sensitivity to dynamic stiffness, which is provided in connection with specific embodiments for comparison and explanation purposes only, and the present invention is not limited to these embodiments.
Aiming at the defects of the existing method, the invention provides a method for identifying the sensitive parts of the complete machine tool based on the dynamic stiffness sensitivity. The dynamic stiffness sensitivity is defined as the rate of change of the machine specific modal dynamic stiffness with respect to the structural stiffness. Firstly, the dynamic parameters (natural frequency and modal shape) of the tested system are identified through experimental modal analysis, and then the sensitivity of each order of modal dynamic stiffness relative to each testing point is analyzed, so that the sensitivity of each order of modal dynamic stiffness of each part is obtained. If the dynamic stiffness sensitivity of a certain order of modes of all the parts is similar, the system has no sensitive part in the order of the modes; if the dynamic stiffness sensitivity of a certain order of mode of a certain component is larger, the component is judged as a sensitive component of the order of mode. The sensitive part has part-dependent and band-dependent properties, and the determined sensitive part is an intrinsic property of the machine tool, independent of the excitation force.
A machine tool complete machine sensitive part identification method based on dynamic stiffness sensitivity comprises the following steps:
in the formula, Hr(ω) is the frequency response function of the order r; kijStiffness of points i to j, KmnStiffness at points m to n;
the vibration mode value of the ith point of the ith dielectric mode is shown;
the mode shape value of the jth point of the ith dielectric mode is shown;
the mode shape value of the mth point of the mth dielectric mode;
the mode shape value of the nth point of the nth dielectric mode is shown.
And 3, obtaining dynamic stiffness sensitivity curves of different parts according to the step 2, and further identifying the sensitive parts of the whole machine tool.
The sensitive part is judged by comprehensively analyzing the dynamic stiffness sensitivity of each modal part of each order, and the mode with outstanding dynamic stiffness sensitivity of the sensitive part is judged as a key mode, so that the key mode of the sensitive part is applied to represent the dynamic characteristic of the whole machine of the machine tool, and the method combines the difference between the dynamic parameter and the dynamic characteristic of multiple parts. The following is a theoretical derivation process:
the equation of motion expression of a undamped multi-degree-of-freedom system is as follows:
wherein [ M ] is]For the system quality matrix, [ K]The system stiffness matrix is a symmetric matrix; { X } and
respectively displacement vectors and acceleration vectors.
In order to solve the characteristic value of the system, the expression of the free vibration characteristic equation is derived as follows:
where omega is the natural frequency of the mode,
is a vector of n × 1, which is a modal shape vector of the system.
And (3) obtaining a frequency response function of the system through transformation:
in the formula mrIs the r-th order modal quality, k, of the systemrIs the r-th order modal stiffness of the system,
is a system ofThe mode shape of the r-th order mode,
is that
Transposed form of (2).
The nth order modal stiffness is defined by a stiffness matrix and a modal shape vector:
the derivative of equation (3) with respect to the structural stiffness matrix K is calculated,
sensitivity expression of the dynamic stiffness of the nth order mode relative to the stiffness among all degrees of freedom of the system:
from equation (6), the coefficient of the dynamic stiffness of the r-th order mode relative to the sensitivity of the system in each degree of freedom
Are all the same, the difference is mainly
In order to obtain sensitive components in a certain order of mode, the dynamic stiffness of the order of mode relative to each component needs to be analyzedSensitivity of rigidity change of each measuring point, and dynamic rigidity of the r-th order mode relative to rigidity KijAnd KmnThe ratio of change was:
the accuracy of the sensitive part is judged by establishing a simulation system to verify the dynamic stiffness sensitivity method.
Fig. 1 is a simplified schematic diagram of a machine tool structure, and in order to improve the similarity between a simulation model and an actual machine tool system, a simulation system similar to the distribution of machine tool components is firstly established, as shown in fig. 2. Two groups of physical parameters are defined aiming at the established spring-mass simulation system, so that the accuracy of the sensitive part is judged by a dynamic stiffness sensitivity analysis method more intuitively. The sensitive part is set by setting a smaller rigidity value between the internal degrees of freedom of the part, namely the part with smaller rigidity is the sensitive part, and the sensitive part does not exist in the case A and exists in the case B. The method comprises the steps of respectively defining the mass and the rigidity of the system according to the two conditions, carrying out modal analysis on the system to obtain dynamic parameters, carrying out dynamic rigidity sensitivity analysis to judge a sensitive component, and comparing the obtained sensitive component with a set sensitive component.
As shown in fig. 2, the simulation system includes 5 components and 50 degrees of freedom in total. Wherein, the freedom degrees 1-10 represent a machine base 5, the freedom degrees 11-20 represent a vertical column 1, the freedom degrees 21-30 represent a spindle box 2, the freedom degrees 31-40 represent a Y workbench 4, and the freedom degrees 41-50 represent an X workbench 3.
