A center hole keyway machining control method, system and medium

Abstract

The present application relates to the technical field of processing control, and specifically includes a center inner hole keyway processing control method, system and medium, the method comprising: based on the network of plug cutting process parameters, combining the tool-workpiece thermal deformation suppression constraint condition, the cutting system chatter suppression constraint condition, determine the candidate plug cutting process combination; Solve the plug cutting process parameter combination that makes the unit keyway processing time minimum in the feasible process window, as the global optimal processing parameter combination. The technical problems of low adaptation degree of processing parameter configuration and actual processing condition, insufficient stability of plug cutting processing caused by geometric taper error, surface roughness threshold setting depending on empirical function are solved, the technical effect of accurately predicting error limit through mechanical sensitive component deformation analysis and cutting heat-force coupling simulation, determining the preset epsilon 1 threshold and the preset epsilon 2 threshold that adapt to the actual processing condition is realized, with the feasible process window optimization with constraints, the stability of processing control is improved.

Description

Technical Field

[0001] This invention relates to the field of machining control technology, specifically to a method, system, and medium for machining control of a central inner hole keyway. Background Technology

[0002] As the core structure for realizing the transmission and mating of shaft and sleeve parts, the machining accuracy and efficiency of the center inner hole keyway directly determine the transmission stability, load-bearing capacity and service life of the assembled parts. With the rapid development of industries such as high-end equipment and precision instruments, stringent requirements have been placed on the machining quality of the center inner hole keyway. It is necessary not only to strictly control geometric errors and surface quality, but also to take into account machining efficiency to adapt to the needs of large-scale production.

[0003] Current control methods for keyway planing in central bores often focus solely on machining efficiency or a single accuracy indicator. Threshold settings for geometric taper error and surface roughness rely heavily on empirical values, which can easily lead to out-of-tolerance geometric taper or substandard surface roughness. Furthermore, there is a lack of real-time acquisition and analysis of key data such as temperature, cutting force, and vibration during the machining process. This makes it impossible to dynamically adjust process parameters or error thresholds based on changes in multi-field coupling strength, resulting in insufficient machining stability and fault tolerance, and making it difficult to meet the machining quality requirements of high-end equipment.

[0004] In summary, existing technologies suffer from problems such as geometric taper error and reliance on empirical functions for surface roughness threshold settings, resulting in low adaptability of machining parameter configurations to actual machining conditions and insufficient stability in planing machining. Summary of the Invention

[0005] This application provides a method, system, and medium for controlling the machining of keyways in central internal holes, aiming to solve the technical problems in the prior art where the setting of geometric taper error and surface roughness threshold depends on empirical functions, resulting in low adaptability of machining parameter configuration to actual machining conditions and insufficient stability of broaching machining.

[0006] In view of the above problems, the technical solution to achieve the present application is as follows:

[0007] A first aspect of this application provides a method for controlling the machining of a central internal keyway, wherein the method includes: setting a slitting process parameter network based on the central through-hole structure of the workpiece to be machined; determining candidate slitting process combinations based on the slitting process parameter network, combined with tool-workpiece thermal deformation suppression constraints and cutting system chatter suppression constraints; inputting the candidate slitting process combinations into a single-objective optimization engine, and setting an objective function according to the unit keyway machining time; simultaneously, constraining the geometric taper error and surface roughness within preset ε1 threshold and preset ε2 threshold, respectively, to form a... Constrained feasible process window; within the feasible process window, solve for the combination of cutting process parameters that minimizes the unit keyway machining time, as the globally optimal combination of machining parameters.

[0008] In possible implementations, for mechanically sensitive components including tool holder overhang length and clamping stiffness, the tool runout deformation caused by cutting force is analyzed, the clamping angle and support position on the machining center spindle are optimized, and the maximum geometric taper error is predicted based on the optimized structural stiffness to determine the preset ε1 threshold; the influence of cutting heat distribution on the tool cutting edge is simulated by finite element simulation, the tool wear acceleration and chip adhesion effect caused by temperature rise are analyzed, the feed per cut and cutting speed are dynamically optimized, and the tool rake face sharpening treatment and coolant directional spray channel are introduced, and the minimum achievable surface roughness is predicted based on the optimized cutting thermo-mechanical coupling model to determine the preset ε2 threshold.

[0009] In possible implementations, for motion control parameters including spindle speed and feed rate, the depth of cut and idle travel time are adjusted to construct an objective function with spindle speed and feed rate as independent variables and unit keyway machining time as dependent variables; within the feasible domain of process parameters that satisfy geometric taper error not exceeding a preset ε1 threshold and surface roughness not exceeding a preset ε2 threshold, the combination of spindle speed and feed rate that minimizes unit keyway machining time is solved.

[0010] In a possible implementation, cutting temperature data, cutting force data, and vibration spectrum data are mapped to the machining coordinate system, and the thermal-mechanical coupling strength between adjacent cutting paths is set. The thermal-mechanical coupling strength between adjacent cutting paths is used to quantify the spatial correlation between heat accumulation and elastic recovery. Based on the machining coordinate system and the thermal-mechanical coupling strength, mutual information nonlinear coupling analysis is performed with the temperature-displacement coupling amplification partition, and tool-workpiece thermal deformation suppression constraints are set.

[0011] In one possible implementation, thermal amplification coupling analysis is performed during the planing process based on the thermo-mechanical coupling effect to construct the heat conduction path between the tool-workpiece contact area and the machine tool spindle, and to determine the thermal deformation matrix. Based on the thermal deformation matrix, the tool tip displacement gradient is predicted by combining the dynamic cutting force waveform. When there is a coherent match between the local temperature rise rate and the main frequency of the cutting force fluctuation, the temperature-displacement coupling amplification partition and the tool-workpiece thermal deformation suppression constraint conditions are determined.

[0012] In a possible implementation, based on the machining coordinate system, the thermo-mechanical coupling strength, and the vibration-displacement coupling amplification partition, a mutual information nonlinear coupling analysis is performed to set the chatter suppression constraint conditions of the cutting system.

[0013] In one possible implementation, chatter amplification coupling analysis is performed during the planing process based on the mechanical-vibration coupling effect. The vibration transmission path between the tool cantilever beam and the spindle bearing is constructed, and the dynamic stiffness matrix is ​​determined. Based on the dynamic stiffness matrix, the vibration acceleration gradient is predicted by combining the cutting force spectrum. When there is a coherent match between the local vibration amplitude and the spindle rotation frequency, the vibration-displacement coupling amplification partition and the chatter suppression constraint conditions of the cutting system are determined.

