A method and system for cold heading of fasteners based on intelligent temperature control

Abstract

This invention relates to the field of fastener cold heading technology, and discloses a method and system for fastener cold heading based on intelligent temperature control. The method includes: identifying the cold heading machine, cold heading die, and a set of test parameters; identifying the target test bar stock set; acquiring the measured die temperature set, peak acceleration increment set, and pulse width ratio set; calculating the average of the measured die temperature set, peak acceleration increment set, and pulse width ratio set to obtain calibration parameters; summarizing the calibration parameters to obtain a calibration parameter set; constructing a calibration comparison table; identifying the bar stock to be formed; performing feature value acquisition based on the cold heading machine and the bar stock to be formed to obtain relative feature parameters; calculating and updating the nozzle injection pulse width value; and completing the intelligent temperature-controlled cold heading of the fastener based on the updated nozzle injection pulse width value. This invention can monitor the cold heading temperature in real time and automatically adjust the cooling amount.

Description

Technical Field

[0001] This invention relates to the field of fastener cold heading technology, and in particular to a fastener cold heading method and system based on intelligent temperature control. Background Technology

[0002] Intelligent temperature control is an automated temperature control method that utilizes sensors to collect vibration and / or temperature signals in real time during the cold heading process. Through a built-in control algorithm, the collected data is analyzed and processed to automatically determine the temperature range of the current heading state. Based on the determination result, the spray parameters of the cooling medium are dynamically adjusted to stabilize the mold temperature within the target range. Fasteners are a general term for mechanical parts used to fasten two or more parts together into a single unit. Cold heading is a processing method that uses a punch to apply high-speed impact pressure to a metal bar at room temperature, causing the metal bar to undergo plastic deformation within a mold cavity, thereby obtaining fasteners of the desired shape and size.

[0003] During cold heading, the metal bar undergoes intense plastic deformation under high-speed impact. Simultaneously, intense friction occurs between the punch and the bar, and between the bar and the die. These combined effects generate a large amount of heat (deformation heat and frictional heat), causing the die temperature to rise rapidly. Excessive die temperature accelerates die softening and wear, leads to die sticking, and affects product dimensional accuracy and surface quality. Conversely, insufficient die temperature reduces metal fluidity, easily resulting in incomplete filling, folding, and other forming defects. Traditional cold heading processes typically use continuous spraying of coolant to cool the die. This open-loop control method has the following problems: first, the cooling amount is fixed and cannot be dynamically adjusted according to actual temperature changes, easily leading to insufficient or excessive cooling; second, the response is lag, failing to track rapid changes in die temperature in real time. Therefore, how to monitor the cold heading temperature in real time and automatically adjust the cooling amount is an urgent technical problem to be solved. Summary of the Invention

[0004] This invention provides a method for cold heading of fasteners based on intelligent temperature control and a computer-readable storage medium. Its main purpose is to monitor the cold heading temperature in real time and automatically adjust the cooling amount.

[0005] To achieve the above objectives, the present invention provides a method for cold heading of fasteners based on intelligent temperature control, comprising: The cold heading machine, cold heading mold, and test condition parameter set were identified. The cold heading machine includes a triaxial accelerometer and a punch. The test condition parameter set includes low temperature test, normal temperature test, and high temperature test. Test conditions are extracted sequentially from the set of test conditions parameters, where the test conditions parameters are low temperature test, normal temperature test, or high temperature test. Based on the extracted test condition parameters, the target test bar set was identified, and based on the target test bar set and the cold heading die, the measured die temperature set, peak acceleration increment set, and pulse width ratio set were obtained. The average values ​​of the measured mold temperature set, peak acceleration increment set, and pulse width ratio set are calculated to obtain the working condition calibration parameters. The working condition calibration parameters include: average measured mold temperature, average peak acceleration increment, and average pulse width ratio. The operating condition calibration parameters are summarized to obtain the operating condition calibration parameter set, which includes: low temperature operating condition calibration parameters, normal operating condition calibration parameters, and high temperature operating condition calibration parameters; A calibration comparison table is constructed based on the working condition calibration parameter set to identify the bar stock to be formed. Based on the cold heading machine and the bar stock to be formed, characteristic value acquisition operations are performed to obtain relative characteristic parameters. The relative characteristic parameters are compared with the calibration reference table to obtain the cold heading temperature range, the current cooling nozzle injection pulse width value is obtained, and the nozzle injection pulse width value is calculated and updated based on the cold heading temperature range and the current cooling nozzle injection pulse width value. Cold heading of fasteners with intelligent temperature control based on updated nozzle pulse width values.

[0006] Optionally, the step of obtaining the measured die temperature set, peak acceleration increment set, and pulse width ratio set based on the target test bar set and cold heading die includes: For each target test bar in the target test bar set, perform the following operations: The peak acceleration and pulse width under no-load conditions are obtained. Data is collected on the target test bar based on the cold heading die to obtain the measured die temperature, peak acceleration and pulse width. The peak acceleration increment is calculated based on the no-load peak acceleration and the peak acceleration, and the pulse width ratio is calculated based on the no-load pulse width and the pulse width. The measured mold temperature, peak acceleration increment, and pulse width ratio are summarized to obtain the measured mold temperature set, peak acceleration increment set, and pulse width ratio set.

[0007] Optionally, obtaining the no-load peak acceleration and no-load pulse width includes: Once the unloaded distance section is identified, the cold heading machine is started. Based on the unloaded distance section and the triaxial accelerometer, unloaded data is collected on the cold heading machine after it is started to obtain the unloaded vibration acceleration set. The absolute value operation is performed on the set of no-load vibration acceleration to obtain the set of absolute values ​​of no-load vibration acceleration, and the peak acceleration of no-load is extracted from the set of absolute values ​​of no-load vibration acceleration. The peak value of the no-load descent acceleration is obtained by multiplying the peak no-load acceleration by a preset descent percentage, and the peak value of the no-load rise acceleration is obtained by multiplying the peak no-load acceleration by a preset rise percentage. The descent acceleration time and the ascent acceleration time under no-load conditions were determined based on the peak values ​​of the descent acceleration and ascent acceleration under no-load conditions. The no-load pulse width is calculated based on the no-load descent acceleration time and the no-load ascent acceleration time.

[0008] Optionally, the step of acquiring data from the target test bar stock based on the cold heading die to obtain the measured die temperature, peak acceleration, and pulse width includes: The target test bar is fed into the cold heading die to obtain the impact test bar. The punch in the cold heading machine and the preset sampling window are used to impact the test bar to obtain the punch vibration acceleration set and the temperature of the mold to be tested. The absolute value operation of each punch vibration acceleration in the punch vibration acceleration set is performed to obtain the absolute value set of acceleration. Calculate pulse width based on the set of absolute acceleration values, and extract peak acceleration from the set of absolute acceleration values; Temperature data is collected from the mold to be tested to obtain a mold temperature set. The maximum mold temperature is then identified from the mold temperature set and used as the actual measured mold temperature.

[0009] Optionally, the step of constructing a calibration comparison table based on the set of operating condition calibration parameters includes: Extract the low-temperature average peak acceleration increment and the low-temperature average pulse width ratio from the low-temperature calibration parameters in the calibration parameter set. Extract the average peak acceleration increment at normal temperature, the average pulse width ratio at normal temperature, the average peak acceleration increment at high temperature, and the average pulse width ratio at high temperature from the calibration parameters under normal operating conditions and high temperature operating conditions, respectively. The set of correction intervals is determined based on the increment of average peak acceleration at low temperature, the ratio of average pulse width at low temperature, the increment of average peak acceleration at normal temperature, the ratio of average pulse width at normal temperature, the increment of average peak acceleration at high temperature, and the ratio of average pulse width at high temperature. The set of correction intervals includes: the correction interval for low temperature, the correction interval for normal temperature, and the correction interval for high temperature. A calibration reference table is constructed based on the calibration interval set.

[0010] Optionally, the step of determining the correction interval set based on the low-temperature average peak acceleration increment, the low-temperature average pulse width ratio, the normal-temperature average peak acceleration increment, the normal-temperature average pulse width ratio, the high-temperature average peak acceleration increment, and the high-temperature average pulse width ratio includes: The first acceleration threshold is calculated based on the average peak acceleration increment at low temperature and the average peak acceleration increment at normal temperature. The first pulse width threshold is calculated based on the ratio of average pulse width at low temperature and the ratio of average pulse width at normal temperature. The second acceleration threshold and the second pulse width threshold are calculated based on the average peak acceleration increment at normal temperature, the average peak acceleration increment at high temperature, the ratio of average pulse width at normal temperature and the ratio of average pulse width at high temperature. The normal temperature acceleration range and the normal temperature pulse width range are constructed based on the first acceleration boundary threshold, the second acceleration boundary threshold, the first pulse width boundary threshold, and the second pulse width boundary threshold. A low-temperature acceleration range and a low-temperature pulse width range are constructed based on a first acceleration boundary threshold and a first pulse width boundary threshold, and a high-temperature acceleration range and a high-temperature pulse width range are constructed based on a second acceleration boundary threshold and a second pulse width boundary threshold. The set of correction intervals was determined based on the normal temperature acceleration interval, normal temperature pulse width interval, low temperature acceleration interval, low temperature pulse width interval, high temperature acceleration interval, and high temperature pulse width interval.

