A cold forging step extrusion drawing method for motor shaft preparation

Abstract

The application relates to the technical field of motor shaft machining, in particular to a cold forging step-by-step extrusion and stretching method for motor shaft preparation, which comprises the following steps: obtaining approximate average force of forward extrusion, quantifying initial deformation resistance of a workpiece based on the approximate average force of forward extrusion, obtaining target parameter increment of reverse extrusion and target average inner diameter of a hollow part of reverse extrusion to determine a target volume deformation amount, determining a process difficulty evaluation index based on the initial deformation resistance and the target volume deformation amount; obtaining adjustment intensity of a set value of stamping force, determining the correlation between the process difficulty evaluation index and subsequent process adjustment intensity based on the adjustment intensity of the current batch of workpieces and the process difficulty evaluation index; and adjusting the difficulty threshold value for determining the difficulty state of workpiece machining based on the process difficulty evaluation index in response to the correlation. Through the initial resistance of the material and the annealing softening effect, the stamping force and speed of the subsequent process are adaptively adjusted.

Description

Technical Field

[0001] This invention relates to the field of motor shaft processing technology, and in particular to a cold forging step-by-step extrusion and stretching method for preparing motor shafts. Background Technology

[0002] As a core transmission component in a motor system, the performance of the motor shaft directly affects the motor's efficiency, reliability, and lifespan. With the rapid development of new energy vehicles and high-end industrial servo systems, there are increasing demands on motor shafts for higher strength, lighter weight, better fatigue performance, and more economical manufacturing costs. Traditional motor shaft manufacturing processes mainly rely on full-cutting machining or "forging + mass cutting," which have inherent drawbacks such as low material utilization (typically less than 60%), interrupted metal flow lines, suboptimal product mechanical properties, slow production cycle time, and high costs.

[0003] To overcome the aforementioned drawbacks, near-net-shape forming technology, especially cold forging (cold plastic forming) technology, has become the preferred direction for manufacturing high-performance motor shafts. The cold forging process directly obtains a workpiece close to its final shape through the plastic deformation of metal at room temperature, and has significant advantages such as high material utilization (up to 90% or more), continuous fiber structure, high product strength, and good dimensional accuracy.

[0004] Currently, publicly available cold forging processes for manufacturing motor shafts include multi-step forming methods (such as upsetting, forward extrusion, and reverse extrusion). For example, a typical process route is: blanking → pre-forming → forward extrusion forming of the shaft shoulder → subsequent machining. However, when dealing with lightweight motor shafts with more complex structures and deep-hole hollow structures, this type of process suffers from insufficient deep-hole forming capability, inaccurate control of wall thickness and diameter, and significant influence on process stability from intermediate states.

[0005] Chinese Patent Application Publication No. CN117583455A discloses a stretching device and method for a hollow motor shaft. The blank is mounted on a positioning frame via a positioning clamp, and the height of the fixed plate is adjusted by a lifting cylinder to align the axial height of the blank with the extrusion rollers, facilitating accurate stretching. A hydraulic cylinder controls the movement of the fixed seat at the top of the mounting base, and a locking screw locks the locking plate onto the guide seat, ensuring the stability of the fixed seat. Simultaneously, a drive motor drives an adjusting disc, which in turn moves a connecting frame via a positioning rod. This causes a moving plate, in conjunction with a bottom moving block, to reciprocate on the guide rail surface, stretching the end of the blank mounted on the positioning clamp onto the extrusion rollers to form the blank into the required size, facilitating subsequent cutting to the appropriate length. However, the aforementioned stretching device and method for a hollow motor shaft have the following problems:

[0006] It is impossible to adaptively adjust the stamping pressure and speed of the cold forging distribution extrusion and stretching process based on the initial resistance of the material and the softening effect of annealing. Summary of the Invention

[0007] Therefore, the present invention provides a cold forging step-by-step extrusion and stretching method for manufacturing motor shafts, which overcomes the problem in the prior art that the stamping pressure and speed of the cold forging step-by-step extrusion and stretching process cannot be adaptively adjusted according to the initial resistance of the material and the softening effect of annealing.

[0008] To achieve the above objectives, the present invention provides a cold forging step-by-step extrusion and stretching method for manufacturing motor shafts, comprising:

[0009] The real-time punching force signal and real-time displacement signal of the punch in the forward extrusion process are obtained. The peak force of forward extrusion is obtained based on the real-time punching force signal and the stable stroke of forward extrusion is obtained based on the real-time displacement signal, so as to determine the approximate average force of forward extrusion.

[0010] Based on the initial deformation resistance of the workpiece with the approximate average force of the forward extrusion, the target parameter increment of the reverse extrusion process and the average inner diameter of the target hollow part of the reverse extrusion are obtained to determine the target volume deformation. Based on the initial deformation resistance and the target volume deformation, the process difficulty evaluation index is determined.

[0011] Based on the process difficulty evaluation index, the difficulty state of the workpiece processing is determined, and in response to the difficulty state, the stamping pressure setting value is adjusted according to the process difficulty evaluation index, or the stamping pressure setting value and the stamping speed setting value are adjusted, or the stamping pressure setting value of the reverse stretching process is adjusted according to the annealing state of the reverse extrusion process.

[0012] The initial resistance gradient at the initial stage of reverse stretching is obtained and combined with the initial deformation resistance to determine the relative softening coefficient. The annealing state of the workpiece is then determined based on the relative softening coefficient.

[0013] In response to the real-time deviation of the workpiece volume deformation obtained in the annealing state, the metal flow during the reverse stretching process is determined based on the real-time deviation. Combined with the temperature rise rate of the workpiece bar shaft wall, the risk of deformation and cracking in the reverse stretching process is determined, and the set values ​​of stamping force and stamping speed are adjusted.

[0014] The adjustment intensity of the set value of the punching force is obtained, and based on several adjustment intensities and process difficulty evaluation indices of the current batch of workpieces, the correlation between the process difficulty evaluation index and the subsequent process adjustment intensity is determined.

[0015] In response to the correlation adjustment, a difficulty threshold is determined based on the process difficulty evaluation index to indicate the difficulty state of the workpiece processing.

[0016] Furthermore, the process of determining the difficulty state of workpiece processing based on the aforementioned process difficulty evaluation index includes:

[0017] When the process difficulty evaluation index is less than or equal to the first difficulty threshold, the workpiece processing is judged to be in the first difficulty state, and the punching force setting value is reduced according to the process difficulty evaluation index.

[0018] When the process difficulty evaluation index is greater than the first difficulty threshold and less than the second difficulty threshold, the workpiece processing is judged to be in the second difficulty state, and the punching force setting value of the reverse stretching process is adjusted according to the annealing state of the reverse extrusion process.

