Digital management system for cold heading and heat treatment processing of fasteners

Abstract

The invention relates to the technical field of digital management, in particular to a digital management system for cold heading and heat treatment processing of fasteners, which comprises a phase deviation identification module, a load regulation and control parameter generation module, a heat treatment efficiency regulation and control module, a defect type association control module and an early warning instruction output module. According to the method, a load change node is positioned through a main shaft angle value, synchronous offset between a main shaft and a slave shaft is identified by combining multi-shaft displacement and load data, an angular displacement point in an impact rhythm, a corresponding speed and a holding time length set value are extracted, and targeted impact regulation and control parameters are formed; in the heat treatment stage, the fluctuation trend of heat conduction efficiency is recognized by combining the surface area and temperature rise data of the fastener, process response establishment of multiple types of defects is achieved by combining the crack size, the hardness value and the surface atlas label in the machining period, and shutdown and feeding interruption signals are issued to the control terminal according to the machining beat continuous triggering condition. Defect closed-loop linkage control in the fastener cold heading and heat treatment process is achieved.

Description

Technical Field

[0001] This invention relates to the field of digital management technology, and in particular to a digital management system for cold heading and heat treatment of fasteners. Background Technology

[0002] Digital management technology involves using information technology to achieve refined, visualized, and systematic management of various resources, processes, data, and information in the manufacturing process. This field integrates automated control systems, manufacturing execution systems, industrial IoT, edge computing platforms, and cloud-based data analytics modules to achieve end-to-end monitoring and optimization of production processes, improving production efficiency, data transparency, and the accuracy of management decisions. Digital management technology is widely applied to multiple key nodes such as manufacturing processes, equipment operating status, energy efficiency, product quality traceability, and compliance control. It emphasizes information interactivity between systems, closed-loop processes, and data-driven dynamic scheduling capabilities, and is one of the core supports of modern intelligent manufacturing systems.

[0003] The digital management system for fastener cold heading and heat treatment aims to build a comprehensive digital collaborative control system for the entire process of fastener cold heading and heat treatment. By collecting key data such as process parameters, equipment operating status, and quality inspection results during processing, and combining rule models and dynamic scheduling logic, the system achieves real-time monitoring, anomaly alarms, energy consumption statistics, and quality traceability for cold heading and heat treatment processes. This improves the automation level, processing consistency, and product controllability of the fastener manufacturing process, and is suitable for high-precision fastener applications in automotive, aerospace, and construction machinery industries.

[0004] Traditional management systems are limited to the level of equipment operation status and quality results, and fail to form a dynamic quantitative identification of changes in the synchronous state of multiple axes. They lack precise modeling and control of the stroke speed and displacement point within the impact cycle, resulting in the inability to identify continuous abnormalities in synchronous offset during the processing cycle in a timely manner, affecting the stability of load balance. Temperature control during the heat treatment stage is only based on adjusting the heat flux according to the feedback value of surface thermocouples, without combining the structural characteristics of fasteners and the trend of temperature rise inflection point changes to correct for thermal conductivity. This easily leads to oxide layer thickening caused by temperature rise efficiency offset, affecting hardness consistency and surface morphology. Defect identification is based on post-test quality inspection, failing to trace back to the cold heading and heat treatment parameter segments, and failing to establish the process response relationship for defect formation. This results in the inability to effectively control processing conditions after defects occur, increasing the probability of rework and the cost of abnormal handling in the production process. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and to propose a digital management system for cold heading and heat treatment of fasteners.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a digital management system for cold heading and heat treatment of fasteners, the system comprising:

[0007] The phase offset recognition module acquires the operating data of the cold heading press during the fastener processing, calculates the synchronous offset value between the main shaft and the driven shaft based on the peak load change rate between nodes and the spindle displacement change rate, filters out the period segments in which the offset value exceeds the error range for three consecutive cycles, and generates a periodic load synchronous offset mark sequence.

[0008] The load control parameter generation module calculates the offset amplitude between the peak stroke load and the change slope based on the periodic load synchronous offset mark sequence, extracts the stroke speed set value and the stamping holding time set value under the three-level control, and generates impact control parameter information for the cold heading process.

[0009] Based on the impact control parameter information of the cold heading process, the heat treatment efficiency control module determines whether the oxide layer growth rate is inversely increasing with the heat flux change value, sets the heating rate increase value and compresses the holding time ratio, and generates a heat treatment heating process control parameter group.

[0010] The defect type association control module, based on the heat treatment heating process control parameter group, counts the number of times the defect type appears in the processing parameter range, filters the combination items with parameter response relationship, and generates a defect type process response comparison list.

[0011] The present invention is improved in that the periodic load synchronous offset marking sequence includes a synchronous offset cycle number, an offset value classification label, and a node position identifier; the cold heading process impact control parameter information includes a stroke speed setpoint group, a stamping holding time adjustment group, and a periodic control label group; the heat treatment heating process control parameter group includes a heating rate adjustment amplitude, a holding time compression ratio, and a station control command number; and the defect type process response comparison list specifically includes a defect type number list, a parameter combination index group, and a response intensity level identifier.

[0012] The present invention is improved in that the phase offset recognition module includes:

[0013] The angle boundary extraction submodule acquires the operating data of the cold heading press during fastener processing. The operating data includes the angle value of the spindle rotary encoder, the response value of the vertical stroke axis loading sensor, the acquisition value of the horizontal feed axis drive torque, and the value of the spindle displacement sensor. Combined with the time axis sorting, the continuous angle change trend is processed by first-order difference processing. The processing cycle boundary is extracted in segments according to the stable interval and inflection point position of the angle change rate. The median value of the start and end positions of each cycle is extracted as the node switching point to generate the processing cycle boundary sequence information.

[0014] Based on the processing cycle boundary sequence information, the node offset analysis submodule calls the response value of the vertical stroke axis loading sensor, the acquisition value of the horizontal feed axis drive torque, and the value of the spindle displacement sensor to calculate the maximum fluctuation range difference of the spindle and slave axis load values ​​in each processing cycle, and compares the load peak change rate between nodes with the spindle displacement change rate to generate inter-axis load synchronization offset rate information.

[0015] The cycle anomaly marking submodule calls the processing cycle control parameters configured in the cold heading equipment setting panel according to the inter-axis load synchronization offset rate information, extracts the step distance setting value and offset error limit ratio corresponding to the current process, calculates the allowable offset range based on the setting value and limit ratio, and uses it as the allowable offset error value of the processing step distance. It then determines whether the offset rate value exceeds the error value within three consecutive cycles, filters and locates the cycle segment positions that meet the conditions, marks the anomaly number, and generates a cycle load synchronization offset marking sequence.

[0016] The present invention is improved in that the load regulation parameter generation module includes:

[0017] The load feature extraction submodule extracts stroke mechanical monitoring data for the corresponding period segment based on the periodic load synchronous offset marker sequence, including stroke peak load, load change time series and main shaft angular displacement change points. By calculating the maximum derivative value between each point between the stroke peak load and the load change time series, the extreme value of the change slope under the period is obtained, and stamping load change slope information is generated.

[0018] The stroke offset judgment submodule calls the stamping load change slope information, combines it with the corresponding stroke peak load, calculates the offset amplitude in each cycle, calls the stamping stroke fluctuation tolerance standard value, calculates the composite offset value, compares it with the tolerance standard value, filters the cycle numbers whose offset exceeds the tolerance, and generates a cycle offset over-limit number set.

[0019] The control parameter output submodule locates the control parameter segment value of the cycle based on the set of cycle offset over-limit numbers, calls the main shaft angle position of the cycle segment and sets the step distance in combination with the control curve, binds the cycle number with the corresponding angle range, extracts the stroke speed setting value and the stamping holding time setting value, forms a combination set of cycle number and control parameters, and generates impact control parameter information for the cold heading process.