If the simulation system is an undamped system, the damping of each degree of freedom of the simulation system is as follows:
C1＝C2＝…＝C50＝0 (9)
the simulation system has the following quality degrees of freedom:
M1＝M2＝…＝M50＝1Kg (10)
for case a, no sensitive parts are included, the stiffness inside the parts is uniform:
K1＝K2＝…＝K50＝1000N/m (11)
for case B, the sensitive part is set as the headstock, the remaining part stiffness is still 1000N/m, and the headstock stiffness is:
K21＝K22＝…＝K30＝1N/m (12)
the mass matrix and stiffness matrix of the system are further described as follows:
and (3) respectively substituting the mass matrix and the rigidity matrix of the condition A and the condition B into the formula (2) to obtain the natural frequency and the mode shape of the first four-order mode of the system, thereby obtaining a dynamic rigidity sensitivity curve according to the formula (8) and analyzing the dynamic rigidity sensitivity of each measuring point of each system. First, the dynamic stiffness sensitivity of the system in each degree of freedom is analyzed in case a, as shown in fig. 3. FIG. 3(a) shows the dynamic stiffness sensitivity of the 1 st order mode of each degree of freedom of the system, and the dynamic stiffness sensitivity of each component is basically the same; FIG. 3(b) shows the dynamic stiffness sensitivity of the 2 nd order mode of each degree of freedom of the system, and the dynamic stiffness sensitivity of the stand 5 is smaller relative to other components; fig. 3(c) shows the 3 rd order modal dynamic stiffness sensitivity of each degree of freedom of the system, and the dynamic stiffness sensitivity of the base 5 is larger than that of other components. Fig. 3(d) shows the 4 th order modal dynamic stiffness sensitivity of each degree of freedom of the system, and the dynamic stiffness sensitivity of the base 5 is larger than that of other components. The result of comprehensively analyzing the dynamic stiffness sensitivity of the first four orders of the degrees of freedom of the system shows that the difference of the dynamic stiffness sensitivity of each order of the modes of different components is small, so that the system has no sensitive component. The sensitivity of the 2 nd order modal dynamic stiffness of the machine base 5 is low, and the sensitivity of the 3 rd and 4 th order modal dynamic stiffness of the machine base 5 is high, in this case, the machine base 5 is possibly located at a special position and is simultaneously connected with a plurality of working tables and the upright posts 1, and small differences of the sensitivity of the modal dynamic stiffness of each component can be related to the spatial position of the component in the system.
And B, analyzing the dynamic stiffness sensitivity of each degree of freedom of the system, as shown in FIG. 4. Fig. 4(a) shows the dynamic stiffness sensitivity of the 1 st order mode of each degree of freedom of the system, and the dynamic stiffness sensitivity of the spindle head 2 is much larger than that of other components. Fig. 4(b) shows the sensitivity of the dynamic stiffness of the 2 nd order mode for each degree of freedom of the system, fig. 4(c) shows the sensitivity of the dynamic stiffness of the 3 rd order mode for each degree of freedom of the system, fig. 4(d) shows the sensitivity of the dynamic stiffness of the 4 th order mode for each degree of freedom of the system, and the sensitivity of the dynamic stiffness of the 2 nd order mode of the head stock is larger than that of the other members in the sensitivity distribution diagrams of the dynamic stiffness of the 2 rd, 3 rd and 4 th order modes. The result of comprehensively analyzing the dynamic stiffness sensitivity of the first four-order mode of each degree of freedom of the system shows that the dynamic stiffness sensitivity of the spindle box 2 relative to other components is much larger, and the dynamic stiffness sensitivity has obvious mutation, so that the spindle box 2 is judged as the sensitive component of the system and is matched with the set result, and the accuracy of identifying the sensitive component according to the dynamic stiffness sensitivity is proved.
The invention also provides a machine tool complete machine sensitive part identification device based on dynamic stiffness sensitivity, which comprises an excitation device, an acceleration sensor, data acquisition equipment and data processing equipment, wherein the excitation device is used for exciting the whole machine tool sensitive part; the excitation device is used for exciting the whole machine tool; the acceleration sensors are arranged on all parts of the complete machine tool of the sensitive part to be identified, and each acceleration sensor is a measuring point; the data acquisition equipment is used for acquiring signals detected by each acceleration sensor; the data processing device is used for processing the signals acquired by the data acquisition device to determine the kinetic parameters.
