Automobile fastener production process parameter control method and system

Abstract

The present application relates to the technical field of factory control system, specifically to a method and system for controlling process parameters of automobile fastener production, comprising the following steps: obtaining forming process cavity pressure and temperature data, extracting stress peak and valley and fluctuation section, comparing compression trajectory and deformation path, analyzing response timing and control difference, identifying delay behavior and deviation direction, and extracting migration record of execution process and control path. In the present application, by extracting nodes of cavity pressure fluctuation section and comparing timing of displacement direction switching, the corresponding relationship between pressure change and deformation path is constructed, combined with time cross analysis of preheating control and compression action, non-synchronous control behavior and response segment are screened, response delay in power regulation and load change is identified, deviation path between input and feedback is extracted, tracking range of multi-parameter disturbance in process is expanded, and identification ability of abnormal fluctuation and response coordination of parameter change are enhanced.

Description

Technical Field

[0001] This invention relates to the field of factory control system technology, and in particular to a method and system for controlling process parameters in automotive fastener production. Background Technology

[0002] The field of factory control systems technology involves the unified scheduling and automatic control of multiple devices, processes, and parameters in industrial manufacturing. Core aspects include temperature control, pressure control, motion execution, sequential logic execution, real-time data acquisition, process status monitoring, and feedback execution during production line operation. Through the integrated use of programmable logic controllers (PLCs), industrial control computers, sensors, and actuators, automated management and refined operation of continuous manufacturing processes are achieved to improve manufacturing stability and parameter controllability. The methodological characteristics of this field are reflected in setting logic control schemes based on the production object and process flow, setting target parameter values, collecting key process data during operation, and correcting and updating parameters based on process standards or experience models to form closed-loop control logic to maintain production process stability. Traditional automotive fastener production process parameter control methods refer to the manual setting, recording, and adjustment of parameters such as temperature, time, speed, torque, and load in fastener forming, heat treatment, and surface treatment processes. These methods typically rely on standard parameter ranges provided in process specifications, with initial settings completed by on-site operators filling out and verifying parameter forms. Data acquisition depends on workshop operation records or the offline recording functions of some equipment.

[0003] Existing technologies rely on static parameter settings and manual data registration for control, lacking the ability to divide the process parameter changes into continuous time periods and identify their direction. This makes it difficult to simultaneously perceive multidimensional data fluctuations and equipment state switching during production. When the clamping action and temperature control operation lack time correlation recognition capabilities, it is impossible to distinguish parameter deviations caused by response delays. This leads to a mismatch between the temperature control rhythm and workpiece deformation in the heat treatment process, and the process parameter deviation direction cannot be confirmed and fed back in a timely manner. Consequently, it results in discontinuous path control and unstable deformation behavior, affecting the manufacturing process's ability to cope with complex disturbances. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a method for controlling process parameters in automotive fastener manufacturing;

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for controlling process parameters in automotive fastener production, comprising the following steps:

[0006] S1: Obtain mold cavity pressure and mold wall temperature data during the forming process of automotive fasteners, extract stress peak and valley points in continuous cycles, divide pressure fluctuation periods, extract the start and end nodes and change direction of each segment, locate the role of the segment in the fluctuation trend, and obtain a set of stress fluctuation segment labels.

[0007] S2: Based on the set of stress fluctuation segment labels, extract the clamping trajectory and displacement change path, compare the direction switching behavior time, and analyze the corresponding relationship to obtain the deformation behavior mapping structure table;

[0008] S3: Based on the deformation behavior mapping structure table, extract the preheating control data and the pressing response time point, compare the actions on the time axis, extract the time segments and control numbers of the asynchronous actions, and obtain the preheating stage temperature control behavior matching list.

[0009] S4: Based on the preheating stage temperature control behavior matching list, extract the power adjustment and load action time, compare the temperature response in sequence, identify continuous delayed behavior, and obtain a set of parameter disturbance behavior fragment sequences.

[0010] S5: Based on the parameter disturbance behavior segment sequence set, extract control commands and feedback data, track the offset direction within the cycle, extract the corresponding execution process, and obtain the migration record of the control path.

[0011] As a further embodiment of the present invention, the stress fluctuation zone label set includes a start node, an end node, pressure trend, change direction, and fluctuation trend position; the deformation behavior mapping structure table includes the starting and ending points of compression, deformation direction path, direction consistency status, and time overlap range; the preheating stage temperature control behavior matching list includes the control action sequence number, control action time segment, and time overlap determination result; the parameter disturbance behavior segment sequence set includes the operation response delay segment number, temperature control action start point, and temperature feedback response point; and the control path migration record includes control input data, feedback data, response difference time point, and parameter state offset direction.

[0012] As a further aspect of the present invention, the stress peak and valley points refer to the highest and lowest points within the pressure cycle of the mold cavity.

[0013] The pressing trajectory refers to the actual movement path and direction changes of the pressing mechanism during the forming process.

[0014] As a further aspect of the present invention, the displacement change path refers to the displacement direction and deformation trajectory of the workpiece during the clamping process;

[0015] The continuous delay behavior refers to a continuous abnormal response in which the control action has occurred but the feedback is continuously delayed.

[0016] As a further aspect of the present invention, the specific steps of S1 are as follows:

[0017] S101: Acquire the continuous output data of the stress and temperature sensors in the mold cavity within a specified time period, extract the periodic stress peak and valley positions from the pressure curve, and match the corresponding time points with the pressure values ​​one by one to obtain a stress peak and valley data reference set.

[0018] S102: Based on the stress peak and valley data comparison set, segment the continuous change process between adjacent data points, extract the start and end nodes of each segment, analyze the direction of pressure increase and decrease between nodes, and obtain a segmented set of pressure change trends.

[0019] S103: Call the pressure change trend segment set, match the start and end nodes of each segment with their corresponding positions in the fluctuation sequence, distinguish the combination relationship between the change direction and the location, and obtain the stress fluctuation segment label set.

[0020] As a further aspect of the present invention, the specific steps of S2 are as follows:

[0021] S201: Based on the time range in the stress fluctuation segment label set, retrieve motion trajectory data and workpiece displacement trend data during the clamping action, extract the starting point of the clamping behavior and the change process of the clamping direction path within the time range, and obtain the clamping action direction path sequence.

