A method for pole processing in the process of large circle interpolation of a tool in a numerical control system

Abstract

The present invention discloses a method for processing poles during the large-circle interpolation of a tool in a numerical control system. The method comprises the following steps: determining the center, radius, machining parameters and pole positions according to the size of the large circle, generating the actual motion trajectory of the tool using an interpolation algorithm, and calculating the speed data at the pole positions; predicting the data error within a future machining time period based on the historical data of the numerical control system machining, and performing error compensation on the data at the poles, so that the tool can smoothly pass through the poles. Using a numerical control machine tool simulation software, simulating the tool path and the machine tool actions, and taking the preset parameters and the error compensation data as inputs. By performing error compensation on the data at the poles, the present invention can effectively reduce machining problems caused by errors, and at the same time establish a mathematical model by correlating the data of the large circle and the poles, so that it is not necessary to obtain pole processing data through cumbersome calculations.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing and analysis, and more specifically, to a method for processing poles during the circular interpolation of a tool in a numerical control system. Background Art

[0002] Circular interpolation of a tool is a path generation technology in numerical control machining, which is used to control the tool to move along an arc trajectory during machining. Specifically, it is a process in which the computer control system makes the tool perform interpolation movement according to a predetermined large circle trajectory in a plane or space. This interpolation method is often used for machining tasks that require circular shapes on the workpiece surface, such as turning, milling, etc., and can effectively achieve the machining of complex curves. A pole refers to a key point on the tool trajectory, where the tool may face sudden changes in speed or acceleration, affecting the smoothness and accuracy of machining. Therefore, processing poles is one of the key steps to ensure the continuity of tool movement and machining quality.

[0003] However, when performing existing circular interpolation, poles are usually directly calculated and processed in a common way, ignoring the errors in actual machining. These errors may cause changes in the parameters at the poles, thus affecting the processing of the poles. At the same time, when machining large circles of different sizes, a large number of complex operations are usually required to obtain the processing data at the poles, making it more complex to obtain the data of the poles.

[0004] For the problems in the related art, no effective solution has been proposed yet. Summary of the Invention

[0005] In view of the problems in the related art, the present invention proposes a method for processing poles during the circular interpolation of a tool in a numerical control system to overcome the above-mentioned technical problems existing in the related art.

[0006] To this end, the specific technical solution adopted by the present invention is as follows:

[0007] A method for processing poles during the circular interpolation of a tool in a numerical control system, the method comprising the following steps:

[0008] S1. Determine the center, radius, machining parameters, and pole positions according to the size of the large circle, generate the actual movement trajectory of the tool using an interpolation algorithm, and calculate the speed data at the pole positions simultaneously;

[0009] S2. Predict the data error within a future machining time period based on the historical data of the numerical control system processing, and perform error compensation on the data at the poles, so that the tool can smoothly pass through the poles;

[0010] S3. Use the numerical control machine tool simulation software to simulate the tool path and the machine tool movements, and take the preset parameters and the error compensation data as inputs to verify the correctness of the pole data. When the pole data value is within the normal range, actual machining can be carried out. When the pole data value is within the abnormal range, adjust the parameters and simulate again;

[0011] S4. After simulation verification, carry out actual machining, monitor the speed parameters at the pole through sensors, and verify the consistency between the actual data and the simulated data;

[0012] S5. Associate the data of the large circle with the pole data and establish a mathematical model. When machining large circles of other sizes, directly input the large circle data information and quickly obtain the pole processing data.

[0013] As a preferred embodiment, determining the center, radius, machining parameters, and pole position according to the size of the large circle, and using the interpolation algorithm to generate the actual movement trajectory of the tool, and at the same time calculating the speed data at the pole position includes the following steps:

[0014] S11. Determine the size parameters of the large circle, including the diameter and the center coordinates;

[0015] S12. Determine the pole position and the machining parameter data. The pole includes the starting point, the maximum speed point, the deceleration point, and the ending point;

[0016] S13. Use the interpolation algorithm to generate the movement trajectory of the tool, and calculate the speed data at the pole position in combination with the movement trajectory, including the speed at the maximum speed point and the deceleration at the deceleration point;

[0017] As a preferred embodiment, using the interpolation algorithm to generate the movement trajectory of the tool, and calculating the speed data at the pole position in combination with the movement trajectory, including the speed at the maximum speed point and the deceleration at the deceleration point includes the following steps:

[0018] S131. Calculate the speed at the maximum speed point. The specific formula is: ; where is the speed at the maximum speed point, is the initial acceleration is the acceleration time; calculate the deceleration at the deceleration point. The specific formula is: ; where a is the deceleration at the deceleration point, and t is the distance from the maximum speed point to the ending point.

