A method for selecting temperature measurement points for machine tool thermal error modeling

Abstract

The invention relates to a method for selecting temperature measurement points for machine tool thermal error modeling, which belongs to the technical field of precision control of numerically controlled machine tools, solves the problems existing in the existing temperature measurement point selection method, and comprises the following steps: according to a pre-established three-dimensional model of a machine tool, a thermal behavior simulation model of the machine tool is established in combination with the thermal boundary conditions of the machine tool; under set working conditions, isolated deformation analysis is performed on each component of the thermal behavior simulation model of the machine tool in turn to obtain the thermal deformation generated by each component under the action of the thermal field of the set working conditions, and the influence degree of the thermal deformation generated by each component of the machine tool on the thermal error is determined through the thermal deformation of each component; the temperature measurement points in the machine tool are determined according to the obtained influence degree, and the selection method of the invention is used to obtain more accurate results.

Description

Technical Field

[0001] The invention relates to the technical field of precision control of numerically controlled machine tools, and in particular to a method for selecting temperature measurement points for thermal error modeling of machine tools. Background Art

[0002] The statements herein merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] With the increasing demand for product precision, ultra-precision machining is being used in more and more scenarios. However, due to the existence of machining errors, dimensional errors of workpieces are caused. Among ultra-precision machining errors, thermal errors account for the largest proportion. Therefore, in order to achieve high-precision machining of precision workpieces, it is necessary to reduce the impact of thermal errors.

[0004] At present, the main measure to control thermal errors is to use error compensation method. The core of error compensation method is to build a thermal error model. Since temperature data is easy to collect and often used as model input for modeling, the type and number of selected temperature measurement points have a direct impact on the performance of the thermal error model. If the type of temperature measurement point is not selected properly, the established model cannot accurately characterize the dynamic changes of thermal errors. If the number of temperature measurement points is too small, it will affect the prediction accuracy of the model. If the number of temperature measurement points is too large, it will bring about problems of complex modeling and data collinearity. Therefore, selecting appropriate temperature measurement points to establish the machine tool thermal error model is the primary prerequisite for controlling thermal errors.

[0005] At present, there are some methods for selecting temperature measurement points for machine tool thermal error modeling. The weighted integrated temperature sensitive point combination selection method for machine tool spindle thermal error modeling, which was authorized by the Chinese invention patent with the authorization number CN111414977B on June 20, 2023, calculates the correlation coefficient between the temperature data and the thermal error data in the preliminary selection range, and uses a clustering algorithm to screen the temperature measurement points based on the correlation coefficient calculation results. The Chinese invention patent with the authorization number CN114895630B on June 21, 2024 is a method for selecting temperature sensitive points for a machine tool thermal error prediction model. Temperature sensors are arranged at all heat sources of the machine tool, and the importance of each temperature is listed by calculating the correlation coefficient between the main component of the standardized temperature data and the thermal deformation. The number and location of the temperature measurement points are determined based on the ranked importance levels.

[0006] From the above analysis, it can be seen that the existing temperature measurement point selection method is mainly divided into two steps. First, the preliminary selection range of the temperature measurement points is determined, and then various screening methods are used to analyze the correlation between the temperature measurement points and thermal errors within the preliminary selection range, and then the selected machine tool temperature measurement points are determined. It can be seen that although the above method can screen the temperature measurement points of the machine tool, there are still some problems. The preliminary selection range of the temperature measurement points is usually determined based on the experience of the researchers, lacking a theoretical basis, and it is very likely that some key temperature measurement points will be missed in the preliminary selection stage. In addition, the screening methods used all analyze the correlation between data from the perspective of mathematical statistics, but fail to fully consider the mechanism of the generation of system thermal errors, resulting in changes in the selected temperature measurement points when the working conditions change, thereby affecting the generalization performance and matching of the model. Summary of the invention

[0007] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a method for selecting temperature measurement points for machine tool thermal error modeling, which solves the problems existing in the current temperature measurement point selection method.