[0014] In a possible implementation, a multi-dimensional sensor array covering the keyway machining area is used to collect surface temperature data, cutting force data, and vibration acceleration data of the workpiece to be machined during the broaching process. Based on the surface temperature data, cutting force data, and vibration acceleration data, the dominant frequency of temperature fluctuation, force pulse intensity, and vibration mode frequency are extracted, and inter-field correlation feature analysis is performed to identify the cross-coupling characteristics between the thermo-mechanical coupling effect and the mechanical-vibration coupling effect. Through the cross-coupling characteristics and the associated mapping of multiple cross-influence factors, combined with a preset safety margin, a multi-field coupling effect threshold is determined. The multi-field coupling effect threshold is used to verify in real time whether the current broaching process parameters are in a stable machining range, and when the cross-coupling intensity is detected to exceed the multi-field coupling effect threshold, a tightening adjustment of the preset ε1 threshold and the preset ε2 threshold is triggered.

[0015] A second aspect of this application provides a control system for machining a central internal keyway, wherein the system includes: a slitting process parameter network setting module: setting a slitting process parameter network based on the central through-hole structure of the workpiece to be machined; a candidate slitting process combination determination module: determining candidate slitting process combinations based on the slitting process parameter network, combined with tool-workpiece thermal deformation suppression constraints and cutting system chatter suppression constraints; an objective function setting module: inputting the candidate slitting process combinations into a single-objective optimization engine and setting an objective function according to the unit keyway machining time; and a feasible process window determination module: simultaneously constraining the geometric taper error and surface roughness within preset ε1 threshold and preset ε2 threshold, respectively, forming a... Constrained feasible process window; Global optimal machining parameter combination determination module: Within the feasible process window, solve for the combination of cutting process parameters that minimizes the unit keyway machining time, and use it as the global optimal machining parameter combination.

[0016] A third aspect of this application provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the central inner hole keyway machining control method of the first aspect.

[0017] In summary, one or more technical solutions provided in this application achieve accurate prediction of error limits through deformation analysis of mechanically sensitive components and cutting thermo-mechanical coupling simulation, determine preset ε1 and preset ε2 thresholds suitable for actual machining conditions, and determine candidate process combinations by integrating dual suppression constraints of tool-workpiece thermal deformation and cutting system chatter, in order to bring Optimizing the feasible process window under constraints improves the technical effect of enhancing the stability of machining control. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0019] Figure 1 This application provides a flowchart illustrating a method for controlling the machining of a central internal keyway.

[0020] Figure 2 This application provides a schematic diagram of the structure of a control system for machining a central internal keyway.

[0021] Explanation of reference numerals in the attached figures: Sliding process parameter network setting module M100, candidate sliding process combination determination module M200, objective function setting module M300, feasible process window determination module M400, and global optimal machining parameter combination determination module M500. Detailed Implementation

[0022] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0023] Example 1: The present application will be described in detail below with reference to the accompanying drawings, as follows... Figure 1 As shown, this application provides a method for controlling the machining of a central internal keyway, wherein the method includes:

[0024] S1: Based on the central through-hole structure of the workpiece to be processed, set up a planing process parameter network; S2: Based on the planing process parameter network, combined with the tool-workpiece thermal deformation suppression constraint condition and the cutting system chatter suppression constraint condition, determine the candidate planing process combination.

[0025] Specifically, planing has become the mainstream machining method for keyway-type structures due to its suitability for internal keyway structures. Furthermore, the planing process parameter network refers to a set of possible planing process parameters constructed based on the structural characteristics of the central through-hole of the workpiece, including spindle speed, feed rate, and depth of cut, used to initially define the basic conditions of the machining process. Tool-workpiece thermal deformation suppression constraints refer to a series of limitations set during machining to prevent deformation of the tool and workpiece due to cutting heat, typically involving parameters such as heat conduction path, temperature distribution, and thermal deformation matrix, used to ensure machining accuracy. Cutting system chatter suppression constraints refer to limitations set to prevent machining errors caused by vibration during cutting, typically involving parameters such as vibration conduction path, dynamic stiffness matrix, and vibration acceleration, used to ensure the stability of the machining process.

[0026] Execution steps: Based on the structural characteristics of the central through hole of the workpiece, a planing process parameter network is constructed. By analyzing the workpiece's geometry, material properties, and machining requirements, a set of preliminary process parameters is generated. Combining tool-workpiece thermal deformation suppression constraints and cutting system chatter suppression constraints, candidate planing process combinations are selected from the initial process parameter network. Specifically, finite element simulation analysis is used to analyze the cutting heat distribution and predict the thermal deformation of the tool and workpiece. Simultaneously, vibration analysis is used to determine the dynamic stiffness of the cutting system and predict chatter risk. For example, simulations show that when the cutting speed exceeds 150 m / min, the tool edge temperature rises, leading to thermal deformation and affecting machining accuracy; when the spindle speed exceeds 2000 r / min, system vibration intensifies, potentially causing chatter. Therefore, these conditions are used as constraints to select process parameter combinations that meet the requirements for thermal deformation and chatter suppression. Preferably, simulation and analysis ensure that the selected candidate process combinations can effectively suppress thermal deformation and chatter in actual machining, thereby improving machining accuracy and stability.

[0027] S3: Input the candidate keyway machining process combination into the single-objective optimization engine, and set the objective function according to the unit keyway machining time; S4: Simultaneously, constrain the geometric taper error and surface roughness within the preset ε1 threshold and preset ε2 threshold, respectively, to form a band Constrained feasible process window; S5: Solve for the combination of cutting process parameters that minimizes the unit keyway machining time within the feasible process window, and use it as the globally optimal machining parameter combination.

[0028] Specifically, a single-objective optimization engine refers to optimizing candidate process parameter combinations based on minimizing processing time using mathematical models and algorithms to find the optimal combination of process parameters; geometric taper error refers to the deviation between the geometry of the machined keyway and the ideal taper, usually expressed in units of angle or length; surface roughness refers to the microscopic unevenness of the machined surface, usually expressed by parameters such as arithmetic mean roughness. Constraints are the conditions in an optimization method that ensure the machining quality is within an acceptable range by setting the maximum allowable values ​​for error and surface roughness. The feasible process window refers to the range of process parameter combinations that are allowed under all constraints. The globally optimal machining parameter combination refers to the combination of process parameters that minimizes the unit keyway machining time after optimization calculation within the feasible process window.

[0029] Execution steps: Construct an objective function. Specifically, use spindle speed and feed rate as independent variables and unit keyway machining time as dependent variable to construct the objective function. For example, the objective function is T=f(n,u), where T is the unit keyway machining time, n is the spindle speed, and u is the feed rate. Determine the influence relationship between spindle speed and feed rate on machining time through simulation data.