[0019] As a preferred embodiment, based on the historical data of the numerical control system machining, predicting the data error within a future machining time period, and performing error compensation on the data at the pole, so that the tool can smoothly pass through the pole includes the following steps:

[0020] S21. Collect historical processing data, including the setting parameters of the CNC machine tool, the setting parameters at the poles, as well as the actual motion trajectory and the actual data at the poles;

[0021] S22. Analyze the historical data to identify parameter errors. The parameter error factors include system response and mechanical wear errors. Based on the historical data analysis, use a statistical model to establish a mathematical model of the parameter error, and use the established error model to predict the parameter error of future processing; Through historical data analysis and modeling, the parameter error of future processing can be accurately predicted.

[0022] S24. Perform error compensation on the data at the poles according to the predicted parameter error: including adjusting the speed at the maximum speed point and the deceleration at the deceleration point.

[0023] As a preferred embodiment, the specific steps of using a statistical model to establish a mathematical model of the parameter error based on the historical data analysis are as follows:

[0024] S221. The specific formula of the prediction model is: ; where is the calculated error parameter, is the system response error, is the mechanical wear error, is the regression coefficient, is the error term.

[0025] As a preferred embodiment, use the CNC machine tool simulation software to simulate the tool path and the machine tool actions, and use the preset parameters and the error compensation data as inputs to verify the correctness of the pole data. When the pole data value is within the normal range, actual processing can be carried out. When the pole data value is within the abnormal range, adjust the parameters and simulate again, including the following steps:

[0026] S31. Set the initial parameters of the CNC machine tool simulation software, including tool speed, machining path, machining depth, etc., input the preset parameters and the error compensation data into the simulation software, run the CNC machine tool simulation software, simulate the tool path and the machine tool actions, and observe the parameters during the simulation process;

[0027] S32. Record the key pole data during the simulation process, including the speed at the maximum speed point and the deceleration at the deceleration point, verify the correctness of the pole data. When the pole data value is within the normal range, actual processing can be carried out. When the pole data value is within the abnormal range, adjust the parameters in the simulation software and execute the simulation again until the pole data is within the normal range.

[0028] Through simulation, the effects of different design and process plans can be quickly evaluated, the product design and manufacturing process can be optimized, and the performance and quality of the product can be improved.

[0029] As a preferred embodiment, after the simulation verification, actual machining is carried out, and the speed parameters at the poles are monitored by sensors. Verifying the consistency between the actual data and the simulation data includes the following steps:

[0030] S41. According to the results of the simulation verification, set the speed at the maximum speed point and the speed at the deceleration point;

[0031] S42. Install a speed sensor and receive the speed data at the poles;

[0032] S43. Compare the actually collected parameter data with the data from the simulation verification to verify the consistency between the actual data and the simulation data.

[0033] As a preferred embodiment, associating the data of the large circle with the pole data and establishing a mathematical model. When machining large circles of other sizes, directly input the large circle data information and quickly obtain the processed data at the poles, including the following steps:

[0034] S51. First, use the standard equation of the circle to describe the shape and size of the large circle, and at the same time associate the geometric parameters of the large circle with the pole data to establish a mathematical model to calculate the data at the poles;

[0035] S52. Use the historical data set to train and verify the pole data processing model to ensure that the model can accurately output the data at the poles. When machining large circles of other sizes, directly input the new large circle data information, and the model will quickly calculate the processed data at the new poles according to the established mathematical model and the trained pole data processing model. There is no need to perform a large amount of cumbersome calculations, which is convenient for pole processing.

[0036] Training through the historical data set can make the pole data processing model more accurate and reliable.

