Screening method for most sensitive heat monitoring points of end milling variable working condition machined workpiece

Abstract

The invention belongs to the field of machining technical models, and particularly relates to a method for screening most sensitive heat monitoring points of a machined workpiece under an end milling variable working condition, which is characterized by specifically comprising the following steps of: 1) modeling: establishing a finite element model of a to-be-machined workpiece by adopting a finite element (FEM) calculation method, setting boundary conditions according to machining process parameters, and establishing a finite element model of the to-be-machined workpiece; simulation calculation of the whole end milling machining process is completed; 2) point selection: selecting a plurality of temperature monitoring points in a non-machining surface area of the workpiece to be machined, and outputting temperature time sequence data of each temperature monitoring point in the machining process; 3) screening: screening the most sensitive heat monitoring points by using a mathematical method; and (4) evaluation is conducted, the candidate measuring point sets of different densities and distance machining areas are evaluated according to the EoP criterion, and the temperature monitoring point is the most sensitive point if the data fluctuation obtained by the temperature monitoring point is the largest. The method has the beneficial effect that sensitive points of temperature distribution in the end milling machining process can be accurately predicted.

Description

Technical Field

[0001] The invention belongs to the field of mechanical processing technology models, and in particular relates to a method for screening the most sensitive thermal monitoring points of a workpiece being processed in an end milling variable working condition. Background Art

[0002] Currently, most manufacturers face the challenge of improving their manufacturing processes, striving for small batches, high quality, and agile production. End milling is one of the most effective machining processes currently available to address this challenge. To improve the productivity and efficiency of end milling, the increasing digitalization of production has opened up numerous possibilities. Finite element method (FEM) simulations can be used to calculate and predict the thermal distribution and evolution of the end milling process. Thermal expansion of the workpiece is a significant factor affecting machining accuracy and is crucial for controlling high-precision end milling processes.

[0003] Chinese invention patent application number 202010583919.3 discloses a five-axis gantry CNC machining center with thermal deformation error compensation. The center includes a thermal deformation error compensation method to compensate for errors caused by thermal deformation of the machine tool spindle. By solving the positioning of the thermally sensitive areas of the spindle and feed system and optimizing the layout of temperature detection points, a continuous temperature perception model for the thermally sensitive areas is established. The influence of the thermally sensitive points of the spindle is analyzed, and the finite element method is used to analyze the thermal characteristics of the machine tool to obtain the thermally sensitive areas of the machine tool. Further, an interpolation algorithm is used to obtain an estimated value of the one-to-one correspondence between the temperature of the entire thermally sensitive area of ​​the spindle and the geometric thermal error. A continuous model of the spindle thermal error is established. Finally, the spindle thermal error is compensated in real time by translating the reference origin of the coordinate system, realizing rapid calibration of the thermal error of the machine tool's geometric accuracy, and finally realizing thermal error compensation control in the interpolation and position control links of the CNC system. However, this compensation method is not suitable for analyzing the actual thermal state of the workpiece under different working conditions during end milling.

[0004] To detect the actual thermal state of the workpiece under different working conditions during end milling, an adaptive estimation method was previously proposed and verified. This method is based on a heat conduction simulation of the sensor configuration and correlates the sensor data with the process simulation. The developed prototype system was used to evaluate the estimation of the workpiece temperature field and the influence of the measurement position. In order to reduce the number of temperature monitoring points and determine the appropriate workpiece temperature monitoring points, a temperature monitoring point effectiveness criterion (EoP) was proposed to obtain sensitive points for accurately predicting the temperature distribution during end milling under various machining conditions. However, the evaluation criteria for the selection of temperature monitoring points in the industry are still uncertain, which affects the accuracy of state estimation. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for screening the most sensitive thermal monitoring points of a workpiece being processed under variable end milling conditions, overcome the shortcomings of the existing technology, conduct research based on the evaluation results of EoP, and accurately predict the sensitive points of temperature distribution in the end milling process under various processing conditions by comparing the trends of the evaluation results of different candidate temperature monitoring points according to the degree of influence of the distribution density or distribution position on the processing accuracy.