[0030] set up Based on the preliminary analysis, the geometric taper error and surface roughness are constrained within preset thresholds ε1 and ε2, respectively, forming a feasible process window with ε constraints. Specifically, under the condition that the geometric taper error does not exceed the preset threshold ε1 and the surface roughness does not exceed the preset threshold ε2, a feasible range of process parameters is determined to meet the requirements of error and surface roughness, forming a feasible process window. Within the feasible process window, the combination of process parameters that minimizes the unit keyway machining time is solved by a single-objective optimization engine.

[0031] Preferably, while meeting the requirements for machining accuracy, the optimal combination of machining parameters is found to maximize machining efficiency. By constraining errors and surface roughness within a reasonable range, the stability of machining quality is ensured, while optimizing machining time improves production efficiency and meets the needs of large-scale production.

[0032] Furthermore, by constraining the geometric taper error and surface roughness within preset threshold values ​​ε1 and ε2, respectively, a feasible process window with ε constraints is formed. The method of this application includes:

[0033] For mechanically sensitive components, including tool holder overhang length and clamping stiffness, the tool runout deformation caused by cutting force is analyzed, the clamping angle and support position on the machining center spindle are optimized, and the maximum geometric taper error is predicted based on the optimized structural stiffness to determine the preset ε1 threshold. The influence of cutting heat distribution on the tool cutting edge is simulated by finite element simulation, the tool wear acceleration and chip adhesion effect caused by temperature rise are analyzed, the feed per cut and cutting speed are dynamically optimized, and the tool rake face sharpening treatment and coolant directional spray channel are introduced. Based on the optimized cutting thermo-mechanical coupling model, the minimum achievable surface roughness is predicted to determine the preset ε2 threshold.

[0034] Specifically, mechanically sensitive components refer to parts that are sensitive to mechanical factors such as cutting forces and vibrations during machining, such as tool holders and clamping devices. The performance of mechanically sensitive components directly affects machining accuracy and stability. Tool runout refers to the change in position or shape of the tool under the action of cutting forces, usually manifested as bending or twisting of the tool. Tool runout affects machining accuracy and leads to geometric errors. Clamping angle and support position refer to the mounting angle and support point position of the tool on the spindle of the machining center. These can improve the rigidity and stability of the tool and reduce machining errors.

[0035] Cutting heat distribution refers to the distribution of heat between the cutting tool and the workpiece during the cutting process. Cutting heat affects tool wear and the quality of the machined surface. Accelerated tool wear refers to the faster wear rate of the tool material under high temperature conditions, leading to a shorter tool life. Chip adhesion effect refers to the adhesion of chips to the cutting edge of the tool at high temperatures, affecting cutting performance and surface quality. Tool rake face sharpening treatment refers to the use of special processes to make the tool rake face sharper, thereby improving cutting efficiency and surface quality. Coolant directional injection channel refers to setting up a dedicated coolant injection path so that the coolant can be precisely applied to the cutting area, reducing cutting temperature and minimizing thermal deformation and tool wear.

[0036] Execution steps: Analyze the mechanically sensitive components, including the tool holder overhang length and clamping stiffness. Determine the influence of cutting force on tool runout deformation through simulation, and optimize the clamping angle and support position of the tool on the machining center spindle. By adjusting the clamping angle to form an optimal angle with the cutting force direction, reduce the influence of cutting force on the tool. At the same time, optimize the support position to increase the rigidity of the tool. Based on the optimized structural stiffness, predict the maximum geometric taper error and use it as the preset ε1 threshold.

[0037] The influence of cutting heat distribution on the tool cutting edge was simulated using finite element method (FEM) simulation. Specifically, the simulation revealed that cutting heat is concentrated in the tool cutting edge region. Further analysis was conducted on the accelerated tool wear and chip adhesion effects caused by temperature rise. For example, the tool wear rate increases at high temperatures, and the chip adhesion effect leads to increased surface roughness. The feed per cut and cutting speed were dynamically optimized to reduce temperature rise and chip adhesion. Preferably, a tool rake face sharpening treatment and a directional coolant spray channel were introduced. For example, the tool cutting efficiency was improved by sharpening the rake face, and the cutting temperature was reduced by directional coolant spray. Based on the optimized cutting thermo-mechanical coupling model, the minimum achievable surface roughness was predicted and used as a preset ε2 threshold.

[0038] In conventional machining, the setting of geometric taper error and surface roughness thresholds relies on empirical functions. Ideally, through precise analysis of mechanically sensitive components and simulation of cutting heat distribution, machining errors and surface quality can be scientifically predicted, thereby determining reasonable preset thresholds. Specifically, optimizing clamping angles and support positions can significantly reduce tool runout and improve machining accuracy. By dynamically optimizing cutting parameters, introducing tool rake face sharpening treatment and directional coolant injection channels, the impact of cutting heat on the tool and machined surface can be effectively reduced, improving surface quality. These optimization measures not only improve machining accuracy and stability but also provide a basis for subsequent process parameter optimization, ensuring the efficiency and reliability of the machining process.

[0039] Furthermore, based on setting the objective function according to the unit keyway machining time, the method of this application includes:

[0040] For motion control parameters including spindle speed and feed rate, adjust the cutting cycle depth and idle travel time to construct an objective function with spindle speed and feed rate as independent variables and unit keyway machining time as dependent variables; within the feasible domain of process parameters that satisfy geometric taper error not exceeding the preset ε1 threshold and surface roughness not exceeding the preset ε2 threshold, solve for the combination of spindle speed and feed rate that minimizes unit keyway machining time.

[0041] Specifically, motion control parameters refer to the key parameters used to control the movement of the machine tool during the machining process, such as spindle speed and feed rate, which directly affect machining efficiency and quality; depth of cut cycle refers to the depth to which the tool enters the workpiece during each cut, which usually affects cutting force and machining accuracy; idle travel time refers to the time the tool spends moving in a non-cutting state, such as the time to move from one keyway to the next; the objective function is used to describe the relationship between the objective variable and other variables in the optimization problem. Furthermore, the objective variable refers to the unit keyway machining time, and the other variables refer to the spindle speed and feed rate.

[0042] Execution steps: Construct an objective function, determine the motion control parameters including spindle speed and feed rate. These parameters are key factors affecting the unit keyway machining time. Adjust the depth of cut and idle travel time, and analyze the impact of the adjusted depth of cut and idle travel time on the machining time through simulation. Construct the objective function with spindle speed and feed rate as independent variables and unit keyway machining time as the dependent variable. For example, the objective function can be expressed as: T(n,u)= Where T is the unit keyway machining time, and L is the keyway length. This refers to the idle travel time; machining time is optimized by adjusting the spindle speed and feed rate.