[0037] The beneficial effects of the present invention are as follows:

[0038] 1. By collecting historical data and predicting the parameter errors in future machining, the present invention compensates for the parameter errors at the poles, which can effectively reduce the reduction of machining accuracy caused by error accumulation. In this way, the machining quality and consistency of products can be guaranteed at different time periods. At the same time, by compensating for the errors at the poles, the machining interruptions or re-machining situations caused by parameter fluctuations can be reduced, thereby improving the continuity and efficiency of machining.

[0039] 2. The present invention correlates the data of the large circle, the parameter data set at the pole, and the pole data, and establishes a mathematical model. When machining large circles of other sizes is required, by directly inputting the large circle data information, the parameter settings and pole data at the pole can be quickly obtained. This method greatly simplifies the calculation steps and avoids cumbersome calculation processes. The operator only needs to focus on inputting and confirming the new large circle parameters, without having to recalculate the detailed parameters required for each size.

[0040] 3. The present invention verifies the correctness of the pole data in the simulation software, which can discover and solve potential problems before actual machining. At the same time, the simulation software can accurately simulate the tool path and machine tool movements, and perform verification in combination with the preset parameters and error compensation data. This can not only improve the accuracy of the pole data, but also quickly adjust the parameters and verify the effects after conducting simulation experiments, helping to optimize the parameter settings and error compensation strategies at the pole, enabling the tool to pass smoothly through the pole and reducing the tool vibration at the pole. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0042] Figure 1 It is a flowchart of a method for processing poles during the large circle interpolation of a tool in a numerical control system according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] To further illustrate the embodiments, the present invention provides drawings. These drawings are part of the disclosure of the present invention, mainly used to illustrate the embodiments, and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, those of ordinary skill in the art should be able to understand other possible implementation manners and the advantages of the present invention.

[0044] According to an embodiment of the present invention, a method for processing poles during the large circle interpolation of a tool in a numerical control system is provided.

[0045] Now, the present invention will be further described in combination with the drawings and specific embodiments. As Figure 1 shown, a method for processing poles during the large circle interpolation of a tool in a numerical control system according to an embodiment of the present invention includes the following steps:

[0046] S1. Determine the center, radius, machining parameters, and pole positions based on the size of the large circle, generate the actual motion trajectory of the tool using interpolation algorithms, and calculate the velocity data at the pole positions simultaneously;

[0047] Further, the step of determining the center, radius, machining parameters, and pole positions based on the size of the large circle, generating the actual motion trajectory of the tool using interpolation algorithms, and calculating the velocity data at the pole positions simultaneously includes the following steps:

[0048] S11. Determine the size parameters of the large circle, including the diameter and center coordinates;

[0049] S12. Determine the pole positions and machining parameter data. The poles include the starting point, maximum velocity point, deceleration point, and end point;

[0050] S13. Generate the motion trajectory of the tool using interpolation algorithms and calculate the velocity data at the pole positions in combination with the motion trajectory, including the velocity at the maximum velocity point and the deceleration at the deceleration point;

[0051] It should be noted that the interpolation algorithm is a commonly used calculation method in numerical control machining, which is used to generate the motion trajectory of the tool to ensure that the tool moves precisely along the expected path. Specifically, the interpolation algorithm calculates the numerical control system instructions under the set machining speed and accuracy requirements, enabling the tool to move and cut precisely along the required trajectory.

[0052] In actual machining, the shapes of the workpieces to be machined are too diverse. To meet the requirements of geometric dimension accuracy, the tool center trajectory should be accurately generated according to the contour shape of the workpiece. For simple curves, the numerical control system can be relatively easily implemented. However, for more complex shapes, directly generating them requires complex algorithms and will also increase the workload of the computer. Therefore, in actual applications, a short straight line or arc is often used for fitting to meet the accuracy requirements, and this fitting method is "interpolation".

[0053] Interpolation is to complete the work of data densification based on limited information. The actual trajectory of the interpolation motion cannot be exactly the same as its ideal trajectory. Therefore, the interpolation points generally do not fall on the ideal trajectory.