[0019] When the process difficulty evaluation index is greater than or equal to the second difficulty threshold, the workpiece processing is judged to be in the third difficulty state. Based on the process difficulty evaluation index, the stamping force setting value is increased and the stamping speed setting value is decreased.

[0020] Furthermore, the process of adjusting the punching force setting value according to the process difficulty evaluation index includes:

[0021] When the process difficulty evaluation index is greater than the preset evaluation index, the upper limit of the pressure setting value of the back extrusion process is increased proportionally.

[0022] When the process difficulty evaluation index is less than the preset evaluation index, the pressure upper limit of the back extrusion process punching pressure setting value is reduced proportionally.

[0023] Furthermore, the process of determining the workpiece annealing state based on the relative softening coefficient includes:

[0024] When the relative softening coefficient is less than the first softening coefficient, the workpiece is judged to be over-annealed;

[0025] When the relative softening coefficient is greater than or equal to the first softening coefficient and less than or equal to the second softening coefficient, the annealing effect is determined to be within the expected window.

[0026] If the relative softening coefficient is greater than the second softening coefficient, the workpiece is judged to be under-annealed.

[0027] When the workpiece is over-annealed or under-annealed, determine whether there is a risk of deformation and cracking in the reverse stretching process.

[0028] Furthermore, the process of determining whether there is a risk of deformation and tearing in the reverse stretching process includes:

[0029] The real-time deviation of the workpiece volume deformation is determined. If the real-time deviation continues to exceed the deviation threshold within a continuous sampling period, it is determined that the metal flow is uneven during the reverse stretching process.

[0030] Furthermore, local temperature rise risk monitoring is conducted for the tension of the workpiece bar's shaft wall;

[0031] During the reverse stretching process of the workpiece, the temperature data of the infrared temperature measurement point on the shaft wall of the workpiece bar is acquired in real time, and the temperature rise rate is calculated based on the temperature data.

[0032] If the temperature rise rate is greater than the temperature rise threshold, it is determined that the workpiece rod has abnormal local overheating of the shaft wall, and there is a risk of local deformation of the shaft wall.

[0033] Furthermore, if the metal flow is uneven and the shaft wall temperature rises abnormally during the reverse stretching process, it is determined that there is a risk of deformation and cracking in the reverse stretching process.

[0034] Furthermore, when there is a risk of deformation and cracking in the reverse stretching process and the workpiece is not sufficiently annealed, the set value of the stamping force is increased proportionally according to the relative softening coefficient.

[0035] If the real-time deviation of volume deformation exceeds the standard or the temperature rise rate exceeds the standard, the stamping speed setting value is reduced according to the ratio of real-time deviation to deviation threshold or the ratio of temperature rise rate to temperature rise threshold.

[0036] Furthermore, the adjustment intensity is determined based on the change in the set value of the impact force;

[0037] Based on the adjustment intensity and process difficulty evaluation index corresponding to several finished motor shafts prepared in the current batch of workpieces, the correlation between the process difficulty evaluation index and the subsequent process adjustment intensity is determined.

[0038] Furthermore, when the correlation is greater than or equal to the first correlation threshold, the process difficulty evaluation index is determined to be strongly correlated with the intensity of subsequent process adjustments;

[0039] When the correlation is less than the first correlation threshold but greater than the second correlation threshold, the process difficulty evaluation index is judged to have a moderate correlation with the intensity of subsequent process adjustments.

[0040] When the correlation is less than the second correlation threshold, the process difficulty evaluation index is judged to be weakly correlated with the intensity of subsequent process adjustments. The second difficulty threshold is increased and the first difficulty threshold is decreased based on the ratio of the correlation to the first correlation threshold.

[0041] Compared with existing technologies, the beneficial effects of this invention are as follows: by real-time monitoring and analysis of key signals throughout the entire process of forward extrusion, reverse extrusion, annealing, and reverse stretching, a three-level intelligent control system of "feedforward prediction - online evaluation - feedback optimization" is constructed; this method can identify the initial resistance of the material and the softening effect of annealing online, and dynamically adjust the stamping pressure and speed of subsequent processes accordingly; it not only achieves self-adaptation to material fluctuations and design changes, but also accurately warns and intervenes in the risk of tearing through the joint judgment of volume deformation deviation and local temperature rise; finally, based on production data feedback, it automatically optimizes the process difficulty evaluation model and control threshold, forming a closed loop of continuous self-learning; it improves the consistency, pass rate and production efficiency of cold forging of complex hollow motor shafts, while reducing mold wear and energy consumption.

[0042] Furthermore, the purpose of the forward extrusion process is to "make the blank" and "position", and a concave pit or a shallow step is stamped at the center of the top of the rod body, providing an accurate initial guiding position for the punch of the subsequent backward extrusion process and ensuring the centering of the hollow part.

[0043] Furthermore, the present invention realizes the early quantitative evaluation of the material state and forming difficulty by collecting the force-displacement signals of the forward extrusion process in real time, detecting and obtaining the initial deformation resistance of the current batch of workpieces, and calculating the process difficulty evaluation index in combination with the design parameters of the motor shaft and the required increase in the depth of the hollow part and the length of the rod body in the backward extrusion process; adaptively divides the processing process into three difficulty levels based on the process difficulty evaluation index, and dynamically and hierarchically adjusts the punching pressure and speed of the subsequent backward extrusion and stretching processes; not only compensates for the material batch fluctuations, but can also optimize the process according to specific design parameters such as the aspect ratio, significantly improving the process adaptability and robustness; while ensuring the internal quality and dimensional accuracy of the complex hollow motor shaft, the production efficiency is improved.

[0044] Furthermore, annealing is carried out after backward extrusion. Annealing enables the material to obtain a uniform spheroidal pearlite structure, significantly improving the plasticity and reducing the deformation resistance of the workpiece. At the same time, there are fluctuations in annealing; the present invention realizes the online quantitative evaluation of the degree of material plasticity improvement in the annealing process by analyzing the force-displacement curve in the initial stage of reverse stretching and calculating the relative softening coefficient; accurately divides the material state after annealing into three states of "excessive", "ideal", and "insufficient", providing a precise control basis for the subsequent stretching process. When it is detected that the material softening is abnormally excessive or insufficient, the system can link the volume deformation and temperature rise monitoring, predict and actively prevent the risk of cracking; the intelligent evaluation overcomes the problem of inconsistent quality caused by furnace temperature fluctuations and insulation differences in the traditional annealing process, significantly improving the stability, qualification rate and product uniformity of the cold forging production of hollow motor shafts.