[0011] Optionally, the step of calculating and updating the nozzle injection pulse width value based on the cold heading temperature range and the current cooling nozzle injection pulse width value includes: To obtain a relatively low cooling attenuation coefficient and a relatively high cooling enhancement coefficient; If the cold heading temperature range is the low-temperature correction range, then the current cooling nozzle injection pulse width value is corrected using the low cooling attenuation coefficient to obtain the first corrected injection pulse width value. If the first corrected injection pulse width value is less than the preset minimum injection pulse width value, then the first corrected injection pulse width value is replaced by the preset zero value to obtain the replaced injection pulse width value. If the cold heading temperature range is within the normal calibration temperature range, then the current cooling nozzle injection pulse width value will be taken as the qualified nozzle injection pulse width value. If the cold heading temperature range is the correction high temperature range, then the current cooling nozzle injection pulse width value is corrected by using the higher cooling enhancement coefficient to obtain the second corrected injection pulse width value. If the second corrected injection pulse width value is greater than the preset maximum injection pulse width value, then the second corrected injection pulse width value is assigned a value using the maximum injection pulse width value to obtain the assigned injection pulse width value. The updated nozzle injection pulse width value is determined based on the first corrected injection pulse width value, the replaced injection pulse width value, the qualified nozzle injection pulse width value, the second corrected injection pulse width value, or the assigned injection pulse width value.

[0012] Optionally, obtaining the lower cooling attenuation coefficient and the higher cooling enhancement coefficient includes: Obtain the test fastener set, and perform the following operations on each test fastener in the test fastener set: The initial low cooling attenuation coefficient and the initial high cooling enhancement coefficient were identified. The test fasteners are cold-forged to obtain the fastener temperature range. The adjustment temperature parameters are obtained based on the fastener temperature range and the initial low cooling attenuation coefficient. Summarize the temperature adjustment parameters to obtain a set of temperature adjustment parameters. Based on the set of temperature adjustment parameters, identify the number of times the adjustment was normal, the number of times the adjustment was too low, and the number of times the adjustment was too high. Based on the total number of adjustments to the test fastener set, the low cooling attenuation coefficient is calculated based on the total number of adjustments, the number of normal adjustments, the number of low adjustments, and the number of high adjustments. The higher cooling enhancement factor is calculated based on the test fastener set and the initial higher cooling enhancement factor.

[0013] Optionally, the formula for calculating the relatively low cooling attenuation coefficient is as follows:

[0014] in, This indicates a low cooling attenuation coefficient. This indicates an initially low cooling attenuation coefficient. This indicates the preset adjustment step size. This indicates that the number of adjustments was too low. This indicates that the number of adjustments was too high. This indicates an adjustment to the total number.

[0015] To achieve the above objectives, the present invention also provides a fastener cold heading system based on intelligent temperature control, comprising: The working condition calibration preparation module is used to identify the cold heading machine, cold heading mold, and test working condition parameter set. The cold heading machine includes a triaxial accelerometer and a punch. The test working condition parameter set includes test low temperature, test normal temperature, and test high temperature. Test working condition parameters are extracted from the test working condition parameter set in sequence. The test working condition parameters are test low temperature, test normal temperature, or test high temperature. The calibration parameter acquisition module is used to identify the target test bar set based on the extracted test condition parameters. Based on the target test bar set and the cold heading die, it obtains the measured die temperature set, peak acceleration increment set, and pulse width ratio set. The mean values ​​of the measured die temperature set, peak acceleration increment set, and pulse width ratio set are calculated to obtain the working condition calibration parameters. The working condition calibration parameters include: average measured die temperature, average peak acceleration increment, and average pulse width ratio. The working condition calibration parameters are summarized to obtain the working condition calibration parameter set, which includes: low temperature working condition calibration parameters, normal working condition calibration parameters, and high temperature working condition calibration parameters. The calibration comparison table construction module is used to construct a calibration comparison table based on the working condition calibration parameter set, identify the bar stock to be formed, and perform feature value acquisition operations based on the cold heading machine and the bar stock to be formed to obtain relative feature parameters; The intelligent temperature control decision module is used to compare the relative characteristic parameters with the calibration reference table to obtain the cold heading temperature range, obtain the current cooling nozzle injection pulse width value, calculate and update the nozzle injection pulse width value based on the cold heading temperature range and the current cooling nozzle injection pulse width value, and complete the intelligent temperature-controlled fastener cold heading based on the updated nozzle injection pulse width value.

[0016] To address the above problems, the present invention also provides an electronic device, the electronic device comprising: Memory, storing at least one instruction; The processor executes the instructions stored in the memory to implement the above-described method for cold heading of fasteners based on intelligent temperature control.

[0017] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the aforementioned method for cold heading of fasteners based on intelligent temperature control.

[0018] To address the problems described in the background art, this invention identifies a cold heading machine, a cold heading die, and a set of test condition parameters. The cold heading machine includes a triaxial accelerometer and a punch. The test condition parameter set includes low-temperature testing, normal-temperature testing, and high-temperature testing. This invention comprehensively covers various temperature states that may occur during the cold heading process of fasteners by using three typical testing conditions: low-temperature testing, normal-temperature testing, and high-temperature testing. This provides a data foundation for establishing a complete temperature-vibration mapping relationship. Test condition parameters are extracted sequentially from the set of test condition parameters, where each test condition parameter is either low-temperature testing, normal-temperature testing, or high-temperature testing. This sequential extraction method ensures that the calibration process for each condition is independent. Each completed calibration of a condition... After calibration, the system waits for the mold to cool to room temperature before proceeding to the next operating condition to avoid mutual interference between different temperature conditions and ensure the reliability and repeatability of the calibration parameters. Based on the extracted test condition parameters, the target test bar set is identified. Based on the target test bar set and the cold heading mold, the measured mold temperature set, peak acceleration increment set, and pulse width ratio set are obtained. This invention obtains the measured mold temperature set, peak acceleration increment set, and pulse width ratio set by repeatedly collecting data from multiple bars under each operating condition. This eliminates random errors in single measurements and improves the statistical reliability of the calibration data. The average values ​​of the measured mold temperature set, peak acceleration increment set, and pulse width ratio set are calculated to obtain the operating condition calibration parameters. The data includes: average measured mold temperature, average peak acceleration increment, and average pulse width ratio. This invention obtains typical characteristic values ​​for each operating condition by arithmetically averaging 10 measurement results. These typical values ​​represent the standard state under that operating condition, eliminating the influence of random fluctuations. The operating condition calibration parameters are then summarized to obtain a set of operating condition calibration parameters, which includes: low-temperature operating condition calibration parameters, normal operating condition calibration parameters, and high-temperature operating condition calibration parameters. This invention summarizes the calibration parameters for low-temperature, normal, and high-temperature operating conditions into a complete set of operating condition calibration parameters, forming a calibration database covering all temperatures from low to high. This provides complete data support for the subsequent construction of a calibration comparison table. A calibration comparison table is constructed based on the operating condition calibration parameter set to confirm... The invention involves collecting feature values ​​of the bar stock to be formed using a cold heading machine and the bar stock itself to obtain relative feature parameters. This feature value collection operation allows for real-time acquisition of the relative feature parameters of each fastener during normal production, enabling uninterrupted online temperature monitoring without stopping the machine. The relative feature parameters are compared with a calibration table to determine the cold heading temperature range. The current cooling nozzle pulse width value is also obtained. Based on the cold heading temperature range and the current cooling nozzle pulse width value, the nozzle pulse width value is calculated and updated. By comparing the relative feature parameters with a calibration table, this invention can quickly determine the current cold heading temperature range, achieving millisecond-level real-time temperature determination without the need for additional temperature sensors. Furthermore, it adjusts the cooling volume in real time.This invention ensures that each fastener is manufactured under molding conditions close to the target temperature, effectively reducing product quality variations caused by temperature fluctuations and improving batch consistency. It achieves intelligent temperature control for fastener cold heading based on updated nozzle pulse width values. Therefore, this invention can monitor the cold heading temperature in real time and automatically adjust the cooling amount. Attached Figure Description

[0019] Figure 1 This is a schematic flowchart of a method for cold heading of fasteners based on intelligent temperature control, provided in an embodiment of the present invention. Figure 2 This is a functional block diagram of a fastener cold heading system based on intelligent temperature control provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device that implements the fastener cold heading method based on intelligent temperature control, according to an embodiment of the present invention.

[0020] Explanation of reference numerals in the attached figures: 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0021] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0023] This application provides a method for cold heading fasteners based on intelligent temperature control. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0024] Reference Figure 1 The diagram shown is a flowchart illustrating a method for cold heading of fasteners based on intelligent temperature control, according to an embodiment of the present invention. In this embodiment, the method for cold heading of fasteners based on intelligent temperature control includes: S1. Identify the cold heading machine, cold heading mold, and test condition parameter set. The cold heading machine includes a triaxial accelerometer and a punch. The test condition parameter set includes low temperature test, normal temperature test, and high temperature test.