[0008] In order to achieve the above object, the present invention is implemented through the following technical solutions:

[0009] An embodiment of the present invention provides a method for selecting temperature measurement points for machine tool thermal error modeling, comprising the following steps:

[0010] According to the pre-established three-dimensional model of the machine tool, the thermal behavior simulation model of the machine tool is established in combination with the thermal boundary conditions of the machine tool;

[0011] Under the set working conditions, the isolated deformation analysis is carried out on each component of the thermal behavior simulation model of the machine tool in turn to obtain the thermal deformation of each component under the action of the thermal field of the set working conditions. The influence of the thermal deformation of each component of the machine tool on the thermal error is determined through the thermal deformation of each component.

[0012] The temperature measurement points in the machine tool are determined according to the obtained influence degree.

[0013] Optionally, the thermal boundary conditions include system heat generation and convection heat transfer coefficients of machine tool setting components.

[0014] Optionally, the system heat generation includes the heat generated by the motor and the heat generated by the bearings of the machine tool.

[0015] Optionally, the heat generated by the motor is obtained based on the motor output torque, motor speed and mechanical efficiency of the motor, and the heat generated by the bearing is obtained based on the bearing rotation speed, the load friction torque generated by the bearing material elastic hysteresis and local differential friction, and the viscous friction torque generated by the bearing and the lubricating fluid.

[0016] Optionally, the convective heat transfer coefficient is obtained based on the Nusselt constant, the fluid heat transfer coefficient, and the component characteristic dimensions of the machine tool setting assembly.

[0017] Optionally, the established three-dimensional model of the machine tool is imported into the thermal simulation platform, and a thermal behavior simulation model of the machine tool is obtained after meshing, adding material properties, and applying thermal boundary conditions.

[0018] Optionally, the temperature and thermal deformation data of the machine tool are experimentally measured under set working conditions to obtain temperature experimental measurement data and thermal deformation experimental measurement data, and at the same time, a temperature field analysis is performed on the thermal behavior model under the set working conditions to obtain temperature field analysis results, the temperature field analysis results are applied to the thermal behavior simulation model and a deformation field analysis is performed to obtain deformation field analysis results, the temperature experimental measurement data are compared with the temperature field analysis results, and the thermal deformation experimental measurement data are compared with the deformation field analysis results. If the temperature experimental measurement data and the temperature field analysis results are inconsistent or the thermal deformation experimental measurement data are inconsistent with the deformation field analysis results, the thermal boundary conditions are optimized until the temperature experimental measurement data and the temperature field analysis results are consistent and the thermal deformation experimental measurement data are consistent with the deformation field analysis results, and then isolated deformation analysis is performed on each component in turn.

[0019] Optionally, the method of isolated deformation analysis is: design the thermal expansion coefficient of the components set in the thermal behavior simulation model of the machine tool to be actual values, set the thermal expansion coefficients of the remaining components to 0, and then perform temperature field analysis, apply the temperature field analysis results to the thermal behavior simulation model and perform deformation field analysis.

[0020] Optionally, deformation field analysis results of each component are obtained after isolated deformation analysis of each component of the machine tool, the total thermal error influence is obtained based on the deformation field analysis results of all components, and the influence of the thermal deformation generated by each component on the thermal error is determined based on the proportion of the deformation field analysis result of each component to the total thermal error influence.

[0021] Optionally, a specific method for determining the temperature measurement point in the machine tool according to the acquired influence degree is:

[0022] Different temperature measurement point selection schemes are brought into the thermal error prediction model for analysis to obtain the thermal error prediction values ​​of different temperature measurement point selection schemes. Actual measurements are performed according to different temperature measurement point selection schemes to obtain the actual thermal error values ​​corresponding to the different temperature measurement point selection schemes.

[0023] Among them, the priority level of the arrangement of the temperature measuring points on each component is determined according to the influence of the thermal deformation of each component of the machine tool on the thermal error;

[0024] The average absolute error is obtained according to multiple thermal error prediction values ​​and the corresponding actual thermal error values, and the temperature measurement point selection scheme corresponding to the minimum average absolute error is selected as the optimal temperature measurement point selection scheme.

