Titanium alloy drill pipe threading method and apparatus

Abstract

The present application relates to a titanium alloy drill pipe thread processing method and device. It includes: constructing a partition thermal coupling model, constructing a plastic model for correcting the plastic mechanics response of the material to be processed, constructing a damage evolution model, and constructing a motion control model. Based on the above-mentioned models, the thread processing simulation of multiple candidate thread processing parameters on the material to be processed is carried out through finite element analysis method, the thread processing indicators corresponding to each candidate thread processing parameter are determined, and the candidate thread processing parameter that meets the predetermined index requirement is selected as the target processing parameter. The thread processing of the material to be processed is controlled according to the target processing parameter by the processing machine tool. The high-precision prediction of the temperature field, cutting force and damage evolution in the thread cutting process of the titanium alloy drill pipe is realized, and the key processing parameters such as spindle angular velocity and feed speed are dynamically optimized.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of oil drilling and production equipment manufacturing technology, and in particular to a method and apparatus for machining threads on titanium alloy drill pipes. Background Technology

[0002] With the extension of oil and gas extraction to deep wells, ultra-deep wells, and highly corrosive formations, titanium alloys have become the preferred choice for high-end drill pipes due to their high strength, low density, and excellent corrosion resistance. The precision of their thread machining directly determines the sealing performance and load-bearing capacity of the connection, but current technologies are insufficient to meet the high-precision machining requirements. Summary of the Invention

[0003] To address the problems existing in the prior art, this specification provides a method and apparatus for machining threads on titanium alloy drill pipes. By constructing a partitioned thermo-mechanical coupling model, an improved constitutive equation, and a taper-multi-physics linkage motion control mechanism, combined with adaptive mesh simulation technology, it achieves high-precision prediction of temperature field, cutting force, and damage evolution during the cutting process of titanium alloy drill pipe threads, while dynamically optimizing key machining parameters such as spindle angular velocity and feed rate.

[0004] The specific technical solutions of the embodiments in this specification are as follows: On one hand, this specification provides an embodiment of a method for machining threads on titanium alloy drill pipes, the method comprising: Based on the latent heat of phase change of the material to be processed, a partitioned thermo-mechanical coupling model is constructed to reflect the temperature field changes of the material during processing. A plastic model is constructed to correct the plastic mechanical response of the material to be processed based on the strain correction coefficients corresponding to the material to be processed. A damage evolution model reflecting damage to the material to be processed is constructed based on the plastic mechanical response of the material to be processed. A taper-multiphysics linkage motion control model is constructed, which is used to control the movement of the cutting tool in the machine tool according to the thread machining parameters; Based on the partitioned thermo-coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, as well as the three-dimensional geometric model of the material to be processed and the cutting tool, the thread processing of the material to be processed is simulated using multiple candidate thread processing parameters through finite element analysis, and the thread processing index corresponding to each candidate thread processing parameter is determined. The candidate thread processing parameters that meet the predetermined index requirements are used as the target processing parameters. The machine tool is controlled to perform thread processing on the material to be processed according to the target processing parameters.

[0005] Furthermore, based on the partitioned thermo-coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, as well as the three-dimensional geometric models of the material to be processed and the cutting tool, the method further includes the following steps in simulating thread processing of the material to be processed using multiple candidate thread processing parameters through finite element analysis: During the simulated thread processing, the three-dimensional temperature field of the material to be processed is monitored. Calculate the temperature gradient based on the three-dimensional temperature field; The mesh size in the simulation parameters of the finite element analysis method is adjusted according to the temperature gradient.

[0006] Furthermore, adjusting the mesh size in the simulation parameters of the finite element analysis method according to the temperature gradient further includes: The first region in which the change of the temperature gradient exceeds a first threshold within a single simulation time step is identified as the first target region. Reduce the size of the grid corresponding to the first target region.

[0007] Furthermore, adjusting the mesh size in the simulation parameters of the finite element analysis method according to the temperature gradient further includes: After a predetermined simulation time step, the reference mesh size of the second region of the material to be processed is adjusted according to the temperature gradient corresponding to the predetermined simulation time step, wherein the gradient level of the second region is inversely proportional to the reference mesh size.

[0008] Furthermore, the formula for adjusting the reference mesh size of the second region of the material to be processed at multiple different gradient levels according to the temperature gradient corresponding to the predetermined simulation time step is as follows: ; Where h represents the adjusted grid size, and h0 represents the baseline grid size. denoted by , where G represents the temperature gradient.

[0009] Furthermore, based on the partitioned thermo-coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, as well as the three-dimensional geometric models of the material to be processed and the cutting tool, the method further includes the following steps in simulating thread processing of the material to be processed using multiple candidate thread processing parameters through finite element analysis: During the thread processing simulation, damage variables in multiple third regions of the material to be processed are monitored. Determine whether there are any damage variables that exceed the second threshold; If so, the third region corresponding to the damage variable exceeding the second threshold is taken as the second target region, and the mesh size corresponding to the second target region is reduced.

[0010] Furthermore, based on the latent heat of phase change of the material to be processed, the formula for constructing a partitioned thermo-mechanical coupling model of the temperature field change of the material during processing is as follows: ; in, The change in thermodynamic energy is the term, where ρ is density. For specific heat capacity, Let t represent temperature and t represent time. For heat conduction, Here, K is the divergence operator, used to describe the flux source intensity of a vector field, and K is the thermal conductivity. The heat generation rate of plastic deformation in the shear zone, The contact friction heat generation rate in the friction zone. This is a correction term for the latent heat of phase transition. Let f be the latent heat of phase transition, and f be the volume fraction of phase transition.

[0011] Furthermore, the formula for constructing a plastic model that corrects the plastic mechanical response of the material to be processed based on the strain correction coefficient is as follows: ; Where σ is stress, To describe the change in material properties with plastic strain under room temperature and quasi-static conditions. The basic hardening terms for the work hardening properties of the developed material are: A = yield stress, B = hardening modulus, and n = hardening exponent. To quantify high strain rate The strain rate correction term for the strengthening effect of flow stress, where C is the strain rate sensitivity coefficient. For reference strain rate, T is the normalized temperature, and T is the instantaneous temperature during the processing. room At room temperature, T m λ is the melting temperature of the material to be processed, m is the thermal softening index, and λ is the strain correction factor.