[0054] Further, the step of generating the motion trajectory of the tool using interpolation algorithms and calculating the velocity data at the pole positions in combination with the motion trajectory, including the velocity at the maximum velocity point and the deceleration at the deceleration point, includes the following steps:

[0055] S131. Calculate the velocity at the maximum velocity point. The specific formula is: ; where is the velocity at the maximum velocity point, is the initial acceleration is the acceleration time; calculate the deceleration at the deceleration point, and the specific formula is: ; where, a is the deceleration at the deceleration point, and t is the distance from the maximum speed point to the end point. It should be noted that controlling the speed at the maximum speed point can ensure that the machining quality will not be affected by too high speed during the machining process, such as avoiding problems such as vibration, increased tool wear or increased surface roughness, so as to ensure the accuracy and surface quality of the product; the deceleration is the speed change rate when the tool decelerates from the maximum speed point to a lower speed. By reasonably controlling the deceleration, the impact or vibration generated by the tool during deceleration can be avoided, and the safety of the machining process and the stable operation of the equipment can be ensured.

[0056] S2. Based on the historical data of CNC machining, predict the data error within a future machining time period, and perform error compensation on the data at the extreme points, so that the tool can pass through the extreme points smoothly;

[0057] Further, the predicting the data error within a future machining time period based on the historical data of CNC machining and performing error compensation on the data at the extreme points, so that the tool can pass through the extreme points smoothly includes the following steps:

[0058] S21. Collect historical machining data, including the setting parameters of the CNC machine tool, the setting parameters at the extreme points, as well as the actual motion trajectory and the actual data at the extreme points;

[0059] S22. Analyze the historical data to identify parameter errors. The parameter error factors include system response and mechanical wear errors. Based on the historical data analysis, use a statistical model to establish a mathematical model of the parameter error, and use the established error model to predict the parameter error of future machining;

[0060] Further, the specific steps of using a statistical model to establish a mathematical model of the parameter error based on the historical data analysis are:

[0061] S221. The specific formula of the prediction model is: ; where, is the calculated error parameter, is the system response error, is the mechanical wear error, is the regression coefficient, is the error term. It should be noted that the statistical model can help analyze and predict the distribution and trend of parameter errors. By establishing a mathematical model, the influence of different parameters on the system output can be quantified, and the main error sources can be identified, so as to optimize and control them targeted;

[0062] S24. Perform error compensation on the data at the poles according to the predicted parameter errors, including adjusting the speed at the maximum speed point and the deceleration at the deceleration point. It should be noted that by performing error compensation on the speed at the maximum speed point and the deceleration at the deceleration point, overshoot and oscillation during the dynamic response process of the system can be reduced, the stability of the system can be improved, and at the same time, the dynamic performance of the system can be effectively optimized.

[0063] S3. Use numerical control machine tool simulation software to simulate the tool path and machine tool movements, and use the preset parameters and error compensation data as inputs to verify the correctness of the pole data. When the pole data values are within the normal range, actual machining can be carried out. When the pole data values are within the abnormal range, adjust the parameters and simulate again;

[0064] Further, the step of using numerical control machine tool simulation software to simulate the tool path and machine tool movements, and using the preset parameters and error compensation data as inputs to verify the correctness of the pole data. When the pole data values are within the normal range, actual machining can be carried out. When the pole data values are within the abnormal range, adjust the parameters and simulate again includes the following steps:

[0065] S31. Set the initial parameters of the numerical control machine tool simulation software, including tool speed, machining path, machining depth, etc. Input the preset parameters and error compensation data into the simulation software, run the numerical control machine tool simulation software, simulate the tool path and machine tool movements, and observe the parameters during the simulation process;

[0066] S32. Record the key pole data during the simulation process, including the speed at the maximum speed point and the deceleration at the deceleration point, verify the correctness of the pole data. When the pole data values are within the normal range, actual machining can be carried out. When the pole data values are within the abnormal range, adjust the parameters in the simulation software and perform the simulation again until the pole data is within the normal range.

[0067] It should be noted that when performing simulation, use VERICUT simulation software for numerical control machining simulation. This simulation software can not only simulate the tool path and machine tool movements in detail, but also has the ability to view the workpiece machining process in real time.