[0025] The beneficial effects of the present invention are as follows:

[0026] The temperature measuring point selection method of the present invention performs isolated deformation analysis on each component of the machine tool in turn, and obtains the thermal deformation of each component of the machine tool under the action of the thermal field, thereby obtaining the degree of influence of the thermal deformation generated by each component on the thermal error, and finally determines the temperature measuring points in the machine tool according to the obtained degree of influence. Compared with the traditional method of selecting temperature measuring points by combing through statistical analysis based on the experience of researchers, the selection method of the present invention guides the screening process of temperature measuring points from the perspective of the formation mechanism of thermal errors, avoids the complicated correlation analysis process, and the selection results are more accurate, avoiding the change of the selected temperature measuring points when the working conditions change, thereby affecting the generalization performance and matching of the model. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0028] Figure 1 is a flow chart of Embodiment 1 of the present invention;

[0029] Figure 2 is a schematic diagram of a three-dimensional model of a machine tool established in Example 1 of the present invention;

[0030] Figure 3 This is a schematic diagram of determining the number of temperature measuring points in Example 1 of the present invention;

[0031] Among them, 1. base, 2. Y-axis feed system, 3. saddle, 4. X-axis feed system, 5. workbench, 6. spindle system, 7. Z-axis feed system, 8. column. DETAILED DESCRIPTION

[0032] Example 1

[0033] This embodiment provides a method for selecting temperature measurement points for integrated thermal error modeling, and takes the ACE-V500 vertical machining center as an example. Figure 1 As shown, the following steps are included:

[0034] Step 1: Create a 3D model of the machine tool.

[0035] In this embodiment, the structural parameters of each component of the machine tool are measured to obtain the structural dimensional parameters and assembly relationships of each component of the machine tool. Then, a three-dimensional model of the machine tool is established in the modeling platform based on the obtained structural dimensional parameters and assembly relationships of each component of the machine tool. The construction of the assembly relationship, the application of dimensional parameters and the interference detection of each component are completed in the three-dimensional model. The structural dimensional parameters of key components must be consistent with those of the actual machine tool, such as the feed system and the spindle system. Some components that have little impact on the thermal behavior solution of the machine tool can be omitted, such as the CNC system and the control cabinet.

[0036] The above steps can be carried out using existing technologies and will not be described in further detail here.

[0037] In this embodiment, Figure 2 As shown, the components of the three-dimensional model of the machine tool include a base 1, a Y-axis feed system 2, a saddle 3, an X-axis feed system 4, a worktable 5, a spindle system 6, a Z-axis feed system 7 and a column 8.

[0038] Step 2: Solve the thermal boundary conditions of the machine tool under different set working conditions.

[0039] In this embodiment, the thermal boundary conditions of the machine tool under six set working conditions are obtained. Since the feed of the worktable 5 has little effect on the thermal error of the machine tool, a fixed feed speed is selected for research in this embodiment. The six set working conditions are shown in Table 1.

[0040] Table 1. Machine tool working conditions

[0041]

[0042] The thermal boundary conditions of the machine tool are obtained under six set working conditions.

[0043] In this embodiment, the thermal boundary conditions of the machine tool include system heat generation and convection heat transfer coefficients of the machine tool setting components.

[0044] Specifically, the system heat generation includes motor heat generation and bearing heat generation.

[0045] The heat generated by the motor is calculated using the following formula:

[0046]

[0047] in is the motor output torque, is the motor speed, is the mechanical efficiency of the motor. The above parameters are the motor’s own parameters and can be obtained through experiments.

[0048] The heat generation of the bearing is calculated using the following formula:

[0049]

[0050] in, is the bearing rotation speed, which is consistent with the motor speed. is the load friction torque generated by the elastic hysteresis of the bearing material and the local differential friction, It is the viscous friction torque generated by the bearing and the lubricating fluid.

[0051] The load friction torque can be expressed as follows:

[0052]

[0053] in, is the bearing load factor, is the bearing working load, is the bearing mean diameter.

[0054] The viscous friction torque can be calculated by the following formula:

[0055]

[0056] in, is a coefficient related to bearing type and lubrication, is the kinematic viscosity of the lubricant inside the bearing.