[0022] S202: Based on the pressing action direction path sequence, extract the workpiece displacement trend data within the corresponding time period, and divide the change path into continuous direction segments to obtain the workpiece deformation path sequence segment group.

[0023] S203: Based on the overlap in time and direction between the pressing action direction path sequence and the workpiece deformation path sequence segment group, compare the directional trend and time position of each segment in the sequence, map the segments with synchronous relationship, and obtain the deformation behavior mapping structure table.

[0024] As a further aspect of the present invention, the specific steps of S3 are as follows:

[0025] S301: Based on the response time period in the deformation behavior mapping structure table, extract the temperature control operation data and heat treatment action time axis within the corresponding time range, filter the action data in the preheating stage, and extract the start time and duration of each group of control actions to obtain the preheating stage control action sequence.

[0026] S302: Based on the preheating stage control action sequence, retrieve the start time of each group of control actions and compare it with the start and end time of the pressing response behavior within the same time range. Separate the corresponding segments of control actions that are not in the same time segment to obtain a set of non-overlapping action time segments.

[0027] S303: Based on the set of non-overlapping action time periods, extract the corresponding control action number sequence according to the time sequence, remove duplicate numbers, and obtain the preheating stage temperature control behavior matching list.

[0028] As a further aspect of the present invention, the specific steps of S4 are as follows:

[0029] S401: Based on the time segments in the preheating stage temperature control behavior matching list, extract the heating power adjustment action and axial load adjustment action within the time range, extract the start time and corresponding duration of the control action from each set of data, and obtain the control action time frame set.

[0030] S402: Based on the control action time frame set, extract the feedback time point sequence from the temperature change record within the same time period, compare the chronological relationship between the control action start time point and the temperature feedback occurrence time point in chronological order, and obtain the response delay correspondence table.

[0031] S403: Based on the response delay correspondence table, identify control behaviors with continuous lag in feedback time points within continuous time segments, extract the action type and start and end positions corresponding to the segments, and obtain a set of parameter disturbance behavior segment sequences.

[0032] As a further aspect of the present invention, the specific steps of S5 are as follows:

[0033] S501: Based on the segment number in the parameter disturbance behavior segment sequence set, retrieve the control command and feedback data of the parameter in the current period, and match the time points of the data sequence in a continuous time period to obtain the control feedback time sequence group.

[0034] S502: Call the control feedback time series group, compare the time point of the control command action with the time point of the feedback response, divide the continuous region where the data has intervals on the time axis, and obtain the response difference time period set;

[0035] S503: Based on the set of response difference time periods, track the numerical trend of each group of parameters within the segment, divide the direction trend and span of numerical changes during the time progression, and obtain the migration record of the control path.

[0036] A process parameter control system for automotive fastener manufacturing includes:

[0037] The stress fluctuation extraction module acquires the cavity pressure and mold wall temperature data during the forming process of automotive fasteners, extracts the stress peak and valley points in a continuous cycle, divides the pressure fluctuation period, extracts the start and end nodes and change direction of each segment, locates the role of the segment in the fluctuation trend, and obtains a set of stress fluctuation segment labels.

[0038] The deformation path comparison module extracts the clamping trajectory and displacement change path based on the time range in the stress fluctuation segment label set, compares the direction switching behavior time, analyzes the corresponding relationship, and obtains the deformation behavior mapping structure table.

[0039] The temperature control behavior screening module extracts preheating control data and pressing response time points based on the response time periods in the deformation behavior mapping structure table, compares the actions on the time axis, extracts time segments and control numbers of asynchronous actions, and obtains a preheating stage temperature control behavior matching list.

[0040] Based on the preheating stage temperature control behavior matching list, the response delay extraction module extracts the power adjustment and load action time, performs sequential comparison of the temperature response, identifies continuous delay behavior, and obtains a set of parameter disturbance behavior fragment sequences.

[0041] The parameter offset tracking module extracts control commands and feedback data based on the numbering of the parameter disturbance behavior segment sequence set, tracks the offset direction within the period, extracts the corresponding execution process, and obtains the migration record of the control path.

[0042] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0043] In this invention, by extracting nodes of the pressure fluctuation section of the mold cavity and comparing the timing of displacement direction switching, a correspondence between pressure change and deformation path is constructed. Combined with the time cross-analysis of preheating control and clamping action, asynchronous control behaviors and response segments are screened, response delays in power adjustment and load change are identified, offset paths between input and feedback are extracted, the tracking range of multi-parameter disturbances in the process is expanded, and the ability to identify abnormal fluctuations and coordinate response to parameter changes is enhanced. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram of the steps of the present invention;

[0046] Figure 2 This is a detailed schematic diagram of S1 of the present invention;

[0047] Figure 3 This is a detailed schematic diagram of S2 of the present invention;

[0048] Figure 4This is a detailed schematic diagram of S3 of the present invention;

[0049] Figure 5 This is a detailed schematic diagram of S4 of the present invention;

[0050] Figure 6 This is a detailed schematic diagram of S5 of the present invention;

[0051] Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0052] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0053] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0054] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0055] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0056] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0057] Please see Figure 1 This invention provides a method for controlling process parameters in automotive fastener manufacturing, comprising the following steps:

[0058] S1: Acquire the cavity contact pressure and mold wall temperature sensing data during the synchronous forming process of automotive fasteners, collect the peak and valley points identified by stress sensors within the same time period, extract the continuous periodic fluctuation behavior, divide the time period of continuous stress change into segments, extract the pressure trend corresponding to the start and end nodes and change direction of the segments, locate the role of the segments in the fluctuation trend, and obtain the stress fluctuation segment label set.

[0059] S2: Based on the time range in the stress fluctuation section label set, call the motion trajectory of the clamping action and the workpiece displacement trend data during the forming process of automotive fasteners, extract the start and end times of the clamping action and the corresponding deformation direction change path within the time period, compare the change of clamping direction and the direction switching behavior in the workpiece deformation path, analyze the correspondence based on the consistency of direction and the time overlap range, and obtain the deformation behavior mapping structure table.