[0025] It needs to be explained that a cold heading machine is a device that uses a punch to apply high-speed impact pressure to a metal bar at room temperature, causing it to undergo plastic deformation within the cavity of a cold heading die, thereby forming fasteners (such as bolts, nuts, screws, etc.). The cold heading die is a forming tool mounted on the cold heading machine, and its internal cavity matches the shape of the fastener. A triaxial accelerometer is a sensor capable of simultaneously measuring acceleration changes in three mutually orthogonal directions (X-axis, Y-axis, Z-axis), and its output signal is proportional to the applied acceleration value. The punch is the component in the cold heading machine used to directly impact the metal bar and cause plastic deformation. The metal bar is a cylindrical material made from metal through drawing, rolling, or extrusion processes. Low-temperature testing refers to the low-temperature ambient temperature set when performing performance tests on the cold heading machine and cold heading die. Normal testing temperature refers to the standard operating ambient temperature set when performing performance tests on the cold heading machine and cold heading die. The high-temperature test is the high-temperature environment temperature set when cold heading machines and cold heading dies are used for performance testing.

[0026] S2. Extract test condition parameters sequentially from the test condition parameter set, where the test condition parameters are test low temperature, test normal temperature, or test high temperature.

[0027] It should be explained that the present invention ensures that the calibration process of each working condition is independent of each other by extracting sequentially. After the calibration of each working condition is completed, the cold heading mold is allowed to cool to room temperature before the next working condition is carried out, so as to avoid mutual interference between working conditions at different temperatures and ensure the reliability of the working condition calibration parameters.

[0028] S3. Based on the extracted test condition parameters, identify the target test bar set, and based on the target test bar set and cold heading die, obtain the measured die temperature set, peak acceleration increment set, and pulse width ratio set.

[0029] Specifically, the acquisition of the measured die temperature set, peak acceleration increment set, and pulse width ratio set based on the target test bar set and cold heading die includes: For each target test bar in the target test bar set, perform the following operations: The peak acceleration and pulse width under no-load conditions are obtained. Data is collected on the target test bar based on the cold heading die to obtain the measured die temperature, peak acceleration and pulse width. The peak acceleration increment is calculated based on the no-load peak acceleration and the peak acceleration, and the pulse width ratio is calculated based on the no-load pulse width and the pulse width. The measured mold temperature, peak acceleration increment, and pulse width ratio are summarized to obtain the measured mold temperature set, peak acceleration increment set, and pulse width ratio set.

[0030] It should be explained that the detailed steps for obtaining the no-load peak acceleration and no-load pulse width, and for collecting data from the target test bar stock based on the cold heading die to obtain the measured die temperature, peak acceleration, and pulse width, will be given later and will not be repeated here. The target test bar stock set is a collection of metal bars prepared for a specific test condition (such as testing at low temperature, normal temperature, or high temperature) during the establishment of the vibration-temperature reference process (i.e., a set of tests conducted after the initial use of the equipment, or after changing the material grade, or changing the fastener specification). The step of calculating the peak acceleration increment based on the no-load peak acceleration and peak acceleration is: subtracting the no-load peak acceleration from the peak acceleration to obtain the acceleration, i.e., the peak acceleration increment. The step of calculating the pulse width ratio based on the no-load pulse width and pulse width is: using the pulse width divided by the no-load pulse width to obtain the ratio, i.e., the pulse width ratio. This invention obtains the pulse width ratio by dividing the working pulse width by the idle pulse width, effectively eliminating the influence of the cold heading machine's own vibration characteristics on the measurement. This ensures that the pulse width ratio only reflects the plastic deformation characteristics of the metal bar during the cold heading process. The measured die temperature set is a collection of measured die temperatures. The peak acceleration increment set is a collection of peak acceleration increments. The pulse width ratio set is a collection of pulse width ratios.

[0031] Specifically, obtaining the no-load peak acceleration and no-load pulse width includes: Once the unloaded distance section is identified, the cold heading machine is started. Based on the unloaded distance section and the triaxial accelerometer, unloaded data is collected on the cold heading machine after it is started to obtain the unloaded vibration acceleration set. The absolute value operation is performed on the set of no-load vibration acceleration to obtain the set of absolute values ​​of no-load vibration acceleration, and the peak acceleration of no-load is extracted from the set of absolute values ​​of no-load vibration acceleration. The peak value of the no-load descent acceleration is obtained by multiplying the peak no-load acceleration by a preset descent percentage, and the peak value of the no-load rise acceleration is obtained by multiplying the peak no-load acceleration by a preset rise percentage. The descent acceleration time and the ascent acceleration time under no-load conditions were determined based on the peak values ​​of the descent acceleration and ascent acceleration under no-load conditions. The no-load pulse width is calculated based on the no-load descent acceleration time and the no-load ascent acceleration time.

[0032] It should be explained that the no-load distance segment is the travel segment of the punch during its forward movement, from the start of its forward motion to just before contact with the target test bar. Within this segment, the punch has begun to move forward, but a certain distance (e.g., 1-3 mm) remains between its tip and the target test bar, and contact has not yet occurred. The no-load data acquisition of the cold heading machine after startup, based on the no-load distance segment and a triaxial accelerometer, involves recording the vibration acceleration signal of the punch within this no-load distance segment using a triaxial accelerometer. The no-load vibration acceleration set is the collection of the punch's vibration accelerations collected by the triaxial accelerometer within the no-load distance segment. The operation of taking the absolute value of the no-load vibration acceleration set involves taking the absolute value of each no-load vibration acceleration in the set. The no-load vibration acceleration absolute value set is a new set obtained by taking the absolute value of each no-load vibration acceleration in the no-load vibration acceleration set. The peak no-load acceleration is the largest absolute value of no-load vibration acceleration in the set of absolute no-load vibration acceleration values. The percentage decrease is a pre-set percentage used to calculate the peak value of the no-load decreasing acceleration. The peak value of the no-load decreasing acceleration is the acceleration obtained by multiplying the peak no-load acceleration by the percentage decrease (e.g., 90%). The percentage increase is a pre-set percentage used to calculate the peak value of the no-load increasing acceleration. The percentage decrease and percentage increase are set as follows: Based on the vibration waveform collected from multiple no-load measurements of the cold heading machine, extract the peak acceleration from each measurement, as well as the acceleration value when the waveform first reaches 10% of the peak value during its rise from the lowest point. Calculate the ratio of this acceleration value to the peak acceleration, and average the ratios of all measurements to obtain the percentage increase. Similarly, extract the peak acceleration from each measurement, as well as the acceleration value when the waveform first drops to 90% of the peak value during its decline from the peak. Calculate the ratio of this acceleration value to the peak acceleration, and average the ratios to obtain the percentage decrease.

[0033] Importantly, the peak unloaded upward acceleration is obtained by multiplying the peak unloaded acceleration by the percentage increase (e.g., 10%). The step of determining the unloaded downward acceleration time and unloaded upward acceleration time based on the peak unloaded downward acceleration and peak unloaded upward acceleration is as follows: A vibration acceleration curve is constructed based on the set of absolute values ​​of unloaded vibration acceleration, where the horizontal axis of the vibration acceleration curve represents time, and the vertical axis represents the absolute value of unloaded vibration acceleration. The starting point of the vibration acceleration curve is used as the search starting point for the upward segment, and this search starting point is recorded as the first search starting point. Starting from the first search starting point, the absolute value of unloaded vibration acceleration on the vibration acceleration curve is scanned point by point along the positive time axis (i.e., the direction of time increase). Each scanned absolute value of unloaded vibration acceleration is compared with the peak unloaded upward acceleration to determine whether the current acceleration value is greater than or equal to the peak unloaded upward acceleration. When the first scanned absolute value of unloaded vibration acceleration is greater than or equal to the peak unloaded upward acceleration... When a point is reached, the scanning stops, and the time corresponding to that point is recorded as the no-load rising acceleration time. Based on the no-load peak acceleration, the position corresponding to the no-load peak acceleration is found from the vibration acceleration curve, and this position is recorded as the peak point, and its time is the peak time. Taking the peak point as the starting point, the first time point after the peak point is taken as the search starting point of the falling segment, and recorded as the second search starting point. Starting from the second search starting point, the absolute value of the no-load vibration acceleration on the vibration acceleration curve is scanned point by point along the positive time axis. Each scanned absolute value of the no-load vibration acceleration is compared with the peak value of the no-load falling acceleration to determine whether the current absolute value of the no-load vibration acceleration is less than or equal to the peak value of the no-load falling acceleration. When the first point where the absolute value of the no-load vibration acceleration is less than or equal to the peak value of the no-load falling acceleration is scanned, the scanning stops, and the time corresponding to that point is recorded as the no-load falling acceleration time. The no-load pulse width is the time interval in the punch vibration acceleration curve when the cold heading machine is running under no-load conditions (i.e., when the punch is moving forward but has not yet contacted the target test bar). It is the time interval from the first time the waveform in the rising phase reaches the peak value of the no-load rising acceleration to the first time the waveform in the falling phase drops to the peak value of the no-load falling acceleration.