[0057] The calculation method of the convection heat transfer coefficient of the machine tool setting component is:

[0058]

[0059] in, For the Angry Shelters constant, is the fluid heat transfer coefficient, The characteristic dimensions of the components of the machine tool setting assembly. The characteristic dimensions refer to the geometric dimensions that affect the flow and heat transfer characteristics of the fluid. The characteristic dimensions are usually dimensions related to the flow boundary layer and can represent important geometric dimensions in the flow direction of the fluid, such as the radial dimensions of the Y-axis bearing seat in the Y-axis feed system 2, the axial dimensions of the spindle in the spindle system 6, and the axial dimensions of the Z-axis screw shaft in the Z-axis feed system 7. In this embodiment, the characteristic dimensions of the components of the machine tool setting assembly can be measured according to actual needs and will not be described in detail here.

[0060] In this embodiment, the thermal boundary conditions under six set working conditions are shown in Table 2:

[0061] Table 2. Thermal boundary conditions for machine tool components

[0062]

[0063] Among them, the spindle motor and the spindle are components in the spindle system 6, the Z-axis proximal bearing and the Z-axis screw shaft are components in the Z-axis feed system 7, and the Y-axis bearing seat is a component in the Y-axis feed system 2.

[0064] Step 3: Establish a thermal behavior simulation model of the machine tool.

[0065] In this embodiment, the established three-dimensional model of the machine tool is imported into the thermal simulation platform, and then the structure is simplified, the mesh is divided, the material properties corresponding to each component are added, and the thermal boundary conditions obtained in step 2 are applied to obtain the thermal behavior simulation model of the machine tool.

[0066] The above steps can be performed using the existing simulation platform operation steps and will not be described in detail here.

[0067] Step 4: In the simulation platform, according to the set working conditions, the temperature field analysis of the thermal behavior simulation model is performed under the set working conditions, and the temperature field of the machine tool is solved to obtain the temperature field analysis results.

[0068] Then the temperature field analysis results are applied to the thermal behavior simulation model and the deformation field analysis is performed to solve the deformation field of the machine tool and obtain the deformation field analysis results.

[0069] Step 5: Under the set working conditions, use a PT100 temperature sensor to measure the temperature of each component of the machine tool to obtain temperature experimental measurement data. In this embodiment, 26 temperature measurement points are selected to verify the accuracy of the thermal behavior simulation model. The distribution of the 26 temperature measurement points in each component of the machine tool can be manually set. Five eddy current displacement sensors are used to measure the strain values ​​of the workbench 5 and the tool before and after deformation using the five-point method, and the strain values ​​are used as thermal deformation experiment measurement data. In the simulation platform, the temperature simulation values ​​of each component are obtained according to the temperature field analysis results. In the simulation platform, the strain values ​​of the tool and the workbench 5 before and after deformation are obtained as deformation field analysis results, and the obtained deformation field analysis results are used as thermal deformation simulation values. If the temperature experiment measurement data and the temperature simulation values ​​are inconsistent or the thermal deformation experiment measurement data and the thermal deformation simulation values ​​are inconsistent, the thermal boundary conditions are adjusted and optimized until the temperature experiment measurement data and the temperature simulation values ​​are consistent, the thermal deformation experiment measurement data and the thermal deformation simulation values ​​are consistent, the temperature experiment measurement data and the temperature simulation values ​​are consistent means that the difference between the two is less than the set first error value, and the thermal deformation experiment measurement data and the thermal deformation simulation values ​​are consistent means that the difference between the two is less than the set second error value.

[0070] By optimizing the thermal boundary conditions, the thermal behavior simulation model of the machine tool can better describe the thermal behavior of the machine tool during operation, and the next step of analysis can be carried out.

[0071] Step 6: Perform isolated deformation analysis on each component of the thermal behavior simulation model in turn. For a component, the specific steps of isolated deformation analysis are as follows:

[0072] In the simulation platform, the thermal expansion coefficient of the component is set to the actual value according to the material properties of the component, and the thermal expansion coefficients of the remaining components of the machine tool are all set to 0, so as to shield the effects of the remaining components on the final thermal error of the machine tool. Then, the temperature field analysis of the thermal behavior simulation model under the set working conditions is performed, and the obtained temperature field analysis results are applied to the thermal behavior simulation model and deformation field analysis is performed to obtain the deformation field analysis results of the component.