[0043] The process involves finding the spindle speed and feed rate combination that minimizes the machining time per unit keyway. Furthermore, within the feasible region of process parameters that satisfy the condition that the geometric taper error does not exceed a preset threshold ε1 and the surface roughness does not exceed a preset threshold ε2, the process further seeks to minimize the machining time per unit keyway. Preferably, by optimizing motion control parameters and tool holder structure settings, machining efficiency and accuracy are further improved. By constructing an objective function and solving for the optimal parameter combination, the process ensures that the machining time per unit keyway is minimized while meeting machining quality requirements, achieving synergistic optimization of machining efficiency and accuracy.

[0044] Furthermore, based on the aforementioned planing process parameter network and combined with the tool-workpiece thermal deformation suppression constraint conditions, the method of this application further includes:

[0045] Cutting temperature data, cutting force data, and vibration spectrum data are mapped to the machining coordinate system. The thermal-mechanical coupling strength between adjacent cutting paths is set. The thermal-mechanical coupling strength between adjacent cutting paths is used to quantify the spatial correlation between heat accumulation and elastic recovery. Based on the machining coordinate system and the thermal-mechanical coupling strength, mutual information nonlinear coupling analysis is performed with temperature-displacement coupling amplification partition, and tool-workpiece thermal deformation suppression constraints are set.

[0046] Specifically, the machining coordinate system refers to the coordinate system used to describe the positional relationship between the tool and the workpiece during the machining process, providing a unified reference framework for data mapping and analysis during the cutting process; the thermo-mechanical coupling strength refers to the strength of the interaction between temperature change and cutting force during the cutting process, used to quantify the spatial correlation between heat accumulation and elastic recovery, reflecting the comprehensive influence of temperature and cutting force on the machining process.

[0047] Temperature-displacement coupling amplification zone refers to the area where the displacement of the tool or workpiece is amplified due to temperature changes during the machining process. It is usually a key area where thermal deformation and mechanical deformation interact. Mutual information nonlinear coupling analysis is used to study the interaction relationship between different physical fields and to identify the strength and distribution law of the coupling effect through analysis. Tool-workpiece thermal deformation suppression constraint conditions refer to the limiting conditions set to prevent the tool and workpiece from affecting the machining accuracy due to thermal deformation during the machining process. They are usually based on the prediction and control of thermal deformation.

[0048] Execution steps: Map cutting temperature data, cutting force data, and vibration spectrum data to the machining coordinate system. For example, by installing multiple sensors in the machining area, cutting temperature, cutting force, and vibration data are collected in real time, and these data are correlated with the position information in the machining coordinate system. Through data mapping, the specific location and distribution of these data in the machining coordinate system are clearly understood. The thermal-mechanical coupling strength between adjacent cutting paths is calculated. Furthermore, by analyzing the relationship between cutting temperature and cutting force, the spatial correlation between heat accumulation and elastic recovery is quantified. For example, through finite element simulation, it is found that the thermal-mechanical coupling strength between adjacent cutting paths is high in some areas, indicating that heat accumulation and elastic recovery in these areas have a greater impact on machining accuracy.

[0049] Based on the machining coordinate system and the thermo-mechanical coupling strength, a mutual information nonlinear coupling analysis is performed on the temperature-displacement coupling amplification partition to identify the region where the tool or workpiece displacement caused by temperature changes is amplified. For example, in a certain segment of the machining path, the tool displacement caused by temperature changes is amplified, forming a temperature-displacement coupling amplification partition. Further analysis is conducted to determine the coupling effect strength and distribution law of the temperature-displacement coupling amplification partition.

[0050] Tool-workpiece thermal deformation suppression constraints are set based on the results of mutual information nonlinear coupling analysis. These constraints limit the impact of thermal deformation on machining accuracy and will be incorporated into subsequent machining parameter optimization to ensure accuracy. Preferably, by mapping cutting temperature, cutting force, and vibration spectrum data to the machining coordinate system and quantifying the thermo-mechanical coupling strength, key areas of heat accumulation and elastic recovery during machining are accurately identified. Further, through mutual information nonlinear coupling analysis, temperature-displacement coupling amplification zones are determined, and tool-workpiece thermal deformation suppression constraints are set. These constraints will be used for process parameter optimization to effectively suppress thermal deformation during machining, achieving dynamic control and accuracy optimization of the machining process.

[0051] Furthermore, by performing mutual information nonlinear coupling analysis with temperature-displacement coupled amplification partitions and setting tool-workpiece thermal deformation suppression constraints, the method of this application also includes:

[0052] Thermal amplification coupling analysis is performed during the planing process based on the thermo-mechanical coupling effect. The heat conduction path between the tool-workpiece contact area and the machine tool spindle is constructed, and the thermal deformation matrix is ​​determined. Based on the thermal deformation matrix, the tool tip displacement gradient is predicted by combining the dynamic cutting force waveform. When there is a coherent match between the local temperature rise rate and the main frequency of the cutting force fluctuation, the temperature-displacement coupling amplification partition and the tool-workpiece thermal deformation suppression constraint conditions are determined.

[0053] Specifically, thermal amplification coupling analysis refers to analyzing the accumulation and conduction effects of cutting heat in the tool-workpiece contact area during planing, and how this thermal effect amplifies deformation and errors during machining. The heat conduction path refers to the specific path through which cutting heat is transferred between the tool and workpiece, typically involving multiple heat transfer methods such as conduction, convection, and radiation. The thermal deformation matrix describes the deformation of the tool and workpiece caused by cutting heat, usually including the relationship between temperature and displacement. The dynamic cutting force waveform refers to the waveform of the cutting force changing over time during cutting, reflecting the dynamic characteristics of the cutting force. The tool tip displacement gradient refers to the rate at which the tool tip position changes with temperature, used to quantify the impact of thermal deformation on machining accuracy. The coherence matching between the local temperature rise rate and the dominant frequency of the cutting force fluctuation refers to the synchronicity of the local temperature rise rate and the dominant frequency of the cutting force fluctuation in frequency or phase, indicating a significant interaction between the two.

[0054] Execution steps: Based on the thermo-mechanical coupling effect, a thermal amplification coupling analysis is performed during the planing process. Through finite element simulation or experimental data, the accumulation and conduction of cutting heat in the tool and workpiece contact area are analyzed. For example, during the planing process, the temperature of the tool edge and workpiece contact area reaches 350°C, and the heat is mainly conducted from the tool to the spindle. The heat conduction path between the tool-workpiece contact area and the machine tool spindle is constructed. Through the heat conduction model, the heat transfer path between the tool and workpiece, as well as the heat distribution in different areas, are determined.