[0012] Furthermore, the formula for constructing a damage evolution model reflecting damage to the material to be processed based on the plastic mechanical response of the material to be processed is as follows: ; in, As a strain-driven term, Let be the temperature-dependent fracture strain, SDEG be the damage variable, and t be the time.

[0013] Furthermore, the formula for constructing the cone-multiphysics linkage motion control model is as follows: Dynamic correction model for spindle angular velocity: Where ω is the principal axis angular velocity, and V c The cutting speed is one of the thread machining parameters. Where ζ is the diameter of the small end of the thread, and ζ is the stress correction factor. This refers to the equivalent stress during the cutting process. The yield strength of the material to be processed; Axial feed rate linkage model: , where V z y is the axial feed rate, P is the thread pitch, n is the spindle speed, and k is the thread pitch. p This is the pitch compensation coefficient; Multi-parameter coupled model of radial feed rate: , where V r Where α is the radial feed rate, and α is the thread taper half-angle. K is the cutting strain rate, k is the strain rate coefficient, and K t This is the temperature correction factor.

[0014] Furthermore, the thread processing parameters include one or more combinations of thread root damage variables, maximum temperature in the cutting zone, cutting force fluctuation coefficient, and processing time.

[0015] On the other hand, embodiments of this specification also provide a titanium alloy drill pipe threading apparatus, the apparatus comprising: A partitioned thermo-coupling model construction unit is used to construct a partitioned thermo-coupling model that reflects the temperature field changes of the material to be processed during the processing based on the latent heat of phase change of the material to be processed. A plastic model construction unit is used to construct a plastic model that corrects the plastic mechanical response of the material to be processed based on the strain correction coefficient corresponding to the material to be processed. The damage evolution model construction unit is used to construct a damage evolution model that reflects the damage of the material to be processed based on the plastic mechanical response of the material to be processed. A motion control model construction unit is used to construct a taper-multiphysics linkage motion control model, which is used to control the movement of the cutting tool in the machine tool according to the thread machining parameters. The machining simulation unit is used to simulate the threading of the material to be machined by using multiple candidate threading parameters through finite element analysis based on the partitioned thermo-mechanical coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, the three-dimensional geometric model of the material to be machined and the cutting tool, and to determine the threading index corresponding to each of the candidate threading parameters. The target machining parameter determination unit is used to take the candidate thread machining parameters that meet the predetermined index requirements as the target machining parameters. The machining control unit is used to control the machine tool to perform thread machining on the material to be processed according to the target machining parameters.

[0016] On the other hand, embodiments of this specification also provide a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the above-described method.

[0017] On the other hand, embodiments of this specification also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0018] On the other hand, embodiments of this specification also provide a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method.

[0019] The methods described in this specification have at least the following beneficial effects: The embodiments in this specification employ advanced finite element analysis simulation technology, which can effectively improve the quality and reliability of thread processing. Through precise thermo-damage coupling analysis, it can more realistically reflect the mechanical response and damage changes of titanium alloys during processing, reducing defects such as thread taper deviation and root cracks caused by simulation bias. This allows the sealing performance and load-bearing capacity of drill pipe threads to better meet the requirements of harsh working conditions such as deep wells and ultra-deep wells, reducing the risk of safety accidents such as downhole leakage and fracture, and fundamentally ensuring the stable operation of drill pipes during oil extraction.

[0020] Through systematic and rigorous analysis, the embodiments in this specification effectively optimize the processing flow and reduce production costs. The previous method, relying on multiple trial cuts to adjust parameters, was not only time-consuming but also resulted in significant waste of titanium alloy materials and cutting tools. In contrast, the embodiments in this specification, through dynamic motion control and parameter optimization, can significantly reduce the number of trial cuts while improving processing efficiency. This leads to shorter production cycles and lower costs for titanium alloy drill pipes, better meeting the oil industry's demands for equipment manufacturing efficiency and cost control, and providing an efficient means to optimize the thread processing parameters of titanium alloy drill pipes.

[0021] In terms of application prospects in the petroleum industry, the embodiments in this specification are not only applicable to the thread processing of current mainstream titanium alloy drill pipes, but also, as oil extraction extends to more complex formations, provide technical support for the research and development and processing of new lightweight alloy drill pipes. It helps companies break free from reliance on "experience-based trial cutting," achieving digitalization and scientific processing of drill pipes through precise simulation, thereby assisting petroleum equipment manufacturing companies in enhancing their core competitiveness. It has significant practical application value and broad application prospects. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this specification 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 only some embodiments of the embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 The diagram shown is a flowchart illustrating a method for machining threads on a titanium alloy drill rod according to an embodiment of this specification. Figure 2 The diagram shown is a flowchart illustrating the adaptive mesh refinement algorithm for dynamically optimizing mesh density in an embodiment of this specification. Figure 3 The diagram shown is a schematic representation of the process by which abrupt temperature gradient triggers the adjustment of the mesh size in the simulation parameters of the finite element analysis method in an embodiment of this specification. Figure 4 The diagram shown is a schematic representation of the process by which the mesh size in the simulation parameters of the finite element analysis method is adjusted in the high-damage-risk zone of an embodiment of this specification. Figure 5 The diagram shown is a structural schematic of a titanium alloy drill rod thread processing device according to an embodiment of this specification. Figure 6 The diagram shown is a structural schematic of the computer device in an embodiment of this specification.

[0024] [Explanation of Figure Markers]: 501. Partitioned thermo-coupling model construction unit; 502. Plastic model building unit; 503. Damage evolution model construction unit; 504. Motion control model construction unit; 505. Machining simulation unit; 506. Target processing parameter determination unit; 507. Processing control unit; 602. Computer equipment; 604, Processor; 606. Memory; 608. Drive mechanism; 610. Input / output module; 612. Input devices; 614. Output devices; 616. Presentation equipment; 618. Graphical User Interface; 620. Network interface; 622. Communication link; 624. Communication bus. Detailed Implementation

[0025] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the embodiments of this specification, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the embodiments of this specification.