[0020] The present invention is improved in that the heat treatment efficiency control module includes:

[0021] The temperature rise change extraction submodule obtains the furnace entry time record value, surface thermocouple temperature rise data and fastener surface area value for the corresponding cycle segment based on the impact control parameter information of the cold heading process. Based on the temperature rise curve, it extracts the time interval value between the initial temperature rise point and the sudden change point of the surface temperature change rate, and generates temperature rise response time difference information.

[0022] The thermal conductivity trend determination submodule obtains oxide layer growth rate data and heat flux change value based on the temperature rise response time difference information, performs trend change comparison of the two data, and sets the thermal conductivity efficiency correction range. The range is calculated by adding the periodic mean of the heat transfer area distribution in the heat treatment cavity of the current batch of equipment to the standard deviation of the offset rate of the unit heat absorption of the fastener surface. The thermal conductivity offset trend value is obtained by calculation, and it is determined whether it is greater than the thermal conductivity efficiency correction range. The thermal conductivity trend determination result is obtained.

[0023] The thermal control command generation submodule extracts the basic value of the heating rate and the original set value of the holding time within the corresponding cycle based on the heat conduction trend judgment result. It compares them with the upper and lower limit control execution ranges respectively, obtains the adjustment ratio coefficient, and redistributes the slope of the heating curve and the holding duration range in combination with the cycle data to generate a set of control parameters for the heat treatment heating process.

[0024] The present invention is improved in that the defect type association control module includes:

[0025] The defect data acquisition submodule collects the location of crack defect markers, size deviation distribution values, Rockwell hardness test values, and surface metallographic classification labels before and after the control cycle according to the heat treatment heating process control parameter group. At the same time, it acquires the cold heading stroke length setting value, heating rate setting value, and furnace entry time record value for the corresponding cycle segment. The data is sorted, classified, and numbered to generate a defect sample collection number table.

[0026] The parameter response calculation submodule extracts each defect type and its corresponding processing parameter segment combination based on the defect sample collection number table. It obtains the actual occurrence frequency, trigger frequency benchmark value, metallographic spectrum grade value, heating rate set value, and cold heading stroke length value of the defect under the current combination. It performs response intensity calculation on the defect type and parameter segment combination, calculates the response intensity value between the defect type and parameter segment combination, sorts the combination results according to the intensity value, sets the response intensity threshold as the sum of the median and standard deviation of the combination intensity values, filters the combination items that are higher than the response intensity threshold, and generates defect parameter response filtering results.

[0027] The trigger comparison output submodule responds to the filtering results based on the defect parameters, maps and matches the extracted defect type and processing parameter segment combination number with the equipment's set process segment classification information, and outputs a readable structured label. It then establishes a combination correspondence form between defect type and process segment and generates a defect type process response comparison list.

[0028] The present invention has an improvement, wherein the system further includes:

[0029] The early warning instruction output module monitors in real time whether the set value of the cold heading stroke length, the set value of the heating rate, and the recorded value of the furnace entry time meet the list combination conditions simultaneously in two consecutive cycles, based on the process response checklist for the defect type. If the conditions are met, the module outputs a stop signal to the workstation control terminal and simultaneously interrupts the material supply control, generating a set of abnormal linkage control instructions for the processing process.

[0030] The abnormal linkage control instruction set for the processing includes a stop signal item, a material supply interruption instruction item, and the target workstation number on the control panel.

[0031] The present invention is improved in that the early warning command output module includes:

[0032] The combination matching and filtering submodule extracts the identified defect types and processing parameter combinations based on the defect type process response comparison list, binds the corresponding cold heading stroke length setting value, heating rate setting value and furnace entry time record value into the parameter structure to form a set of combination parameter key values, and numbers and labels the key values ​​to generate a combination parameter matching sequence number;

[0033] The cycle condition recognition submodule calls the combined parameter matching sequence number to synchronously monitor the cold heading stroke length setting value, heating rate setting value, and furnace entry time recording value within the current two consecutive processing cycles. It compares whether the three parameter groups in the cycle are consistent with any combination item in the sequence number. If the two cycles match consecutively, it records the workstation and cycle number position and generates a combined cycle matching number set.

[0034] The signal command output submodule locates the corresponding workstation number and its control interface port according to the combined cycle number set, maps the stop signal and material supply interruption command into a linkage control command code structure, and uploads it to the output area of ​​the control terminal through the processing unit communication channel to generate a linkage control command set for abnormal processing.

[0035] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0036] In this invention, the load change node is located by the spindle angle value, and the synchronous offset between the master and slave axes is identified by combining multi-axis displacement and load data. The abnormal periodic segment of continuous offset is screened, and the offset amplitude between the stroke peak and the change slope is used as the basis to extract the angular displacement point in the impact cycle and the corresponding speed and holding time set value to form targeted impact control parameters. In the heat treatment stage, the thermal conductivity fluctuation trend is identified by combining the fastener surface area and temperature rise data. The heating rate and heat preservation ratio are adjusted according to the inverse growth relationship to construct a heat treatment parameter group. By combining the crack size, hardness value and surface map label in the processing cycle, the frequency of defects in the parameter segment is statistically analyzed and compared with the benchmark value to identify parameter combinations with related characteristics. This realizes the establishment of process response to multiple types of defects. Based on the continuous triggering condition of the processing cycle, the stop and material supply interruption signals are issued to the control terminal to realize the closed-loop linkage control of defects in the fastener cold heading and heat treatment process. Attached Figure Description

[0037] Figure 1 This is a system flowchart of the present invention;

[0038] Figure 2 This is a flowchart of the phase offset recognition module of the present invention;

[0039] Figure 3 This is a flowchart of the load regulation parameter generation module of the present invention;

[0040] Figure 4 This is a flowchart of the heat treatment efficiency control module of the present invention;

[0041] Figure 5 This is a flowchart of the defect type association control module of the present invention;

[0042] Figure 6 This is a flowchart of the early warning command output module of the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0044] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0045] Please see Figure 1 The present invention provides a technical solution: a digital management system for cold heading and heat treatment of fasteners, the system including a phase offset identification module, a load control parameter generation module, a heat treatment efficiency control module, a defect type association control module, and an early warning command output module;

[0046] The phase offset recognition module acquires the operating data of the cold heading press during fastener processing. The operating data includes the spindle rotary encoder angle value, the vertical stroke axis load sensor response value, the horizontal feed axis drive torque acquisition value, and the spindle displacement sensor value. Based on the rotation angle value, the processing cycle boundary is extracted, the load change node position is located, and the synchronous offset value between the spindle and the driven axis is calculated according to the load peak change rate between nodes and the spindle displacement change rate. The allowable offset error value of the processing step is compared, and the cycle segment where the offset value exceeds the error range within three consecutive cycles is selected to generate a cycle load synchronous offset mark sequence.

[0047] The load control parameter generation module extracts the peak stroke load, load change slope, and spindle angular displacement change points within the marked period segment based on the periodic load synchronous offset mark sequence. It calculates the offset amplitude between the peak stroke load and the change slope, and determines whether the offset amplitude is greater than the stamping stroke fluctuation tolerance threshold. For period segments that exceed the threshold, it performs a three-level segmentation judgment, extracts the stroke speed setpoint and stamping holding time setpoint under the three-level control, and generates impact control parameter information for the cold heading process by combining the corresponding angle points under the marked period.