[0045] Furthermore, in the processing process of the motor shaft, changes in wall thickness, changes in the depth of the hollow part, and changes in the length of the rod material will all affect the volume deformation amount, and the volume deformation amount is an accurate measure of the metal plastic flow amount in the backward extrusion process. The present invention realizes the precise online monitoring of the uniformity of metal plastic flow by calculating the volume deformation deviation of the workpiece in the reverse stretching process in real time and comparing it with the preset theoretical value; at the same time, combined with the real-time monitoring of the local temperature rise rate of the shaft wall, it can keenly capture the abnormal material flow and local overheating risks; when the volume deviation and temperature rise anomaly occur simultaneously, the system can intelligently determine it as a precursor of high-risk deformation cracking, and immediately link and control; when the annealing is insufficient, increase the punching pressure proportionally to ensure forming, and automatically reduce the speed when deviation or overheating is detected to prevent the defect from expanding; this collaborative monitoring and control mechanism effectively prevents the cracking and folding defects of the hollow motor shaft in the complex cold forging process, significantly improving the consistency of the internal quality of the product and the production stability.

[0046] Furthermore, ideally, the process difficulty evaluation index should be positively correlated with the intensity of subsequent process adjustments or the failure rate. This invention achieves closed-loop verification and self-optimization of the effectiveness of the process prediction model by quantitatively analyzing the statistical correlation between the process difficulty evaluation index and the intensity of subsequent stamping pressure adjustments. When the system detects a weak correlation and prediction failure, it can automatically adjust the threshold for difficulty state classification, making the graded control more consistent with the current production reality. This intelligent learning mechanism based on data feedback enables the process control system to continuously adapt to the long-term drift of material properties and equipment status, continuously improve the prediction accuracy and control matching degree of forming difficulty, and ultimately ensure the long-term stability of the production quality of complex motor shaft cold forging and the autonomous evolution of the process knowledge system. Attached Figure Description

[0047] Figure 1 This is a schematic flowchart of a cold forging step-by-step extrusion and stretching method for preparing motor shafts in an embodiment of the present invention.

[0048] Figure 2 This is a schematic diagram of the reverse extrusion stretching device in an embodiment of the present invention;

[0049] Figure 3 This is a schematic diagram of the blank in an embodiment of the present invention;

[0050] Figure 4 This is a schematic cross-sectional view of the workpiece after the forward extrusion process in an embodiment of the present invention;

[0051] Figure 5 This is a schematic cross-sectional view of the workpiece after the reverse extrusion process in an embodiment of the present invention;

[0052] Figure 6 This is a schematic cross-sectional view of the workpiece after the reverse stretching process in an embodiment of the present invention;

[0053] In the figure: 1-bar body, 2-transition part, 3-protrusion part, 4-hollow part, 11-upper pad, 12-column, 13-upper mold base, 14-upper liner, 15-slider, 16-lower punch, 17-lower punch pressure plate, 18-lower pad block, 19-lower pad block pressure ring, 20-blank. Detailed Implementation

[0054] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0055] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0056] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0057] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0058] Please see Figures 1-6 As shown, Figure 1 This is a schematic flowchart of a cold forging step-by-step extrusion and stretching method for preparing motor shafts in an embodiment of the present invention. Figure 2 This is a schematic diagram of the reverse extrusion stretching device in an embodiment of the present invention; Figure 3 This is a schematic diagram of the blank in an embodiment of the present invention; Figure 4 This is a schematic cross-sectional view of the workpiece after the forward extrusion process in an embodiment of the present invention; Figure 5 This is a schematic cross-sectional view of the workpiece after the reverse extrusion process in an embodiment of the present invention; Figure 6 This is a schematic cross-sectional view of the workpiece after the reverse stretching process in an embodiment of the present invention.

[0059] The cold forging step-by-step extrusion and stretching method for manufacturing motor shafts provided in this embodiment of the invention includes:

[0060] Step S1: Obtain the real-time punching force signal and real-time displacement signal of the punch in the forward extrusion process. Obtain the peak force of forward extrusion based on the real-time punching force signal and the stable stroke of forward extrusion based on the real-time displacement signal to determine the approximate average force of forward extrusion.

[0061] Step S2: Based on the initial deformation resistance of the workpiece with the approximate average force of the forward extrusion, obtain the target parameter increment of the reverse extrusion process and the average inner diameter of the target hollow part of the reverse extrusion to determine the target volume deformation. Based on the initial deformation resistance and the target volume deformation, determine the process difficulty evaluation index.

[0062] Step S3: Determine the difficulty state of workpiece processing based on the process difficulty evaluation index, and adjust the stamping pressure setting value or the stamping pressure setting value and the stamping speed setting value according to the process difficulty evaluation index in response to the difficulty state, or adjust the stamping pressure setting value of the reverse stretching process according to the annealing state of the reverse extrusion process.

[0063] Step S4: Obtain the initial resistance gradient of the initial stage of reverse stretching and combine it with the initial deformation resistance to determine the relative softening coefficient, and determine the annealing state of the workpiece based on the relative softening coefficient.

[0064] Step S5: In response to the workpiece annealing state, obtain the real-time deviation of the workpiece volume deformation, determine whether the metal flow is uniform during the reverse stretching process based on the real-time deviation, and determine whether there is a risk of deformation and cracking in the reverse stretching process by combining the temperature rise rate of the workpiece bar shaft wall, and adjust the set values ​​of the stamping force and stamping speed.

[0065] Step S6: Obtain the adjustment intensity of the set value of the punching force, and determine the correlation between the process difficulty evaluation index and the subsequent process adjustment intensity based on several adjustment intensities and process difficulty evaluation indices of the current batch of workpieces.

[0066] Step S7: In response to the correlation adjustment, determine the difficulty threshold of the workpiece processing difficulty state based on the process difficulty evaluation index.

[0067] Specifically, by real-time monitoring and analysis of key signals throughout the entire process of forward extrusion, reverse extrusion, annealing, and reverse stretching, a three-level intelligent control system of "feedforward prediction - online evaluation - feedback optimization" was constructed. This method can identify the initial resistance of the material and the softening effect of annealing online, and dynamically adjust the stamping pressure and speed of subsequent processes accordingly. It not only achieves self-adaptation to material fluctuations and design changes, but also accurately warns and intervenes in the risk of tearing by jointly judging volume deformation deviation and local temperature rise. Finally, based on production data feedback, the process difficulty evaluation model and control threshold are automatically optimized to form a closed loop of continuous self-learning. This improves the consistency, pass rate, and production efficiency of cold forging of complex hollow motor shafts, while reducing mold wear and energy consumption.

[0068] In this embodiment, the motor shaft includes a rod body 1, a transition portion 2, and a protrusion 3. The rod body has a hollow portion 4 inside. The diameter of the rod body is larger than the diameter of the protrusion. The transition portion is tapered and used to seamlessly connect the rod body and the protrusion. The hollow portion is located inside the rod body.