[0055] Based on the heat conduction path, the thermal deformation matrix is ​​determined through finite element analysis. The thermal deformation matrix describes the relationship between temperature change and tool and workpiece deformation. Combined with the dynamic cutting force waveform, the tool tip displacement gradient is predicted. By analyzing the cutting force waveform, the influence of dynamic changes in cutting force on tool tip displacement is determined. When there is a coherent match between the local temperature rise rate and the dominant frequency of cutting force fluctuation, the temperature-displacement coupling amplification zone is determined. For example, through spectrum analysis, it was found that there is a coherent match between the local temperature rise rate and the dominant frequency of cutting force fluctuation at 50Hz, indicating that at this frequency, the thermal effect and the dynamic change of cutting force interact, significantly amplifying the tool tip displacement.

[0056] Furthermore, the temperature-displacement coupling amplification zone and the tool-workpiece thermal deformation suppression constraint conditions are determined. These constraints will be incorporated into subsequent process parameter optimization to ensure machining accuracy. Preferably, the thermo-mechanical coupling effect is analyzed in depth to accurately predict the impact of cutting heat on tool and workpiece deformation; a heat conduction path and thermal deformation matrix are constructed to quantify the deformation caused by cutting heat; and through dynamic cutting force waveform analysis, the interaction region between thermal effects and dynamic changes in cutting force is identified. This further determines the temperature-displacement coupling amplification zone and thermal deformation suppression constraint conditions, effectively suppressing the impact of thermal deformation on machining accuracy and ensuring the stability and accuracy of the machining process.

[0057] Furthermore, based on the aforementioned planing process parameter network and combined with the chatter suppression constraints of the cutting system, the method of this application further includes:

[0058] Based on the machining coordinate system and the thermo-mechanical coupling strength, a mutual information nonlinear coupling analysis is performed with the vibration-displacement coupling amplification partition to set the chatter suppression constraint conditions for the cutting system.

[0059] Specifically, vibration-displacement coupling amplification zone refers to the area where the displacement of the tool or workpiece caused by vibration is significantly amplified during the machining process. It is usually a key area where vibration and mechanical deformation interact, and has a significant impact on machining accuracy and stability. Mutual information nonlinear coupling analysis is used to study the interaction between different physical fields such as thermal field, force field and vibration field. By analyzing and identifying the strength and distribution law of coupling effect, it reveals the complex interaction between different physical fields. The chatter suppression constraint condition of the cutting system refers to the limiting condition set to prevent chatter caused by vibration during the cutting process. It is usually based on vibration characteristic analysis and is used to ensure the stability of the machining process.

[0060] Execution steps: Based on the machining coordinate system and thermo-mechanical coupling strength, identify vibration-displacement coupling amplification zones during machining. Collect vibration data through sensors, and combine it with cutting force and temperature data to analyze the impact of vibration on tool and workpiece displacement. Analyze that vibration causes significant amplification of tool displacement in certain areas, forming vibration-displacement coupling amplification zones. Further analyze the interaction between thermo-mechanical coupling strength and vibration-displacement coupling amplification zones. Through mathematical models and simulation analysis, identify the coupling effects between different physical fields. For example, the analysis found that when the thermo-mechanical coupling strength is high, the vibration amplitude of the vibration-displacement coupling amplification zone further increases. Specifically, in areas where the temperature rises and the cutting force increases, the amplification of tool displacement caused by vibration is more significant.

[0061] Based on the results of mutual information nonlinear coupling analysis, chatter suppression constraints are set for the cutting system to limit vibration amplitude and frequency, ensuring the stability of the machining process. These constraints will be incorporated into subsequent process parameter optimization to prevent chatter. Preferably, a scientific basis for chatter suppression is provided by in-depth analysis of the interaction between vibration-displacement coupling amplification zone and thermo-mechanical coupling strength. Through mutual information nonlinear coupling analysis, the complex relationship between vibration and thermo-mechanical coupling effects is identified, allowing for precise setting of chatter suppression constraints. Further setting of these constraints controls tool vibration within allowable limits, reducing machining errors and tool wear caused by chatter, thereby significantly improving machining quality and tool life. Through scientific coupling effect analysis and the setting of chatter suppression constraints, the impact of vibration on machining accuracy and stability is effectively reduced, improving the reliability and efficiency of the machining process.

[0062] Furthermore, by performing mutual information nonlinear coupling analysis with the vibration-displacement coupled amplification partition and setting chatter suppression constraints for the cutting system, the method of this application includes:

[0063] Based on the mechanical-vibration coupling effect, chatter amplification coupling analysis is performed during the planing process. The vibration transmission path between the tool cantilever beam and the spindle bearing is constructed, and the dynamic stiffness matrix is ​​determined. Based on the dynamic stiffness matrix, the vibration acceleration gradient is predicted by combining the cutting force spectrum. When there is a coherent match between the local vibration amplitude and the spindle rotation frequency, the vibration-displacement coupling amplification partition and the chatter suppression constraint conditions of the cutting system are determined.

[0064] Specifically, the mechanical-vibration coupling effect refers to the interaction between the vibration characteristics of mechanical structures such as tool cantilever beams and spindle bearings and the cutting force during machining, which affects the vibration response and stability during machining. The vibration transmission path refers to the specific path of vibration propagation in the mechanical structure, usually involving the transfer and distribution of vibration energy. The dynamic stiffness matrix is ​​used to describe the stiffness characteristics of the mechanical structure under dynamic loads, reflecting the structure's response to vibration. The cutting force spectrum refers to the frequency distribution of the cutting force over time, reflecting the magnitude of the cutting force at different frequency components during the cutting process. The vibration acceleration gradient refers to the rate at which the vibration acceleration changes with position, used to quantify the intensity change of vibration at different positions. The coherence matching between the local vibration amplitude and the spindle rotation frequency refers to the synchronicity of the local vibration amplitude and the spindle rotation frequency in frequency or phase, indicating a significant interaction between the two.

[0065] Execution steps: Based on the mechanical-vibration coupling effect, a chatter amplification coupling analysis is performed during the planing process. By analyzing the vibration characteristics of the tool cantilever beam and the spindle bearing, the interaction between cutting force and vibration is determined, and the vibration transmission path between the tool cantilever beam and the spindle bearing is constructed. Furthermore, through finite element analysis, the specific path of vibration transmission from the tool cantilever beam to the spindle bearing, as well as the distribution of vibration energy along the path, are determined.