[0060] S3: Based on the response time period in the deformation behavior mapping structure table, extract the temperature control operation data and action execution time axis of the heat treatment stage within the same time range, cross-compare the start time of the control action and the time of the pressing response behavior during the preheating process, filter out continuous segments where the actions do not occur simultaneously, extract the control sequence number according to the order of appearance, and obtain the temperature control behavior matching list for the preheating stage.

[0061] S4: Based on the time segments corresponding to the temperature control behavior matching list in the preheating stage, extract the heating power adjustment action and axial load adjustment behavior within the same time period, compare the start time of the control action with the feedback time point corresponding to the actual temperature change in time sequence, identify the operation behavior that continuously has response delay, and obtain the parameter disturbance behavior segment sequence set.

[0062] S5: Based on the segment numbers listed in the parameter disturbance behavior segment sequence set, extract the control input and actual feedback data of each parameter in the current cycle, the response difference time points of the corresponding data in the continuous time period, track the offset direction of the parameter state during the process, and obtain the migration record of the control path.

[0063] The stress fluctuation zone label set includes the start node, end node, pressure trend, change direction, and fluctuation trend location. The deformation behavior mapping structure table includes the start and end points of compression, deformation direction path, direction consistency status, and time overlap range. The preheating stage temperature control behavior matching list includes the control action sequence number, control action time segment, and time overlap judgment result. The parameter disturbance behavior segment sequence set includes the operation response delay segment number, temperature control action start point, and temperature feedback response point. The control path migration record includes control input data, feedback data, response difference time point, and parameter state offset direction.

[0064] Please see Figure 2 The specific steps of S1 are as follows:

[0065] S101: Acquire the continuous output data of the stress and temperature sensors in the mold cavity within a specified time period, extract the periodic stress peak and valley positions from the pressure curve, and match the corresponding time points with the pressure values ​​one by one to obtain a stress peak and valley data reference set.

[0066] To acquire continuous output data from stress and temperature sensors within the mold cavity over a specified time period, practical applications require first identifying the type and location of the sensors used in the mold cavity. By reading the raw data records from the pressure and temperature sensors, a sequence of stress and temperature values ​​recorded per second or higher during the injection molding cycle is obtained. This time period must be set to cover one or more complete injection molding cycles, in conjunction with the control parameters of the mold cavity processing cycle. For example, selecting a data segment covering 10 cycles, assuming the sensor samples at a frequency of 100 times per second, results in 2000 data points collected per cycle. During reading, the pressure values ​​and corresponding times must be listed sequentially according to timestamps to form a time series. When extracting stress peak and valley points from this series, the system simultaneously assesses whether the pressure in that segment exceeds the safe fluctuation range and adjusts the heating power setpoint for the next cycle accordingly. To achieve a lower output level, or to advance the starting point of the pressing action to an earlier control node, the temperature control rhythm and stress peak value are dynamically matched. The upward or downward trend needs to be determined by the difference between consecutive values. The specific operation is to traverse all data points, starting from the second point, and compare the value with the previous and next values ​​in turn. If the current value is greater than the two values ​​before and after, it is identified as a peak; if it is less, it is identified as a trough. For example, if the value of point 1234 is 52.3, the previous value is 50.8, and the next value is 50.1, then this point is marked as a peak. Continue traversing until the end point. For each peak or trough identified, its time position and pressure value need to be recorded. For example, if the sampling time of point 1234 is 61.7 seconds and the corresponding pressure is 52.3, then it is recorded as the data pair (61.7, 52.3). After all peak and trough data pairs are sorted in chronological order, a stress peak and trough data comparison set is obtained.

[0067] S102: Based on the stress peak and valley data comparison set, the continuous change process between adjacent data points is segmented, the start and end nodes of each segment are extracted, and the direction of pressure increase and decrease between nodes is analyzed to obtain the segmented set of pressure change trends.

[0068] First, rearrange all data pairs in chronological order to ensure that each peak or trough has a unique sequential relationship on the time axis. Connect each adjacent data pair sequentially to form a range of pressure change. Taking the first data pair (t1, p1) and the second data pair (t2, p2) as an example, set this as the first range, with t1 as the starting node and t2 as the ending node. Continue connecting each adjacent data pair in the same way until the last pair. Each range must satisfy the condition that "the ending time of the previous range equals the starting time of the next range." After each range is established, calculate the pressure difference Δp and time difference Δt: Δp is obtained by subtracting the starting pressure value from the ending pressure value, and Δt is obtained by subtracting the starting time from the ending time. For example, in a range where the starting pressure is 34.2 and the ending pressure is 48.7, Δp is 14.5; and the starting time is 12.4 and the ending time is 14.3, Δt is 1.9. After obtaining Δp, its trend needs to be determined (this trend will serve as the input for the clamping control module; if the system determines that multiple consecutive segments show an abnormal upward trend without a peak drop, it is considered a lag in the pressure system response. In this case, the clamping duration setting will be automatically lowered, and the loading speed setting for the next segment will be reduced simultaneously to prevent excessive stress accumulation in the mold cavity structure due to continuous pressurization): If Δp is greater than 0, the trend is determined to be "rising"; if Δp is less than 0, it is determined to be "falling"; if Δp equals 0, it is determined to be "flat". The judgment process should be implemented using direct numerical comparison, that is, comparing Δp with 0 one by one. To avoid misjudgment caused by small fluctuations, a minimum effective change threshold θp needs to be set, and it is recommended that θp be set to 0.5. When the absolute value of Δp is less than 0.5, it is considered to have no significant change and is marked as "flat". This threshold can be set according to the sensor accuracy and data noise. For example, when the sensor accuracy is 0.2 and the noise fluctuation range is ±0.3, θp should not be lower than 0.5. The actual value can be adjusted based on experience and specific machine models. After determining the trend, all intervals are bound to their corresponding trends to generate a segmented trend label list. For example, if an interval consists of (23.1, 42.7) to (24.9, 38.2), then the trend of that segment is determined to be "downward", and a segmented set of pressure change trends is obtained.