[0073] Using the same method, the deformation field analysis results of each component are obtained in turn.

[0074] The total thermal error influence is obtained based on the deformation field analysis results of all components. The influence of the thermal deformation of each component under the set working condition thermal field on the thermal error is determined based on the proportion of the deformation field analysis result of each component to the total thermal error influence.

[0075] In this embodiment, the influence of various components of the machine tool on the thermal error is shown in Table 3:

[0076] Table 3. Effect of deformation of each component on thermal error

[0077]

[0078] The Z-axis direction is the output movement direction of the Z-axis feeding system 7 , the X-axis direction is the output movement direction of the X-axis feeding system 4 , and the Y-axis direction is the output movement direction of the Y-axis feeding system 2 .

[0079] It can be seen from Table 3 that for any direction and working condition, the influence of each component on the thermal error is different, but the most significant influences are the spindle system 6, base 1, column 8 and saddle 3 of the machine tool.

[0080] Step 7: Select the temperature measurement points based on the influence of each component on the thermal error, and further determine the number and location of the temperature measurement points.

[0081] In this embodiment, different temperature measurement point selection schemes are selected and brought into the prediction model for analysis to obtain thermal error prediction values ​​corresponding to different temperature measurement point selection schemes, and multiple thermal error prediction values ​​and corresponding actual thermal error values ​​obtained by actual measurements are brought into the mean absolute error model to obtain the mean absolute error, and the temperature measurement point selection scheme corresponding to the minimum mean absolute error is selected as the optimal temperature measurement point selection scheme.

[0082] Among them, the priority level of arrangement of temperature measuring points on each component is determined according to the influence of thermal deformation of each component of the machine tool on thermal error.

[0083] The method for determining the temperature measurement point selection scheme is: the number of temperature measurement points is selected as 1, 2, 3, 4, 5, 6, 7 and 8 respectively.

[0084] In this embodiment, the influence of each component of the machine tool on the thermal error is arranged from large to small as the spindle system 6, the base 1, the column 8, the saddle 3, the Z-axis feed system 7, the Y-axis feed system 2, the X-axis feed system 4, and the worktable 5.

[0085] The priority of arranging the temperature measuring points on each component is determined according to the influence of the thermal deformation of each component of the machine tool on the thermal error, that is, the temperature measuring points are preferentially arranged on the components with higher influence.

[0086] Specifically, when the number of temperature measuring points is 1, the temperature measuring point is selected and arranged on the spindle system 6 which is most affected by the thermal error. When the number of temperature measuring points is 2, the temperature measuring points are selected and arranged on the spindle system 6 and the base 1. When the number of temperature measuring points is 3, the temperature measuring points are selected and arranged on the spindle system 6, the base 1 and the column 8. When the number of temperature measuring points is 4, the temperature measuring points are selected and arranged on the spindle system 6, the base 1, the column 8 and the saddle 3. When the number of temperature measuring points is 5, the temperature measuring points are selected and arranged on the spindle system 6, the base 1, the column 8, the saddle 3 and the Z-axis feed system. 7, when the number of temperature measuring points is 6, the temperature measuring points are selected and arranged on the spindle system 6, base 1, column 8, saddle 3, Z-axis feed system 7 and Y-axis feed system 2; when the number of temperature measuring points is 7, the temperature measuring points are selected and arranged on the spindle system 6, base 1, column 8, saddle 3, Z-axis feed system 7, Y-axis feed system 2 and X-axis feed system 4; when the number of temperature measuring points is 8, the temperature measuring points are selected and arranged on the spindle system 6, base 1, column 8, saddle 3, Z-axis feed system 7, Y-axis feed system 2, X-axis feed system 4 and workbench 5.