[0066] Based on the vibration transmission path, the dynamic stiffness matrix is ​​determined. The dynamic stiffness matrix describes the stiffness characteristics of the mechanical structure under dynamic loads and reflects the structure's response to vibration. Combined with the cutting force spectrum, the vibration acceleration gradient is predicted. By analyzing the cutting force spectrum, the influence of cutting forces of different frequency components on vibration is determined. When there is a coherent match between the local vibration amplitude and the spindle rotation frequency, it indicates that the vibration is significantly amplified at certain frequencies. Through spectrum analysis, it is found that when the spindle rotation frequency is 100Hz, the local vibration amplitude increases significantly, indicating the existence of a coherent match. At this time, the vibration-displacement coupled amplification zone is determined, indicating that the vibration of the vibration-displacement coupled amplification zone has a significant impact on machining accuracy and stability.

[0067] The vibration-displacement coupling amplification zone and chatter suppression constraints of the cutting system are determined. These constraints will be incorporated into subsequent process parameter optimization to ensure machining stability. By adjusting the spindle speed and cutting parameters, machining at frequencies with matching coherence is avoided, thereby reducing chatter occurrence. A thorough analysis of the mechanical-vibration coupling effect accurately predicts the impact of vibration on machining accuracy and stability during cutting. The construction of vibration transmission paths and dynamic stiffness matrices quantifies the propagation and response characteristics of vibration in the mechanical structure. Preferably, further prediction of vibration acceleration gradients and identification of vibration-displacement coupling amplification zones provide a scientific basis for chatter suppression in the cutting system. The chatter suppression constraints effectively reduce the impact of vibration on machining accuracy and stability, ensuring the reliability and efficiency of the machining process.

[0068] Furthermore, the method of this application includes:

[0069] A multi-dimensional sensor array covering the keyway machining area is used to collect surface temperature data, cutting force data, and vibration acceleration data of the workpiece during the broaching process. Based on the surface temperature data, cutting force data, and vibration acceleration data, the dominant frequency of temperature fluctuation, force pulse intensity, and vibration mode frequency are extracted, and inter-field correlation feature analysis is performed to identify the cross-coupling characteristics between the thermo-mechanical coupling effect and the mechanical-vibration coupling effect. Multiple cross-influence factors mapped by the cross-coupling characteristics are combined with a preset safety margin to determine the multi-field coupling effect threshold. The multi-field coupling effect threshold is used to verify in real time whether the current broaching process parameters are in a stable machining range, and when the cross-coupling intensity is detected to exceed the multi-field coupling effect threshold, the tightening adjustment of the preset ε1 threshold and the preset ε2 threshold is triggered.

[0070] Specifically, a multi-dimensional sensor array refers to multiple sensors arranged in the machining area to simultaneously measure different physical quantities. The multi-dimensional sensor array can cover the entire keyway machining area, providing comprehensive real-time data; the dominant frequency of temperature fluctuation refers to the main frequency component of temperature change in surface temperature data, reflecting the dynamic characteristics of the heat source; the force pulse intensity refers to the intensity of the pulse signal in cutting force data, reflecting the instantaneous force change during the cutting process; and the vibration modal frequency refers to the main frequency component of vibration in vibration acceleration data, reflecting the vibration characteristics of the mechanical system.

[0071] Inter-field correlation feature analysis refers to analyzing the interrelationships between different physical fields such as temperature field, force field, and vibration field to identify the characteristics of coupling effects. Cross-coupling features refer to the interaction characteristics between thermo-mechanical coupling effects and mechanical-vibration coupling effects, reflecting the complex relationship between multiple physical fields. Cross-influence factors refer to multiple influencing factors mapped through cross-coupling features, used to quantify the strength of multi-field coupling effects. Multi-field coupling effect threshold refers to a threshold determined based on cross-influence factors and preset safety margins, used to monitor the stability of the processing process in real time. Tightening adjustment refers to adjusting the preset error threshold when the detected cross-coupling strength exceeds the multi-field coupling effect threshold to maintain the geometric accuracy and surface integrity of the keyway, thereby ensuring the stability of the processing process.

[0072] Execution steps: A multi-dimensional sensor array covering the keyway machining area is used to collect surface temperature data, cutting force data, and vibration acceleration data of the workpiece in real time during the broaching process. For example, multiple thermocouple sensors, strain gauges, and accelerometers are arranged in the machining area to measure temperature, cutting force, and vibration acceleration, respectively. Based on the collected data, the dominant frequency of temperature fluctuation, force pulse intensity, and vibration mode frequency are extracted, and inter-field correlation feature analysis is performed to identify the cross-coupling characteristics between the thermo-mechanical coupling effect and the mechanical-vibration coupling effect. Furthermore, through correlation analysis, it is found that there is a significant correlation between the dominant frequency of temperature fluctuation and the vibration mode frequency, indicating that there is a cross-coupling between the thermal effect and the vibration effect.

[0073] By mapping multiple cross-influence factors through cross-coupling features and combining them with a preset safety margin, a multi-field coupling threshold is determined. This threshold is used to verify in real time whether the current cutting process parameters are within a stable processing range. For example, if the dimensionless cross-influence factor is 0.8 and the preset safety margin is 10%, then the multi-field coupling threshold is set to 0.88. When a cross-coupling strength of 0.9 is detected, it exceeds the multi-field coupling threshold of 0.88, indicating that there may be an instability risk in the current processing.

[0074] When the cross-coupling strength is detected to exceed the multi-field coupling threshold, a tightening adjustment of the preset ε1 and preset ε2 thresholds is triggered. Preferably, the multi-dimensional sensor array monitors multiple physical quantities in the processing process in real time. Through feature extraction and correlation analysis, the complex relationship between thermo-mechanical coupling effects and mechanical-vibration coupling effects is identified. The multi-field coupling threshold is determined, the stability of the processing process is monitored in real time, and threshold adjustment is triggered when necessary to ensure that the processing process is always in a stable range, realizing dynamic monitoring and adaptive adjustment of the processing process. Furthermore, by monitoring and analyzing multi-physics data in real time, potential unstable factors can be detected in a timely manner, and by adjusting the error threshold, the processing accuracy and stability can be ensured, significantly improving the reliability and adaptability of the processing process.

[0075] In summary, the beneficial effects of the embodiments of this application are:

[0076] Because a center through-hole structure based on the workpiece is adopted, a planing process parameter network is set. Based on the planing process parameter network, combined with the tool-workpiece thermal deformation suppression constraint and the cutting system chatter suppression constraint, candidate planing process combinations are determined. The candidate planing process combinations are input into a single-objective optimization engine, and the objective function is set according to the unit keyway machining time. At the same time, the geometric taper error and surface roughness are constrained within the preset ε1 threshold and preset ε2 threshold, respectively, forming a band The feasible process window is constrained; within the feasible process window, the combination of planing process parameters that minimizes the unit keyway machining time is solved as the globally optimal machining parameter combination. This application provides a control method, system, and medium for machining center inner hole keyways, which achieves accurate prediction of error limits through deformation analysis of mechanically sensitive components and cutting thermo-mechanical coupling simulation, determines preset ε1 and preset ε2 thresholds adapted to actual machining conditions, and integrates dual suppression constraints of tool-workpiece thermal deformation and cutting system chatter to determine candidate process combinations, thereby bringing... Optimizing the feasible process window under constraints improves the technical effect of enhancing the stability of machining control.