[0034] It should be noted that, in the above steps of this invention, to avoid interference from irrelevant travel data during the no-load operation of the cold heading machine and to ensure consistent and controllable acquisition conditions, this invention first defines an unloaded distance segment. Then, to obtain the vibration acceleration signal throughout the entire no-load operation of the cold heading machine, after defining the unloaded distance segment, the cold heading machine is started, and a triaxial accelerometer is used to collect the unloaded vibration acceleration set within the unloaded distance segment. Subsequently, because acceleration has positive and negative directions, which can easily cause numerical interference and is not conducive to uniformly identifying vibration amplitude and stably extracting the unloaded peak acceleration, this invention performs absolute value processing on the collected unloaded vibration acceleration set to obtain the unloaded vibration acceleration absolute value set. Furthermore, because it is necessary to uniformly set the judgment criteria for acceleration rise and fall and reduce the deviation caused by subjective human judgment, the percentage decrease and percentage increase are respectively... Multiplying the peak acceleration under no-load conditions with the peak acceleration under no-load conditions yields the peak acceleration under no-load conditions for both the descent and ascent. These two peak values ​​are then used as threshold values. The corresponding times of these threshold values ​​are retrieved from the vibration acceleration curve to determine the duration of the acceleration descent and ascent processes. Combined with the dynamic law of acceleration changing over time, the pulse change characteristics of the vibration signal of the cold heading machine under no-load conditions are quantified. The no-load pulse width can then be calculated based on these two determined time periods. This ensures the consistency and repeatability of the no-load characteristic parameter acquisition, while eliminating the influence of directional interference, human error, and invalid data, effectively improving the objectivity and accuracy of the no-load peak acceleration and no-load pulse width detection results.

[0035] In detail, the data acquisition based on the cold heading die on the target test bar to obtain the measured die temperature, peak acceleration, and pulse width includes: The target test bar is fed into the cold heading die to obtain the impact test bar. The punch in the cold heading machine and the preset sampling window are used to impact the test bar to obtain the punch vibration acceleration set and the temperature of the mold to be tested. The absolute value operation of each punch vibration acceleration in the punch vibration acceleration set is performed to obtain the absolute value set of acceleration. Calculate pulse width based on the set of absolute acceleration values, and extract peak acceleration from the set of absolute acceleration values; Temperature data is collected from the mold to be tested to obtain a mold temperature set. The maximum mold temperature is then identified from the mold temperature set and used as the actual measured mold temperature.

[0036] It should be explained that the test bar stock is the target test bar stock that has been introduced into the cold heading die and is awaiting impact by the punch. The sampling window is a time window before and after the punch impacts the test bar stock, during which vibration and temperature signals are collected. The punch vibration acceleration set is the collection of punch vibration accelerations collected by a triaxial accelerometer within the sampling window. The temperature-detecting die is the cold heading die after the target test bar stock has undergone cold heading, and its temperature rises due to the heat generated by the plastic deformation of the target test bar stock and frictional heat. The acceleration absolute value set is a new set obtained by taking the absolute value of each punch vibration acceleration in the punch vibration acceleration set. The method for calculating the pulse width based on the acceleration absolute value set is the same as the method for calculating the no-load pulse width based on the no-load vibration acceleration absolute value set, and will not be repeated here. The temperature acquisition of the mold to be tested involves continuously collecting the mold temperature within a 0.2-second time window after the punch impacts the bar stock, using thermocouples embedded in the cold heading mold. The mold temperature set is the collection of all temperature values ​​of the cold heading molds collected by thermocouples within the 0.2-second acquisition window after impact. The maximum mold temperature is the mold temperature that is highest in the mold temperature set. The measured mold temperature is the maximum mold temperature confirmed from the mold temperature set, representing the highest temperature reached by the cold heading mold after this cold heading process. The peak acceleration is the largest absolute acceleration value in the set of absolute acceleration values.

[0037] S4. Calculate the mean values ​​of the measured mold temperature set, peak acceleration increment set, and pulse width ratio set to obtain the working condition calibration parameters. The working condition calibration parameters include: average measured mold temperature, average peak acceleration increment, and average pulse width ratio.

[0038] It should be explained that the average measured mold temperature is the arithmetic mean of all measured mold temperature values ​​collected after multiple cold heading processes under the same test conditions (e.g., testing at low temperature, normal temperature, or high temperature). The average peak acceleration increment is the arithmetic mean of all peak acceleration increments calculated after multiple cold heading processes under the same test conditions. The average pulse width ratio is the arithmetic mean of all pulse width ratios calculated after multiple cold heading processes under the same test conditions.

[0039] S5. Summarize the operating condition calibration parameters to obtain the operating condition calibration parameter set, which includes: low temperature operating condition calibration parameters, normal operating condition calibration parameters, and high temperature operating condition calibration parameters.

[0040] It should be explained that the low-temperature calibration parameters are obtained by collecting, calculating, and averaging data from multiple target test bars under low-temperature testing conditions, and include the average measured die temperature, average peak acceleration increment, and average pulse width ratio. The normal operating condition calibration parameters are obtained by collecting, calculating, and averaging data from multiple target test bars under normal temperature testing conditions, and include the average measured die temperature, average peak acceleration increment, and average pulse width ratio. The high-temperature calibration parameters are obtained by collecting, calculating, and averaging data from multiple target test bars under high-temperature testing conditions, and include the average measured die temperature, average peak acceleration increment, and average pulse width ratio.

[0041] S6. Based on the working condition calibration parameter set, construct a calibration comparison table to identify the bar stock to be formed. Based on the cold heading machine and the bar stock to be formed, perform characteristic value acquisition operations to obtain relative characteristic parameters.

[0042] It should be explained that the bar stock to be formed refers to the metal bar stock awaiting cold heading during the normal production stage. The method for acquiring feature values ​​based on the cold heading machine and the bar stock to be formed is the same as the method for acquiring data from the target test bar stock based on the cold heading die to obtain the measured die temperature, peak acceleration, and pulse width, and will not be repeated here. The relative feature parameters are a set including the ratio of the peak acceleration increment of the bar stock to the pulse width of the bar stock to be formed.

[0043] In detail, the construction of the calibration comparison table based on the operating condition calibration parameter set includes: Extract the low-temperature average peak acceleration increment and the low-temperature average pulse width ratio from the low-temperature calibration parameters in the calibration parameter set. Extract the average peak acceleration increment at normal temperature, the average pulse width ratio at normal temperature, the average peak acceleration increment at high temperature, and the average pulse width ratio at high temperature from the calibration parameters under normal operating conditions and high temperature operating conditions, respectively. The set of correction intervals is determined based on the increment of average peak acceleration at low temperature, the ratio of average pulse width at low temperature, the increment of average peak acceleration at normal temperature, the ratio of average pulse width at normal temperature, the increment of average peak acceleration at high temperature, and the ratio of average pulse width at high temperature. The set of correction intervals includes: the correction interval for low temperature, the correction interval for normal temperature, and the correction interval for high temperature. A calibration reference table is constructed based on the calibration interval set.

[0044] It should be explained that the low-temperature average peak acceleration increment and the low-temperature average pulse width ratio are the average values ​​of the peak acceleration increment and pulse width ratio corresponding to all test bars at low temperatures. The normal-temperature average peak acceleration increment and the normal-temperature average pulse width ratio are the average values ​​of the peak acceleration increment and pulse width ratio corresponding to all test bars at normal temperatures. The high-temperature average peak acceleration increment and the high-temperature average pulse width ratio are the average values ​​of the peak acceleration increment and pulse width ratio corresponding to all test bars at high temperatures. The detailed steps for determining the correction interval set based on the low-temperature average peak acceleration increment, the low-temperature average pulse width ratio, the normal-temperature average peak acceleration increment, the normal-temperature average pulse width ratio, the high-temperature average peak acceleration increment, and the high-temperature average pulse width ratio will be given later and will not be repeated here.

[0045] Specifically, the step of determining the correction interval set based on the low-temperature average peak acceleration increment, the low-temperature average pulse width ratio, the normal-temperature average peak acceleration increment, the normal-temperature average pulse width ratio, the high-temperature average peak acceleration increment, and the high-temperature average pulse width ratio includes: The first acceleration threshold is calculated based on the average peak acceleration increment at low temperature and the average peak acceleration increment at normal temperature. The first pulse width threshold is calculated based on the ratio of average pulse width at low temperature and the ratio of average pulse width at normal temperature. The second acceleration threshold and the second pulse width threshold are calculated based on the average peak acceleration increment at normal temperature, the average peak acceleration increment at high temperature, the ratio of average pulse width at normal temperature and the ratio of average pulse width at high temperature. The normal temperature acceleration range and the normal temperature pulse width range are constructed based on the first acceleration boundary threshold, the second acceleration boundary threshold, the first pulse width boundary threshold, and the second pulse width boundary threshold. A low-temperature acceleration range and a low-temperature pulse width range are constructed based on a first acceleration boundary threshold and a first pulse width boundary threshold, and a high-temperature acceleration range and a high-temperature pulse width range are constructed based on a second acceleration boundary threshold and a second pulse width boundary threshold. The set of correction intervals was determined based on the normal temperature acceleration interval, normal temperature pulse width interval, low temperature acceleration interval, low temperature pulse width interval, high temperature acceleration interval, and high temperature pulse width interval.

[0046] It should be explained that the first acceleration boundary threshold is a value obtained by averaging the ratio of the average pulse width at low temperature and the ratio of the average pulse width at normal temperature. This threshold serves as the dividing line between the peak acceleration at the test low temperature and the test normal temperature, distinguishing the range of acceleration increments between the low temperature and normal temperature ranges. The first pulse width boundary threshold is a value obtained by averaging the ratio of the average pulse width at low temperature and the ratio of the average pulse width at normal temperature. This threshold serves as the dividing line between the pulse width at the test low temperature and the test normal temperature, defining the range of pulse width ratios between the low temperature and normal temperature ranges. The method for calculating the second acceleration boundary threshold and the second pulse width boundary threshold based on the average peak acceleration increment at normal temperature, the average peak acceleration increment at high temperature, the ratio of the average pulse width at normal temperature, and the ratio of the average pulse width at high temperature is the same as the method for calculating the first acceleration boundary threshold and the first pulse width boundary threshold based on the average peak acceleration increment at low temperature, the average peak acceleration increment at normal temperature, the ratio of the average pulse width at low temperature, and the ratio of the average pulse width at normal temperature, and will not be repeated here. The second acceleration threshold is a value obtained by averaging the average peak acceleration increment at normal temperature and the average peak acceleration increment at high temperature. This threshold serves as the dividing line between the peak acceleration at normal test temperature and high test temperature, and is used to distinguish the range of acceleration increment values ​​between the normal temperature range and the high temperature range.