[0048] The heat treatment efficiency control module is based on the impact control parameter information of the cold heading process. According to the corresponding cycle segment, it obtains the record value of the fastener entering the furnace, the surface thermocouple temperature rise data and the fastener surface area value, calculates the time interval between the initial temperature rise segment and the sudden change point of the surface temperature change rate, and determines whether the oxide layer growth rate is inversely increasing with the heat flux change value. If the trend change is greater than the set thermal conductivity correction range, it sets the heating rate increase value and compresses the heat holding time ratio, combines the two control parameters, and generates a heat treatment heating process control parameter group.

[0049] The defect type association control module collects the crack defect marking positions, size deviation distribution values, Rockwell hardness test values, and surface metallographic classification labels of fasteners before and after the control cycle based on the heat treatment heating process control parameter group. It also collects the cold heading stroke length setting value, heating rate setting value, and furnace entry time record value within the corresponding processing period. The module counts the number of times the defect type appears in the processing parameter segment, calculates the frequency distribution, compares it with the defect trigger frequency benchmark value corresponding to the type, filters the combination items with parameter response relationship, and generates a defect type process response comparison list.

[0050] The early warning instruction output module is based on the defect type process response checklist. According to the identified combination items, it monitors in real time whether the set value of cold heading stroke length, the set value of heating rate and the recorded value of furnace entry time meet the checklist combination conditions in two consecutive cycles. If the conditions are met, it outputs a stop signal to the workstation control terminal and interrupts the material supply control simultaneously, generating a set of abnormal linkage control instructions for the processing process.

[0051] The cyclic load synchronous offset marker sequence includes the synchronous offset cycle number, offset value classification label, and node position identifier. The impact control parameter information of the cold heading process includes the stroke speed setpoint group, the stamping holding time adjustment group, and the cycle control label group. The heat treatment heating process control parameter group includes the heating rate adjustment amplitude, the holding time compression ratio, and the station control command number. The defect type process response comparison list specifically includes the defect type number list, the parameter combination index group, and the response intensity level identifier. The processing process abnormal linkage control command set includes the stop signal item, the material supply interruption command item, and the control panel target station number.

[0052] Please see Figure 2 The phase offset recognition module includes:

[0053] The angle boundary extraction submodule acquires the operating data of the cold heading press during fastener processing. The operating data includes the angle value of the spindle rotary encoder, the response value of the vertical stroke axis loading sensor, the acquisition value of the horizontal feed axis drive torque, and the value of the spindle displacement sensor. Combined with the time axis sorting, the continuous angle change trend is processed by first-order difference processing. The processing cycle boundary is extracted in segments according to the stable interval and inflection point position of the angle change rate. The median value of the start and end positions of each cycle is extracted as the node switching point to generate the processing cycle boundary sequence information.

[0054] When acquiring the operating data of the cold heading press during fastener processing, the following steps are taken: first, the angle value sequence collected by the spindle rotary encoder, the load signal output by the vertical stroke axis loading sensor, the torque value fed back by the horizontal feed axis servo drive module, and the displacement record of the spindle displacement sensor are read. All data are mapped to the time axis and then timestamp alignment is performed. The spindle angle value sequence is then ordered according to the acquisition frequency to construct an angle change trend sequence. Next, a first-order difference calculation is performed on the angle values ​​at adjacent time points to generate an angle change rate sequence. This sequence can be used to characterize the stability of the spindle motion state. For example, during execution, the spindle angle values ​​are sequentially 10°, 30°, 55°, 80°, 105°, 130°, 160°, 190°, 215°, and 245°, corresponding to sampling times from 0s to 9s, acquired once per second. This data is then processed using the first-order difference... The angle change rates per second were determined to be 20° / s, 25° / s, 25° / s, 25° / s, 25° / s, 30° / s, 30° / s, 25° / s, and 30° / s. Based on the stable range of the change rate, it was determined that the spindle had a uniform speed range. Therefore, when the change rate changed abruptly, it was identified as an inflection point in the motion state. The time index value of the moment of abrupt change in the change trend before and after the inflection point was extracted as a reference point for cycle division. The entire angle change sequence was divided into intervals according to the inflection point time. Furthermore, the first and last angle values ​​of each cycle were extracted, and the median value was taken as the node switching point. For example, if the first angle of a cycle is 30° and the last angle is 130°, then the median angle of the corresponding node is 80°. This ultimately forms the processing cycle boundary sequence information. In this process, to set the judgment interval for the angle change rate, an angle change rate abrupt change judgment threshold Δθ was introduced. th It is defined as 10% of the difference between the average rate of change and the maximum instantaneous rate of change during the stable interval. Maximum instantaneous rate of change Δθ at the point of change max =30° / s, then Δθ th = (30-25)×0.1=0.5° / s. In actual judgment, when the difference in angular velocity between two adjacent time points exceeds 0.5° / s, it can be marked as an inflection point.

[0055] Table 1. Data on the rate of change of angle

[0056] Time point (s) Angle value (°) Rate of change of angle (° / s) 1 30 20.0 2 55 25.0 3 80 25.0 4 105 25.0 5 130 25.0

[0057] As shown in Table 1, the angle change rate data tends to stabilize in the 3 to 5 second range, which can be used as a reference standard for identifying stable segments within the recognition period. The threshold Δθ set for identifying abrupt changes in the rate of change is... th =0.5° / s is set based on the deviation between the mean value of the stable segment and the abrupt change point, ensuring that the spindle has a sensitive response capability to changes in its operating characteristics.

[0058] The node offset analysis submodule, based on the processing cycle boundary sequence information, calls the response value of the vertical stroke axis loading sensor, the acquisition value of the horizontal feed axis drive torque, and the value of the spindle displacement sensor to calculate the maximum fluctuation range difference of the spindle and slave axis load values ​​in each processing cycle. It also compares the load peak change rate between nodes with the spindle displacement change rate to generate inter-axis load synchronization offset rate information.

[0059] Based on the processing cycle boundary sequence information, the operating state parameters within each defined cycle are extracted. First, the response value sequence of the vertical stroke axis load sensor, the drive torque value sequence of the horizontal feed axis, and the value sequence of the spindle displacement sensor corresponding to that cycle are read. Each sequence is extracted to the time interval of the corresponding cycle, and the difference between the maximum and minimum values ​​in that interval is calculated as the maximum fluctuation interval difference within the cycle. Then, the difference between adjacent peak values ​​of multiple load peaks between the start and end nodes of the cycle is extracted and divided by the time interval to obtain the load peak change rate. At the same time, the ratio of the difference in spindle displacement at adjacent moments to the time interval is recorded to generate a displacement change rate sequence. Element-level corresponding position ratio calculation is performed on the two sequences to generate the inter-axis load synchronization offset rate information. A real example illustrates that if the maximum vertical stroke load value within a certain cycle is F... max =12.4kN, minimum is F min =8.6kN, then the difference in the fluctuation range is ΔF = F max -F min =3.8kN. If the peak values ​​of the three main loads within this cycle are 11.8kN, 12.0kN, and 12.4kN, corresponding to sampling times of 1.2s, 1.4s, and 1.6s respectively, then their rates of change are 1.0kN / s and 2.0kN / s respectively. The corresponding rates of change of the spindle displacement are 0.5mm / s and 0.6mm / s respectively. Therefore, the inter-axis synchronous offset rate can be calculated as 1.0 / 0.5 = 2.0 and 2.0 / 0.6 ≈ 3.3 respectively. This results in an offset rate list for the corresponding cycle, constituting the inter-axis load synchronous offset rate information for the entire cycle. An anomaly identification benchmark value δ for the synchronous offset rate is set. ref This value is the upper limit of the normal load-displacement ratio defined by the system. It is derived from the 90th percentile of the maximum offset rate across all cycles in historically stable operating batches. In a certain type of fastener processing test, the stable sample for cycle offset rate is [1.2, 1.8, 2.0, 2.1, 2.3, 2.5, 2.6, 2.9, 3.0, 3.3]. Its 90th percentile position after sorting is the 9th item, i.e., δ. ref =3.0, if the offset rate in subsequent cycles is greater than this value, it is considered an abnormal synchronization offset.