[0077] Example 2, based on the same inventive concept as the central inner hole keyway machining control method in the aforementioned examples, such as... Figure 2 As shown in the figure, this application embodiment provides a control system for machining a central internal keyway, wherein the system includes:

[0078] Slab cutting process parameter network setting module M100: Based on the central through hole structure of the workpiece to be processed, set the slab cutting process parameter network.

[0079] Candidate Saw Cutting Process Combination Determination Module M200: Based on the saw cutting process parameter network, combined with the tool-workpiece thermal deformation suppression constraint condition and the cutting system chatter suppression constraint condition, candidate saw cutting process combinations are determined.

[0080] Objective function setting module M300: Inputs the candidate cutting process combination into the single-objective optimization engine and sets the objective function according to the unit keyway machining time.

[0081] Feasible process window determination module M400: Simultaneously, geometric taper error and surface roughness are constrained within preset ε1 threshold and preset ε2 threshold, respectively, forming a band Constrained feasible process window.

[0082] Global optimal machining parameter combination determination module M500: Within the feasible process window, it solves for the combination of broaching process parameters that minimizes the unit keyway machining time, and uses this combination as the global optimal machining parameter combination.

[0083] Furthermore, the feasible process window determination module M400 is used to perform the following method:

[0084] For mechanically sensitive components, including tool holder overhang length and clamping stiffness, the tool runout deformation caused by cutting force is analyzed, the clamping angle and support position on the machining center spindle are optimized, and the maximum geometric taper error is predicted based on the optimized structural stiffness to determine the preset ε1 threshold. The influence of cutting heat distribution on the tool cutting edge is simulated by finite element simulation, the tool wear acceleration and chip adhesion effect caused by temperature rise are analyzed, the feed per cut and cutting speed are dynamically optimized, and the tool rake face sharpening treatment and coolant directional spray channel are introduced. Based on the optimized cutting thermo-mechanical coupling model, the minimum achievable surface roughness is predicted to determine the preset ε2 threshold.

[0085] Furthermore, the objective function setting module M300 is used to perform the following method:

[0086] For motion control parameters including spindle speed and feed rate, adjust the cutting cycle depth and idle travel time to construct an objective function with spindle speed and feed rate as independent variables and unit keyway machining time as dependent variables; within the feasible domain of process parameters that satisfy geometric taper error not exceeding the preset ε1 threshold and surface roughness not exceeding the preset ε2 threshold, solve for the combination of spindle speed and feed rate that minimizes unit keyway machining time.

[0087] Furthermore, the candidate cutting process combination determination module M200 is also used to perform the following method:

[0088] Cutting temperature data, cutting force data, and vibration spectrum data are mapped to the machining coordinate system. The thermal-mechanical coupling strength between adjacent cutting paths is set. The thermal-mechanical coupling strength between adjacent cutting paths is used to quantify the spatial correlation between heat accumulation and elastic recovery. Based on the machining coordinate system and the thermal-mechanical coupling strength, mutual information nonlinear coupling analysis is performed with temperature-displacement coupling amplification partition, and tool-workpiece thermal deformation suppression constraints are set.

[0089] Furthermore, the candidate cutting process combination determination module M200 is also used to perform the following method:

[0090] Thermal amplification coupling analysis is performed during the planing process based on the thermo-mechanical coupling effect. The heat conduction path between the tool-workpiece contact area and the machine tool spindle is constructed, and the thermal deformation matrix is ​​determined. Based on the thermal deformation matrix, the tool tip displacement gradient is predicted by combining the dynamic cutting force waveform. When there is a coherent match between the local temperature rise rate and the main frequency of the cutting force fluctuation, the temperature-displacement coupling amplification partition and the tool-workpiece thermal deformation suppression constraint conditions are determined.

[0091] Furthermore, the candidate cutting process combination determination module M200 is also used to perform the following method:

[0092] Based on the machining coordinate system and the thermo-mechanical coupling strength, a mutual information nonlinear coupling analysis is performed with the vibration-displacement coupling amplification partition to set the chatter suppression constraint conditions for the cutting system.

[0093] Furthermore, the candidate cutting process combination determination module M200 is also used to perform the following method:

[0094] Based on the mechanical-vibration coupling effect, chatter amplification coupling analysis is performed during the planing process. The vibration transmission path between the tool cantilever beam and the spindle bearing is constructed, and the dynamic stiffness matrix is ​​determined. Based on the dynamic stiffness matrix, the vibration acceleration gradient is predicted by combining the cutting force spectrum. When there is a coherent match between the local vibration amplitude and the spindle rotation frequency, the vibration-displacement coupling amplification partition and the chatter suppression constraint conditions of the cutting system are determined.

[0095] Furthermore, the feasible process window determination module M400 is also used to perform the following method:

[0096] A multi-dimensional sensor array covering the keyway machining area is used to collect surface temperature data, cutting force data, and vibration acceleration data of the workpiece during the broaching process. Based on the surface temperature data, cutting force data, and vibration acceleration data, the dominant frequency of temperature fluctuation, force pulse intensity, and vibration mode frequency are extracted, and inter-field correlation feature analysis is performed to identify the cross-coupling characteristics between the thermo-mechanical coupling effect and the mechanical-vibration coupling effect. Multiple cross-influence factors mapped by the cross-coupling characteristics are combined with a preset safety margin to determine the multi-field coupling effect threshold. The multi-field coupling effect threshold is used to verify in real time whether the current broaching process parameters are in a stable machining range, and when the cross-coupling intensity is detected to exceed the multi-field coupling effect threshold, the tightening adjustment of the preset ε1 threshold and the preset ε2 threshold is triggered.

[0097] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Figure 1 The central internal keyway machining control method and specific example in Embodiment 1 are also applicable to the central internal keyway machining control system of this embodiment. Through the foregoing detailed description of the central internal keyway machining control method, those skilled in the art can clearly understand the central internal keyway machining control system of this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.

[0098] Example 3 provides a storage medium on which a computer program is stored, which, when executed by a processor, implements any step of Example 1.

[0099] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0100] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.