[0069] S103: Call the pressure change trend segment set, match the start and end nodes of each segment with their corresponding positions in the fluctuation sequence, distinguish the combination relationship between the change direction and the location, and obtain the stress fluctuation segment label set;

[0070] The time position and pressure value of the start and end nodes of each segment are read sequentially from the trend segment list obtained in the previous section. The index positions of these start and end nodes in the original peak-trough sequence are then matched one by one. This matching process is achieved by comparing the start time recorded in the trend segment with the time of each pair of data in the peak-trough sequence. When the absolute value of the time difference between two times is less than the set matching threshold θt, they are considered to be the same node. The setting of θt depends on the sampling frequency and error range. In injection mold cavity pressure field monitoring, where the sampling frequency is high and the error does not exceed 0.02, θt can be set to 0.05. After the start node matching is completed, the same comparison process is used to match the end nodes one by one. Matching ensures that each item in the trend segment can find its true location in the peak-trough sequence. For example, if a segment in the trend segment set is recorded with a start time of 12:4, and a node with a time of 12:39 exists in the peak-trough sequence, the time difference between the two is 0.01, which is less than the threshold of 0.05, so it is marked as a successful match. Subsequently, the end time of 14:3 is compared with 14:32 in the sequence, and the difference is 0.02, which also meets the threshold condition, thus establishing a correspondence between the start and end nodes. After confirming the node position, a classification action needs to be performed on the direction of change of the segment. The trend direction already recorded in the trend segment is recalled, and this is achieved by comparing the trend direction string content with the preset direction identifier set item by item. The directional label set can be categorized into three types: "rising," "falling," and "stable." The comparison process directly compares the trend direction with each label character by character. Once they match completely, the direction of that segment is determined. If a segment's Δp is 14.5, the direction is recorded as "rising"; if a segment's Δp is −9.3, the direction is recorded as "falling"; if a segment's Δp is 0.3 but less than the previously set minimum pressure change threshold θp of 0.5, the direction is recorded as "stable." After the direction is confirmed, the location needs to be determined. The location determination is based on the node type of the peak-trough sequence. The location label is determined by judging whether the starting node of the segment is a peak or a trough. The determination action is performed by directly reading the node in the peak-trough sequence. The label field is implemented as follows: for example, each node in the sequence is pre-recorded as a "peak" or "valley". If the starting node is a "peak" and the direction is "descending", the positional relationship of that segment is marked as "descending after peak". If the starting node is a "valley" and the direction is "ascending", it is marked as "ascending after valley". If the starting node is a "peak" and the direction is "flat", it is marked as "flat after peak". All combinations can be obtained through simple logical matching. To avoid the labels being too sensitive, a judgment threshold θp2 can be set for the node type to confirm the stability of the peak or valley. This threshold can be set according to the pressure change amplitude. For example, it is required that the difference between adjacent points is greater than 10 to be identified as a peak or valley. If the pressure of a certain node is 52.3, and the pressures of the two points before and after it are 40.1 and 41.If the difference is 0, a difference exceeding 10 is considered a peak; if the difference is only 6, it is not considered a peak. This threshold is determined based on the actual fluctuation amplitude, typically set between 8 and 15. Using 12 as an example value is reasonable. After all the above actions are completed, the direction label and position label are combined and concatenated into a final segment label. This combined label will be synchronously sent to the control rule table. If the system detects multiple consecutive "flat after valley" labels without a normal "rise after valley" label, it indicates insufficient heating effect. The initial heating power setting value for the next cycle will be automatically increased, and subsequent peak and valley points will be re-collected to verify whether the peak value has fallen back, thus obtaining a set of stress fluctuation segment labels.

[0071] Please see Figure 3 The specific steps of S2 are as follows:

[0072] S201: Based on the time range in the stress fluctuation section label set, retrieve motion trajectory data and workpiece displacement trend data during the clamping action process, extract the starting point of the clamping behavior and the change process of the clamping direction path within the time range, and obtain the clamping action direction path sequence.

[0073] First, after sequentially reading the start and end times corresponding to each tag from the tag set, this time range needs to be compared item by item with the motion trajectory data recorded during the pressing action. By comparing the tag start time and the trajectory data time, when the absolute value of the time difference between the two is less than the set matching threshold θt, the trajectory point can be considered to correspond to the start time of the action segment. θt should be set according to the accuracy of trajectory acquisition; for example, when the trajectory recording error does not exceed 0.03, θt can be set to 0.05. In the example, if the tag time is 21.4 and the trajectory point time is 21.37, the difference is 0.03, which meets the matching condition, so this point can be used as the starting point. The same method can be used to determine the trajectory point corresponding to the tag end time, thereby obtaining the complete action range. Subsequently, all trajectory records are extracted within this time range, and the coordinate differences between two adjacent trajectory points are compared point by point, using the Euclidean method to characterize the degree of displacement. Taking points A (12.5, 4.2) and B (13.1, 4.2) as examples, their position changes by 0.6 in the X direction but not in the Y direction, so the linear displacement between the two points is 0.6. By connecting the trajectory points in this way, a continuous trajectory displacement trend can be formed. During this process, the workpiece displacement trend also needs to be acquired simultaneously. By aligning a set of data in the workpiece record and the trajectory record that are close in time (e.g., the difference is less than 0.05), they are used as the correspondence at the same moment, thus identifying the workpiece's position change at different time points. For example, if the previous position is 2.4 and the next position is 3.0 at a certain moment, then the displacement amplitude of this segment is 0.6. By connecting segments in this way, a complete workpiece displacement trend can be obtained. After both trends are clear, the starting point of the clamping action can be further identified. This starting point is determined by finding the first point in the trajectory data where three consecutive displacement amplitudes exceed the threshold θd. θd needs to be set based on the range of small fluctuations in the equipment when it is stationary. For example, in a clamping device, the noise amplitude is usually below 0.2, so θd can be set to 0.5. If the amplitudes of three displacements are 0.6, 0.8, and 1.1 respectively, all exceeding the threshold, then the first point of the sequence is marked as the starting point of the action. Next, the path direction recognition stage begins. By comparing the changes in coordinates between the trajectory point and its previous position, when the X-direction position value increases and the Y-direction change does not exceed 0.1, the direction can be marked as positive X; if the X-direction value decreases and the Y-direction change still does not exceed 0.1, it is marked as negative X; if the Y-direction value increases and the X-direction remains basically unchanged, it is marked as positive Y; if the Y-direction value decreases and the X-direction remains stable, it is marked as negative Y. For example, the range from (12.5, 4.2) to (13.1, 4.2) is positive X, and the range from (13.1, 4.2) to (13.1, 3.4) is negative Y. By connecting each directional marker in this way, a sequence of pressing action directional paths is obtained.