[0047] Understandably, the second pulse width threshold is a value obtained by averaging the average pulse width ratio at normal temperature and the average pulse width ratio at high temperature. This threshold serves as the dividing line between the pulse width ratio at normal test temperature and high test temperature, distinguishing the range of pulse width ratio values ​​for the normal temperature range and the high temperature range. The normal temperature acceleration range is defined by the first acceleration threshold as the lower limit and the second acceleration threshold as the upper limit. The normal temperature pulse width range is defined by the first pulse width threshold as the lower limit and the second pulse width threshold as the upper limit. The low temperature acceleration range is the range greater than or equal to the first acceleration threshold. The low temperature pulse width range is the range less than or equal to the first pulse width threshold. The high temperature acceleration range is the range less than or equal to the second acceleration threshold. The high temperature pulse width range is the range greater than or equal to the second pulse width threshold. The calibration interval set includes the normal temperature acceleration range, the normal temperature pulse width range, the low temperature acceleration range, the low temperature pulse width range, the high temperature acceleration range, and the high temperature pulse width range.

[0048] S7. Compare the relative characteristic parameters with the calibration reference table to obtain the cold heading temperature range, obtain the current cooling nozzle injection pulse width value, and calculate and update the nozzle injection pulse width value based on the cold heading temperature range and the current cooling nozzle injection pulse width value.

[0049] It should be explained that the cold heading temperature range is determined by comparing the relative characteristic parameters with a calibration table, based on the region where the relative characteristic parameters fall. The current cooling nozzle injection pulse width value is the parameter currently in use to control the duration of cooling medium injection.

[0050] Specifically, the calculation and updating of the nozzle injection pulse width value based on the cold heading temperature range and the current cooling nozzle injection pulse width value includes: To obtain a relatively low cooling attenuation coefficient and a relatively high cooling enhancement coefficient; If the cold heading temperature range is the low-temperature correction range, then the current cooling nozzle injection pulse width value is corrected using the low cooling attenuation coefficient to obtain the first corrected injection pulse width value. If the first corrected injection pulse width value is less than the preset minimum injection pulse width value, then the first corrected injection pulse width value is replaced by the preset zero value to obtain the replaced injection pulse width value. If the cold heading temperature range is within the normal calibration temperature range, then the current cooling nozzle injection pulse width value will be taken as the qualified nozzle injection pulse width value. If the cold heading temperature range is the correction high temperature range, then the current cooling nozzle injection pulse width value is corrected by using the higher cooling enhancement coefficient to obtain the second corrected injection pulse width value. If the second corrected injection pulse width value is greater than the preset maximum injection pulse width value, then the second corrected injection pulse width value is assigned a value using the maximum injection pulse width value to obtain the assigned injection pulse width value. The updated nozzle injection pulse width value is determined based on the first corrected injection pulse width value, the replaced injection pulse width value, the qualified nozzle injection pulse width value, the second corrected injection pulse width value, or the assigned injection pulse width value.

[0051] It should be explained that the detailed steps for obtaining the low cooling attenuation coefficient and the high cooling enhancement coefficient will be given later and will not be repeated here. If the cold heading temperature range is the corrected low temperature range, it means that the metal material temperature is low, hardness is high, and plasticity is poor during the cold heading process of the current bar stock, resulting in strong impact vibration. It is necessary to reduce cooling to raise the temperature of the cold heading die, thereby improving the metal's forming performance. The first corrected spray pulse width value is the product of the low cooling attenuation coefficient and the current cooling nozzle spray pulse width value. The minimum spray pulse width value is a preset threshold to prevent insufficient cooling effect or nozzle response failure due to excessively short spray time. The zero value is 0. The replaced spray pulse width value is the spray pulse width value obtained by replacing the first corrected spray pulse width value with the zero value when the first corrected spray pulse width value is less than the minimum spray pulse width value. If the cold heading temperature range is within the calibrated normal temperature range, it indicates that the metal material temperature, hardness, and plasticity are at a good level during the cold heading process, resulting in stable forming quality and no need to adjust the cooling amount. The qualified nozzle pulse width value is the current cooling nozzle pulse width value corresponding to the cold heading temperature range being within the calibrated normal temperature range. If the cold heading temperature range is within the calibrated high temperature range, it indicates that the metal material temperature is too high, hardness is low, and plasticity is good during the cold heading process, leading to smooth impact vibration. Increased cooling is required to lower the cold heading mold temperature and prevent the metal from becoming too soft, which could cause forming defects. The second calibrated pulse width value is the product of the higher cooling enhancement coefficient and the current cooling nozzle pulse width value. The maximum pulse width value is a preset threshold to prevent excessive cooling or waste of cooling medium due to prolonged nozzle spraying time. The assigned pulse width value is the pulse width value obtained by assigning the maximum pulse width value when the second calibrated pulse width value is greater than the preset maximum pulse width value.

[0052] Importantly, the minimum and maximum injection pulse width values ​​are set as follows: based on the response characteristics of the solenoid valve of the cooling nozzle, the following timeframes are determined experimentally: the time from when the controller sends an open signal (solenoid valve is energized) to when the solenoid valve core is fully open and coolant begins to spray (called the open response time), and the time from when the controller sends a close signal (i.e., the solenoid valve is de-energized) to when the solenoid valve core is fully closed and coolant spray stops (i.e., the close response time). After receiving the open command, the solenoid valve requires a certain reaction time to fully open. If the injection pulse width (i.e., the energizing time) is less than this reaction time, the solenoid valve receives the close command before it has fully opened, and the coolant cannot be sprayed normally or the spray volume is severely insufficient. Therefore, the larger of the open and close response times is taken and multiplied by a safety factor of 1.2 as the minimum injection pulse width value to ensure that the solenoid valve cannot reliably open when the injection pulse width is lower than this value. In this case, cooling will be stopped once to avoid ineffective spraying. Secondly, based on the process requirements of cold heading of fasteners, experiments determined that under extreme high-temperature conditions, the temperature of the cold heading die gradually decreases as the spraying time of the cooling nozzle increases. However, after the spraying time increases to a certain extent, further increasing the spraying time has a negligible effect on reducing the die temperature. The spraying time corresponding to this point is called the saturation spraying time. 90% of the saturation spraying time (i.e., multiplied by a safety factor of 0.9) is taken as the maximum spraying pulse width value to avoid excessive spraying of cooling medium, resulting in waste and overcooling. The cooling nozzle is a spraying device installed near the cold heading die, used to spray the cooling medium (such as emulsion, cooling oil, water-based coolant, etc.) into the die surface or punch surface in a mist or columnar form.

[0053] It should be noted that, in the above steps of this invention, since a single fixed parameter cannot adapt to the cooling control requirements of different temperature ranges, this invention sets a lower cooling attenuation coefficient and a higher cooling enhancement coefficient to form a differentiated control logic that reduces cooling intensity at low temperatures and increases cooling intensity at high temperatures. Because the temperature rise of the cold heading mold itself is low under low temperature conditions, it does not require a large cooling flow rate. Therefore, when the cold heading temperature is in the corrected low temperature range, a lower cooling attenuation coefficient is used to attenuate and correct the current cooling nozzle spray pulse width value to obtain a first corrected spray pulse width value. This reduces the nozzle spray duration, reduces cooling input, and saves cooling medium consumption. Furthermore, because if the corrected spray pulse width is too small, it will exceed the controllable working range of the equipment, which may easily cause abnormal spray pulse width and equipment control failure, when the first corrected spray pulse width value is less than the minimum spray pulse width value, a zero value is used to replace it to obtain the replaced spray pulse width value, thereby limiting the minimum output value of the nozzle spray pulse width under low temperature conditions. Since the temperature of the cold heading die is within a reasonable range within the calibrated normal temperature range, stable operation can be maintained without modifying cooling parameters. Therefore, when the cold heading temperature falls within the calibrated normal temperature range, the current cooling nozzle pulse width value is directly used as the qualified nozzle pulse width value, avoiding operational fluctuations caused by meaningless parameter adjustments. Because the temperature rise of the cold heading die is high under high-temperature conditions, increased cooling and heat dissipation are required. Therefore, when the cold heading temperature is within the calibrated high-temperature range, a higher cooling enhancement coefficient is used to enhance and correct the current cooling nozzle pulse width value, resulting in a second corrected pulse width value. This amplifies the pulse width, extends the nozzle spray duration, and improves the cooling and heat dissipation effect. Furthermore, if the corrected pulse width is too large, it will exceed the maximum output capacity of the equipment, easily causing overcooling and equipment overload. Therefore, in the second corrected pulse width... When the width value is greater than the maximum spray pulse width value, the maximum spray pulse width value is directly assigned to obtain the assigned spray pulse width value, thereby limiting the upper limit of the spray pulse width output under high temperature conditions. Based on the first corrected spray pulse width value, the replaced spray pulse width value, the qualified nozzle spray pulse width value, the second corrected spray pulse width value, or the assigned spray pulse width value corresponding to different temperature ranges, the final updated nozzle spray pulse width value can be determined. It is precisely by using interval coefficient correction combined with upper and lower limit thresholds (i.e., minimum spray pulse width value and maximum spray pulse width value) to limit the amplitude that not only can the cooling spray intensity be adaptively matched according to the actual temperature of the cold heading, but also the spray pulse width can be constrained within the reasonable working range of the equipment, thereby ensuring the stability of the cold heading mold temperature control and the standardization of the cooling adjustment logic, while taking into account the safety of equipment operation and the rational use of cooling resources.