Example 1
In order to obtain the dynamic parameters of the machine tool, experimental modal analysis is carried out on a five-axis gantry machining center. The force hammer model selected in the experiment is PCB-HDFC-DFC-1 (sensitivity: 2.2 mv/N; measuring range: +/-2224N), five-axis gantry machining center, acceleration sensor, LMS SCADAS Mobile SCM05 data acquisition equipment and other equipment.
33 measuring points are arranged on a main shaft 6, a swinging head 7, a ram 8, a cross beam 9 and a tool handle 10 of the planer type milling machine structure, and a three-way acceleration sensor is adopted for signal acquisition, as shown in the arrangement of measuring points in a knocking experiment in fig. 5. The measuring points 1-7 are arranged on the spindle 6 part, the measuring points 8-18 are arranged on the pendulum head 7 part, the measuring points 19-28 are arranged on the ram 8 part, the measuring points 29-32 are arranged on the beam 9 part, the measuring point 33 is arranged on the tool shank 10 part, and the measuring point 33 is set as the reference point of the experiment. Because the LMS SCADAS Mobile SCM05 data acquisition equipment can only be connected with 12 acceleration sensors at a time, the three-way acceleration sensors except the part of the tool handle 10 need to be fixed as reference points, and the other 11 acceleration sensors respectively move 3 positions to complete the measurement of all measuring points.
And in the static state of the machine tool, exciting the machine tool by a force hammer, collecting a vibration response signal and obtaining the dynamic parameters (natural frequency and modal shape) of the machine tool by applying an experimental modal analysis method. The knocking point is selected as a measuring point of the tool handle 10, the knocking direction is the X direction, the X direction is the left movement direction of the cross beam 9, and the sampling frequency is 4096 Hz. In order to suppress noise interference, the tapping experiment was repeated five times, and then the average value of the collected signals was taken five times. And simultaneously, acquiring an input force signal (the machine tool is knocked by force hammer excitation, and the force hammer knocking signal is used as an input force) and an output vibration signal, and after a frequency response function is calculated, identifying the kinetic parameters of the machine tool by using a PloyMax algorithm carried by LMS software. And (3) carrying out kinetic parameter identification on frequency response functions of all measuring points in the X direction in a tapping experiment, setting an analysis frequency band within 10-500Hz, and setting a modal order to be 32 orders. The frequency response functions of all measuring points of the machine tool are comprehensively analyzed, a steady state diagram of experimental modal analysis is obtained and is shown in fig. 6, and curves of the frequency response function 11 and the modal index function 12 are shown in fig. 6. According to the Frequency Response Function (FRF) and the distribution of pole queues in the steady-state diagram, six-order modes are identified in the range of 10-500Hz, the natural frequencies of the modes in each order are detailed in Table 1, and the mode shapes are not listed in specific values. The modal natural frequency of each order corresponds to the modal shape one by one.
TABLE 1 sixth order modal natural frequency of machine tool
And (3) substituting the modal shape obtained by the experimental modal analysis into the formula (8), so that the dynamic stiffness sensitivity of each degree of freedom of the machine tool is analyzed according to a dynamic stiffness sensitivity algorithm, and the dynamic stiffness sensitivity of each degree of freedom is arranged according to the sequence of the measuring points, as shown in fig. 7. Fig. 7(a) to 7(f) sequentially show the first six-order modal dynamic stiffness sensitivity of each measurement point of the machine tool. Fig. 7(a) shows the 1 st order modal dynamic stiffness sensitivity of each degree of freedom of the machine tool, and it is easy to observe that the peak values of the main shaft 6, the swing head 7 and the ram 8 are not greatly different, and are all much larger relative to the cross beam 9, i.e. the cross beam 9 has lower dynamic stiffness sensitivity relative to other components. Fig. 7(b) shows the 2 nd order modal dynamic stiffness sensitivity of each degree of freedom of the machine tool, the peak values of the swing head 7 and the ram 8 are close to and maximum, the peak value of the main shaft 6 is second, and the peak value of the cross beam 9 is minimum, namely the dynamic stiffness sensitivity of the swing head 7 and the slide matrix is high. Fig. 7(c) shows the 3 rd order modal dynamic stiffness sensitivity of each degree of freedom of the machine tool, and the position of the swing head 7 relative to the main shaft 6, the ram 8 and the cross beam 9 is much higher, that is, the dynamic stiffness sensitivity of the swing head 7 relative to other components is much higher. Fig. 7(d) shows the 4 th order modal dynamic stiffness sensitivity of each degree of freedom of the machine tool, and it is easy to observe that the peak values of the main shaft 6, the swing head 7 and the ram 8 are not greatly different, and all are much larger relative to the cross beam 9, i.e. the cross beam 9 has lower dynamic stiffness sensitivity relative to other components. Fig. 7(e) shows the sensitivity of the dynamic stiffness of the 5 th order mode of each degree of freedom of the machine tool, and similarly to the case of the 3 rd order mode, the sensitivity of the dynamic stiffness of