[0074] S202: Based on the pressing action direction path sequence, extract the workpiece displacement trend data within the corresponding time period, and divide the change path into continuous direction segments to obtain the workpiece deformation path sequence segment group.

[0075] First, read the direction markers and corresponding start and end times of each path segment from the path sequence. Then, extract the time range covered by each path segment on the time axis. Next, call all data points recorded within that time range from the workpiece displacement trend data, and read the workpiece's coordinate position data at each time point, including the values ​​in the X and Y directions. Then, determine the direction of the coordinate changes between two consecutive time points by comparing the coordinates of the later point with the previous point. If the X direction increases and the Y direction changes within ±0.1, the direction is defined as positive X; if the X direction decreases and the Y direction changes... If the change in the Y direction is within ±0.1, it is defined as negative X-direction. If the Y direction increases and the change in the X direction is within ±0.1, it is defined as positive Y-direction. If the Y direction decreases and the change in the X direction is within ±0.1, it is defined as negative Y-direction. In a certain example, if the workpiece is at position t1 (6.4, 3.1) and at position t2 (6.9, 3.0), then the change in the X direction is 0.5 and the change in the Y direction is −0.1, which meets the condition for positive X-direction. Therefore, this segment is marked as positive X-direction. If the next point is (6.9, 2.5), then the X direction is 0 and the Y direction is −0.5, which is marked as negative Y-direction. Similarly, by judging the continuity of direction, continuous segments in the same direction are merged into one direction segment. The merging process compares adjacent data points with the same direction as the merging condition. Within each direction segment formed after merging, the system monitors whether the cumulative displacement value deviates too much from the set expected value. If the deviation occurs continuously, the servo control curve will be adjusted to reduce the displacement stroke or adjust the motion angle. Only when the continuous directions are consistent and the cumulative displacement value exceeds the set threshold θm is it considered a valid direction segment. θm needs to be set in combination with the equipment accuracy and workpiece deformation characteristics. For example, if the workpiece elastic deformation is small... Since the device's positioning accuracy is 0.1, setting θm to 0.3 is reasonable. If a continuous positive X displacement value is 0.12, 0.09, and 0.15, the cumulative value is 0.36, which exceeds the threshold θm. The three segments can be merged into one positive X displacement segment. If there are only two points with a total displacement of 0.18, it is not enough to constitute a valid segment. This judgment is completed by comparing the cumulative displacement value with θm. Finally, the index, start and end time, direction category, and cumulative displacement value of each valid direction segment in the path sequence are organized in a structured manner to obtain the workpiece deformation path sequence segment group.

[0076] S203: Based on the overlap in time and direction between the pressing action direction path sequence and the workpiece deformation path sequence segment group, compare the directional trend and time position of each segment in the sequence, map the segments with synchronous relationship, and obtain the deformation behavior mapping structure table.

[0077] First, the start time, end time, and direction identifier of each segment in the compaction path sequence and deformation path segment group need to be read separately. These two sets of information are then expanded along the time axis and compared segment by segment. For each compaction path segment, a time overlap judgment operation is performed with all deformation path segments. Specifically, the start and end time ranges of the two segments are compared to see if they overlap. If the start time of the compaction segment is less than the end time of the deformation segment and the end time of the compaction segment is greater than the start time of the deformation segment, then the two segments are considered to overlap. For example, if the start and end times of the compaction segment are (10.2, 11.8) and the time of the deformation segment is (11.0, 12.0), then the overlapping time range is (11.0, 11.8). After the time overlap segment is confirmed, further... A direction consistency determination operation is performed by matching the string content of the compression segment direction and the deformation segment direction. If they are completely identical, they are considered to be in directional synchronization. For example, if the compression segment direction is positive X and the deformation segment direction is also positive X, then they can be considered to be in directional consistency. Under the condition of time overlap and direction consistency, the two segments are marked as synchronized. This operation requires performing nested loop traversal, comparing the time and direction of each segment in the compression path with each segment in the deformation path segment group. All segment pairs that meet the synchronization conditions are recorded by constructing a nested index structure, and these are recorded as compression segment number, compression segment time range, compression segment direction, deformation segment number, deformation segment time range, deformation segment direction, and time overlap range, respectively. When determining directional consistency, a directional recognition threshold θa needs to be set to tolerate minor angular deviations. When the path segment direction is represented by an angle, the directional angle difference can be compared with θa. For example, if a pressing direction is 0 degrees and the corresponding deformation direction is 5 degrees, the difference is 5, which is less than θa (10), so it is still considered that the directions are consistent. If the difference is 15, it is considered that they are different. This angle threshold θa is set according to the path acquisition accuracy and actual assembly error, with a recommended range of 8 to 12 degrees. The example value is 10. If the direction record is text, there is no need for angle judgment; the matching action can directly compare the string content. After all segment pairs that meet the synchronization conditions are confirmed, a deformation behavior mapping relationship is constructed. If a mapping relationship is detected... If multiple time overlaps are less than 0.2 seconds or the directions are inconsistent, the system will proactively update the compression start time setting value in the next cycle and re-check whether the overlapping interval has returned to the synchronization range to ensure synchronous deformation execution. This information is organized by creating a structure table. Each row of the structure table corresponds to a set of synchronization segment pairs. The structure table records are sorted in order of time start. For example, a structure table record is: compression segment number A1, time range (10.2, 11.8), direction X positive; deformation segment number B3, time range (11.0, 12.0), direction X positive, overlap interval (11.0, 11.8). Based on this rule, all segment pairs that meet the conditions are constructed into a structure table, resulting in a deformation behavior mapping structure table.

[0078] Please see Figure 4The specific steps of S3 are as follows:

[0079] S301: Based on the response time period in the deformation behavior mapping structure table, extract the temperature control operation data and heat treatment action time axis within the corresponding time range, filter the action data in the preheating stage, and extract the start time and duration of each group of control actions to obtain the preheating stage control action sequence.