[0054] Specifically, obtaining the relatively low cooling attenuation coefficient and the relatively high cooling enhancement coefficient includes: Obtain the test fastener set, and perform the following operations on each test fastener in the test fastener set: The initial low cooling attenuation coefficient and the initial high cooling enhancement coefficient were identified. The test fasteners are cold-forged to obtain the fastener temperature range. The adjustment temperature parameters are obtained based on the fastener temperature range and the initial low cooling attenuation coefficient. Summarize the temperature adjustment parameters to obtain a set of temperature adjustment parameters. Based on the set of temperature adjustment parameters, identify the number of times the adjustment was normal, the number of times the adjustment was too low, and the number of times the adjustment was too high. Based on the total number of adjustments to the test fastener set, the low cooling attenuation coefficient is calculated based on the total number of adjustments, the number of normal adjustments, the number of low adjustments, and the number of high adjustments. The higher cooling enhancement factor is calculated based on the test fastener set and the initial higher cooling enhancement factor.

[0055] It should be explained that the test fastener set is a collection of fastener samples used for self-learning optimization of the cooling adjustment coefficient. The initial low cooling attenuation coefficient is the initial value of the low cooling attenuation coefficient before the start of self-learning optimization. The initial high cooling enhancement coefficient is the initial value of the high cooling enhancement coefficient before the start of self-learning optimization. It should be understood that both the initial low cooling attenuation coefficient and the initial high cooling enhancement coefficient are the optimal values ​​saved after the last optimization. The method for obtaining the fastener temperature range by performing cold heading operation on the test fastener is the same as the method for obtaining the cold heading temperature range based on the bar stock to be formed, and will not be repeated here. The fastener temperature range is the temperature range of the fastener during cold heading after performing cold heading operation on a fastener, determined by comparing the relative characteristic parameters with the calibration reference table. The method for obtaining the adjustment temperature parameter based on the fastener temperature range and the initial low cooling attenuation coefficient is the same as the method for calculating and updating the nozzle injection pulse width value based on the cold heading temperature range and the current cooling nozzle injection pulse width value, and will not be repeated here.

[0056] Understandably, the adjusted temperature parameter is a classification identifier recorded based on the temperature range determination result after cold forging the test fasteners. This classification identifier is either a low-temperature correction range, a normal correction range, or a high-temperature correction range. The adjusted temperature parameter set is a collection obtained by summing the adjusted temperature parameters of each fastener in the test fastener set after cold forging all fasteners. The number of times the adjustment is normal is the number of fasteners in the test fastener set whose temperature range is determined to be within the normal correction range. The number of times the adjustment is too low is the number of fasteners in the test fastener set whose temperature range is determined to be within the low-temperature correction range. The number of times the adjustment is too high is the number of fasteners in the test fastener set whose temperature range is determined to be within the high-temperature correction range. The total number of adjustments is the total number of fasteners in the test fastener set. The low-cooling attenuation coefficient is a coefficient calculated by formula based on the initial low-cooling attenuation coefficient, combined with the total number of adjustments, the number of low-adjustments, the number of high-adjustments, and the preset adjustment step size. The method for calculating the high cooling enhancement coefficient based on the test fastener set and the initial high cooling enhancement coefficient is the same as the method for obtaining the low cooling attenuation coefficient based on the initial low cooling attenuation coefficient and the test fastener set, and will not be described again here. The high cooling enhancement coefficient is a new coefficient calculated based on the temperature range statistical results of the test fastener set using an optimization algorithm similar to that used for the low cooling attenuation coefficient.

[0057] In detail, the formula for calculating the relatively low cooling attenuation coefficient is as follows:

[0058] in, This indicates a low cooling attenuation coefficient. This indicates an initially low cooling attenuation coefficient. This indicates the preset adjustment step size. This indicates that the number of adjustments was too low. This indicates that the number of adjustments was too high. This indicates an adjustment to the total number.

[0059] It should be noted that the adjustment step size is a pre-set value used to control the magnitude of each optimization adjustment for the low cooling attenuation coefficient. The adjustment step size is set as follows: Under normal operating conditions of the cold heading machine, based on an initial low cooling attenuation coefficient of 0.8 and an initial high cooling enhancement coefficient of 1.3, multiple sets of self-learning optimization experiments are conducted using different candidate step size values ​​(such as 0.005, 0.008, 0.010, 0.012, 0.015, and 0.020). For each set of experiments, the temperature range judgment results of 200 fasteners are continuously collected, and the temperature pass rate (i.e., the proportion judged as normal) of each set of experiments is calculated. The step size value that results in the highest temperature pass rate is selected as the final adjustment step size.

[0060] Importantly, the above-mentioned formula for calculating the low cooling attenuation coefficient uses the initial low cooling attenuation coefficient as a base value. It uses the adjustment step size to limit the change in the low cooling attenuation coefficient in a single correction. Then, it divides the difference between the number of adjustments for low and high temperatures by the total number of adjustments to reflect the overall distribution difference between low and high temperatures in the working conditions. The initial low cooling attenuation coefficient is then compensated and corrected in a linear manner. Furthermore, based on the statistical results of the actual temperature adjustment after the cold heading of the fasteners, the initial low cooling attenuation coefficient is adaptively fine-tuned to make the calculated low cooling attenuation coefficient match the actual cold heading temperature change law. This is used to accurately correct the cooling nozzle spray pulse width under subsequent low temperature conditions, eliminating the problem of mismatch between the fixed initial low cooling attenuation coefficient and the actual working conditions, and improving the accuracy and applicability of the cooling spray pulse width adjustment.

[0061] S8. Cold heading of fasteners with intelligent temperature control based on updated nozzle pulse width values.

[0062] It should be noted that this invention applies the updated nozzle pulse width value to the cooling control of the next fastener, realizing a fully automatic closed-loop control process of data acquisition, temperature range determination, cooling pulse width adjustment, and repeated cycles. The entire process requires no manual intervention, reducing the technical requirements for operators. At the same time, based on precise temperature control, it can effectively reduce molding defects caused by improper temperature (such as folding, incomplete filling, sticking to the mold, etc.), thereby reducing the scrap rate and improving material utilization.

[0063] To address the problems described in the background art, this invention identifies a cold heading machine, a cold heading die, and a set of test condition parameters. The cold heading machine includes a triaxial accelerometer and a punch. The test condition parameter set includes low-temperature testing, normal-temperature testing, and high-temperature testing. This invention comprehensively covers various temperature states that may occur during the cold heading process of fasteners by using three typical testing conditions: low-temperature testing, normal-temperature testing, and high-temperature testing. This provides a data foundation for establishing a complete temperature-vibration mapping relationship. Test condition parameters are extracted sequentially from the set of test condition parameters, where each test condition parameter is either low-temperature testing, normal-temperature testing, or high-temperature testing. This sequential extraction method ensures that the calibration process for each condition is independent. Each completed calibration of a condition... After calibration, the system waits for the mold to cool to room temperature before proceeding to the next operating condition to avoid mutual interference between different temperature conditions and ensure the reliability and repeatability of the calibration parameters. Based on the extracted test condition parameters, the target test bar set is identified. Based on the target test bar set and the cold heading mold, the measured mold temperature set, peak acceleration increment set, and pulse width ratio set are obtained. This invention obtains the measured mold temperature set, peak acceleration increment set, and pulse width ratio set by repeatedly collecting data from multiple bars under each operating condition. This eliminates random errors in single measurements and improves the statistical reliability of the calibration data. The average values ​​of the measured mold temperature set, peak acceleration increment set, and pulse width ratio set are calculated to obtain the operating condition calibration parameters. The data includes: average measured mold temperature, average peak acceleration increment, and average pulse width ratio. This invention obtains typical characteristic values ​​for each operating condition by arithmetically averaging 10 measurement results. These typical values ​​represent the standard state under that operating condition, eliminating the influence of random fluctuations. The operating condition calibration parameters are then summarized to obtain a set of operating condition calibration parameters, which includes: low-temperature operating condition calibration parameters, normal operating condition calibration parameters, and high-temperature operating condition calibration parameters. This invention summarizes the calibration parameters for low-temperature, normal, and high-temperature operating conditions into a complete set of operating condition calibration parameters, forming a calibration database covering all temperatures from low to high. This provides complete data support for the subsequent construction of a calibration comparison table. A calibration comparison table is constructed based on the operating condition calibration parameter set to confirm... The invention involves collecting feature values ​​of the bar stock to be formed using a cold heading machine and the bar stock itself to obtain relative feature parameters. This feature value collection operation allows for real-time acquisition of the relative feature parameters of each fastener during normal production, enabling uninterrupted online temperature monitoring without stopping the machine. The relative feature parameters are compared with a calibration table to determine the cold heading temperature range. The current cooling nozzle pulse width value is also obtained. Based on the cold heading temperature range and the current cooling nozzle pulse width value, the nozzle pulse width value is calculated and updated. By comparing the relative feature parameters with a calibration table, this invention can quickly determine the current cold heading temperature range, achieving millisecond-level real-time temperature determination without the need for additional temperature sensors. Furthermore, it adjusts the cooling volume in real time.This invention ensures that each fastener is manufactured under molding conditions close to the target temperature, effectively reducing product quality variations caused by temperature fluctuations and improving batch consistency. It achieves intelligent temperature control for fastener cold heading based on updated nozzle pulse width values. Therefore, this invention can monitor the cold heading temperature in real time and automatically adjust the cooling amount.