[0069] The cold forging steps for preparing the motor shaft include: bar cutting, cutting the bar into blanks 20 of a predetermined mass, and annealing the cut blanks to remove hardness;

[0070] In this embodiment, the workpiece is annealed once after bar cutting and once after reverse extrusion. The hardness of the motor shaft after stress-relief annealing of bar cutting is HB115-165, and the hardness of the motor shaft after stress-relief annealing of upsetting is HB140-200. The annealing temperature of the cut workpiece is 820℃, and the annealing temperature of the reverse extrusion workpiece is 820℃.

[0071] In the forward extrusion process, after annealing, the center of the top of the center positioning bar 1 is placed into the forward extrusion die, and the center point of the top of the forward extrusion bar is punched by the hydraulic press to form a preliminary step;

[0072] In the reverse extrusion process, the forward extrusion die is replaced with a reverse extrusion die, and the initial step is punched by reverse extrusion using a hydraulic press. The direction of metal flow is opposite to the direction of punch movement, and it flows upward along the gap between the punch and the reverse extrusion die to form a hollow part, increasing the depth of the initial step and the length of the workpiece rod. The increased depth of the initial step forms a hollow part.

[0073] After reverse stretching and extrusion, the workpiece is annealed to reduce hardness. The reverse extrusion die is replaced with a stretching die. The hollow part of the workpiece is reverse stretched and stamped by a hydraulic press. A pressure is applied from the inside to the bottom of the hollow part to punch the workpiece rod through a reverse stretching die with a smaller aperture, thereby reducing the diameter and wall thickness of the workpiece rod and increasing the length of the rod while further increasing the depth of the hollow part.

[0074] Specifically, the purpose of the forward extrusion process is to "preform" and "position" the blank by punching a recess or shallow step at the center of the top of the blank, which provides a precise initial guiding position for the punch in the subsequent reverse extrusion process and ensures the centering of the hollow part.

[0075] like Figure 2 As shown, the reverse stretching device consists of an upper die and a lower die. The upper die is a square structure composed of an upper pad 11, a column 12 and an upper die base 13. An upper liner 14 is provided at the top and sliders 15 are provided on both sides of the bottom.

[0076] The lower die is provided with a lower punch 16 passing through the upper die base. The lower punch is connected to the lower punch pressure plate 17. A lower pad hard block 18 is provided at the bottom. The lower pad hard block is connected to the lower pad hard block pressure ring 19.

[0077] Signal acquisition: Real-time punching force signal of punch in the forward extrusion process is acquired through pressure sensor of hydraulic press, and real-time displacement signal of punch in the forward extrusion process is acquired through displacement sensor.

[0078] During implementation, the sampling frequency of the real-time punching force signal is greater than or equal to 100Hz, and the real-time displacement signal is synchronized with the real-time punching force signal.

[0079] Extract the peak force and approximate average force of forward extrusion from the real-time punching force signal, and extract the stable stroke of forward extrusion from the real-time displacement signal;

[0080] Specifically, the peak force of forward extrusion is the maximum value in the real-time punching force signal, and the stable stroke of forward extrusion is the displacement change during the period when the real-time punching force rises to reach the peak force of forward extrusion.

[0081] The approximate average force of forward extrusion is calculated as (1 / stable stroke of forward extrusion) × ∫P dS, where P is the peak force of forward extrusion, S is the stable stroke of forward extrusion, and the integral interval in the formula is the displacement segment from the real-time pressing pressure to the peak force of forward extrusion.

[0082] The initial deformation resistance of the workpiece blank is quantitatively calculated, and the average contact area of ​​the forward extrusion deformation zone within the die during the forward extrusion process is calculated. The average contact area is calculated as π × (the filling diameter of the blank within the forward extrusion die cavity). 2 - Diameter of the working end of the extrusion punch 2 ) / 4;

[0083] The initial average flow stress of the material is calculated. The initial average flow stress = approximate average force of forward extrusion / average contact area. The initial average flow stress comprehensively reflects the yield strength, work hardening rate and friction conditions of the material in the initial cold state, and is directly defined as the initial deformation resistance index.

[0084] Obtain the design parameters of the motor shaft, determine the increment of the target rod length after reverse extrusion, the increment of the target hollow depth after reverse extrusion, and the average inner diameter of the target hollow after reverse extrusion. The average inner diameter of the target hollow after reverse extrusion is determined based on the diameter of the reverse extrusion punch.

[0085] Calculate the target volume deformation, where the target volume deformation = π × the average inner diameter of the hollow part of the reverse-extrusion target. 2 / 4×Increment of target hollow depth after reverse extrusion +π×Filling diameter of billet in forward extrusion die cavity 2 / 4×Increment of target rod length after reverse extrusion;

[0086] Specifically, the first term of the formula for calculating the target volumetric deformation amount represents the metal outflow volume required to form the hollow part through the reverse extrusion material, and the second term represents the metal axial extension volume corresponding to the overall growth of the rod body. The target volumetric deformation amount is used to quantify the total plastic deformation amount that needs to be completed in the reverse extrusion process.

[0087] Calculate the process difficulty evaluation index, which is used to quantify the process difficulty of "driving the current deformation resistance material to complete the predetermined deformation amount";

[0088] The process difficulty evaluation index = first weighting coefficient × (initial deformation resistance / material reference resistance) m × (Target volume deformation / Volume deformation baseline) n +Second weighting coefficient ×|Increase in target rod length after reverse extrusion / Increment in target hollow depth after reverse extrusion - Ideal length-diameter deformation ratio|;

[0089] In the formula, the increase in the length of the target rod after reverse extrusion / the increase in the depth of the hollow part of the target after reverse extrusion is the length-to-diameter deformation ratio, and only the ratio value is taken as a dimensionless parameter.

[0090] The sum of the first weighting coefficient and the second weighting coefficient is one. Optionally, the first weighting coefficient ranges from 0.7 to 0.9, and the second weighting coefficient ranges from 0.1 to 0.3.

[0091] Preferably, the first weighting coefficient is 0.8 in a preferred embodiment, and the second weighting coefficient is 0.2 in a preferred embodiment.

[0092] Specifically, the core function of the weighting coefficients is to quantify the "proportion of importance" of two different types of technological difficulties in the overall evaluation. The range of values ​​for the first and second weighting coefficients is set based on general engineering experience in metal plastic forming, especially cold forging. The necessary condition for metal plastic forming depends primarily on whether the equipment has sufficient force (determined by material resistance) and energy (determined by the amount of deformation) to complete the plastic deformation. Therefore, in the overall difficulty evaluation, this item is assigned a high weight of 70%-90%, indicating that it is the main contradiction in the difficulty evaluation.