[0080] First, the overlapping time intervals of the compression and deformation segments for each group of records in the structure table are read sequentially. Each interval consists of a start time and an end time. Using each record as an index, the system iterates through the data. For each time interval, the corresponding temperature control operation data and heat treatment action timeline data are retrieved. During data retrieval, a time field matching method is used to compare the time points of all records in the temperature control operation and heat treatment data with the start and end times of the target interval one by one. If the start time of a certain temperature control data is earlier than the end time of the target interval, and the end time is later than the start time of the target interval, then... The data is determined to be within the target range. Let the temperature control recording time be (8.2, 9.5), the target range be (8.0, 9.0), and their intersection be (8.2, 9.0), satisfying the overlap condition. After confirmation, the system proceeds to filter data for the preheating stage. Determining whether the data belongs to the preheating stage requires comparison based on the temperature control status field or the heating control command field. The system analyzes the temperature gradient slope of the preheating control segment to determine the heating efficiency. If the temperature rise per unit time is lower than the internal evaluation threshold, the current preheating duration is automatically extended, or the heater response level is increased in stages. If the field value is "Heating Start" or "Heating Before Constant Temperature Start," it is determined to be in the preheating stage. If the field value is "Constant Temperature" or "Heating," it is not in the preheating stage. To improve the accuracy of the judgment, a temperature change judgment operation needs to be introduced. That is, if the temperature value shows an upward trend in continuous recording and the final value does not reach the set constant temperature reference value θT, it can also be determined to be in the preheating stage. This θT is set according to the process requirements. For example, if the workpiece requires a constant temperature of 180°C, then θT is set to 180°C. If the starting temperature in a heating process is 45°C and the ending temperature is 160°C, and θT is not reached, it is considered to be a preheating process, and the record passes. Extract the start time and duration of the control action. The start time is directly read from the start time field of the corresponding record. The duration is calculated by the difference between the start and end times. For example, if the start time is 8.2 and the end time is 9.1, the duration is 0.9. Process each temperature control record that meets the conditions in the above way, and record its response time period number, control command type, start time, duration, temperature change range and other fields. Organize them into a structured data item, and summarize all data items that meet the conditions in sequence to finally obtain the control action sequence of the preheating stage.

[0081] S302: Based on the control action sequence of the preheating stage, retrieve the start time of each group of control actions and compare it with the start and end time of the pressing response behavior within the same time range. Separate the corresponding segments of control actions that are not in the same time segment to obtain a set of non-overlapping action time segments.

[0082] First, extract the start time and duration of each control action from the sequence, calculate the end time of each action, and form a complete action time segment. Taking record number C1 as an example, if the start time is 6.8 and the duration is 1.2, then its end time is 8.0. Then, sequentially read the corresponding clamping response behavior time segment from the deformation behavior mapping structure table, and record the start and end times of the clamping segment. For example, the time segment of clamping segment number P3 is (7.0, 9.0). Perform time overlap judgment on the time segments C1 and P3, comparing whether the start and end times of the control actions fall entirely within the time range of the clamping response segment. If the start time of a control action is less than the start time of the clamping section or greater than the end time of the clamping section, it is determined that the action is not in the same time segment. For example, in the time segment (6.8, 8.0), the start time is earlier than the start time of the clamping section (7.0), so it is marked as non-overlapping, and the next record C2 is processed. If its time segment is (9.2, 10.5), while the time segment of the clamping section P4 is (9.0, 10.0), then because the end time of C2 is later than the end time of the clamping section, it is also marked as non-overlapping. Such non-overlapping segments will be prioritized for execution in the next cycle through heat treatment plan rearrangement. The system will automatically adjust the execution order based on the response differences. The sequence ensures that heating is completed before the pressing operation. After determining that there is no overlap, the control action segment needs to be separated from the overall control action sequence, marked as an independent segment, and its original number, start time, end time, temperature control action type, target temperature, and other fields recorded. This provides a positioning basis for subsequent structural reconstruction. During the separation process, it is also necessary to determine whether there is partial overlap, that is, the start and end times of the control action only partially overlap with the pressing segment. This is achieved by comparing whether the start and end boundaries of the two segments intersect. If there is an intersection, the control action is divided into overlapping and non-overlapping segments. For example, the control segment C3 time is (8.4, 9.5). If the compression period is (8.8, 9.2), then the overlapping interval is (8.8, 9.2), and the non-overlapping interval is (8.4, 8.8) and (9.2, 9.5). The control segment needs to be split into three segments, and the non-overlapping segments before and after are marked. They are assigned the numbers C3a and C3c and added to the non-overlapping action time period set. This splitting action is achieved by updating the start and end times of the original records to the boundary values ​​of the new segments, and re-recording an independent index number for each segment. Finally, all non-overlapping action time period sets are organized into a structured data table, which includes fields such as action number, start and end time, original associated segment number, and overlap status identifier, thus obtaining the non-overlapping action time period set.

[0083] S303: Based on the set of non-overlapping action time periods, extract the corresponding control action number sequence according to the time sequence, remove duplicate numbers, and obtain the preheating stage temperature control behavior matching list.

[0084] First, extract the control action number and its start time for each record from the set. Combine all numbers and times into a two-dimensional sequence. Then, sort the sequence in ascending order of start time. The sorting operation is achieved by comparing the values ​​of all time fields and rearranging the index order. For example, in the original data, number C5 starts at 5.8, number C3 at 4.5, and number C8 at 6.1; after resorting, the order is C3, C5, C8. After sorting, a deduplication operation is performed. This is done by sequentially reading each number in the sorted sequence and comparing it with the preceding number. If two numbers are identical, discard the current number and move to the next. If the numbers are different, write the number to the output list. Repeat this process until the last item. The deduplication operation retains the first occurrence of the number to ensure that each control action is recorded only once in the list. During processing, it is necessary to determine if the same number is split into multiple segments, such as C4. Both 'a' and 'C4b' originate from the original number C4. At this point, the sub-numbers need to be uniformly restored to the main number. The processing method is to read the number string and remove the extended part of the last letter, retaining only the first part as the main number. Logical merging is achieved through main number identification, followed by deduplication to avoid repeatedly identifying the same control actions. During the above process, it is also necessary to check for empty or abnormal number records. If empty values ​​or non-standard named numbers exist, the current item is skipped and not included in the list, ensuring that the output numbers are valid and usable. Finally, the cleaned control action numbers are output as a list in sorted order. This list will be directly issued as an execution command list in the system task scheduling module. Each action number is bound to a real-time execution control strategy to achieve segmented precise temperature control. The list records C1, C3, C4, C5, and C8, indicating that the control actions corresponding to these numbers all appear in non-overlapping action time periods and are a unique and ordered set, resulting in the preheating stage temperature control behavior matching list.