[0068] S4. After simulation verification, perform actual machining, and monitor the speed parameters at the poles through sensors to verify the consistency between the actual data and the simulated data;

[0069] Further, the step of performing actual machining after simulation verification, and monitoring the speed parameters at the poles through sensors to verify the consistency between the actual data and the simulated data includes the following steps:

[0070] S41. Set the speed at the maximum speed point and the speed at the deceleration point according to the results of the simulation verification;

[0071] S42. Install a speed sensor and receive the speed data at the pole;

[0072] S43. Compare the actually collected parameter data with the simulated and verified data to verify the consistency between the actual data and the simulated data.

[0073] It should be noted that by comparing the actual data with the simulated data, possible deviations or errors in the model can be discovered and adjusted, further optimizing the parameter settings. At the same time, accurate simulated data verification can provide a basis for improving the actual production process.

[0074] S5. Associate the data of the large circle with the pole data and establish a mathematical model. When machining large circles of other sizes, directly input the large circle data information and quickly obtain the processed pole data.

[0075] Furthermore, the step of associating the data of the large circle with the pole data and establishing a mathematical model, when machining large circles of other sizes, directly inputting the large circle data information and quickly obtaining the processed pole data includes the following steps:

[0076] S51. First, use the standard equation of the circle to describe the shape and size of the large circle, and at the same time associate the geometric parameters of the large circle with the pole data to establish a mathematical model to calculate the data at the pole;

[0077] S52. Use the historical data set to train and verify the pole data processing model to ensure that the model can accurately output the data at the pole. When machining large circles of other sizes, directly input the new large circle data information, and the model will quickly calculate the processed data at the new pole according to the established mathematical model and the trained pole data processing model. There is no need to perform a large number of cumbersome calculations, which is convenient for pole processing.

[0078] It should be noted that the processed pole data usually needs to be obtained through a large number of calculations. Associating the data of the large circle with the pole data can effectively reduce the calculation steps. When machining large circles of other sizes, it can improve the calculation efficiency of the pole data and quickly obtain the processed data at the pole.

[0079] In summary, the present invention collects historical data, predicts the parameter errors of future processing, and compensates for the parameters at the poles, which can effectively reduce the reduction of machining accuracy caused by error accumulation. In this way, the machining quality and consistency of products can be ensured at different time periods. At the same time, by compensating for the errors at the poles, the machining interruptions or rework caused by parameter fluctuations can be reduced, thereby improving the continuity and efficiency of machining; the present invention correlates the data of the large circle, the parameter data set at the poles, and the pole data, and establishes a mathematical model. When machining large circles of other sizes are required, directly inputting the large circle data information can quickly obtain the parameter settings and pole data at the poles. This method greatly simplifies the calculation steps and avoids cumbersome calculation processes. The operator only needs to focus on inputting and confirming the new large circle parameters without having to recalculate the detailed parameters required for each size; the present invention verifies the correctness of the pole data in the simulation software, can discover and solve potential problems before actual machining. At the same time, the simulation software can accurately simulate the tool path and machine tool movements, and verify in combination with the preset parameters and error compensation data. Not only can the accuracy of the pole data be improved, but after the simulation experiment, the parameters can also be quickly adjusted and the effects verified, helping to optimize the parameter settings and error compensation strategies at the poles, enabling the tool to pass smoothly through the poles and reducing the tool vibration at the poles.

[0080] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for processing poles during the circular interpolation of a large tool in a numerical control system, characterized in that, The method includes the following steps: S1. Determine the center, radius, machining parameters, and pole position according to the size of the large circle, generate the actual motion trajectory of the tool using the interpolation algorithm, and calculate the speed data at the pole position simultaneously; S2. Based on the historical data of CNC machining, predict the data error within a future machining time period, and perform error compensation on the data at the pole, so that the tool can pass through the pole smoothly; S21. Collect historical machining data, including the setting parameters of the CNC machine tool, the setting parameters at the pole, as well as the actual motion trajectory and the actual data at the pole; S22. Analyze the historical data to identify parameter errors. The parameter error factors include system response and mechanical wear errors. Based on the historical data analysis, establish a mathematical model of the parameter error using a statistical model, and use the established error model to predict the parameter error of future machining; S221. The specific formula of the prediction model is as follows: , where is the calculated error parameter, is the system response error, is the mechanical wear error, is the regression coefficient, is the error term; S23. Perform error compensation on the data at the pole according to the predicted parameter error: including adjusting the speed at the maximum speed point and the deceleration at the deceleration point; S3. Use CNC machine tool simulation software to simulate the tool path and machine tool actions, and use the preset parameters and error compensation data as inputs to verify the correctness of the pole data. When the pole data value is within the normal range, actual machining can be carried out. When the pole data value is within the abnormal range, adjust the parameters and simulate again; S4. After simulation verification, perform actual machining, monitor the speed parameters at the pole through sensors, and verify the consistency between the actual data and the simulated data; S5. Associate the data of the large circle with the pole data and establish a mathematical model. When machining large circles of other sizes, directly input the large circle data information and quickly obtain the pole processing data.