[0093] Specifically, the material reference resistance is the average initial deformation resistance of qualified motor shaft products using the same material, obtained through historical data statistics.

[0094] The volume deformation benchmark is the statistical average value of the target volume deformation of the motor shaft series products. m and n are exponential coefficients determined by data fitting. In practice, 0.5≤m,n≤1.0 is used to reflect the nonlinearity of the influence of the initial deformation resistance and the target volume deformation on the difficulty.

[0095] Optionally, the value of m ranges from 0.8 to 1.2, and the value of n ranges from 0.5 to 0.8;

[0096] Preferably, in this embodiment, m is 1.0 and n is 0.7;

[0097] Specifically, m is an index of the impact of initial deformation resistance on difficulty. A value of m close to 1 indicates that within the conventional cold forging deformation range, the forming force and the yield strength of the material's flow stress are roughly linearly proportional. Therefore, doubling the material hardness will approximately double the required pressure and process difficulty. A value of m slightly lower than 1 takes into account the existence of work hardening in the material. Materials that are initially harder may have a slightly slower subsequent hardening rate, and process parameters such as lubrication can provide some compensation. Therefore, the actual increase in difficulty may be slightly less than a linear proportion. A value of m slightly higher than 1 indicates that if the process system is extremely sensitive to material hardness, such as when the mold strength margin is very small, a small increase in hardness may lead to a sharp increase in pressure or even the risk of overload. In this case, a value slightly greater than 1 should be used to amplify its impact. n is an index of the impact of the target volume deformation on the difficulty. The difficulty of the process is mainly reflected in the fact that the required forming force and energy do not increase strictly proportionally with the deformation volume. For cold extrusion and stretching processes, the relationship between deformation work or average pressure and the degree of deformation, such as the logarithm of the extrusion ratio, is often a function with a power less than 1. If n is too large, such as close to 1.5, it will over-amplify the difficulty of "large workpieces" and cause the system to be too conservative.

[0098] During implementation, in the trial production or historical data accumulation stage, multiple sets of process data samples containing the following fields are collected: initial deformation resistance, target volume deformation, length-to-diameter ratio, and a quantitative label characterizing the actual process difficulty, such as the average adjustment intensity of subsequent processes or the difficulty level assessed based on the forming condition.

[0099] Based on this dataset, the unknown parameters m and n are fitted using multivariate nonlinear regression analysis. The goal of the fitting is to minimize the error between the model's predicted values ​​and the actual difficulty labels. To prevent overfitting, the fitting process is typically performed under constraints (0.5 ≤ m, n ≤ 1.0), and cross-validation is used to evaluate the model's generalization ability. Finally, the values ​​of m and n that provide the most accurate predictions are determined and implemented in the control system.

[0100] The ideal length-to-diameter ratio is the ratio corresponding to the most stable deformation mode determined by process tests or simulations. In practice, the range of the ideal length-to-diameter ratio that can be selected is 1.2-2.5; preferably, in this embodiment, the preferred embodiment of the ideal length-to-diameter ratio is 1.8.

[0101] Specifically, the process test calibration method for the ideal length-to-diameter deformation ratio involves using the same batch of materials to produce several workpieces with different ratios of the target bar length increment / target hollow depth increment after back extrusion. Other design parameters are adjusted proportionally to keep the target volume deformation relatively constant.

[0102] By using methods such as ultrasonic flaw detection and metallographic sectioning, we evaluate which of the following ratios best represents the internal quality and dimensional consistency of the workpiece. The corresponding ratio is the ideal length-to-diameter deformation ratio determined by the experiment.

[0103] When the process difficulty evaluation index is less than or equal to the first difficulty threshold, the workpiece processing is judged to be in the first difficulty state, and the punching force setting value is reduced according to the process difficulty evaluation index.

[0104] When the process difficulty evaluation index is greater than the first difficulty threshold and less than the second difficulty threshold, the workpiece processing is judged to be in the second difficulty state, and the punching force setting value of the reverse stretching process is adjusted according to the annealing state of the reverse extrusion process.

[0105] When the process difficulty evaluation index is greater than or equal to the second difficulty threshold, the workpiece processing is judged to be in the third difficulty state, and the stamping force setting value is increased and the stamping speed setting value is adjusted according to the process difficulty evaluation index.

[0106] Specifically, when the process difficulty evaluation index is greater than the preset evaluation index, the upper limit of the pressure setting value of the back extrusion process is increased proportionally to ensure that there is enough force to complete the deformation;

[0107] When the process difficulty evaluation index is less than the preset evaluation index, the upper limit of the pressure setting value of the back extrusion process is reduced proportionally to save energy and protect the mold.

[0108] During implementation, when the workpiece processing is at the third difficulty level, the stamping speed setting value of the reverse extrusion process is reduced. The reduced stamping speed setting value = stamping speed setting value / (1 + 0.2 × process difficulty evaluation index).

[0109] Wherein, the first difficulty threshold is 0.8, the second difficulty threshold is 1.3, and the preset evaluation index is 1.0.

[0110] In implementation, the principle behind setting the process difficulty evaluation index in this method lies in constructing a unified benchmark that can quantitatively integrate the initial resistance of the material, the target deformation, and the rationality of the geometric design. Its preset evaluation index represents the balance point of "ideal process difficulty" under benchmark materials and standard designs. By setting a first difficulty threshold and a second difficulty threshold, the complex continuous process difficulty is discretized into three control intervals with clear engineering directions. The first state indicates that the material is easily deformable or the workload is small; the system focuses on reducing pressure to achieve energy saving and mold protection. The second state represents moderate difficulty; at this point, the key variable for process success shifts from the initial material to the intermediate annealing effect, so the control logic switches to relying on the evaluation of the material state after annealing to precisely adjust the subsequent tensile force. The third state indicates that the process has entered a high-difficulty zone, with hard material or large deformation; the system adopts a composite conservative strategy of increasing force and reducing speed, proportionally increasing the stamping force to ensure forming, while reducing speed to alleviate high-load impact, control temperature rise, and improve metal flow stability.

[0111] Specifically, this invention acquires force-displacement signals from the forward extrusion process in real time to detect and determine the initial deformation resistance of the current batch of workpieces. It then calculates a process difficulty evaluation index based on the design parameters of the motor shaft and the increased hollow depth and rod length required for the reverse extrusion process, enabling early quantitative assessment of material condition and forming difficulty. Based on the process difficulty evaluation index, the processing is adaptively divided into three difficulty levels, and the punching force and speed of subsequent reverse extrusion and stretching processes are dynamically and hierarchically adjusted. This not only compensates for batch material fluctuations but also optimizes the process according to specific design parameters such as length-to-diameter ratio, significantly improving process adaptability and robustness. While ensuring the internal quality and dimensional accuracy of the complex hollow motor shaft, it also improves production efficiency.