[0064] like Figure 2 The diagram shown is a functional block diagram of a fastener cold heading system based on intelligent temperature control provided in an embodiment of the present invention.

[0065] The fastener cold heading system 100 based on intelligent temperature control described in this invention can be installed in an electronic device. Depending on the functions implemented, the fastener cold heading system 100 based on intelligent temperature control may include a working condition calibration preparation module 101, a calibration parameter acquisition module 102, a calibration lookup table construction module 103, and an intelligent temperature control decision module 104. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and which are stored in the memory of the electronic device. The working condition calibration preparation module 101 is used to identify the cold heading machine, cold heading mold and test working condition parameter set. The cold heading machine includes a triaxial accelerometer and a punch. The test working condition parameter set includes a test low temperature, a test normal temperature and a test high temperature. Test working condition parameters are extracted from the test working condition parameter set in sequence. The test working condition parameters are either test low temperature, test normal temperature or test high temperature. The calibration parameter acquisition module 102 is used to identify the target test bar set based on the extracted test condition parameters, and to obtain the measured mold temperature set, peak acceleration increment set, and pulse width ratio set based on the target test bar set and the cold heading die. The module then calculates the average of the measured mold temperature set, peak acceleration increment set, and pulse width ratio set to obtain the operating condition calibration parameters. These operating condition calibration parameters include: average measured mold temperature, average peak acceleration increment, and average pulse width ratio. Finally, the module summarizes the operating condition calibration parameters to obtain the operating condition calibration parameter set, which includes: low-temperature operating condition calibration parameters, normal operating condition calibration parameters, and high-temperature operating condition calibration parameters. The calibration comparison table construction module 103 is used to construct a calibration comparison table based on the working condition calibration parameter set, identify the bar stock to be formed, and perform feature value acquisition operations based on the cold heading machine and the bar stock to be formed to obtain relative feature parameters. The intelligent temperature control decision module 104 is used to compare the relative characteristic parameters with the calibration reference table to obtain the cold heading temperature range, obtain the current cooling nozzle injection pulse width value, calculate and update the nozzle injection pulse width value based on the cold heading temperature range and the current cooling nozzle injection pulse width value, and complete the intelligent temperature-controlled fastener cold heading based on the updated nozzle injection pulse width value.

[0066] In detail, the modules in the intelligent temperature-controlled fastener cold heading system 100 described in this embodiment of the invention employ the same methods as described above during use. Figure 1 The method used is the same as the cold heading method for fasteners based on intelligent temperature control described in the previous section, and can produce the same technical effect, so it will not be repeated here.

[0067] like Figure 3 The diagram shown is a structural schematic of an electronic device that implements a fastener cold heading method based on intelligent temperature control, according to an embodiment of the present invention.

[0068] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a fastener cold heading method program based on intelligent temperature control.

[0069] The memory 11 includes at least one type of readable storage medium, including flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as the portable hard drive of the electronic device 1. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code of a fastener cold heading method program based on intelligent temperature control, but also to temporarily store data that has been output or will be output.

[0070] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a fastener cold heading method program based on intelligent temperature control) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0071] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0072] Figure 3 Only electronic devices with components are shown; those skilled in the art will understand that... Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0073] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0074] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0075] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0076] The fastener cold heading method program based on intelligent temperature control, stored in the memory 11 of the electronic device 1, is a combination of multiple instructions. When run in the processor 10, it can achieve the following: The cold heading machine, cold heading mold, and test condition parameter set were identified. The cold heading machine includes a triaxial accelerometer and a punch. The test condition parameter set includes low temperature test, normal temperature test, and high temperature test. Test conditions are extracted sequentially from the set of test conditions parameters, where the test conditions parameters are low temperature test, normal temperature test, or high temperature test. Based on the extracted test condition parameters, the target test bar set was identified, and based on the target test bar set and the cold heading die, the measured die temperature set, peak acceleration increment set, and pulse width ratio set were obtained. The average values ​​of the measured mold temperature set, peak acceleration increment set, and pulse width ratio set are calculated to obtain the working condition calibration parameters. The working condition calibration parameters include: average measured mold temperature, average peak acceleration increment, and average pulse width ratio. The operating condition calibration parameters are summarized to obtain the operating condition calibration parameter set, which includes: low temperature operating condition calibration parameters, normal operating condition calibration parameters, and high temperature operating condition calibration parameters; A calibration comparison table is constructed based on the working condition calibration parameter set to identify the bar stock to be formed. Based on the cold heading machine and the bar stock to be formed, characteristic value acquisition operations are performed to obtain relative characteristic parameters. The relative characteristic parameters are compared with the calibration reference table to obtain the cold heading temperature range, the current cooling nozzle injection pulse width value is obtained, and the nozzle injection pulse width value is calculated and updated based on the cold heading temperature range and the current cooling nozzle injection pulse width value. Cold heading of fasteners with intelligent temperature control based on updated nozzle pulse width values.

[0077] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0078] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0079] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following: The cold heading machine, cold heading mold, and test condition parameter set were identified. The cold heading machine includes a triaxial accelerometer and a punch. The test condition parameter set includes low temperature test, normal temperature test, and high temperature test. Test conditions are extracted sequentially from the set of test conditions parameters, where the test conditions parameters are low temperature test, normal temperature test, or high temperature test. Based on the extracted test condition parameters, the target test bar set was identified, and based on the target test bar set and the cold heading die, the measured die temperature set, peak acceleration increment set, and pulse width ratio set were obtained. The average values ​​of the measured mold temperature set, peak acceleration increment set, and pulse width ratio set are calculated to obtain the working condition calibration parameters. The working condition calibration parameters include: average measured mold temperature, average peak acceleration increment, and average pulse width ratio. The operating condition calibration parameters are summarized to obtain the operating condition calibration parameter set, which includes: low temperature operating condition calibration parameters, normal operating condition calibration parameters, and high temperature operating condition calibration parameters; A calibration comparison table is constructed based on the working condition calibration parameter set to identify the bar stock to be formed. Based on the cold heading machine and the bar stock to be formed, characteristic value acquisition operations are performed to obtain relative characteristic parameters. The relative characteristic parameters are compared with the calibration reference table to obtain the cold heading temperature range, the current cooling nozzle injection pulse width value is obtained, and the nozzle injection pulse width value is calculated and updated based on the cold heading temperature range and the current cooling nozzle injection pulse width value. Cold heading of fasteners with intelligent temperature control based on updated nozzle pulse width values.

[0080] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0081] The modules described as separate components may or may not be physically separate. The components shown as modules 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 modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] Furthermore, the functional modules in the various embodiments of the present invention 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 in the form of hardware plus software functional modules.

[0083] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for cold heading fasteners based on intelligent temperature control, characterized in that, The method includes: The cold heading machine, cold heading mold, and test condition parameter set were identified. The cold heading machine includes a triaxial accelerometer and a punch. The test condition parameter set includes low temperature test, normal temperature test, and high temperature test. Test conditions are extracted sequentially from the set of test conditions parameters, where the test conditions parameters are low temperature test, normal temperature test, or high temperature test. Based on the extracted test condition parameters, the target test bar set was identified, and based on the target test bar set and the cold heading die, the measured die temperature set, peak acceleration increment set, and pulse width ratio set were obtained. The average values ​​of the measured mold temperature set, peak acceleration increment set, and pulse width ratio set are calculated to obtain the working condition calibration parameters. The working condition calibration parameters include: average measured mold temperature, average peak acceleration increment, and average pulse width ratio. The operating condition calibration parameters are summarized to obtain the operating condition calibration parameter set, which includes: low temperature operating condition calibration parameters, normal operating condition calibration parameters, and high temperature operating condition calibration parameters; A calibration comparison table is constructed based on the working condition calibration parameter set to identify the bar stock to be formed. Based on the cold heading machine and the bar stock to be formed, characteristic value acquisition operations are performed to obtain relative characteristic parameters. The relative characteristic parameters are compared with the calibration reference table to obtain the cold heading temperature range, the current cooling nozzle injection pulse width value is obtained, and the nozzle injection pulse width value is calculated and updated based on the cold heading temperature range and the current cooling nozzle injection pulse width value. Cold heading of fasteners with intelligent temperature control based on updated nozzle pulse width values.