[0085] Please see Figure 5 The specific steps of S4 are as follows:

[0086] S401: Based on the time segments in the preheating stage temperature control behavior matching list, extract the heating power adjustment action and axial load adjustment behavior within the time range, extract the start time and corresponding duration of the control action from each set of data, and obtain the control action time frame set.

[0087] First, the start and end times of each control action are read sequentially from the list, forming an independent time period sequence. This time period is then used as a query window to retrieve data points item by item from the heating power adjustment action data. The start and end times of all records are extracted from the data table, and each record is compared numerically with the current window time. When the start time of an adjustment action intersects with a time period recorded in the list (i.e., the start time is earlier than the end time of the time period and the end time is later than the start time), the adjustment action is considered to belong to that time range. For example, if the time period is (7.2, 8.0), then... The start and end times of the heat adjustment action are (7.4, 8.3), and there is an intersection between them (7.4, 8.0). Therefore, this adjustment record is extracted. The same operation is then performed on the axial load adjustment data, extracting the start and end times of each load adjustment record and comparing them with the time periods in the list. For example, if a load adjustment record's time period is (6.9, 7.6), and the intersection within the matching time period (7.0, 8.1) is (7.0, 7.6), this record is also extracted. From the above filtering results, the start time and duration of the heating power adjustment and load adjustment actions are extracted respectively. The start time is directly adjusted... The start time field in each record is used, and the duration is calculated by subtracting the start time from the end time. For example, if the adjustment action starts at 7:4 and ends at 8:00, the duration is 0.6. If the axial load adjustment action starts at 7:00 and ends at 7:6, the duration is also 0.6. After extraction, each action data is organized into structural units, including action type fields (such as "heating adjustment" or "load adjustment"), action number, start time, end time, duration, and control target value fields. All structural units are sorted by time, and their corresponding records are recorded. The system assigns a list number to establish a correspondence between actions and temperature control behaviors. Throughout the process, actions with a duration less than a set threshold θd must be removed. The θd setting is used to filter short-term invalid control records. Based on the device's control frequency and response delay, a θd value of 0.2 is recommended. If the duration of an action is 0.1, it will not be recorded. However, when multiple consecutive short-term actions appear in the same control window, the system merges them into a single continuous main control command and issues it for execution to ensure the continuity of power regulation and response effect. Finally, after completing the combination of all matched and filtered action structure units, a set of control action time frames is obtained.

[0088] S402: Based on the set of control action time frames, extract the feedback time point sequence from the temperature change records within the same time period, compare the chronological relationship between the start time of the control action and the temperature feedback occurrence time, and obtain the response delay correspondence table.

[0089] First, the start and end times of each control action record are read sequentially. This time period is used as the search range. Temperature feedback records within the same time period are extracted from the temperature change records. Specifically, each record in the temperature change data table is traversed, its corresponding timestamp is read, and it is determined whether the timestamp is greater than or equal to the start time of the control action and less than or equal to its end time. If this time range condition is met, the record is retained as a response feedback data point. During the extraction process, the temperature records need to be sorted by time to form a feedback time point sequence, with each time point corresponding to a temperature value. The existence of a change response is determined by calculating the temperature difference between adjacent points. When the temperature change between two consecutive points is greater than the set temperature response threshold θT, that point is recorded as a feedback response time point. The θT setting needs to be combined with the sensor accuracy and environmental fluctuations. If the temperature sensor accuracy is 0.2 and the environmental fluctuation is ±0.3, then θT can be set to 0.5. If the temperature at one point is 115.3 and the next point is 115.9, then the change is 0.6, which is greater than... θT is used to determine the latter as the feedback response point. After completing the construction of the feedback time point sequence, each feedback point is compared with the start time of the control action. Specifically, the start time of the action is read and the value of each feedback time point is compared. If the feedback time point is greater than the start time of the action, the difference between the two is calculated as the response delay time. For example, if the start time of the control action is 9.2 and the feedback time point is 9.6, the response delay is 0.4. If the feedback time point is earlier than the start time, it is not included in the delay. If multiple feedback points meet the conditions, the earliest one is recorded as the first response point. If no feedback point that meets the threshold change is found, it is recorded as no feedback. If the feedback point is later than the start of the action and exceeds the response tolerance threshold, the power surge is first limited and the output setpoint is corrected by segmented boosting to avoid overshoot caused by sudden temperature rise after hysteresis. All matching results are summarized by action number, and the fields of control action number, start time, feedback time point, and response delay time are organized into structured record units. All structured units are then combined into a table and sorted by the start time of the action to obtain the response delay correspondence table.

[0090] S403: Based on the response delay correspondence table, identify control behaviors with continuous lag in feedback time points in continuous time segments, extract the action type and start and end positions corresponding to the segments, and obtain a set of parameter disturbance behavior segment sequences;

[0091] First, the start time and feedback response time of each control action in the response delay correspondence table are read sequentially and arranged in chronological order to form a delay behavior sequence. Then, it is determined whether there is continuous feedback lag or no feedback response between adjacent actions. When multiple actions exhibit response lag characteristics within a continuous time range, the segment is identified as a continuous control anomaly segment. After confirming the segment, the system further distinguishes between heating power adjustment lag and load adjustment response lag by combining the action type field. The starting and ending action positions corresponding to the segment are extracted to determine the disturbance range. Simultaneously, the control decision and execution stages are triggered to dynamically correct this type of continuous lag behavior. For example, in the case of temperature control response lag, the preheating power output level of the next stage is automatically increased; in the case of load response lag, the compression loading rate is automatically reduced or the load application start point is delayed, thereby avoiding lag accumulation that could lead to temperature or pressure overshoot. Finally, the continuous lag segment is structurally encapsulated according to action type, start and end positions, and delay characteristics, and a disturbance segment number is generated to obtain a parameter disturbance behavior segment sequence set.