[0026] It should be noted that the terms "first," "second," etc., in the description, claims, and accompanying drawings of the embodiments herein are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, apparatus, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0027] It should be noted that the acquisition, storage, use, and processing of data in the technical solutions of the embodiments of this specification all comply with the relevant provisions of national laws and regulations.

[0028] It should be noted that in the embodiments of this specification, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, they do not mean that the applicant has used or necessarily used the solution.

[0029] The inventors discovered in their research that existing thread machining analysis methods suffer from low accuracy in thermo-mechanical coupling analysis, fail to distinguish between heat sources in the shear and friction zones, and the constitutive model does not consider the high strain rate sensitivity and temperature nonlinearity of titanium alloys, resulting in large errors in temperature field and cutting force prediction. Furthermore, motion control and taper linkage are poor, and fixed parameters lack dynamic feedback, easily leading to tool chatter and excessive pitch deviation. Simulation is disconnected from actual machining, requiring multiple trial cuts to determine parameters, resulting in high costs, long cycles, and low machining efficiency. Reliable theoretical methods for parameter optimization are also lacking.

[0030] To overcome the shortcomings of the existing technology, the inventors proposed a method for machining threads on titanium alloy drill pipes. Addressing the pain points of insufficient accuracy in thermo-mechanical coupling analysis, poor motion control and taper linkage, and disconnect between simulation and actual machining in existing titanium alloy thread machining simulations, this method constructs a partitioned thermo-mechanical coupling model, an improved constitutive equation, and a taper-multiphysics linkage motion control mechanism. Combined with adaptive mesh simulation technology, it achieves high-precision prediction of temperature field, cutting force, and damage evolution during the cutting process of titanium alloy drill pipe threads, while dynamically optimizing key machining parameters such as spindle angular velocity and feed rate. The embodiments in this specification, through the above-described technical solutions, can accurately reflect the physical field changes during actual processing, solving the problems of large prediction errors and difficulty in controlling taper and pitch accuracy caused by simplified heat source models and fixed motion parameters in existing simulations. Simultaneously, it integrates a complete "modeling-solving-optimization-visualization" workflow, outputting optimal processing parameters that can directly guide actual production. This solves the problems of numerous trial cuts, high costs, and long development cycles in the traditional "trial cutting-adjustment" model. Ultimately, it provides scientific and reliable simulation support for high-quality processing of titanium alloy drill pipe threads, helping the oil drilling and production ultra-deep well equipment manufacturing field improve processing efficiency, reduce production costs, and ensure drill pipe connection safety.

[0031] Specifically, Figure 1 The diagram shown is a flowchart illustrating a method for machining threads on titanium alloy drill pipes according to an embodiment of this specification. The order of steps listed in the embodiment is merely one possible execution order among many and does not represent the only possible order. In actual system or device products, the methods shown in the embodiment or accompanying drawings can be executed sequentially or in parallel. Specifically, as shown... Figure 1 As shown, the method is executed by a computer and may include: Step 101: Construct a partitioned thermo-mechanical coupling model that reflects the temperature field changes of the material during processing based on the latent heat of phase change of the material to be processed; Step 102: Construct a plastic model that corrects the plastic mechanical response of the material to be processed based on the strain correction coefficients corresponding to the material to be processed; Step 103: Construct a damage evolution model that reflects the damage to the material to be processed based on the plastic mechanical response of the material to be processed; Step 104: Construct a taper-multiphysics linkage motion control model, which is used to control the movement of the cutting tool in the machine tool according to the thread machining parameters; Step 105: Based on the partitioned thermo-mechanical coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, as well as the three-dimensional geometric model of the material to be processed and the cutting tool, the thread processing of the material to be processed is simulated using multiple candidate thread processing parameters through finite element analysis, and the thread processing index corresponding to each candidate thread processing parameter is determined. Step 106: Select the candidate thread processing parameters that meet the predetermined index requirements as the target processing parameters; Step 107: Control the machine tool to perform thread processing on the material to be processed according to the target processing parameters.

[0032] In the embodiments of this specification, in order to simulate the machining of titanium alloy drill pipe threads using the finite element method, a parametric three-dimensional geometric model of the titanium alloy drill pipe and the machining tool is first constructed. Taking the machining of a certain type of titanium alloy drill pipe thread in a practical application as an example, based on the accuracy requirements of the geometric model in finite element analysis, a high-precision three-dimensional geometric model including the drill pipe body, thread structure, and carbide tool needs to be constructed according to the thread design parameters. Multi-dimensional automatic calibration is then used to ensure that the model matches the simulation requirements. The system can automatically calculate related parameters such as the tool starting position based on the input core thread parameters, without manual intervention.

[0033] This specification supports two generation modes for assemblies: First, a parametric generation mode, which includes not only core parameters such as the thread taper ratio, pitch, and small end diameter, but also key geometric parameters of the cutting tool, including the rake angle, clearance angle, axial starting position, and radial starting position. These parameters are directly related to the cutting edge shape of the tool, the relative position of the cutting start point and the threaded workpiece, and automatically calculate the interference of the cutting trajectory between the tool and the workpiece, ensuring that the tool feed path conforms to the geometric constraints of thread machining and avoiding overcutting or undercutting. Second, a model import mode, compatible with mainstream 2D ​​and 3D file formats. After import, it automatically completes datum coaxiality verification, unit consistency matching, and detects potential geometric interference problems in the model.