[0087] Temperature sensors are arranged on the machine tool according to the above eight temperature measurement point selection schemes. Under each scheme, the thermal error prediction value is obtained based on the temperature value measured by the temperature sensor and the corresponding thermal error prediction model. The actual value of the thermal error corresponding to each scheme is obtained by measuring using an eddy current displacement sensor and the five-point method.

[0088] In this embodiment, the thermal error prediction model is a model for establishing a mapping relationship between temperature values ​​and thermal errors. This example uses a BP neural network to construct a thermal error prediction model. The BP neural network is particularly suitable for nonlinear problem solving such as thermal error modeling due to its back propagation and weight update characteristics. The BP neural network used in this example is a three-layer structure, the input layer is the temperature value, and the number of neurons depends on the selection results of the temperature measurement points. The output layer is the thermal error, and the number of neurons is 3, corresponding to the thermal errors in 3 directions.

[0089] The thermal error prediction model can be established using existing technology and will not be described in detail here.

[0090] The mean absolute error model is used to evaluate the model performance of the eight schemes. The mean absolute error model is as follows:

[0091]

[0092] in, is the actual value of thermal error, is the predicted value of thermal error, is the number of sample analyses, and MAE is the mean absolute error.

[0093] The solution corresponding to the minimum MAE value is the best temperature measurement point selection solution. In this embodiment, Figure 3 As shown, the MAE value is the smallest when the number of temperature measuring points is 4, so the optimal number of temperature measuring points N is 4, and the best prediction effect can be achieved when the number of temperature measuring points is 4.

[0094] Temperature measuring points are arranged on the first N components in the order of influence from large to small, with one temperature measuring point arranged on each component. Therefore, one temperature measuring point is set on the spindle system 6, the base 1, the column 8 and the saddle 3 respectively, for a total of four temperature measuring points.

[0095] The spindle system 6 is composed of multiple components. An isolated deformation analysis is performed on each component of the spindle system 6 in turn. The steps of the isolated deformation analysis are as follows:

[0096] In the simulation platform, the thermal expansion coefficients of the components of the spindle system 6 are set to actual values, and the thermal expansion coefficients of the remaining components of the machine tool are set to 0. Then, the temperature field analysis is performed under the set working conditions, and the temperature field analysis results are applied to the thermal behavior simulation model and the deformation field analysis is performed.

[0097] By adopting the above steps, the thermal deformation analysis results of each component of the spindle system 6 are obtained, and then the influence of the thermal deformation generated by each component of the spindle system 6 on the thermal error is determined according to the thermal deformation analysis results, and the component with the greatest influence is selected to install a temperature sensor as the temperature measuring point. In this embodiment, the temperature sensor is installed at the front bearing position of the spindle system as the temperature measuring point.

[0098] The saddle 3, column 8 and base 1 are already a whole, so there is no need to use isolated deformation analysis to select the temperature measurement position. In addition, the deformation of the saddle, column and base that affects the thermal error is transmitted through the connection part, and most of the heat is also transmitted from this connection part, so the connection position is selected as the key temperature measurement point.

[0099] Therefore, the positions of the four temperature measurement points in this embodiment are shown in Table 4:

[0100] Table 4. Selected temperature measurement point locations

[0101]

[0102] The installation position of the temperature sensor is determined according to the determined temperature measuring point position. Since four temperature measuring points are set, four temperature sensors are installed. The four temperature sensors are numbered PE1, PE2, PE3, and PE4 respectively. In this embodiment, due to the structural limitations of the machine tool itself, the determined temperature measuring point position may not be installed due to structural interference. At this time, a suitable temperature sensor installation position must be selected near the original position.

[0103] Compared with the traditional method of selecting temperature measurement points by combing through statistical analysis based on the experience of researchers, the selection method of this embodiment can guide the screening process of temperature measurement points from the perspective of the formation mechanism of thermal errors, avoid the complicated correlation analysis process, and the selection results are more accurate.