[0112] After the reverse extrusion process, the motor shaft workpiece is annealed at a temperature of 820 degrees Celsius.

[0113] During the first 10%-20% of the stroke in the initial stage of reverse stretching, the impact force-displacement curve is collected in real time, and the initial resistance gradient of this initial stage is calculated. The initial resistance gradient is dP / dS.

[0114] Calculate the relative softening coefficient, where the relative softening coefficient = (initial resistance gradient / ideal gradient of the curve) × (initial deformation resistance / material reference resistance), and the ideal gradient of the curve is the statistical average of the slope of the initial segment of the punching force-displacement curve of historical qualified workpieces;

[0115] The initial resistance gradient is dP / dS of the current workpiece in the initial stage of reverse tension, representing the "manifest hardness" or "instantaneous deformation resistance gradient" of the material in the initial stage of cold forging deformation after annealing.

[0116] The ideal gradient of the curve is the average dP / dS of a qualified workpiece under standard annealing process and standard initial materials. This represents the benchmark for "ideal performance".

[0117] The initial deformation resistance is the average value of the standard initial deformation resistance corresponding to k_nominal.

[0118] The material reference resistance is the initial deformation resistance of the current workpiece measured in the first extrusion process, representing the "original hardness" of the material before annealing.

[0119] To ensure the reliability of the assessment, a material anomaly warning is triggered when the initial deformation resistance deviates from the material reference resistance by more than ±30%. When the initial resistance of the material is within the normal fluctuation range, the annealing state is classified according to the relative softening coefficient value.

[0120] The relative softening coefficient is used to reflect the degree of deviation of the softening effect brought about by the annealing process from the standard state.

[0121] When the relative softening coefficient is less than the first softening coefficient, it is judged that the workpiece is over-annealed, the material yield strength is too low, and the plasticity is too high.

[0122] When the relative softening coefficient is greater than or equal to the first softening coefficient and less than or equal to the second softening coefficient, the annealing effect is determined to be within the expected window.

[0123] When the relative softening coefficient is greater than the second softening coefficient, the workpiece is judged to be under-annealed and retains more machining hardness.

[0124] When the workpiece is over-annealed or under-annealed, determine whether there is a risk of deformation and cracking in the reverse stretching process;

[0125] The first softening coefficient is 0.85, and the second softening coefficient is 1.15.

[0126] In practice, the principle behind setting the relative softening coefficient is to construct a normalized index that can isolate the initial performance differences of materials and purely quantify the actual effect of the annealing process. The numerator directly compares the apparent hardness of the current workpiece with that of a standard workpiece in the initial stage of reverse tensile testing, reflecting the overall state after annealing; while the reciprocal of the denominator serves as a "correction factor" to offset the baseline influence on apparent hardness caused by differences in the hardness of incoming batches. By setting the first and second softening coefficients as criterion thresholds, the annealing effect is precisely divided into three states: over-softening, ideal window, and under-softening.

[0127] Specifically, after reverse extrusion, annealing is performed. Annealing gives the material a uniform spherical pearlite structure, significantly improving plasticity and reducing the workpiece's deformation resistance. However, annealing is subject to fluctuations. This invention analyzes the force-displacement curve at the initial stage of reverse stretching and calculates the relative softening coefficient, enabling online quantitative evaluation of the degree of plasticity improvement achieved by the annealing process. The post-annealing material state is precisely divided into three states: "excessive," "ideal," and "insufficient," providing a precise control basis for subsequent stretching processes. When abnormally excessive or insufficient softening of the material is detected, the system can link volume deformation and temperature rise monitoring to predict and proactively prevent the risk of tearing. Intelligent evaluation overcomes the quality inconsistencies caused by furnace temperature fluctuations and holding differences in traditional annealing processes, significantly improving the stability, pass rate, and product uniformity of cold forging production of hollow motor shafts.

[0128] In the machining process of the motor shaft, changes in wall thickness, hollow depth, and bar length will all affect the volumetric deformation. The volumetric deformation is a precise measure of the amount of plastic flow of metal in the reverse extrusion process.

[0129] When the reverse extrusion process is over-annealed or under-annealed, the risk of tearing is judged based on the real-time deviation of the workpiece volume deformation in the reverse stretching process and the risk of local temperature rise. The stamping force setting value and stamping speed setting value are then adjusted accordingly.

[0130] Monitor the consistency of volume deformation of the workpiece during the reverse stretching process, obtain the reverse stretching stroke of the punch according to the initial detection cycle, obtain the theoretical design parameters of the motor shaft, and the theoretical instantaneous volume deformation corresponding to the reverse stretching stroke = shaft wall area × reverse stretching stroke, wherein the shaft wall area is the difference between the cross-sectional area of ​​the rod body and the cross-sectional area of ​​the hollow part.

[0131] Since the reverse stretching die in the reverse stretching process has a fixed shape and volume, there is a corresponding relationship between the real-time reverse stretching stroke and the volume deformation. The actual plastic deformation volume of the workpiece in the reverse stretching process can be determined based on the correspondence between the real-time reverse stretching stroke of the punch and the volume deformation in the reverse stretching process.

[0132] Calculate the real-time deviation of the workpiece volume deformation, wherein the real-time deviation = |actual plastic deformation volume - theoretical instantaneous volume deformation amount| / theoretical instantaneous volume deformation amount;

[0133] If the real-time deviation continues to exceed the deviation threshold within a continuous sampling period, it is determined that the metal flow is uneven during the reverse stretching process.

[0134] Specifically, the duration of the continuous sampling period is 0.5 seconds, and the deviation threshold is 5%.

[0135] Local temperature rise risk monitoring is performed on the axial wall tension of the workpiece bar. During the reverse tensioning process of the workpiece, the temperature data of the infrared temperature measurement point of the axial wall of the workpiece bar is acquired in real time, and the temperature rise rate is calculated based on the temperature data.

[0136] If the temperature rise rate is greater than the temperature rise threshold, it is determined that the workpiece bar has abnormal local overheating of the shaft wall and there is a risk of local deformation of the shaft wall.

[0137] When the metal flow is uneven and the shaft wall temperature rises abnormally during the reverse stretching process, it is determined that there is a risk of deformation and cracking in the reverse stretching process.

[0138] The temperature rise threshold value ranges from 20 to 25°C / s.

[0139] When there is a risk of deformation and cracking in the reverse stretching process and the workpiece is not annealed enough, the set value of the stamping force should be increased. In practice, the set value of the stamping force should be increased proportionally according to the relative softening coefficient.