[0034] Then, a partitioned thermo-mechanical coupling model reflecting the temperature field changes of the material under processing is constructed based on the latent heat of phase transformation. During cutting, the titanium alloy generates heat due to plastic deformation in the shear zone and contact friction in the friction zone. The phase transformation is accompanied by changes in latent heat, which need to be accurately described by equations. The heat conduction control model (including latent heat correction for phase transformation), based on energy conservation and considering the influence of thermophysical properties and phase transformation, has the following formula for the partitioned thermo-mechanical coupling model in the embodiments of this specification: ; in, This is the change in thermodynamic energy, reflecting the cumulative thermodynamic energy per unit volume over time, and embodying the transient characteristics of temperature. ρ represents density. For specific heat capacity, Let t represent temperature and t represent time. This is a thermal conductivity term, describing the spatial diffusion of heat due to a temperature gradient. The thermal conductivity K is adapted to the temperature dependence of titanium alloys. Here, K is the divergence operator used to describe the flux source intensity of a vector field, and K is the thermal conductivity. The heat generation rate of plastic deformation in the shear zone is given by the following parameters: During cutting, the titanium alloy undergoes intense plastic slip in the shear zone, converting mechanical energy into heat energy. The heat generation rate of plastic deformation in the shear zone is determined by the shear stress τ and the shear velocity V. s and the shear zone area A s Decision, that is ; The contact friction heat generation rate in the friction zone is determined by the friction coefficient μ and the friction force F. Frictional heat is generated by the relative sliding between the tool rake face and the chip. p and sliding speed V p Decision, that is ; This is a latent heat correction term. When the cutting temperature of the titanium alloy reaches the phase transformation range, the material undergoes a phase transformation and absorbs and releases latent heat. p Let f be the latent heat of phase change and f be the volume fraction of phase change. The hyperbolic tangent function is used to accurately describe its continuous change with temperature. , The median temperature of the phase transition. This is the parameter for the width of the phase transition temperature range.

[0035] The finite element method is used to spatially discretize the governing equations, and an explicit time integration algorithm is combined to handle the time term, enabling transient solutions of the temperature field and capturing rapid temperature changes during cutting. Temperatures at key locations are collected through cutting experiments, and the simulation results are compared to adjust the temperature dependence of parameters such as thermal conductivity and friction coefficient, ensuring model accuracy and providing reliable temperature field data for subsequent multi-field coupling analysis.

[0036] Titanium alloys operate under high strain rate and wide temperature range conditions during thread cutting. The traditional Johnson-Cook plasticity model is difficult to accurately adapt to their strain hardening, strain rate strengthening and temperature softening behavior. Therefore, the embodiments in this specification improve the plasticity model to provide a reliable constitutive basis for cutting force field analysis.

[0037] Specifically, the formula for constructing a plastic model that corrects the plastic mechanical response of the material to be processed based on the strain correction coefficient is as follows: ; Where σ is stress, This is a fundamental hardening term describing the work hardening characteristics of a material as a function of plastic strain ε under room temperature and quasi-static conditions. A represents the yield stress, B the hardening modulus, and n the hardening exponent. To quantify the high strain rate during actual processing The strain rate correction term for the strengthening effect of flow stress, where C is the strain rate sensitivity coefficient. For reference strain rate, T is the normalized temperature, and T is the instantaneous temperature during the processing. room At room temperature, T m Here, is the melting temperature of the material to be processed (i.e., titanium alloy), m is the thermal softening index, and λ is the strain correction factor. 's' represents the strain rate strengthening correction parameter adapted to the high strain rate sensitivity of titanium alloys. Its function is to accurately quantify the additional strengthening effect of flow stress in titanium alloys under high strain rate conditions, compensating for the shortcomings of the traditional Johnson-Cook equation in describing the high strain rate characteristics of titanium alloys. In the modified plastic model... Defined as a secondary hardening term, it adapts to the nonlinear hardening trend that occurs in titanium alloys after plastic strain ε > 0.5. After introducing the high strain correction factor λ, the flow stress is increased by 7% to 10% compared with the traditional equation, and the agreement with experimental data is improved from 65% to 92%.

[0038] Multi-condition mechanical data were collected through high strain rate experiments, high temperature tensile experiments, and quasi-static tensile experiments, and the parameters of the calibration equation were fitted using the least squares method.

[0039] During the cutting process, the damage to titanium alloys, from its initiation to its development and ultimately to its critical state, is closely coupled with physical fields such as strain and temperature. The embodiments in this specification construct a dynamic damage evolution model to describe the gradual accumulation of damage in real time, providing a basis for predicting machining quality and optimizing the process. Specifically, the time evolution of the damage variable SDEG (e.g., taking values ​​from 0 to 1, where 0 represents no damage and 1 represents complete material fracture) follows the following model: ; in, As a strain-driven term, plastic strain ε is the direct cause of damage initiation. f The fracture strain is temperature-dependent. As a temperature-accelerated term, the instantaneous temperature T during processing accelerates damage development. m The melting temperature of the titanium alloy is T / T. m The larger the value, the higher the damage rate. The square root relationship is suitable for the characteristics of titanium alloys that promote damage at high temperatures but have a toughness limit, avoiding overestimation of the temperature damage effect. t is time.

[0040] Model adaptability and verification, coupled strain and temperature field, reproduced the thermo-mechanical synergistic damage law, and the damage distribution showed a good agreement with the experiment (>85%), with an error of less than 10% in the root damage depth, providing a basis for damage prediction for process optimization.

[0041] According to one embodiment of this specification, the taper-multiphysics linkage motion control model achieves high-precision control of the thread taper and pitch by adjusting the angular velocity through stress feedback, correcting the feed rate through temperature compensation, and controlling the radial velocity through multi-parameter coupling. This includes: A dynamic correction model for spindle angular velocity is presented. Spindle angular velocity is a core parameter affecting cutting stress distribution. In high-strain-rate cutting of titanium alloys, a fixed angular velocity can easily lead to tool breakage (stress exceeding the allowable tool strength) or chatter (periodic stress fluctuations) due to localized stress concentration. This specification's embodiments establish a dynamic feedback adjustment mechanism based on real-time calculations of the equivalent stress in the cutting zone using finite element analysis simulation. The formula for the dynamic correction model of spindle angular velocity is: ; Where ω is the principal axis angular velocity, V c The cutting speed is one of the thread machining parameters. Where σ is the diameter of the small end of the thread, ζ is the stress correction factor, and σ is the small end diameter of the thread. e ζ represents the equivalent stress during the cutting process, and σ0 represents the yield strength of the material to be processed. Dynamic adjustment based on equivalent stress feedback is achieved through the nonlinearly increasing value of ζ, avoiding tool chipping or chatter caused by stress concentration.