[0060] The cycle anomaly marking submodule calls the processing cycle control parameters configured in the cold heading equipment setting panel based on the inter-axis load synchronization offset rate information, extracts the step distance setting value and offset error limit ratio corresponding to the current process, calculates the allowable offset range based on the setting value and limit ratio, and uses it as the allowable offset error value of the processing step distance. It then determines whether the offset rate value exceeds the error value within three consecutive cycles, filters and locates the cycle segment positions that meet the conditions, marks the anomaly number, and generates a cycle load synchronization offset marking sequence.

[0061] Based on the inter-axis load synchronization offset rate information, the process parameter settings stored in the cold heading press setting panel are further called. The step distance setting value and its allowable offset error limit ratio configured in the current machining scheme are extracted. For example, if the step distance setting value is S = 80mm and the limit ratio is ε = 3%, then the allowable offset range is ΔS = S × ε = 2.4mm, which serves as the benchmark value for subsequent cycle judgment. The aforementioned offset rate sequence is traversed, and within each three consecutive cycles, all offset rates within that cycle are compared to see if they all exceed the offset range. If the condition is met, it is determined that there is continuous offset in that cycle segment. The start and end cycle numbers and their time positions are recorded, an anomaly flag number is assigned, and the anomaly flag array is written. Simultaneously, a "Cycle Anomaly Number" field is entered into the control panel to mark the quality analysis label for the current batch of processing. Finally, all cycle segments that meet the offset conditions are sequentially formed into a processing cycle load synchronous offset mark sequence, which is linked with the angle boundary information and inter-axis load information in the preceding module. To verify the rationality of the offset tolerance threshold setting, typical processing tests are designed. The actual measured values ​​of asynchronous offsets are 2.2mm, 2.5mm, 3.0mm, 2.1mm, and 2.3mm. According to the test statistics, 95% of the samples are concentrated below 3.0mm. Setting ΔS = 2.4mm can effectively cover most of the offset fluctuations and ensure the rationality of the boundary judgment.

[0062] Please see Figure 3 The load regulation parameter generation module includes:

[0063] The load feature extraction submodule extracts the stroke mechanical monitoring data of the corresponding period segment based on the periodic load synchronous offset marker sequence, including the stroke peak load, load change time series and main shaft angular displacement change points. By calculating the maximum derivative value between each point between the stroke peak load and the load change time series, the extreme value of the change slope under the period is obtained, and the stamping load change slope information is generated.

[0064] When extracting stroke mechanics monitoring data for the corresponding period segment based on the periodic load synchronous offset marker sequence, the period number recorded in the marker sequence is first determined and arranged in chronological order. Then, three core parameters are called for the stroke execution data within each period: the first is the peak stroke load, which can be obtained by reading the maximum instantaneous output value of the vertical stroke axis loading sensor in that period; the second is the load change time series, which is the measured sequence formed by mapping the load signal with a sampling frequency of 1000Hz within that period to the time axis; and the third is the spindle angular displacement change point, which is extracted from the continuous angular change data obtained by the spindle angle sensor by identifying points with significant change amplitudes. The above three types of data are then combined. After combining the load change time series according to the period dimension, a difference operation is performed. The change value between each adjacent sampling point is calculated and divided by the time interval to obtain the derivative sequence, i.e., the load change rate sequence. The maximum value is extracted as the extreme value of the change slope for that period. For example, if the load sequence in a certain period is [8.6, 10.2, 11.8, 12.3, 12.4] kN and the sampling interval is 0.002s, the change rates are 800, 800, 250, and 50 kN / s, respectively. The maximum value of 800 kN / s is taken as the extreme value of the change slope for that period. This step is repeated to generate the stamping load change slope information for all marked periods. In the above process, the derivative threshold δ used to determine the slope abrupt change point is used. s The threshold δ is set to the mean of all periodic derivative value samples plus 1.2 times the standard deviation. For example, if the slope sample sequence is [0.8, 1.0, 1.2, 0.9, 1.3] kN / s, with a mean of 1.04 kN / s and a standard deviation of 0.19 kN / s, then the threshold δ is... s =1.04 + 1.2 × 0.19 = 1.268 kN / s. All rates of change greater than this value are considered to be abrupt change points, thereby improving the accuracy of periodic feature identification.

[0065] The stroke offset judgment submodule calls the stamping load change slope information, combines it with the corresponding stroke peak load, calculates the offset amplitude in each cycle, and calls the stamping stroke fluctuation tolerance standard value. The tolerance standard value is 1.5 times the standard deviation of the fluctuation range between the upper and lower limits of the stroke energy stability range, using the formula:

[0066]

[0067] The composite offset value is calculated and compared with the tolerance standard value. Period numbers whose offsets exceed the tolerance are filtered out, and a set of period offset over-limit numbers is generated.

[0068] Where ΔP represents the composite offset value, L p S represents the normalized value of the peak load during the stroke, obtained as the ratio of the current cycle load value to the average load value across the entire batch. vThe normalized value representing the slope of load variation is obtained as the ratio of the current period's slope value to the median value of the slope distribution, A. t V represents the normalized value of the stroke duration, obtained as the ratio of the current cycle length to the average stroke time. θ The normalized value representing the rate of change of the spindle angular displacement is calculated by normalizing the rate of change of the time difference collected by the angular displacement sensor, V. θ,ref The normalized value representing the standard velocity of the spindle angular displacement is set by the equipment operating specifications and generated through static sampling calibration. (D) r It represents the relative dynamic stability of the stroke, which is the weighted average of the peak load fluctuation rate and the slope deviation rate, and is used to measure the load disturbance trend within a short period.

[0069] The system retrieves the stamping load change slope information and the corresponding stroke peak load, and performs paired calculations on the parameters according to each cycle number. First, it performs stroke peak load normalization processing, which is set by dividing the current cycle peak load by the average peak load of the entire batch. For example, if the current cycle load is 12.4 kN and the average is 12.2 kN, then the normalized value L... p =12.4 / 12.2≈1.016. Next, the slope of change is normalized by dividing the current cycle slope by the median of all cycle slopes. For example, if the current slope is 2.8 kN / s and the median is 2.5 kN / s, then S... v =2.8 / 2.5 = 1.12. The third step is to normalize the stroke duration, setting it as the ratio of the current cycle length to the average stroke time of all cycles. For example, if the current cycle is 0.62s and the average is 0.61s, then A t =0.62 / 0.61=1.016, and the angular displacement change rate is normalized by dividing the angular displacement time difference rate by the set standard velocity V. θ,ref Therefore, the standard velocity is calculated by dividing the set angular displacement (e.g., 30°) by the set time (e.g., 0.027s) to obtain V. θ,ref =1111.11° / s, V is calculated from the actual period. θ =1089.1° / s, then the normalized value is V θ / V θ,ref ≈0.980, combined with the stroke relative dynamic stability D r We set the weighted average of the peak load standard deviation and the slope offset rate to 0.12, and then substitute the above-mentioned parameters into the composite offset formula:

[0070]

[0071] In the above formula structure, the first term The adjustment factor indicates the degree of deviation between the peak load and its corresponding slope during the stroke. As a normalized stroke duration factor, it is used to compare the impact effect of drastic load changes in short strokes. If the deviation between the peak value and the slope is larger in short stroke times, then the output value of this term is larger; the second term |V θ -V θ,ref | represents the offset value of the spindle angular displacement change rate, used to assess whether the periodic stroke is executed too slowly or too quickly on the angular path, thus affecting the cycle stability of the machining process; the third term ln(1+D r D in ) r The dynamic disturbance degree of the stroke is the weighted average of the peak load fluctuation rate and the slope deviation rate. The function is processed using a logarithmic function to enhance its sensitive response under small disturbances and suppress the maximum amplification effect. The sum of the three results constitutes the total composite deviation ΔP of the cycle, which is used to measure the comprehensive deviation state between load, response time, angle execution speed and overall disturbance within a cycle.