[0006] To achieve the above object, the present invention is implemented through the following technical solutions:

[0007] A method for screening the most sensitive thermal monitoring points of a workpiece being processed under variable end milling conditions specifically includes the following steps: 1) modeling, using the finite element (FEM) calculation method to establish a finite element model of the workpiece to be processed, setting the calculation boundary conditions according to the processing parameters, and completing the simulation calculation of the entire end milling process; 2) point selection, selecting several temperature monitoring points in the non-processing area of ​​the workpiece to be processed, and outputting the temperature time series data of each temperature monitoring point during the processing process; 3) screening, using mathematical methods to screen the most sensitive thermal monitoring points;

[0008]

[0009] Where, T i,n Represents the reference measurement point temperature data sequence of the nominal model parameters, i represents the number of temperature monitoring points, i ranges from 1 to N, T i,k represents the temperature data sequence of the measuring point under different boundary condition groups of finite element simulation, k represents the number of boundary condition groups of finite element simulation, and k ranges from 1 to M; 4) Evaluation, the EoP criterion is used to evaluate the candidate measuring point sets with different densities and distances to the processing areas. The larger the EOP value, the greater the data fluctuation obtained by the temperature monitoring point, that is, the most sensitive point.

[0010] Furthermore, the nominal model formula of the EoP is:

[0011]

[0012] Furthermore, in the step 1), the workpiece to be processed is simulated by using an end milling cutter, and when simulating the end milling process, heat is directly applied to the workpiece.

[0013] Furthermore, the calculation boundary conditions in step 1) are to set the variation range of the heat source, the material thermal conductivity and the convection heat transfer coefficient, and are selected within a range of 50% fluctuation.

[0014] Furthermore, in step 2), the temperature monitoring points are selected according to distribution density or distribution position.

[0015] Furthermore, the upper limit of M in step 3) is 13.

[0016] Furthermore, in step 3), N is set to any value among 6, 10, and 16.

[0017] Furthermore, before the evaluation in step 4), the results of different temperature monitoring candidate point sets are compared, and the point with the highest peak value of the EoP value is selected.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] 1) Based on the EoP evaluation results, the influence of temperature monitoring points on machining accuracy by distribution density or distribution location is studied. By comparing the trends of the evaluation results of different candidate temperature monitoring points, the sensitive points for accurately predicting the temperature distribution during end milling under various machining conditions are obtained.

[0020] 2) The evaluation criterion proposed in this invention is applicable to the quantitative assessment of effective thermally sensitive measuring points. The effectiveness of the criterion in temperature prediction is preliminarily verified through a case study, and the reasonable consistency between the predicted and measured results proves the feasibility of the criterion. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is the end milling surface processing path of the workpiece in the embodiment of the present invention;

[0022] Figure 2 The finite element model of the workpiece in the embodiment of the present invention;

[0023] Figure 3 Schematic diagram of the number and position distribution of temperature monitoring points on a workpiece in Example 1 of the present invention;

[0024] Figure 4 Schematic diagram of the number and position distribution of temperature monitoring points on a workpiece in Example 2 of the present invention;

[0025] Figure 5 is the EOP analysis result of Example 1 of the present invention;

[0026] Figure 6 This is the EOP analysis result of Example 2 of the present invention. DETAILED DESCRIPTION

[0027] The technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments.

[0028] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the specific embodiments required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the specific embodiments described below are some implementation methods of the present invention. For ordinary technicians in this field, other specific embodiments can be obtained based on these specific embodiments without paying any creative work.

[0029] The components of the embodiments of the present invention generally described and shown in the specific embodiments herein can be arranged and designed in countless different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the specific embodiments is not intended to limit the scope of the claimed invention, but is merely representative of selected embodiments of the present invention.

[0030] The method for screening the most sensitive thermal monitoring points of a workpiece being processed under variable milling conditions of the present invention specifically comprises the following steps:

[0031] 1) Modeling: Use the finite element (FEM) calculation method to establish a finite element model of the workpiece to be processed, set boundary conditions according to the processing parameters, and complete the simulation calculation of the entire end milling process;

[0032] 2) Point selection: select several temperature monitoring points in the non-machining area of ​​the workpiece to be processed, and output the temperature time series data of each temperature monitoring point during the processing;

[0033] 3) Screening: using mathematical methods to screen the most sensitive thermal monitoring points;

[0034]

[0035] In formula (1), T i,n Represents the reference measurement point temperature data sequence of the nominal model parameters, i represents the number of temperature monitoring points, i ranges from 1 to N, T i,k represents the temperature data sequence of the measuring points under different boundary condition groups of finite element simulation, k represents the number of boundary condition groups of finite element simulation, and k ranges from 1 to M;

[0036] 4) Evaluation, the EoP criterion is used to evaluate the candidate measurement point sets with different densities and distances to the processing area. The larger the EoP value, the greater the fluctuation of the data obtained by the temperature monitoring point, which is the most sensitive point.