[0042] The stress correction factor ζ satisfies a nonlinear functional relationship. , where σ eq Equivalent plastic strain is a core scalar parameter describing the cumulative plastic deformation of titanium alloys during cutting, and is also a key input for multi-field coupling analysis, constitutive model calculation, and damage evolution prediction; for example, when At this time, the upper limit of ζ is set to 0.01 to avoid cutting instability caused by excessive adjustment of the spindle angular velocity.

[0043] The axial feed rate linkage model directly determines the thread pitch. Traditional fixed feed rates in titanium alloy cutting are prone to pitch deviations due to the following issues: the feed rate does not change synchronously when the spindle angular velocity is adjusted, causing a fundamental pitch deviation; the thermal expansion coefficient of titanium alloy leads to workpiece thermal expansion due to increased temperature in the cutting zone, resulting in pitch contraction upon cooling. This specification's embodiment ensures pitch accuracy through a dual mechanism of spindle speed linkage and temperature compensation. The formula for the axial feed rate linkage model is: ; Among them, V zWhere is the axial feed rate, P is the thread pitch, and n is the spindle speed (unit: r / min). The conversion relationship between spindle speed n and angular velocity is n = 30ω / π. When ω is adjusted due to stress feedback, n changes synchronously and drives V. z Automatic adaptation ensures that the deviation between the actual machined pitch and the designed pitch is <0.01mm; at the same time, a pitch compensation coefficient k is introduced. p k is the pitch compensation coefficient. p = 1 + 0.00001×(T 切削 - 20), T 切削 To determine the temperature in the cutting zone, a slight increase in V is made. z It compensates for pitch shrinkage caused by thermal expansion of titanium alloy materials, further improves pitch machining accuracy, and avoids the impact of temperature fluctuations on thread fit performance.

[0044] A multi-parameter coupled model for radial feed rate is presented. Radial feed rate directly determines thread taper. In titanium alloy cutting, taper deviation mainly stems from multi-physics coupling issues, including uneven material flow due to high strain rate, localized cutting deviations caused by damage accumulation, and excessive radial cutting due to high-temperature softening. This specification's embodiments integrate four key parameters—taper ratio, cutting strain rate, damage variable, and temperature—to establish a multi-dimensional coupled control formula, achieving dynamic taper optimization. The formula for the multi-parameter coupled model of radial feed rate is: ; Among them, V r Where α is the radial feed rate, and α is the thread taper half-angle. Here, k is the cutting strain rate, k is the strain rate coefficient, and k is the strain rate correction term. Increasing V at high strain rates r To compensate for material flow, K t K is the temperature correction factor. t =1 + 0.00001×(T 切削 – T0), to avoid tapering deviation caused by material softening in high-temperature areas, and to achieve tapering accuracy optimization under multi-physics field collaborative control. T0 is the initial ambient temperature for titanium alloy thread machining.

[0045] Then, based on the partitioned thermo-coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, as well as the three-dimensional geometric models of the material to be processed and the cutting tool, the thread processing of the material to be processed can be simulated using multiple candidate thread processing parameters through finite element analysis. The solver configuration adopts automatic time step control, with steady-state simulation (steady cutting stage) iterating 2000-5000 times and unsteady-state simulation (initial / final cutting) iterating 5000-8000 times; the boundary conditions are set as workpiece rotation and cutting tool performing axial and radial coupled motion.

[0046] During the simulation, the thread processing index corresponding to each of the candidate thread processing parameters is determined. The thread processing index includes one or more combinations of thread root damage variables, maximum temperature in the cutting zone, cutting force fluctuation coefficient, and processing time.

[0047] Then, the candidate thread processing parameters that meet the predetermined index requirements are used as the target processing parameters.

[0048] Finally, the machine tool is controlled to perform thread machining on the material to be processed according to the target machining parameters.

[0049] In some other embodiments of this specification, adaptive mesh simulation of the finite element analysis method is the core element for achieving a balance between accuracy and efficiency. Its core logic is to adjust the mesh density based on the dynamically changing physical field (temperature gradient) during the cutting process and match it with the corresponding time step. This ensures computational accuracy in high-gradient regions (such as the cutting edge and thread root) while reducing redundant computation in low-gradient regions (such as the workpiece interior). Specifically, the embodiments of this specification propose an adaptive mesh refinement algorithm to dynamically optimize mesh density. Based on a temperature gradient-driven + event-triggered mechanism, it dynamically adjusts the element size, reducing computational load while maintaining accuracy in critical areas.

[0050] Specifically, Figure 2 The diagram shown illustrates the process of dynamically optimizing mesh density using an adaptive mesh refinement algorithm in an embodiment of this specification. Based on the partitioned thermo-coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, as well as the three-dimensional geometric models of the material to be processed and the cutting tool, the method further includes the following steps during the simulation of thread processing of the material to be processed using multiple candidate thread processing parameters through finite element analysis: Step 201: Monitor the three-dimensional temperature field of the material to be processed during the processing simulation; Step 202: Calculate the temperature gradient based on the three-dimensional temperature field; Step 203: Adjust the mesh size in the simulation parameters of the finite element analysis method according to the temperature gradient.

[0051] In the embodiments described in this specification, the global three-dimensional temperature field distribution is extracted in real time through a thermo-coupling solution module, and the temperature gradient is obtained based on spatial derivative calculation. Its mathematical expression is as follows: ; Where G represents the temperature gradient. The three-dimensional temperature field of the material to be processed is shown in the figure. The three-dimensional spatial partial derivatives reflect the three-dimensional temperature field of the material to be processed. The rate of change in different coordinate system directions (x, y, z) together constitutes the magnitude of the temperature gradient, which intuitively reflects the degree of drastic change in the temperature field.

[0052] Therefore, the mesh size in the simulation parameters of the finite element analysis method is adjusted according to the temperature gradient.