[0072] Substitute the following into the above example:

[0073]

[0074] The final composite offset was 0.237. This result indicates that the load input deviated significantly from the typical slope change within this cycle, and the angular displacement velocity was lower than the standard preset. The overall disturbance trend showed an upward trend, thus it was considered that there was a certain level of anomaly in the dynamic stroke execution of this cycle. This value was compared with the stroke fluctuation tolerance standard value P. tol For comparison, the tolerance standard value is calculated by multiplying the fluctuation range between the upper and lower limits of the stroke energy sequence by 1.5 times the standard deviation. Energy is the integral of load multiplied by stroke time. If the standard deviation is 0.11, then P... tol =1.5 × 0.11 = 0.165, the period is ΔP = 0.237 > P tol The deviation is considered to be the over-limit cycle. In summary, ΔP is used as a joint evaluation index to establish a unified tolerance comparison benchmark among multi-dimensional dynamic parameters. The larger the deviation value, the more the overall mechanical execution state of the cycle deviates from the normal window. This is used as the basis for subsequent selection of cycle numbers to form the over-limit number set.

[0075] Table 2 Calculation of Composite Offset

[0076]

[0077] As shown in Table 2, by inputting the normalized parameters into the composite offset calculation formula, the ΔP for each cycle and the tolerance value P are obtained. tol =0.165. P2, P3, P4, and P5 are all greater than the tolerance, and are judged to be abnormal offset cycles, forming a set of cycle offset exceeding the limit numbering.

[0078] The control parameter output submodule locates the control parameter segment value of the cycle based on the set of cycle offset over-limit numbers, calls the main spindle angle position of the cycle segment and sets the step distance in combination with the control curve, binds the cycle number with the corresponding angle range, extracts the stroke speed set value and the stamping holding time set value, forms a combination set of cycle number and control parameters, and generates impact control parameter information for the cold heading process.

[0079] Based on the set of cycle offset exceedance numbers, control parameters are sequentially called for cycle numbers P2, P3, P4, P5, etc. First, the spindle angle position for each cycle is extracted. This data is acquired in real time by an angle sensor. The cycle is divided into three parts: acceleration, constant speed, and deceleration. The peak angle is used as a reference point to locate the stroke range. Then, the preset control curve in the control panel is called, and the speed control function value and time hold function value at the corresponding angle point are read. The cycle number, control angle segment, control speed value, and stroke hold time value are assembled into a control parameter set. For example, if the angle segment of cycle P2 is 60°~150°, the stroke speed is set to 220mm / s, and the hold time is 0.08s, then the combination of control parameters for this cycle is:

[0080] [P2,(60°,150°),220mm / s,0.08s], ultimately forming a set of control parameters for all abnormal cycles. The control speed setting is based on the minimum deformation speed lower limit after the conversion of the material's plastic load coefficient. This value is derived from the material's yield strength of 420MPa and the processing area of ​​25mm2. According to the unit load speed correspondence table, the speed should not be less than 180mm / s under the condition of ensuring deformation integrity. Combined with the current abnormal segment, it is set to 220mm / s. The holding time is selected according to the load holding platform fitting model, which is the time required for the strain to increase to 95%, i.e., 0.08s.

[0081] Please see Figure 4 The heat treatment efficiency control module includes:

[0082] The temperature rise change extraction submodule obtains the furnace entry time record value, surface thermocouple temperature rise data and fastener surface area value for the corresponding cycle segment based on the impact control parameter information of the cold heading process. Based on the temperature rise curve, it extracts the time interval value between the initial temperature rise point and the sudden change point of the surface temperature change rate, and generates temperature rise response time difference information.

[0083] Based on the impact control parameters of the cold heading process, the furnace entry time record value for each cycle is first retrieved. This value can be obtained by calling the processing batch number from the furnace entry control execution timestamp recording unit, with the corresponding unit being seconds. Then, the surface thermocouple temperature rise data is retrieved, and the thermocouple response temperature time series within the cycle is read. The sampling frequency is 10Hz, and a temperature-time curve is constructed. Combined with the fastener surface area value within the cycle, the data is archived using the average surface area measurement result. For example, if the measured surface area of ​​the fastener in cycle C1 is 1280mm², the first derivative function of the temperature curve is extracted to identify the time interval between the point where the temperature begins to stabilize and the point of maximum derivative. For example, if the starting point is at t = 12.4s and the abrupt change point is at t = 17.6s, the response time difference is 5.2s. This process is repeated for each cycle to form the temperature rise response time difference information. This information is used to characterize the time delay dynamics of heat energy conduction to the fastener surface during heat treatment. A temperature rise abrupt change identification threshold ΔT is set. th It is 1.5 times the standard deviation of the periodic temperature rise rate. If the standard deviation of the temperature rise rate is 1.2℃ / s, then ΔT th =1.8℃ / s, used to extract mutation locations.

[0084] The thermal conductivity trend determination submodule, based on the temperature rise response time difference information, acquires oxide layer growth rate data and heat flux change values, performs a trend change comparison of the two data points, and sets a thermal conductivity efficiency correction range. This range is calculated by adding the periodic mean of the heat transfer area distribution within the heat treatment chamber of the current batch of equipment to the standard deviation of the offset rate of the unit heat absorption on the fastener surface. It represents the acceptable energy efficiency offset limit under stable heat transfer conditions, using the formula:

[0085]

[0086] The thermal conductivity offset trend value is calculated, and it is determined whether it is greater than the thermal conductivity efficiency correction range. The thermal conductivity trend judgment result is obtained.

[0087] Where Γ represents the thermal conductivity shift trend value, G represents the normalized value of the oxide layer growth rate, obtained by dividing the change in oxide thickness by the periodic average oxidation rate, Q represents the normalized value of the heat flux change value, obtained by the ratio of the current heat flux per unit time to the historical average heat flux under the same operating conditions, T represents the normalized value of the temperature rise response time difference value, taken as the ratio of the time interval within the current cycle to the average heating duration, and R represents the dynamic value of thermal resistance, calculated from the ratio of the thermocouple surface temperature gradient to the unit heat flux. ref The static reference thermal resistance is determined by material properties and design structural constants. Z represents the normalized value of the furnace cavity heat transfer area, S represents the normalized value of the surface heat absorption area, and E represents the normalized value of the total energy input.