2. The pole processing method during the large circle interpolation of a tool in a numerical control system according to claim 1, characterized in that, The step of determining the center, radius, machining parameters, and pole position according to the size of the large circle, generating the actual motion trajectory of the tool using the interpolation algorithm, and calculating the speed data at the pole position simultaneously includes the following steps: S11. Determine the size parameters of the large circle, including the diameter and the center coordinates; S12. Determine the pole position and machining parameter data. The pole includes the starting point, the maximum speed point, the deceleration point, and the ending point; S13. Use the interpolation algorithm to generate the motion trajectory of the tool, and calculate the speed data at the pole position in combination with the motion trajectory, including the speed at the maximum speed point and the deceleration at the deceleration point.

3. A method for processing poles during the large circle interpolation of a tool in a numerical control system according to claim 2, characterized in that, The step of using the interpolation algorithm to generate the motion trajectory of the tool, and calculating the speed data at the pole position in combination with the motion trajectory, including the speed at the maximum speed point and the deceleration at the deceleration point includes the following steps: S131. Calculate the speed at the maximum speed point. The specific formula is: ; where is the speed at the maximum speed point, is the initial acceleration is the acceleration time; Calculate the deceleration at the deceleration point. The specific formula is: ; where is the deceleration at the deceleration point, is the distance from the maximum speed point to the end point.

4. A method for processing poles in the circular interpolation process of a tool in a numerical control system according to claim 1, characterized in that The step of using CNC machine tool simulation software to simulate the tool path and machine tool actions, and using the preset parameters and error compensation data as inputs to verify the correctness of the pole data. When the pole data value is within the normal range, actual machining can be carried out. When the pole data value is within the abnormal range, adjust the parameters and simulate again includes the following steps: S31. Set the initial parameters of the CNC machine tool simulation software, including the tool speed, machining path, and machining depth. Input the preset parameters and error compensation data into the simulation software, run the CNC machine tool simulation software, simulate the path of the tool and the actions of the machine tool, and observe the parameters during the simulation process; S32. Record the key pole data during the simulation process, including the speed at the maximum speed point and the deceleration at the deceleration point, verify the correctness of the pole data. When the pole data value is within the normal range, actual machining can be carried out. When the pole data value is within the abnormal range, adjust the parameters in the simulation software and execute the simulation again until the pole data is within the normal range.

5. A method for pole processing in the large circle interpolation process of a tool in a numerical control system according to claim 1, characterized in that After the simulation verification, actual machining is carried out. Monitoring the speed parameters at the pole through sensors, verifying the consistency between the actual data and the simulation data includes the following steps: S41. According to the results of the simulation verification, set the speed at the maximum speed point and the speed at the deceleration point; S42. Install a speed sensor and receive the speed data at the pole; S43. Compare the actually collected parameter data with the data verified by the simulation to verify the consistency between the actual data and the simulation data.

6. A method for processing poles in the circular interpolation of a large tool in a numerical control system according to claim 1, characterized in that Associating the data of the large circle with the pole data and establishing a mathematical model. When machining large circles of other sizes, directly input the large circle data information and quickly obtain the processed pole data including the following steps: S51. First, use the standard equation of the circle to describe the shape and size of the large circle, and at the same time associate the geometric parameters of the large circle with the pole data to establish a mathematical model to calculate the data at the pole; S52. Use the historical data set to train and verify the pole data processing model to ensure that the model can accurately output the data at the pole. When machining large circles of other sizes, directly input the new large circle data information, and the model will quickly calculate the processed data at the new pole according to the established mathematical model and the trained pole data processing model.

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