[0053] Specifically, the embodiments of this specification propose event triggering methods, including temperature gradient abrupt change triggering or high damage risk zone triggering.

[0054] Figure 3 The diagram shown illustrates the process of adjusting the mesh size in the simulation parameters of the finite element analysis method based on a sudden temperature gradient change in an embodiment of this specification. The adjustment of the mesh size in the simulation parameters of the finite element analysis method according to the temperature gradient further includes: Step 301: Determine the first region where the change in the temperature gradient exceeds a first threshold within a single simulation time step, and designate it as the first target region; Step 302: Reduce the mesh size corresponding to the first target region.

[0055] like Figure 4 The diagram shows a flowchart illustrating the process of adjusting the mesh size in the simulation parameters of the finite element analysis method triggered by a high-damage-risk zone in an embodiment of this specification. Based on the partitioned thermo-coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, as well as the three-dimensional geometric models of the material to be processed and the cutting tool, the method further includes the following steps during the simulation of thread processing of the material to be processed using multiple candidate thread processing parameters through finite element analysis: Step 401: Monitor the damage variables of multiple third regions of the material to be processed during the processing simulation; Step 402: Determine whether there are any damage variables that exceed the second threshold; Step 403: If so, the third region corresponding to the damage variable that exceeds the second threshold is taken as the second target region, and the mesh size corresponding to the second target region is reduced.

[0056] In the embodiments of this specification, either the first threshold or the second threshold can be an experimental value or an empirical value. The first region where the change in temperature gradient exceeds the first threshold within a single simulation time step is designated as the first target region, or the third region corresponding to the damage variable exceeding the second threshold is designated as the second target region. This triggers "emergency mesh refinement," which reduces the mesh size corresponding to the first or second target region. For example, the cell size of this region can be temporarily reduced by 50%, and the next mesh adjustment cycle can be shortened to 50 time steps to ensure the calculation accuracy of high-risk regions.

[0057] Furthermore, the embodiments in this specification also propose a periodic triggering mechanism. For example, after completing 100 time steps of calculation, the system automatically extracts the current global temperature field, recalculates the temperature gradient G, and adjusts the mesh size. 100 time steps are chosen as the period because the temperature field changes continuously during titanium alloy cutting; 100 time steps (approximately...) Within this range, the temperature gradient variation is ≤5%, and the grid will not become disconnected from the physical field due to excessively long periods.

[0058] According to one embodiment of this specification, to further improve the performance, the gradient levels of different regions of the titanium alloy material can be pre-defined according to numerical ranges, with the gradient level inversely proportional to the reference mesh size. For example, the tool-workpiece cutting contact area can be designated as a high gradient region, where the reference mesh size is smaller and the mesh is denser, ensuring that details such as temperature abrupt changes and local high-temperature points in the cutting area are accurately captured; the thread profile surface and near-surface area can be designated as a medium gradient region, where the reference mesh size is moderate, balancing accuracy requirements and computational efficiency; and the non-machined areas inside the workpiece can be designated as low gradient regions, where the reference mesh size is larger and the mesh is sparser, thereby reducing the computational load in non-critical areas.

[0059] Therefore, in this embodiment of the specification, after a predetermined simulation time step, the reference mesh size of the second region of the material to be processed at multiple different gradient levels is adjusted according to the temperature gradient corresponding to the predetermined simulation time step.

[0060] According to one embodiment of this specification, in order to avoid computational stability problems caused by abrupt changes in mesh size, the system sets mesh transition constraints, and the ratio of element size in adjacent regions needs to be controlled within a reasonable range. By adding a transition layer mesh, the size is smoothly connected, ensuring that the geometric quality of all elements (such as element twist rate and aspect ratio) meets the convergence requirements of explicit dynamic solution, and avoiding numerical divergence caused by mesh distortion.

[0061] During mesh adjustment, the system automatically performs a "cell reconstruction-data mapping" operation. First, cells in the original mesh whose dimensions do not meet the current temperature gradient requirements are deleted, and then a new mesh is generated based on the new dimensions. At the same time, the temperature, stress, strain, and other data of the original mesh are mapped to the new mesh through an interpolation algorithm to ensure that the data continuity mapping error is controlled within a specified range. Specifically, the "weighted least squares method" is used, where the physical quantities of the new cell nodes are calculated from the physical quantities of the surrounding original cell nodes according to distance weights (the closer the distance, the greater the weight), avoiding data loss or abrupt changes.

[0062] The methods described in this specification have at least the following beneficial effects: The embodiments in this specification employ advanced finite element analysis simulation technology, which can effectively improve the quality and reliability of thread processing. Through precise thermo-damage coupling analysis, it can more realistically reflect the mechanical response and damage changes of titanium alloys during processing, reducing defects such as thread taper deviation and root cracks caused by simulation bias. This allows the sealing performance and load-bearing capacity of drill pipe threads to better meet the requirements of harsh working conditions such as deep wells and ultra-deep wells, reducing the risk of safety accidents such as downhole leakage and fracture, and fundamentally ensuring the stable operation of drill pipes during oil extraction.

[0063] Through systematic and rigorous analysis, the embodiments in this specification effectively optimize the processing flow and reduce production costs. The previous method, relying on multiple trial cuts to adjust parameters, was not only time-consuming but also resulted in significant waste of titanium alloy materials and cutting tools. In contrast, the embodiments in this specification, through dynamic motion control and parameter optimization, can significantly reduce the number of trial cuts while improving processing efficiency. This leads to shorter production cycles and lower costs for titanium alloy drill pipes, better meeting the oil industry's demands for equipment manufacturing efficiency and cost control, and providing an efficient means to optimize the thread processing parameters of titanium alloy drill pipes.

[0064] In terms of application prospects in the petroleum industry, the embodiments in this specification are not only applicable to the thread processing of current mainstream titanium alloy drill pipes, but also, as oil extraction extends to more complex formations, provide technical support for the research and development and processing of new lightweight alloy drill pipes. It helps companies break free from reliance on "experience-based trial cutting," achieving digitalization and scientific processing of drill pipes through precise simulation, thereby assisting petroleum equipment manufacturing companies in enhancing their core competitiveness. It has significant practical application value and broad application prospects.