[0088] Based on the temperature rise response time difference information, the oxide layer growth rate data and heat flux change value for the corresponding cycle are obtained. The oxide layer growth rate data is the normalized index G obtained by dividing the ratio of the oxide thickness obtained after processing in that cycle to the cycle duration by the average value under the process specification. The heat flux normalized value Q is the ratio of the heat flux per unit time to the average heat flux under standard operating conditions. The response time difference normalized value T is obtained by dividing the temperature rise response interval of that cycle by the average heating time of all cycles. Subsequently, the cycle thermal resistance value R is obtained, which is determined by the ratio of the temperature gradient within 10 seconds before and after the thermocouple to the unit heat flux. The static thermal resistance R ref Using the reference values ​​obtained from the material's thermal conductivity and shape factor under standard adiabatic conditions within the furnace cavity, the normalized values ​​of heat transfer area Z, surface heat absorption area S, and input energy E are then substituted into the following calculation formulas:

[0089]

[0090] In the formula structure, the first term Characterizing the degree of inverse deviation between oxide layer growth and heat flow input, adjustment term To suppress the nonlinear effect of heating time, when the heat flux is sufficient but oxidation growth slows down, or conversely, oxidation increases but heat flux decreases, the first term increases; the second term... The third item characterizes the degree to which changes in thermal resistance affect the heat conduction process; a larger difference indicates that the actual heating transfer efficiency deviates from the material's design state. This is used to adjust the coupling behavior between furnace cavity area and unit energy absorption capacity. A higher value indicates that the system structure heat transfer efficiency deviates from the design steady-state condition. The sum of the three items constitutes the thermal conductivity offset trend value Γ, which is used to evaluate whether the thermal behavior is stable within the cycle.

[0091] Taking period C3 as an example, its participating terms are: G = 1.20, Q = 1.08, T = 1.10, R = 1.12, R ref =1.00, Z=1.12, S=1.08, E=1.05, substitute into the calculation:

[0092]

[0093] The calculation result Γ = 1.308 indicates that the system's thermal conductivity deviates significantly from steady state within the current cycle, requiring inclusion in subsequent adjustments. Simultaneously, a correction range Γ for thermal conductivity efficiency should be set. th Let Γ be the average heat transfer area of ​​the furnace cavity plus the standard deviation of the unit heat absorption rate. If the average heat transfer area is 1.05 and the standard deviation of the heat absorption rate is 0.08, then Γ th =1.13, the period C3 is outside this range, and it is determined to be an abnormal thermal conductivity.

[0094] Table 3 Calculation Table of Thermal Conductivity Migration Trend

[0095]

[0096] As shown in Table 3, both periods C3 and C5 are greater than the correction range Γ. th =1.13, which is identified as an abnormal thermal conductivity cycle and enters the subsequent heat treatment control process.

[0097] The heat control command generation submodule extracts the basic value of the heating rate and the original set value of the holding time within the corresponding cycle based on the heat conduction trend judgment result. It compares them with the upper and lower limit control execution ranges respectively, obtains the adjustment ratio coefficient, and redistributes the slope of the heating curve and the holding duration range in combination with the cycle data to generate a set of control parameters for the heat treatment heating process.

[0098] Based on the labeling results of the abnormal thermal conductivity trend, the baseline value V of the heating rate for the corresponding period is extracted. b Compared with the original setting value T of heat preservation time h For example, if the base heating rate for cycle C3 is 18.0℃ / min and the holding time is 540s, and the upper limit of the heat treatment control settings is set to 20.0℃ / min and the lower limit to 16.0℃ / min, then the upper limit offset range is set to ±2.0℃ / min; if the current cycle Γ>Γ th This indicates a heating rate acceleration period is required. The heating rate adjustment coefficient is set to 1.08, and the updated heating slope is V. b ×1.08=19.44℃ / min. Since the insulation time needs to be adjusted to match the heat transfer efficiency, the shortening ratio is set to 0.92. Therefore, the updated insulation time is T. h ×0.92 = 496.8s. Combining this with the cycle position data (e.g., the 28th cycle), a control instruction set [C3,28,19.44,496.8] is generated, ultimately forming the control parameter group for the heat treatment heating process. The control ratio coefficient is set according to the following principle: If Γ = 1.308, Γ th =1.13, then Rounded to 1.08, this ensures that the control coefficient has a linear response and stability.

[0099] Please see Figure 5 The defect type association control module includes:

[0100] The defect data acquisition submodule collects the location of crack defect markers, size deviation distribution values, Rockwell hardness test values, and surface metallographic classification labels before and after the control cycle based on the control parameter group of the heat treatment heating process. At the same time, it acquires the cold heading stroke length setting value, heating rate setting value, and furnace entry time record value of the corresponding cycle segment. The data is sorted, classified, and numbered to generate a defect sample collection number table.

[0101] Based on the control parameter set for the heat treatment heating process, the cycle numbers marked as abnormal were first determined. Quality inspection data from the two cycles before and after the abnormal cycle were retrieved from the heat treatment control system. Each data point was extracted, including the location of the crack defect marker, the distribution of dimensional deviations, Rockwell hardness test values, and surface metallographic image analysis results. The crack location was mapped to an XY coordinate structure, dimensional deviations were expressed as positive and negative tolerances, and hardness test values ​​were recorded in HRC units. Image recognition tools were used to classify the metallographic images into levels 1 to 5. Then, the control parameter set corresponding to each defect record within the specified cycle was extracted, including the cold heading stroke length. The set values ​​(in mm), heating rate set values ​​(in °C / min), and furnace entry time records (in s) are all recorded. Finally, all records are grouped according to defect type, and each type of defect is assigned a unique defect type number (such as CRK, DVR, HRD, etc.). Combined with the corresponding cycle segment number, the numbering rule is "defect type - cycle number", such as CRK-P14, DVR-P13, etc., and they are uniformly included in the "defect sample collection numbering table". During the data processing, the data integrity requirement is set that all five elements must be present. If any one is missing, the current data group is removed to ensure the effectiveness of subsequent statistical correlation assessment.

[0102] The parameter response calculation submodule, based on the defect sample collection number table, extracts each defect type and its corresponding processing parameter segment combination. It then obtains the actual occurrence frequency, trigger frequency baseline value, metallographic grade value, heating rate setpoint, and cold heading stroke length value for the current combination. Finally, it performs response intensity calculation on the defect type and parameter segment combination using the following formula:

[0103]

[0104] The response intensity values ​​between defect types and parameter segments are calculated and obtained. The combination results are sorted according to the intensity values. The response intensity threshold is set as the sum of the median and standard deviation of the combination intensity values. The threshold is used to define the boundary condition that the defect type and parameter segment constitute a significant correlation. Combinations with higher response intensity values ​​are filtered to generate defect parameter response filtering results.

[0105] Where, U represents the defect parameter response intensity value, F represents the actual frequency of the defect type in the parameter segment, B represents the reference frequency of the defect type in the parameter segment, G represents the metallographic spectrum grade value corresponding to the defect type, given by the metallographic hierarchy, M represents the normalized value of the heating rate corresponding to the occurrence of the defect type, obtained by the ratio of the heating rate to the average heating rate of the batch, L represents the normalized value of the cold heading stroke length in the period of occurrence of the defect type, obtained by the ratio of the cold heading length of the corresponding period to the set standard length, and e is the base of the natural logarithm.

[0106] Based on the defect sample collection number table, a statistical set is constructed according to the combination of defect type and processing parameter segment. Five core parameters are extracted for each combination: the actual occurrence frequency F of the defect type in the parameter segment, the trigger frequency baseline value B of the parameter segment corresponding to the defect type, the metallographic grade value G of the defect sample, the normalized value M of the heating rate (derived from the ratio of the actual heating rate to the average heating rate of the batch), and the normalized value L of the cold heading stroke length (calculated from the ratio of the set cold heading length within the cycle to the standard set length). The above data are then substituted into the defect parameter response intensity formula:

[0107]

[0108] Among them, the first item e -|F-B| This measure measures the exponential decay relationship between the actual frequency of the defect and its set expected frequency. When the actual frequency is significantly higher than the baseline frequency, this term approaches zero, indicating that the defect frequently deviates from the control target; the second term... This describes the coupling strength between the structural microscopic performance level (characterized by metallographic grade G) and the process execution rate (reflected by the normalized value of heating rate M) under the current defect type. The influence is smoothed and adjusted using the normalized value of cold heading step distance L to avoid artificially high response intensity when the cold heading step distance is too short. The larger the overall index U is, the stronger the influence of the current defect on the combination of process parameters, which belongs to a combination with high response correlation.