the pendulum head 7 is much higher compared with other components. Fig. 7(f) shows the dynamic stiffness sensitivity of the 6 th order mode of each degree of freedom of the machine tool, and similarly to the case of the 3 rd order mode, the dynamic stiffness sensitivity of the pendulum head 7 is much higher compared with other components. The sensitivity of the dynamic stiffness of the first six-order mode relative to the change of the stiffness of each measuring point of the machine tool is comprehensively analyzed, and the dynamic stiffness sensitivity of the swing head 7 component is much higher than that of other components. As can be seen from fig. 7(c), 7(e), and 7(f), in the third-order modal dynamic stiffness sensitivity analysis, the dynamic stiffness sensitivity of the swing head 7 is much higher than that of other components, so that the swing head 7 component is used as a sensitive component, and the 3 rd, 5 th, and 6 th order modes are used as key modes to characterize the complete machine dynamics characteristics of the machine tool.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (10)
1. A machine tool complete machine sensitive part identification method based on dynamic stiffness sensitivity is characterized by comprising the following steps:
step 1, obtaining the r-th order modal shape of the whole machine tool through modal analysis of the whole machine tool
Step 2, according to the dynamic stiffness of the r-th order mode relative to the stiffness KijAnd KmnAnd (3) obtaining the sensitivity of relative rigidity of different measuring points according to the changed proportion, wherein the formula is as follows:
in the formula, Hr(ω) is the frequency response function of the order r; kijStiffness of points i to j, KmnStiffness at points m to n;
the mode shape value of the ith point of the nth-order mode is shown;
the mode shape value of the jth point of the nth-order mode is shown;
the mode shape value of the mth point of the mth order mode;
the mode shape value of the nth point of the nth order mode is shown;
and 3, obtaining dynamic stiffness sensitivity curves of different parts according to the step 2, and further identifying the sensitive parts of the whole machine tool.
2. The machine tool complete machine sensitive part identification method based on the dynamic stiffness sensitivity is characterized in that the step 1 comprises the following steps:
setting a measuring point;
exciting the machine tool and collecting signals;
and (3) acquiring the kinetic parameters of the machine tool by using an experimental modal analysis method.
3. The method for identifying the sensitive part of the complete machine tool based on the dynamic stiffness sensitivity is characterized in that the acquired signals comprise input force signals and output vibration signals.
4. The method for identifying the sensitive parts of the complete machine tool based on the dynamic stiffness sensitivity is characterized in that the dynamic parameters comprise natural frequency and modal shape.
5. The method for identifying the sensitive parts of the complete machine tool based on the dynamic stiffness sensitivity of the claim 4 is characterized in that 1-30 measuring points are arranged on each part.
6. The method for identifying the sensitive parts of the complete machine tool based on the dynamic stiffness sensitivity of claim 5 is characterized in that 33 measuring points are arranged on a main shaft, a swing head, a ram, a cross beam and a tool shank of a planomiller.
7. The method for identifying the sensitive part of the complete machine tool based on the dynamic stiffness sensitivity of claim 6 is characterized in that 7 measuring points are arranged on the main shaft, 11 measuring points are arranged on the swing head, 10 measuring points are arranged on the ram, 4 measuring points are arranged on the cross beam, 1 measuring point is arranged on the tool shank, and the measuring points on the tool shank are set as reference points.
8. The method for identifying the sensitive parts of the complete machine tool based on the dynamic stiffness sensitivity of the claim 6 is characterized in that the excitation of the complete machine tool is as follows: the machine tool is excited by the force hammer, a knocking point is selected as a measuring point on the tool handle, the knocking direction is the X direction, the X direction is the left movement direction of the cross beam, and the sampling frequency is 4096 Hz.
9. The method for identifying the sensitive parts of the complete machine tool based on the dynamic stiffness sensitivity of any one of claims 2 to 8, wherein excitation of the machine tool is repeated for a plurality of times, vibration response signals of a plurality of experiments are collected and averaged.
10. A machine tool complete machine sensitive part identification device based on dynamic stiffness sensitivity executes the machine tool complete machine sensitive part identification method based on dynamic stiffness sensitivity of any one of claims 1 to 9, and is characterized by comprising an excitation device, an acceleration sensor, data acquisition equipment and data processing equipment;
the excitation device is used for exciting the whole machine tool;
the acceleration sensors are arranged on each part of the whole machine tool of the sensitive part to be identified, and each acceleration sensor is a measuring point;
the data acquisition equipment is used for acquiring signals detected by the acceleration sensors;
the data processing equipment is used for processing the signals acquired by the data acquisition equipment and determining kinetic parameters.
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