[0140] If the real-time deviation of volume deformation exceeds the standard or the temperature rise rate exceeds the standard, the stamping speed setting value is reduced. In practice, the stamping speed setting value is reduced according to the ratio of real-time deviation to deviation threshold or the ratio of temperature rise rate to temperature rise threshold.

[0141] Specifically, in the machining process of the motor shaft, changes in wall thickness, changes in the depth of the hollow part, and changes in the length of the bar will all affect the volume deformation amount, which is an accurate measure of the metal plastic flow amount in the backward extrusion process. The present invention realizes the accurate on-line monitoring of the uniformity of metal plastic flow by calculating the volume deformation deviation of the workpiece in the backward stretching process in real time and comparing it with the preset theoretical value; at the same time, combined with the real-time monitoring of the local temperature rise rate of the shaft wall, it can sensitively capture the abnormal material flow and the risk of local overheating; when the volume deviation and the temperature rise anomaly appear simultaneously, it can be intelligently judged as a precursor of high-risk deformation and cracking, and immediately linked to adjust; when the annealing is insufficient, increase the punching pressure in proportion to ensure forming, and automatically reduce the speed when deviation or overheating is detected to prevent the defect from expanding; this collaborative monitoring and control mechanism effectively prevents the cracking and folding defects of the hollow motor shaft in the complex cold forging process, and significantly improves the consistency of the internal quality of the product and the production stability.

[0142] In this embodiment, the volume deformation amount is used as an input variable to establish a mapping relationship model with the deformation resistance state after backward extrusion annealing. By collecting the displacement and punching pressure data in the backward stretching process of each pass in real time, calculate the change rate and cumulative value of the current volume deformation amount, and then judge the uniformity and stability of the metal plastic flow.

[0143] Combined with the distribution characteristics of the volume deformation amount under different deformation resistance states in the historical batches, set the threshold interval for each state to dynamically identify the deformation resistance state of the current workpiece. On this basis, feedback the recognition result to the process parameter regulation module to realize the adaptive adjustment of the key parameters, so as to ensure that the material response after annealing matches the established process window and improve the forming consistency.

[0144] Obtain the adjustment intensity of the set value of the punching pressure, and the adjustment intensity = |the adjusted set value of the punching pressure - the set value of the punching pressure before adjustment| / the set value of the punching pressure before adjustment;

[0145] According to the adjustment intensity and the process difficulty evaluation index corresponding to several motor shaft finished products prepared from the current batch of workpieces, determine the correlation between the process difficulty evaluation index and the subsequent process adjustment intensity;

[0146] The correlation = the sum of [ (the process difficulty evaluation index of any workpiece finished product - the average value of several process difficulty evaluation indexes) × (the adjustment intensity of any workpiece finished product - the average value of several adjustment intensities) ] of several workpiece finished products / [ the sum of several workpiece finished products of (the process difficulty evaluation index of any workpiece finished product - the average value of several process difficulty evaluation indexes) 2 The sum × the sum of several workpiece finished products of (the adjustment intensity of any workpiece finished product - the average value of several adjustment intensities) 2 The square root of the sum];

[0147] When the correlation is greater than or equal to the first correlation threshold, the process difficulty evaluation index is judged to be strongly correlated with the intensity of subsequent process adjustments.

[0148] When the correlation is less than the first correlation threshold but greater than the second correlation threshold, the process difficulty evaluation index is judged to have a moderate correlation with the intensity of subsequent process adjustments.

[0149] When the correlation is less than the second correlation threshold, the process difficulty evaluation index is judged to be weakly correlated with the intensity of subsequent process adjustments. The second difficulty threshold is increased and the first difficulty threshold is decreased based on the ratio of the correlation to the first correlation threshold.

[0150] The first correlation threshold is 0.7, and the second correlation threshold is 0.4.

[0151] Specifically, the core of correlation is the linear relationship between the predictive variable of the quantified process difficulty evaluation index and the actual process response variable of the subsequent stamping pressure adjustment intensity. This correlation coefficient ranges from -1 to 1. This logic focuses on positive correlation, setting a first and second correlation threshold. This is an engineering-based classification based on statistical conventions (|r|>0.7 for strong correlation, 0.4<|r|<0.7 for moderate correlation, and |r|<0.4 for weak correlation). The underlying logic is: if the correlation is strong or moderate, it proves that the actual process difficulty can be effectively predicted, and the current parameters are maintained; if a weak correlation is detected, it indicates that the predictive ability has failed, and the currently set difficulty level classification threshold is no longer applicable. Negative feedback adjustment is then initiated, using the ratio of the correlation to the first correlation threshold, r / 0.7, a coefficient less than 1, to simultaneously increase the second difficulty threshold and decrease the first difficulty threshold. The physical meaning is that when the model prediction is inaccurate, the system actively narrows the judgment range of the ideal control area of ​​the "second difficulty state" while widening the range of the low-risk area of ​​the "first difficulty state" and the high-risk area of ​​the "third difficulty state". This forces more workpieces to enter the "insurance" range with a fixed and conservative strategy, thereby ensuring process safety during the period of model inaccuracy until new data accumulation completes the model update and optimization.

[0152] Specifically, ideally, the process difficulty evaluation index should be positively correlated with the intensity of subsequent process adjustments or the failure rate. This invention achieves closed-loop verification and self-optimization of the effectiveness of the process prediction model by quantitatively analyzing the statistical correlation between the process difficulty evaluation index and the intensity of subsequent stamping pressure adjustments. When the system detects a weak correlation and prediction failure, it can automatically adjust the threshold for difficulty state classification, making the graded control more consistent with the current production reality. This intelligent learning mechanism based on data feedback enables the process control system to continuously adapt to the long-term drift of material properties and equipment status, continuously improve the prediction accuracy and control matching degree of forming difficulty, and ultimately ensure the long-term stability of the production quality of complex motor shaft cold forging and the autonomous evolution of the process knowledge system.