[0109] Taking combination number D4 as an example, the actual frequency is 10, the reference frequency is 12, G=1, M=0.88, L=1.10, and the formula is used to calculate:

[0110]

[0111] The value U = 0.088 indicates that the response intensity is low under the current parameter range. All combinations of U are sorted, and the response intensity threshold is set to the median plus the standard deviation of all combinations. For example, if the median of all U is 0.06 and the standard deviation is 0.08, then the threshold is 0.12. U = 0.088 is less than the threshold and is not screened, thus forming the defect parameter response screening result.

[0112] The trigger comparison output submodule responds to the filtering results based on the defect parameters, maps and matches the extracted defect type and processing parameter segment combination number with the equipment setting process segment classification information, and outputs a readable structured label, establishes a combination correspondence form between defect type and process segment, and generates a defect type process response comparison list.

[0113] Based on the defect parameter response screening results, the defect type label and its corresponding processing parameter segment identifier are extracted from the selected significant response combination numbers. The cold heading step, heating rate and furnace entry time combinations of the parameter segments are classified and grouped. For example, the step length segment is set as A (<75mm), B (75-85mm), C (>85mm), the heating rate segment is set as L (<17℃ / min), M (17-19℃ / min), H (>19℃ / min), and the furnace entry time is divided into T1 (<500s), T2 (500-600s), T3 (>600s). Then, the combination corresponding to D4 is mapped to the defect HRD@parameter segment BM-T2. It is mapped to the process segment management structure set on the equipment side and readable structure label is encoded, such as "HRD_BMT2". Finally, a defect type process response comparison list is established. This list will serve as a structured mapping for multi-cycle tracking and will be used as a reference for quality closed-loop control during subsequent process settings.

[0114] Please see Figure 6 The early warning command output module includes:

[0115] The combination matching and filtering submodule extracts the identified defect types and processing parameter combinations based on the defect type process response comparison list. It binds the corresponding cold heading stroke length setting, heating rate setting, and furnace entry time record value into the parameter structure to form a set of combination parameter key values. The key values ​​are numbered and labeled to generate a combination parameter matching sequence number.

[0116] Based on the parameter combination items corresponding to each defect in the defect type process response checklist, three key process control parameters involved in the combination are extracted: the cold heading stroke length set value (in mm), the heating rate set value (in °C / min), and the furnace entry time record value (in s). These three are bound into an inseparable parameter key-value structure, forming a combination of "[cold heading length]-[heating rate]-[furnace entry time]". Each unique parameter key-value structure is further assigned a corresponding number to construct a set of combined parameter key-value pairs, such as 80mm. -18.5℃ / min–560s corresponds to the number G001, 82mm–19.0℃ / min–570s corresponds to the number G002, and so on, forming a "combination parameter matching sequence number" with a one-to-one correspondence between parameters and numbers. Before binding each set of parameters, a parameter range standardization verification is performed, that is, the cold heading length must be 75-85mm, the heating rate must be 17-20℃ / min, and the furnace entry time must be 500~600s. If any item is not in the valid range, the combination is removed to prevent abnormal parameters from entering the cycle monitoring link.

[0117] Table 4. Matching sequence list of combined parameters

[0118]

[0119] As shown in Table 4, numbers G001 to G005 correspond to different parameter combinations for use by the subsequent beat comparison module. The system caches this table in the control terminal RAM and sets it as a read-only protected structure for use.

[0120] The cycle condition recognition submodule calls the combination parameter matching sequence number to synchronously monitor the cold heading stroke length setting value, heating rate setting value, and furnace entry time record value within the current two consecutive processing cycles. It compares whether the three parameter groups in the cycle are consistent with any combination item in the sequence number. If the two cycles match consecutively, it records the workstation and cycle number position and generates a combination cycle matching number set.

[0121] During cycle time condition recognition, the system continuously calls the real-time parameter status of the latest two processing cycles in the processing equipment cycle controller. It binds and reads the cold heading length setpoint, heating rate setpoint, and furnace entry time record, and constructs parameter combination pairs for the two cycles. For example, the parameters for cycles #143 and #144 are [80, 18.5, 560] and [80, 18.5, 560] respectively. This combination pair is compared with all combination numbers in the matching sequence table. If both cycles continuously match any combination item in the sequence table (i.e., all three parameters are consistent), then... If a match is deemed successful, the current workstation number and cycle number are recorded in the "Combined Cycle Number Match Set" along with the matching information. This is recorded in the format [Workstation Number - Cycle Start Number - Match Number], such as "W03-143-G001". This indicates that workstation W03 has a continuous matching processing anomaly starting from cycle 143. During the comparison operation, a hash structure is used to quickly map and retrieve the combined parameters. The parameter keys are constructed as a hash index in the form of strings such as "80-18.5-560", ensuring that the comparison operation during cycle execution is completed within 50ms.

[0122] The signal command output submodule locates the corresponding workstation number and its control interface port according to the combined cycle beat number set, maps the stop signal and material supply interruption command into a linkage control command code structure, and uploads it to the output area of ​​the control terminal through the processing unit communication channel to generate a linkage control command set for abnormal processing.

[0123] After capturing the set of combined cycle beat numbers, the station number field recorded in the set can be mapped and matched with the station control interface dictionary configured on the equipment control terminal to lock the hardware interface ID of the target station controller. For example, the interface ID corresponding to number W03 is CT203. The stop flag and material supply interruption flag in the current abnormal information structure are set to "1". At the same time, an abnormal linkage instruction code structure is constructed with the field structure: [station ID|cycle beat number|abnormal type code|action bit], such as "CT203|143|E004|1". This structure is packaged into a control data frame by the communication protocol layer and sent to the control terminal processing area via the processing unit's lower bus. Finally, it triggers the actual processing process stop action and the upstream material supply channel synchronous interruption. Among them, the abnormal type code E004 represents "defect process matching continuously established", and the action bit "1" represents the activation of the interrupt action. All abnormal linkage control instruction sets will be stored in the event log module for subsequent analysis and report generation.

[0124] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A digital management system for cold heading and heat treatment of fasteners, characterized in that, The system includes: The phase offset recognition module acquires the operating data of the cold heading press during the fastener processing, calculates the synchronous offset value between the main shaft and the driven shaft based on the peak load change rate between nodes and the spindle displacement change rate, filters out the period segments in which the offset value exceeds the error range for three consecutive cycles, and generates a periodic load synchronous offset mark sequence. The load control parameter generation module calculates the offset amplitude between the peak stroke load and the change slope based on the periodic load synchronous offset mark sequence, extracts the stroke speed set value and the stamping holding time set value under the three-level control, and generates impact control parameter information for the cold heading process. Based on the impact control parameter information of the cold heading process, the heat treatment efficiency control module determines whether the oxide layer growth rate is inversely increasing with the heat flux change value, sets the heating rate increase value and compresses the holding time ratio, and generates a heat treatment heating process control parameter group. The defect type association control module, based on the heat treatment heating process control parameter group, counts the number of times the defect type appears in the processing parameter range, filters the combination items with parameter response relationship, and generates a defect type process response comparison list.