Claims

1. A center bore keyway machining control method, characterized by, The method includes: Based on the central through-hole structure of the workpiece to be processed, a cutting process parameter network is set up; Based on the aforementioned planing process parameter network, and combined with the tool-workpiece thermal deformation suppression constraint conditions and the cutting system chatter suppression constraint conditions, candidate planing process combinations are determined. The candidate cutting process combinations are input into a single-objective optimization engine, and the objective function is set according to the unit keyway machining time. Meanwhile, the geometric taper error and the surface roughness are respectively constrained within preset ε1 threshold and preset ε2 threshold, forming a constrained feasible process window; Within the feasible process window, the combination of cutting process parameters that minimizes the unit keyway machining time is determined and used as the globally optimal combination of machining parameters. The method involves constraining the geometric taper error and surface roughness within preset thresholds ε1 and ε2, respectively, to form a feasible process window with ε constraints. For mechanically sensitive components including tool holder overhang length and clamping stiffness, analyze the tool runout deformation caused by cutting force, optimize the clamping angle and support position on the machining center spindle, and predict the maximum geometric taper error based on the optimized structural stiffness to determine the preset ε1 threshold. The influence of cutting heat distribution on the cutting edge is simulated by finite element method. The accelerated tool wear and chip adhesion caused by temperature rise are analyzed. The feed per cut and cutting speed are dynamically optimized. Tool rake face sharpening treatment and coolant directional spray channel are introduced. Based on the optimized cutting thermo-mechanical coupling model, the minimum achievable surface roughness is predicted, and the preset ε2 threshold is determined.

2. The method of claim 1, wherein the keyway is formed in the center bore. The method includes setting an objective function based on the unit keyway machining time, and comprising: For motion control parameters including spindle speed and feed rate, adjust the depth of cut and idle travel time, and construct an objective function with spindle speed and feed rate as independent variables and unit keyway machining time as dependent variables; Within the feasible region of process parameters that satisfy the condition that the geometric taper error does not exceed the preset threshold ε1 and the surface roughness does not exceed the preset threshold ε2, solve for the combination of spindle speed and feed rate that minimizes the unit keyway machining time.

3. The method of claim 1, wherein the method further comprises: Based on the aforementioned planing process parameter network, and combined with the tool-workpiece thermal deformation suppression constraint conditions, the method further includes: Cutting temperature data, cutting force data, and vibration spectrum data are mapped to the machining coordinate system, and the thermal-mechanical coupling strength between adjacent cutting paths is set. The thermal-mechanical coupling strength between adjacent cutting paths is used to quantify the spatial correlation between heat accumulation and elastic recovery. Based on the machining coordinate system and the thermo-mechanical coupling strength, a mutual information nonlinear coupling analysis is performed with the temperature-displacement coupling amplification partition, and a constraint condition for suppressing tool-workpiece thermal deformation is set.

4. The method for controlling the machining of a central inner hole keyway as described in claim 3, characterized in that, The method further includes performing mutual information nonlinear coupling analysis with temperature-displacement coupled amplification partitioning, setting tool-workpiece thermal deformation suppression constraints, and also includes: Based on the thermo-mechanical coupling effect, thermal amplification coupling analysis is performed during the planing process to construct the heat conduction path between the tool-workpiece contact area and the machine tool spindle, and to determine the thermal deformation matrix. Based on the thermal deformation matrix and combined with the dynamic cutting force waveform to predict the tool tip displacement gradient, when there is a coherent match between the local temperature rise rate and the main frequency of the cutting force fluctuation, the temperature-displacement coupling amplification partition and the tool-workpiece thermal deformation suppression constraint conditions are determined.

5. The method of claim 3, wherein the keyway is formed in the center bore. Based on the aforementioned planing process parameter network, and combined with the chatter suppression constraints of the cutting system, the method further includes: ​ Based on the machining coordinate system and the thermo-mechanical coupling strength, a mutual information nonlinear coupling analysis is performed with the vibration-displacement coupling amplification partition to set the chatter suppression constraint conditions for the cutting system.

6. The method of claim 5, wherein the keyway is formed in the center bore. The method includes performing mutual information nonlinear coupling analysis with vibration-displacement coupled amplification partitions, and setting chatter suppression constraints for the cutting system. Based on the mechanical-vibration coupling effect, a chatter amplification coupling analysis is performed during the planing process to construct the vibration transmission path between the tool cantilever beam and the spindle bearing and determine the dynamic stiffness matrix. Based on the dynamic stiffness matrix and combined with the cutting force spectrum to predict the vibration acceleration gradient, when there is a coherent match between the local vibration amplitude and the spindle rotation frequency, the vibration-displacement coupling amplification partition and the chatter suppression constraint conditions of the cutting system are determined.

7. The method of claim 6, wherein the keyway is formed in the center bore. The method includes: ​ A multi-dimensional sensor array covering the keyway machining area is used to collect surface temperature data, cutting force data, and vibration acceleration data of the workpiece to be machined during the planing process. Based on the surface temperature data, cutting force data, and vibration acceleration data, the dominant frequency of temperature fluctuation, force pulse intensity, and vibration mode frequency are extracted, and inter-field correlation feature analysis is performed to identify the cross-coupling characteristics between the thermo-mechanical coupling effect and the mechanical-vibration coupling effect. The threshold for multi-field coupling effect is determined by using multiple cross-influence factors mapped by the cross-coupling feature and combining them with a preset safety margin. The multi-field coupling threshold is used to verify in real time whether the current cutting process parameters are in a stable processing range, and when the cross-coupling strength is detected to exceed the multi-field coupling threshold, it triggers the tightening adjustment of the preset ε1 threshold and the preset ε2 threshold.

8. A center bore keyway machining control system, comprising: The system is used for implementing the method for controlling the machining of a central internal keyway according to any one of claims 1-7, and the system comprises: Slab cutting process parameter network setting module: Based on the central through hole structure of the workpiece, set the slab cutting process parameter network; Candidate slitting process combination determination module: Based on the slitting process parameter network, combined with the tool-workpiece thermal deformation suppression constraint condition and the cutting system chatter suppression constraint condition, the candidate slitting process combination is determined; Objective function setting module: Input the candidate cutting process combination into the single-objective optimization engine and set the objective function according to the unit keyway machining time; The feasible process window determination module: at the same time, the geometric taper error and the surface roughness are respectively constrained within the preset ε1 threshold and the preset ε2 threshold, forming a feasible process window with constraints ​ Global optimal machining parameter combination determination module: Within the feasible process window, solve for the combination of broaching process parameters that minimizes the unit keyway machining time, and use it as the global optimal machining parameter combination.

9. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the central inner hole keyway machining control method according to any one of claims 1 to 7.

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