[0153] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0154] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A cold-forging fractional extrusion-drawing method for the production of motor shafts, characterized by the fact that, include: The real-time punching force signal and real-time displacement signal of the punch in the forward extrusion process are obtained. The peak force of forward extrusion is obtained based on the real-time punching force signal and the stable stroke of forward extrusion is obtained based on the real-time displacement signal, so as to determine the approximate average force of forward extrusion. The peak force of forward extrusion is the maximum value in the real-time punching force signal, and the stable stroke of forward extrusion is the displacement change during the period when the real-time punching force rises to reach the peak force of forward extrusion; the approximate average force of forward extrusion = (1 / stable stroke of forward extrusion) × ∫P dS, where P is the peak force of forward extrusion, S is the stable stroke of forward extrusion, and the integral interval in the formula is the displacement segment from the real-time punching force to the peak force of forward extrusion. Based on the initial deformation resistance of the workpiece with the approximate average force of the forward extrusion, the target parameter increment of the reverse extrusion process and the average inner diameter of the target hollow part of the reverse extrusion are obtained to determine the target volume deformation. Based on the initial deformation resistance and the target volume deformation, the process difficulty evaluation index is determined. Calculate the average contact area of ​​the forward extrusion deformation zone within the die during the forward extrusion process. The average contact area = π × (the filling diameter of the billet within the forward extrusion die cavity). 2 - Diameter of the working end of the extrusion punch 2 ) / 4; Calculate the initial average flow stress of the material, wherein the initial average flow stress = approximate average force of forward extrusion / average contact area, and define the initial average flow stress as the initial deformation resistance; Target volume deformation = π × average inner diameter of the hollow part of the reverse-extrusion target 2 / 4×Increment of target hollow depth after reverse extrusion +π×Filling diameter of billet in forward extrusion die cavity 2 / 4×Increment of target rod length after reverse extrusion; Based on the process difficulty evaluation index, the difficulty state of the workpiece processing is determined. When the process difficulty evaluation index is less than or equal to the first difficulty threshold, the workpiece processing is judged to be in the first difficulty state, and the stamping pressure setting value is reduced according to the process difficulty evaluation index. When the process difficulty evaluation index is greater than the first difficulty threshold and less than the second difficulty threshold, the workpiece processing is judged to be in the second difficulty state, and the stamping pressure setting value of the reverse stretching process is adjusted according to the annealing state of the reverse extrusion process. When the process difficulty evaluation index is greater than or equal to the second difficulty threshold, the workpiece processing is judged to be in the third difficulty state, and the stamping pressure setting value is increased and the stamping speed setting value is decreased according to the process difficulty evaluation index. Based on the difficulty state, the initial resistance gradient of the initial stage of reverse stretching is obtained and the relative softening coefficient is determined by combining the initial deformation resistance. Based on the relative softening coefficient, the annealing state of the workpiece is determined. In the first 10%-20% of the stroke of the initial stage of reverse stretching, the punching force-displacement curve is collected in real time, and the initial resistance gradient of this initial stage is calculated. The initial resistance gradient is dP / dS. In response to the annealing state of the workpiece, the real-time deviation of the workpiece volume deformation is obtained. Based on the real-time deviation, it is determined whether the metal flow is uniform during the reverse stretching process. Combined with the temperature rise rate of the workpiece bar shaft wall, the set values ​​of the stamping force and stamping speed of the reverse stretching process are adjusted. The adjustment intensity of the set value of the punching force is obtained. Based on several adjustment intensities and process difficulty evaluation indices of the current batch of workpieces, the correlation between the process difficulty evaluation index and the subsequent process adjustment intensity is determined. Wherein, the adjustment intensity = |adjusted punching force set value - original punching force set value| / original punching force set value. In response to the correlation, the difficulty threshold for determining the difficulty state of workpiece processing based on the process difficulty evaluation index is adjusted.

2. The cold forging step-by-step extrusion and stretching method for preparing motor shafts according to claim 1, characterized in that, The process of adjusting the punching force setting value based on the process difficulty evaluation index includes: When the process difficulty evaluation index is greater than the preset evaluation index, the upper limit of the pressure setting value of the back extrusion process is increased proportionally. When the process difficulty evaluation index is less than the preset evaluation index, the pressure upper limit of the back extrusion process punching pressure setting value is reduced proportionally.

3. The cold-forging fractional extrusion-drawing method for the preparation of motor shafts according to claim 2, characterized in that, The process of determining the annealing state of a workpiece based on the relative softening coefficient includes determining that the workpiece is over-annealed when the relative softening coefficient is less than the first softening coefficient. When the relative softening coefficient is greater than or equal to the first softening coefficient and less than or equal to the second softening coefficient, the annealing effect is determined to be within the expected window. If the relative softening coefficient is greater than the second softening coefficient, the workpiece is judged to be under-annealed. When the workpiece is over-annealed or under-annealed, determine whether there is a risk of deformation and cracking in the reverse stretching process.

4. The cold-forging fractional extrusion-drawing method for the preparation of motor shafts according to claim 3, characterized in that, The process of determining whether there is a risk of deformation and tearing in the reverse stretching process includes, The real-time deviation of the workpiece volume deformation is determined. If the real-time deviation continues to exceed the deviation threshold within a continuous sampling period, it is determined that the metal flow is uneven during the reverse stretching process.

5. The cold-forging fractional extrusion-drawing method for the preparation of motor shafts according to claim 4, characterized by the fact that, During the reverse stretching process of the workpiece, local temperature rise risk monitoring is carried out for the stretching of the shaft wall of the workpiece bar. The temperature data of the infrared temperature measurement point on the shaft wall of the workpiece bar is acquired in real time, and the temperature rise rate is calculated based on the temperature data; If the temperature rise rate is greater than the temperature rise threshold, it is determined that the workpiece rod has abnormal local overheating of the shaft wall, and there is a risk of local deformation of the shaft wall.

6. The cold-forging fractional extrusion-drawing method for the preparation of motor shafts according to claim 5, characterized by the fact that, If the metal flow is uneven and the shaft wall temperature rises abnormally during the reverse stretching process, it is determined that there is a risk of deformation and cracking in the reverse stretching process.

7. The cold forging step-by-step extrusion and stretching method for preparing motor shafts according to claim 6, characterized in that, When there is a risk of deformation and cracking in the reverse stretching process and the workpiece is not annealed enough, the set value of the stamping force is increased proportionally according to the relative softening coefficient. If the real-time deviation of volume deformation exceeds the standard or the temperature rise rate exceeds the standard, the stamping speed setting value is reduced according to the ratio of real-time deviation to deviation threshold or the ratio of temperature rise rate to temperature rise threshold.

8. The cold-forging fractional extrusion-drawing method for the production of motor shafts according to claim 7, characterized in that, When the correlation is greater than or equal to the first correlation threshold, the process difficulty evaluation index is judged to be strongly correlated with the intensity of subsequent process adjustments. When the correlation is less than the first correlation threshold but greater than the second correlation threshold, the process difficulty evaluation index is judged to have a moderate correlation with the intensity of subsequent process adjustments. When the correlation is less than the second correlation threshold, the process difficulty evaluation index is judged to be weakly correlated with the intensity of subsequent process adjustments. The second difficulty threshold is increased and the first difficulty threshold is decreased based on the ratio of the correlation to the first correlation threshold.

Images