2. The digital management system for cold heading and heat treatment of fasteners according to claim 1, characterized in that, The cycle load synchronous offset marker sequence includes a synchronous offset cycle number, an offset value classification label, and a node position identifier. The cold heading process impact control parameter information includes a stroke speed setpoint group, a stamping holding time adjustment group, and a cycle control label group. The heat treatment heating process control parameter group includes a heating rate adjustment amplitude, a holding time compression ratio, and a station control command number. The defect type process response comparison list specifically includes a defect type number list, a parameter combination index group, and a response intensity level identifier.

3. The digital management system for cold heading and heat treatment of fasteners according to claim 2, characterized in that, The phase offset recognition module includes: The angle boundary extraction submodule acquires the operating data of the cold heading press during fastener processing. The operating data includes the angle value of the spindle rotary encoder, the response value of the vertical stroke axis loading sensor, the acquisition value of the horizontal feed axis drive torque, and the value of the spindle displacement sensor. Combined with the time axis sorting, the continuous angle change trend is processed by first-order difference processing. The processing cycle boundary is extracted in segments according to the stable interval and inflection point position of the angle change rate. The median value of the start and end positions of each cycle is extracted as the node switching point to generate the processing cycle boundary sequence information. Based on the processing cycle boundary sequence information, the node offset analysis submodule calls the response value of the vertical stroke axis loading sensor, the acquisition value of the horizontal feed axis drive torque, and the value of the spindle displacement sensor to calculate the maximum fluctuation range difference of the spindle and slave axis load values ​​in each processing cycle, and compares the load peak change rate between nodes with the spindle displacement change rate to generate inter-axis load synchronization offset rate information. The cycle anomaly marking submodule calls the processing cycle control parameters configured in the cold heading equipment setting panel according to the inter-axis load synchronization offset rate information, extracts the step distance setting value and offset error limit ratio corresponding to the current process, calculates the allowable offset range based on the setting value and limit ratio, and uses it as the allowable offset error value of the processing step distance. It then determines whether the offset rate value exceeds the error value within three consecutive cycles, filters and locates the cycle segment positions that meet the conditions, marks the anomaly number, and generates a cycle load synchronization offset marking sequence.

4. The digital management system for cold heading and heat treatment of fasteners according to claim 3, characterized in that, The load regulation parameter generation module includes: The load feature extraction submodule extracts stroke mechanical monitoring data for the corresponding period segment based on the periodic load synchronous offset marker sequence, including stroke peak load, load change time series and main shaft angular displacement change points. By calculating the maximum derivative value between each point between the stroke peak load and the load change time series, the extreme value of the change slope under the period is obtained, and stamping load change slope information is generated. The stroke offset judgment submodule calls the stamping load change slope information, combines it with the corresponding stroke peak load, calculates the offset amplitude in each cycle, calls the stamping stroke fluctuation tolerance standard value, calculates the composite offset value, compares it with the tolerance standard value, filters the cycle numbers whose offset exceeds the tolerance, and generates a cycle offset over-limit number set. The control parameter output submodule locates the control parameter segment value of the cycle based on the set of cycle offset over-limit numbers, calls the main shaft angle position of the cycle segment and sets the step distance in combination with the control curve, binds the cycle number with the corresponding angle range, extracts the stroke speed setting value and the stamping holding time setting value, forms a combination set of cycle number and control parameters, and generates impact control parameter information for the cold heading process.

5. The digital management system for cold heading and heat treatment of fasteners according to claim 4, characterized in that, The heat treatment efficiency control module includes: The temperature rise change extraction submodule obtains the furnace entry time record value, surface thermocouple temperature rise data and fastener surface area value for the corresponding cycle segment based on the impact control parameter information of the cold heading process. Based on the temperature rise curve, it extracts the time interval value between the initial temperature rise point and the sudden change point of the surface temperature change rate, and generates temperature rise response time difference information. The thermal conductivity trend determination submodule obtains oxide layer growth rate data and heat flux change value based on the temperature rise response time difference information, performs trend change comparison of the two data, and sets the thermal conductivity efficiency correction range. The range is calculated by adding the periodic mean of the heat transfer area distribution in the heat treatment cavity of the current batch of equipment to the standard deviation of the offset rate of the unit heat absorption of the fastener surface. The thermal conductivity offset trend value is obtained by calculation, and it is determined whether it is greater than the thermal conductivity efficiency correction range. The thermal conductivity trend determination result is obtained. The thermal control command generation submodule extracts the basic value of the heating rate and the original set value of the holding time within the corresponding cycle based on the heat conduction trend judgment result. It compares them with the upper and lower limit control execution ranges respectively, obtains the adjustment ratio coefficient, and redistributes the slope of the heating curve and the holding duration range in combination with the cycle data to generate a set of control parameters for the heat treatment heating process.

6. The digital management system for cold heading and heat treatment of fasteners according to claim 5, characterized in that, The defect type association control module includes: The defect data acquisition submodule collects the location of crack defect markers, size deviation distribution values, Rockwell hardness test values, and surface metallographic classification labels before and after the control cycle according to the heat treatment heating process control parameter group. At the same time, it acquires the cold heading stroke length setting value, heating rate setting value, and furnace entry time record value for the corresponding cycle segment. The data is sorted, classified, and numbered to generate a defect sample collection number table. The parameter response calculation submodule extracts each defect type and its corresponding processing parameter segment combination based on the defect sample collection number table. It obtains the actual occurrence frequency, trigger frequency benchmark value, metallographic spectrum grade value, heating rate set value, and cold heading stroke length value of the defect under the current combination. It performs response intensity calculation on the defect type and parameter segment combination, calculates the response intensity value between the defect type and parameter segment combination, sorts the combination results according to the intensity value, sets the response intensity threshold as the sum of the median and standard deviation of the combination intensity values, filters the combination items that are higher than the response intensity threshold, and generates defect parameter response filtering results. The trigger comparison output submodule responds to the filtering results based on the defect parameters, maps and matches the extracted defect type and processing parameter segment combination number with the equipment's set process segment classification information, and outputs a readable structured label. It then establishes a combination correspondence form between defect type and process segment and generates a defect type process response comparison list.

7. The digital management system for cold heading and heat treatment of fasteners according to claim 6, characterized in that, The system also includes: The early warning instruction output module monitors in real time whether the set value of the cold heading stroke length, the set value of the heating rate, and the recorded value of the furnace entry time meet the list combination conditions simultaneously in two consecutive cycles, based on the process response checklist for the defect type. If the conditions are met, the module outputs a stop signal to the workstation control terminal and simultaneously interrupts the material supply control, generating a set of abnormal linkage control instructions for the processing process. The abnormal linkage control instruction set for the processing includes a stop signal item, a material supply interruption instruction item, and the target workstation number on the control panel.

8. The digital management system for cold heading and heat treatment of fasteners according to claim 7, characterized in that, The early warning command output module includes: The combination matching and filtering submodule extracts the identified defect types and processing parameter combinations based on the defect type process response comparison list, binds the corresponding cold heading stroke length setting value, heating rate setting value and furnace entry time record value into the parameter structure to form a set of combination parameter key values, and numbers and labels the key values ​​to generate a combination parameter matching sequence number; The cycle condition recognition submodule calls the combined parameter matching sequence number to synchronously monitor the cold heading stroke length setting value, heating rate setting value, and furnace entry time recording value within the current two consecutive processing cycles. It compares whether the three parameter groups in the cycle are consistent with any combination item in the sequence number. If the two cycles match consecutively, it records the workstation and cycle number position and generates a combined cycle matching number set. The signal command output submodule locates the corresponding workstation number and its control interface port according to the combined cycle number set, maps the stop signal and material supply interruption command into a linkage control command code structure, and uploads it to the output area of ​​the control terminal through the processing unit communication channel to generate a linkage control command set for abnormal processing.

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