[0065] Based on the same inventive concept, embodiments of this specification also provide a titanium alloy drill pipe thread processing device, such as... Figure 5 The diagram shown is a structural schematic of a titanium alloy drill pipe thread processing device according to an embodiment of this specification, including: Partitioned thermo-coupling model construction unit 501 is used to construct a partitioned thermo-coupling model that reflects the temperature field change of the material to be processed during the processing based on the latent heat of phase change of the material to be processed. The plastic model construction unit 502 is used to construct a plastic model that corrects the plastic mechanical response of the material to be processed based on the strain correction coefficient corresponding to the material to be processed. The damage evolution model construction unit 503 is used to construct a damage evolution model that reflects the damage of the material to be processed based on the plastic mechanical response of the material to be processed. The motion control model construction unit 504 is used to construct a taper-multiphysics linkage motion control model, which is used to control the movement of the tool in the machine tool according to the thread machining parameters. The machining simulation unit 505 is used to simulate the threading of the material to be machined by using multiple candidate threading parameters through finite element analysis based on the partitioned thermo-coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, the three-dimensional geometric model of the material to be machined and the cutting tool, and to determine the threading index corresponding to each of the candidate threading parameters. The target machining parameter determination unit 506 is used to take the candidate thread machining parameters that meet the predetermined index requirements as the target machining parameters. The machining control unit 507 is used to control the machine tool to perform thread machining on the material to be processed according to the target machining parameters.

[0066] The beneficial effects obtained by the above-described device are the same as those obtained by the above-described method, and will not be described in detail in the embodiments of this specification.

[0067] like Figure 6 The diagram shown is a structural schematic of a computer device according to an embodiment of this specification. The methods described in this specification can be applied to the computer device of this embodiment.

[0068] Computer device 602 may include one or more processors 604, such as one or more central processing units (CPUs), each of which may implement one or more hardware threads. Computer device 602 may also include any memory 606 for storing information of any kind, such as code, settings, data, etc. Non-limitingly, for example, memory 606 may include any type of RAM, any type of ROM, flash memory, hard disk, optical disk, etc. More generally, any storage resource can be used to store information using any technology.

[0069] Furthermore, any storage resource can provide volatile or non-volatile retention of information.

[0070] Furthermore, any storage resource can represent a fixed or removable component of the computer device 602. In one case, when the processor 604 executes associated instructions stored in any storage resource or combination of storage resources, the computer device 602 can perform any operation of the associated instructions. The computer device 602 also includes one or more drive mechanisms 608 for interacting with any storage resource, such as a hard disk drive system, an optical disk drive system, etc.

[0071] Computer device 602 may also include an input / output module 610 (I / O) for receiving various inputs (via input device 612) and providing various outputs (via output device 614). A specific output mechanism may include a presentation device 616 and an associated graphical user interface (GUI) 618. In other embodiments, the input / output module 610 (I / O), input device 612, and output device 614 may be omitted, and the device may function solely as a computer device within a network. Computer device 602 may also include one or more network interfaces 620 for exchanging data with other devices via one or more communication links 622. One or more communication buses 624 couple the components described above together.

[0072] Communication link 622 can be implemented in any way, such as via a local area network, a wide area network (e.g., the Internet), a point-to-point connection, or any combination thereof. Communication link 622 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

[0073] This specification also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0074] This specification also provides computer-readable instructions, wherein when a processor executes the instructions, the program therein causes the processor to perform the above-described method.

[0075] It should be understood that in the various embodiments of this specification, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this specification.

[0076] It should also be understood that, in the embodiments of this specification, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the embodiments of this specification, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0077] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this specification can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of the embodiments in this specification.

[0078] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0079] In the embodiments provided in this specification, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces, devices, or units, or they may be electrical, mechanical, or other forms of connection.

[0080] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments described in this specification, depending on actual needs.

[0081] Furthermore, the functional units in the various embodiments of this specification can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0082] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this specification, in essence, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this specification. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0083] This specification describes the principles and implementation methods of the embodiments using specific examples. The above descriptions of the embodiments are only for the purpose of helping to understand the methods and core ideas of the embodiments in this specification. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the embodiments in this specification. Therefore, the content of this specification should not be construed as a limitation on the embodiments in this specification.

Claims

1. A method for machining threads on titanium alloy drill rods, characterized in that, The method includes: Based on the latent heat of phase change of the material to be processed, a partitioned thermo-mechanical coupling model is constructed to reflect the temperature field changes of the material during processing. A plastic model is constructed to correct the plastic mechanical response of the material to be processed based on the strain correction coefficients corresponding to the material to be processed. A damage evolution model reflecting damage to the material to be processed is constructed based on the plastic mechanical response of the material to be processed. A taper-multiphysics linkage motion control model is constructed, which is used to control the movement of the cutting tool in the machine tool according to the thread machining parameters; Based on the partitioned thermo-coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, as well as the three-dimensional geometric model of the material to be processed and the cutting tool, the thread processing of the material to be processed is simulated using multiple candidate thread processing parameters through finite element analysis, and the thread processing index corresponding to each candidate thread processing parameter is determined. The candidate thread processing parameters that meet the predetermined index requirements are used as the target processing parameters. The machine tool is controlled to perform thread machining on the material to be processed according to the target machining parameters; The formula for constructing a plastic model that corrects the plastic mechanical response of the material to be processed based on the strain correction coefficient is as follows: ； Where σ is stress, To describe the change in material properties with plastic strain under room temperature and quasi-static conditions. The basic hardening terms for the work hardening properties of the developed material are: A = yield stress, B = hardening modulus, and n = hardening exponent. To quantify high strain rate The strain rate correction term for the strengthening effect of flow stress, where C is the strain rate sensitivity coefficient. For reference strain rate, T is the normalized temperature, and T is the instantaneous temperature during the processing. room At room temperature, T m λ is the melting temperature of the material to be processed, m is the thermal softening index, and λ is the strain correction factor. The formula for constructing a damage evolution model that reflects damage to the material to be processed based on the plastic mechanical response of the material is as follows: ； in, As a strain-driven term, Let be the temperature-dependent fracture strain, SDEG be the damage variable, and t be the time.