[0037] The temperature monitoring sensitive measurement points are selected using the nominal model formula of EoP as shown below:

[0038]

[0039] In the embodiment of the present invention, the temperature boundary conditions calculated by the settings in Table 1, the material property variation range in Table 2 and the material properties of each group in Table 3 were used to conduct 13 groups of end milling finite element numerical simulation experiments. Figure 1 As shown in the figure, the upper surface is completely machined. The finite element simulation model is as follows Figure 2 As shown. Extract 13 sets of temperature history results calculated by finite simulation analysis, according to Figure 3 and Figure 4 The number and location of monitoring points were designed, and the temperature time history results of two different monitoring point arrangements were extracted: 6 locations (as Example 1) and 10 locations (as Example 2). Calculations were performed using formulas (1) and (2), and the results are shown in the figure below: Figure 5 and Figure 6 shown.

[0040] Table 1 Basic simulation parameters of S45C (JIS) steel

[0041] name Numerical density <![CDATA[7850kg / m 3 <!-- 3 -->]]> Initial temperature 10.8℃ Ambient temperature 10.8℃

[0042] Table 2 Performance limit variation range of S45C (JIS) steel

[0043]

[0044] Table 3 S45C (JIS) different working conditions

[0045]

[0046] The results show that when six monitoring points are selected, the EOP value at monitoring location 6-CH5 is the highest, making it the most sensitive temperature monitoring point. When 10 monitoring points are selected, the EOP value at monitoring location 10-CH8 is the highest, and monitoring location 6-CH5 is close to monitoring location 10-CH8. This shows that the most sensitive temperature points selected by the formula in this patent are at the same location.

[0047] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for screening the most sensitive thermal monitoring points of a workpiece under variable end milling conditions, characterized in that: The specific steps include: 1) Modeling: Use the finite element (FEM) calculation method to establish a finite element model of the workpiece to be processed, set the calculation boundary conditions according to the processing parameters, and complete the simulation calculation of the entire end milling process; 2) Point selection: select several temperature monitoring points in the non-machining area of ​​the workpiece to be processed, and output the temperature time series data of each temperature monitoring point during the processing; 3) Screening: using mathematical methods to screen the most sensitive thermal monitoring points; Where, T i,n Represents the reference measurement point temperature data sequence of the nominal model parameters, i represents the number of temperature monitoring points, i ranges from 1 to N, T i,k represents the temperature data sequence of the measuring points under different boundary condition groups of finite element simulation, k represents the number of boundary condition groups of finite element simulation, and k ranges from 1 to M; 4) Evaluation, the EoP criterion is used to evaluate the candidate measurement point sets with different densities and distances to the processing area. The larger the EoP value, the greater the fluctuation of the data obtained by the temperature monitoring point, which is the most sensitive point.

2. The method for screening the most sensitive thermal monitoring points of a workpiece processed under variable working conditions of end milling according to claim 1, characterized in that: The nominal model formula for the EoP is:

3. The method for screening the most sensitive thermal monitoring points of a workpiece processed under variable working conditions of end milling according to claim 1, characterized in that: In the step 1), the workpiece to be processed is simulated by using an end milling cutter. When simulating the end milling process, heat is directly applied to the workpiece.

4. The method for screening the most sensitive thermal monitoring points of a workpiece processed under variable working conditions of end milling according to claim 1, characterized in that: The calculation boundary conditions in step 1) are to set the variation range of the heat source, the thermal conductivity of the material and the convection heat transfer coefficient, and are selected within a range of 50% fluctuation.

5. The method for screening the most sensitive thermal monitoring points of a workpiece processed under variable working conditions of end milling according to claim 1, characterized in that: In step 2), the temperature monitoring points are selected according to distribution density or distribution position.

6. The method for screening the most sensitive thermal monitoring points of a workpiece processed under variable working conditions of end milling according to claim 1, characterized in that: The upper limit of M in step 3) is 13.

7. The method for screening the most sensitive thermal monitoring points of a workpiece processed under variable working conditions of end milling according to claim 1, characterized in that: In step 3), N is set to any value among 6, 10, and 16.

8. The method for screening the most sensitive thermal monitoring points of a workpiece processed under variable working conditions of end milling according to claim 1, characterized in that: Before the evaluation in step 4), the results of different temperature monitoring candidate point sets are compared, and the point with the highest peak value of the EoP value is selected.

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