2. The method for cold heading of fasteners based on intelligent temperature control as described in claim 1, characterized in that, The acquisition of the measured die temperature set, peak acceleration increment set, and pulse width ratio set based on the target test bar stock set and cold heading die includes: For each target test bar in the target test bar set, perform the following operations: The peak acceleration and pulse width under no-load conditions are obtained. Data is collected on the target test bar based on the cold heading die to obtain the measured die temperature, peak acceleration and pulse width. The peak acceleration increment is calculated based on the no-load peak acceleration and the peak acceleration, and the pulse width ratio is calculated based on the no-load pulse width and the pulse width. The measured mold temperature, peak acceleration increment, and pulse width ratio are summarized to obtain the measured mold temperature set, peak acceleration increment set, and pulse width ratio set.

3. The method for cold heading of fasteners based on intelligent temperature control as described in claim 2, characterized in that, The acquisition of the no-load peak acceleration and no-load pulse width includes: Once the unloaded distance section is identified, the cold heading machine is started. Based on the unloaded distance section and the triaxial accelerometer, unloaded data is collected on the cold heading machine after it is started to obtain the unloaded vibration acceleration set. The absolute value operation is performed on the set of no-load vibration acceleration to obtain the set of absolute values ​​of no-load vibration acceleration, and the peak acceleration of no-load is extracted from the set of absolute values ​​of no-load vibration acceleration. The peak value of the no-load descent acceleration is obtained by multiplying the peak no-load acceleration by a preset descent percentage, and the peak value of the no-load rise acceleration is obtained by multiplying the peak no-load acceleration by a preset rise percentage. The descent acceleration time and the ascent acceleration time under no-load conditions were determined based on the peak values ​​of the descent acceleration and ascent acceleration under no-load conditions. The no-load pulse width is calculated based on the no-load descent acceleration time and the no-load ascent acceleration time.

4. The method for cold heading fasteners based on intelligent temperature control as described in claim 3, characterized in that, The data acquisition based on the cold heading die for the target test bar, obtaining the measured die temperature, peak acceleration, and pulse width, includes: The target test bar is fed into the cold heading die to obtain the impact test bar. The punch in the cold heading machine and the preset sampling window are used to impact the test bar to obtain the punch vibration acceleration set and the temperature of the mold to be tested. The absolute value operation of each punch vibration acceleration in the punch vibration acceleration set is performed to obtain the absolute value set of acceleration. Calculate pulse width based on the set of absolute acceleration values, and extract peak acceleration from the set of absolute acceleration values; Temperature data is collected from the mold to be tested to obtain a mold temperature set. The maximum mold temperature is then identified from the mold temperature set and used as the actual measured mold temperature.

5. The method for cold heading fasteners based on intelligent temperature control as described in claim 4, characterized in that, The construction of the calibration comparison table based on the set of operating condition calibration parameters includes: Extract the low-temperature average peak acceleration increment and the low-temperature average pulse width ratio from the low-temperature calibration parameters in the calibration parameter set. Extract the average peak acceleration increment at normal temperature, the average pulse width ratio at normal temperature, the average peak acceleration increment at high temperature, and the average pulse width ratio at high temperature from the calibration parameters under normal operating conditions and high temperature operating conditions, respectively. The set of correction intervals is determined based on the increment of average peak acceleration at low temperature, the ratio of average pulse width at low temperature, the increment of average peak acceleration at normal temperature, the ratio of average pulse width at normal temperature, the increment of average peak acceleration at high temperature, and the ratio of average pulse width at high temperature. The set of correction intervals includes: the correction interval for low temperature, the correction interval for normal temperature, and the correction interval for high temperature. A calibration reference table is constructed based on the calibration interval set.

6. The method for cold heading fasteners based on intelligent temperature control as described in claim 5, characterized in that, The set of correction intervals determined based on the low-temperature average peak acceleration increment, the low-temperature average pulse width ratio, the normal-temperature average peak acceleration increment, the normal-temperature average pulse width ratio, the high-temperature average peak acceleration increment, and the high-temperature average pulse width ratio includes: The first acceleration threshold is calculated based on the average peak acceleration increment at low temperature and the average peak acceleration increment at normal temperature. The first pulse width threshold is calculated based on the ratio of average pulse width at low temperature and the ratio of average pulse width at normal temperature. The second acceleration threshold and the second pulse width threshold are calculated based on the average peak acceleration increment at normal temperature, the average peak acceleration increment at high temperature, the ratio of average pulse width at normal temperature and the ratio of average pulse width at high temperature. The normal temperature acceleration range and the normal temperature pulse width range are constructed based on the first acceleration boundary threshold, the second acceleration boundary threshold, the first pulse width boundary threshold, and the second pulse width boundary threshold. A low-temperature acceleration range and a low-temperature pulse width range are constructed based on a first acceleration boundary threshold and a first pulse width boundary threshold, and a high-temperature acceleration range and a high-temperature pulse width range are constructed based on a second acceleration boundary threshold and a second pulse width boundary threshold. The set of correction intervals was determined based on the normal temperature acceleration interval, normal temperature pulse width interval, low temperature acceleration interval, low temperature pulse width interval, high temperature acceleration interval, and high temperature pulse width interval.

7. The method for cold heading fasteners based on intelligent temperature control as described in claim 6, characterized in that, The calculation and updating of the nozzle injection pulse width value based on the cold heading temperature range and the current cooling nozzle injection pulse width value includes: To obtain a relatively low cooling attenuation coefficient and a relatively high cooling enhancement coefficient; If the cold heading temperature range is the low-temperature correction range, then the current cooling nozzle injection pulse width value is corrected using the low cooling attenuation coefficient to obtain the first corrected injection pulse width value. If the first corrected injection pulse width value is less than the preset minimum injection pulse width value, then the first corrected injection pulse width value is replaced by the preset zero value to obtain the replaced injection pulse width value. If the cold heading temperature range is within the normal calibration temperature range, then the current cooling nozzle injection pulse width value will be taken as the qualified nozzle injection pulse width value. If the cold heading temperature range is the correction high temperature range, then the current cooling nozzle injection pulse width value is corrected by using the higher cooling enhancement coefficient to obtain the second corrected injection pulse width value. If the second corrected injection pulse width value is greater than the preset maximum injection pulse width value, then the second corrected injection pulse width value is assigned a value using the maximum injection pulse width value to obtain the assigned injection pulse width value. The updated nozzle injection pulse width value is determined based on the first corrected injection pulse width value, the replaced injection pulse width value, the qualified nozzle injection pulse width value, the second corrected injection pulse width value, or the assigned injection pulse width value.

8. The method for cold heading of fasteners based on intelligent temperature control as described in claim 7, characterized in that, The process of obtaining the low cooling attenuation coefficient and the high cooling enhancement coefficient includes: Obtain the test fastener set, and perform the following operations on each test fastener in the test fastener set: The initial low cooling attenuation coefficient and the initial high cooling enhancement coefficient were identified. The test fasteners are cold-forged to obtain the fastener temperature range. The adjustment temperature parameters are obtained based on the fastener temperature range and the initial low cooling attenuation coefficient. Summarize the temperature adjustment parameters to obtain a set of temperature adjustment parameters. Based on the set of temperature adjustment parameters, identify the number of times the adjustment was normal, the number of times the adjustment was too low, and the number of times the adjustment was too high. Based on the total number of adjustments to the test fastener set, the low cooling attenuation coefficient is calculated based on the total number of adjustments, the number of normal adjustments, the number of low adjustments, and the number of high adjustments. The higher cooling enhancement factor is calculated based on the test fastener set and the initial higher cooling enhancement factor.

9. The method for cold heading of fasteners based on intelligent temperature control as described in claim 8, characterized in that, The formula for calculating the relatively low cooling attenuation coefficient is as follows: ， in, This indicates a low cooling attenuation coefficient. This indicates an initially low cooling attenuation coefficient. This indicates the preset adjustment step size. This indicates that the number of adjustments was too low. This indicates that the number of adjustments was too high. This indicates an adjustment to the total number.

10. A fastener cold heading system based on intelligent temperature control, characterized in that, The system includes: The working condition calibration preparation module is used to identify the cold heading machine, cold heading mold, and test working condition parameter set. The cold heading machine includes a triaxial accelerometer and a punch. The test working condition parameter set includes test low temperature, test normal temperature, and test high temperature. Test working condition parameters are extracted from the test working condition parameter set in sequence. The test working condition parameters are test low temperature, test normal temperature, or test high temperature. The calibration parameter acquisition module is used to identify the target test bar set based on the extracted test condition parameters. Based on the target test bar set and the cold heading die, it obtains the measured die temperature set, peak acceleration increment set, and pulse width ratio set. The mean values ​​of the measured die temperature set, peak acceleration increment set, and pulse width ratio set are calculated to obtain the working condition calibration parameters. The working condition calibration parameters include: average measured die temperature, average peak acceleration increment, and average pulse width ratio. The working condition calibration parameters are summarized to obtain the working condition calibration parameter set, which includes: low temperature working condition calibration parameters, normal working condition calibration parameters, and high temperature working condition calibration parameters. The calibration comparison table construction module is used to construct a calibration comparison table based on the working condition calibration parameter set, identify the bar stock to be formed, and perform feature value acquisition operations based on the cold heading machine and the bar stock to be formed to obtain relative feature parameters; The intelligent temperature control decision module is used to compare the relative characteristic parameters with the calibration reference table to obtain the cold heading temperature range, obtain the current cooling nozzle injection pulse width value, calculate and update the nozzle injection pulse width value based on the cold heading temperature range and the current cooling nozzle injection pulse width value, and complete the intelligent temperature-controlled fastener cold heading based on the updated nozzle injection pulse width value.

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