[0104] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for selecting temperature measurement points for machine tool thermal error modeling, characterized in that: The following steps are involved: According to the pre-established three-dimensional model of the machine tool, the thermal behavior simulation model of the machine tool is established in combination with the thermal boundary conditions of the machine tool; Under the set working conditions, the isolated deformation analysis is carried out on each component of the thermal behavior simulation model of the machine tool in turn, and the thermal deformation of each component under the action of the thermal field of the set working conditions is obtained. The influence of the thermal deformation of each component of the machine tool on the thermal error is determined through the thermal deformation of each component. Determine the temperature measurement points in the machine tool according to the acquired influence degree; Conducting experimental measurements on the temperature and thermal deformation data of the machine tool under set working conditions to obtain temperature experimental measurement data and thermal deformation experimental measurement data, and conducting temperature field analysis on the thermal behavior simulation model under set working conditions to obtain temperature field analysis results, applying the temperature field analysis results to the thermal behavior simulation model and conducting deformation field analysis to obtain deformation field analysis results, comparing the temperature experimental measurement data with the temperature field analysis results, and comparing the thermal deformation experimental measurement data with the deformation field analysis results. If the temperature experimental measurement data and the temperature field analysis results are inconsistent or the thermal deformation experimental measurement data and the deformation field analysis results are inconsistent, optimizing the thermal boundary conditions until the temperature experimental measurement data and the temperature field analysis results are consistent and the thermal deformation experimental measurement data and the deformation field analysis results are consistent, and then conducting isolated deformation analysis on each component in turn; The method of isolated deformation analysis is: the thermal expansion coefficient of the components set in the thermal behavior simulation model of the machine tool is designed to be the actual value, the thermal expansion coefficient of the other components is set to 0, and then the temperature field analysis is performed, and the temperature field analysis results are applied to the thermal behavior simulation model and the deformation field analysis is performed; The specific method for determining the temperature measurement points in the machine tool according to the degree of influence obtained is: Different temperature measurement point selection schemes are brought into the thermal error prediction model for analysis to obtain the thermal error prediction values ​​of different temperature measurement point selection schemes. Actual measurements are performed according to different temperature measurement point selection schemes to obtain the actual thermal error values ​​corresponding to the different temperature measurement point selection schemes. Among them, the priority level of the arrangement of the temperature measuring points on each component is determined according to the influence of the thermal deformation of each component of the machine tool on the thermal error; The average absolute error is obtained according to multiple thermal error prediction values ​​and the corresponding actual thermal error values, and the temperature measurement point selection scheme corresponding to the minimum average absolute error is selected as the optimal temperature measurement point selection scheme.

2. A method for selecting temperature measurement points for machine tool thermal error modeling as claimed in claim 1, characterized in that: The thermal boundary conditions include system heat generation and convective heat transfer coefficients of machine tool setting components.

3. A method for selecting temperature measurement points for machine tool thermal error modeling as described in claim 2, characterized in that: System heat generation includes the heat generated by the machine tool's motor and bearings.

4. A method for selecting temperature measurement points for machine tool thermal error modeling as described in claim 3, characterized in that: The heat generated by the motor is obtained based on the motor output torque, motor speed and mechanical efficiency of the motor. The heat generated by the bearing is obtained based on the bearing rotation speed, the load friction torque generated by the bearing material elastic hysteresis and local differential friction, and the viscous friction torque generated by the bearing and the lubricating fluid.

5. A method for selecting temperature measurement points for machine tool thermal error modeling as claimed in claim 2, characterized in that: The convective heat transfer coefficient is obtained based on the Nusselt constant, the fluid heat transfer coefficient, and the component characteristic dimensions of the machine tool setting assembly.

6. A method for selecting temperature measurement points for machine tool thermal error modeling as claimed in claim 1, characterized in that: The established three-dimensional model of the machine tool is imported into the thermal simulation platform, and the thermal behavior simulation model of the machine tool is obtained after meshing, adding material properties, and applying thermal boundary conditions.

7. A method for selecting temperature measurement points for machine tool thermal error modeling as claimed in claim 1, characterized in that: The deformation field analysis results of each component are obtained by isolated deformation analysis of each component of the machine tool. The total thermal error influence is obtained based on the deformation field analysis results of all components. The influence of the thermal deformation generated by each component on the thermal error is determined based on the proportion of the deformation field analysis results of each component to the total thermal error influence.

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