2. The method according to claim 1, characterized in that, Based on the aforementioned partitioned thermo-coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, as well as the three-dimensional geometric models of the material to be processed and the cutting tool, the method further includes the following steps in simulating thread processing of the material to be processed using multiple candidate thread processing parameters through finite element analysis: During the simulated thread processing, the three-dimensional temperature field of the material to be processed is monitored. Calculate the temperature gradient based on the three-dimensional temperature field; The mesh size in the simulation parameters of the finite element analysis method is adjusted according to the temperature gradient.

3. The method according to claim 2, characterized in that, Adjusting the mesh size in the simulation parameters of the finite element analysis method based on the temperature gradient further includes: The first region in which the change of the temperature gradient exceeds a first threshold within a single simulation time step is identified as the first target region. Reduce the size of the grid corresponding to the first target region.

4. The method according to claim 2, characterized in that, Adjusting the mesh size in the simulation parameters of the finite element analysis method based on the temperature gradient further includes: After a predetermined simulation time step, the reference mesh size of the second region of the material to be processed is adjusted according to the temperature gradient corresponding to the predetermined simulation time step, wherein the gradient level of the second region is inversely proportional to the reference mesh size.

5. The method according to claim 4, characterized in that, The formula for adjusting the reference mesh size of the second region of the material to be processed at multiple different gradient levels according to the temperature gradient corresponding to the predetermined simulation time step is as follows: ； Where h represents the adjusted grid size, and h0 represents the baseline grid size. denoted by , where G represents the temperature gradient.

6. The method according to claim 1, characterized in that, Based on the aforementioned partitioned thermo-coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, as well as the three-dimensional geometric models of the material to be processed and the cutting tool, the method further includes the following steps in simulating thread processing of the material to be processed using multiple candidate thread processing parameters through finite element analysis: During the thread processing simulation, damage variables in multiple third regions of the material to be processed are monitored. Determine whether there are any damage variables that exceed the second threshold; If so, the third region corresponding to the damage variable exceeding the second threshold is taken as the second target region, and the mesh size corresponding to the second target region is reduced.

7. The method according to claim 1, characterized in that, The formula for the partitioned thermo-mechanical coupling model of the temperature field change of the material under processing, based on the latent heat of phase change of the material, is as follows: ； in, The change in thermodynamic energy is the term, where ρ is density. For specific heat capacity, Let t represent temperature and t represent time. For heat conduction, Here, K is the divergence operator, used to describe the flux source intensity of a vector field, and K is the thermal conductivity. The heat generation rate of plastic deformation in the shear zone, The contact friction heat generation rate in the friction zone. This is a latent heat correction term for phase transition. Let f be the latent heat of phase transition, and f be the volume fraction of phase transition.

8. The method according to claim 1, characterized in that, The formula for constructing the cone-multiphysics linkage motion control model is as follows: Dynamic correction model for spindle angular velocity: Where ω is the principal axis angular velocity, and V c The cutting speed is one of the thread machining parameters. Where ζ is the diameter of the small end of the thread, and ζ is the stress correction factor. This refers to the equivalent stress during the cutting process. The yield strength of the material to be processed; Axial feed rate linkage model: , where V z y is the axial feed rate, P is the thread pitch, n is the spindle speed, and k is the thread pitch. p This is the pitch compensation coefficient; Multi-parameter coupled model of radial feed rate: , where V r Where α is the radial feed rate, and α is the thread taper half-angle. K is the cutting strain rate, k is the strain rate coefficient, and K t This is the temperature correction factor.

9. The method according to claim 1, characterized in that, The thread processing parameters include one or more combinations of thread root damage variables, maximum temperature in the cutting zone, cutting force fluctuation coefficient, and processing time.

10. A device for machining threads on titanium alloy drill rods, characterized in that, The device includes: A partitioned thermo-coupling model construction unit is used to construct a partitioned thermo-coupling model that reflects the temperature field changes of the material to be processed during the processing based on the latent heat of phase change of the material to be processed. A plastic model construction unit is used to construct a plastic model that corrects the plastic mechanical response of the material to be processed based on the strain correction coefficient corresponding to the material to be processed. The damage evolution model construction unit is used to construct a damage evolution model that reflects the damage of the material to be processed based on the plastic mechanical response of the material to be processed. A motion control model construction unit is used to construct a taper-multiphysics linkage motion control model, which is used to control the movement of the cutting tool in the machine tool according to the thread machining parameters. The machining simulation unit is used to simulate the threading of the material to be machined by using multiple candidate threading parameters through finite element analysis based on the partitioned thermo-mechanical coupling model, plasticity model, damage evolution model, and taper-multiphysics linkage motion control model, the three-dimensional geometric model of the material to be machined and the cutting tool, and to determine the threading index corresponding to each of the candidate threading parameters. The target machining parameter determination unit is used to take the candidate thread machining parameters that meet the predetermined index requirements as the target machining parameters. A machining control unit is used to control a machine tool to perform thread machining on the material to be processed according to the target machining parameters. The formula for constructing a plastic model that corrects the plastic mechanical response of the material to be processed based on the strain correction coefficient is as follows: ； Where σ is stress, To describe the change in material properties with plastic strain under room temperature and quasi-static conditions. The basic hardening terms for the work hardening properties of the developed material are: A = yield stress, B = hardening modulus, and n = hardening exponent. To quantify high strain rate The strain rate correction term for the strengthening effect of flow stress, where C is the strain rate sensitivity coefficient. For reference strain rate, T is the normalized temperature, and T is the instantaneous temperature during the processing. room At room temperature, T m λ is the melting temperature of the material to be processed, m is the thermal softening index, and λ is the strain correction factor. The formula for constructing a damage evolution model that reflects damage to the material to be processed based on the plastic mechanical response of the material is as follows: ； in, As a strain-driven term, Let be the temperature-dependent fracture strain, SDEG be the damage variable, and t be the time.

11. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 9.

13. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 9.

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