[0092] Please see Figure 6 The specific steps of S5 are as follows:

[0093] S501: Based on the segment number in the parameter disturbance behavior segment sequence set, retrieve the control command and feedback data of the parameter in the current period, match the time points of the data sequence in a continuous time period, and obtain the control feedback time sequence group.

[0094] First, each segment number recorded in the sequence set is read item by item. Based on this number, the corresponding time segment is retrieved from the control input data table and feedback data table for the current period. By reading the start and end time fields associated with the segment number, a continuous target time interval is formed. Then, a time comparison operation is performed on each data record in the control input data table, comparing the recorded timestamp with the target interval. If the recorded time is greater than or equal to the start time of the interval and less than or equal to the end time, the record is included in the control input sequence corresponding to this segment. For example, the time range of segment number D4 is (12.4, 14.0). If a record in the input table has a time of 13.1, it falls within the specified interval and is extracted. Simultaneously, the system retrieves the feedback data, reading the timestamp of each record in the feedback data table. By comparing each record with the target interval in the same manner, feedback data records whose times fall within the specified interval are retained, constructing a feedback data subsequence. The system then determines whether the fluctuation trend of the feedback subsequence deviates from the main trajectory of the control sequence. If consecutive reversals occur, the system synchronously updates the setting parameters of the heating power and load control curves for the next cycle at the end of the current cycle and issues the update. For example, if the feedback record times are 12.6 and 13.9, both within the example interval, then a reverse... After extracting the control input and feedback sequences, to ensure a one-to-one correspondence between time points, both sequences need to be sorted by timestamp and then time alignment is performed. Specifically, this involves iterating through each time point in the control input sequence and calculating the difference between it and each time point in the feedback sequence. When the absolute value of the difference is less than a set threshold θc, the control input and feedback data are considered to correspond. θc is set in conjunction with the acquisition synchronization error. For example, if the recording error between the two types of data does not exceed 0.03, then θc can be set to 0.05. If the control input time is 13:12 and the feedback time is 13:14, then the difference is 0.02, which is less than the threshold. The data points are recorded as a set of corresponding data points. If multiple feedback points meet the conditions, the one with the smallest time difference is selected as the final corresponding point. Furthermore, if a control input point fails to find a corresponding point in the feedback sequence that meets the threshold conditions, it is recorded as missing in the result, forming a mark that the control point and the feedback point do not correspond. Conversely, if a feedback point has no corresponding control input point, it is also recorded as an isolated feedback point. The time point comparison corresponding to all time segment numbers is completed in the above manner, and a time series group consisting of several control input points and feedback data points is formed for each number. Finally, all time series groups corresponding to the numbers are packaged in numerical order to form a control feedback time series group.

[0095] S502: Call the control feedback time series group, compare the time point of the control command action with the time point of the feedback response, divide the continuous area where the data has intervals on the time axis, and obtain the response difference time period set;

[0096] First, the control input time point and feedback response time point corresponding to each segment in the sequence are read item by item, and then expanded into a set of discrete points on the time axis in chronological order. By reading the time fields of the control input point and feedback point, two independent time series are formed. During the comparison, the closest feedback time point in the feedback series is found for each control input time point. Matching is achieved by calculating the time difference between the two. If the control point time is 15.2 and the feedback point time is 15.6, the difference is 0.4. After establishing the differences between all input points and feedback points, these differences are arranged in chronological order and then compared with the threshold θg for difference judgment. Let θg be set as... The threshold θg is used to identify "significant intervals" and can be determined based on the periodic sampling frequency and the upper limit of the response delay. For example, if the normal range of the system's maximum response delay is 0.3, then θg can be set to 0.3. When the difference is greater than θg, it is determined that there is a time interval between the input and the feedback, and the control point is identified as the starting point of the delay segment. The time continues to be read sequentially. If the difference between multiple consecutive control input points is greater than θg, then the time intervals to which this series of control input points belong are merged into a continuous interval region. For example, if the input points are 15.2, 15.5, and 15.9 in sequence, and their corresponding feedback differences are 0.4, 0.6, and 0.5 respectively, then because the differences between the three input points are greater than θg, the time intervals are merged into a continuous interval region. All values ​​greater than θg form continuous interval segments, ranging from the earliest control point 15.2 to the latest control point 15.9. Conversely, if the difference in a sequence is 0.1, less than the threshold, it is not included in the interval segment and is skipped as a valid response point. When merging time periods, connectivity checks are performed on adjacent interval segments. The difference between the start time of the next segment and the end time of the previous segment is compared to determine whether to merge. If the difference is less than the continuity threshold θc2, for example, if θc2 is set to 0.2 and the current interval segment ends at 15.9, and the next segment starts at 16.0, then the difference is 0.1, which is less than θc2, and the preceding and following interval regions need to be merged. Throughout the entire processing... The system needs to handle situations where a control input point lacks a corresponding feedback point. If a control point does not match a feedback point, its difference is considered as no response and set as the maximum difference marker. It is then added to the interval segment. If multiple such points are adjacent, they are all added to the same interval segment. Finally, all interval segments corresponding to each segment number are recorded in chronological order from early to late as structured information consisting of three items: segment number, start time, end time, and difference range. All segment records are summarized into a table, which is the response difference time period set. (If the response difference time period set appears more than twice in the same parameter channel, the system will consider it as control path drift and call the backup control strategy parameter table to perform redundant control replacement.)

[0097] S503: Based on the response difference time period set, track the numerical trend of each group of parameters within the segment, divide the direction trend and span of numerical change during the time process, and obtain the migration record of the control path.

[0098] First, the start and end times for each time period are read sequentially from the collection. This time range is then used as a window for parameter value tracking. Continuous data records for each parameter within its corresponding segment are extracted according to their assigned numbers. The data includes control input values, feedback values, or a calculated value combining both. Based on the data type, the field representing the control path is selected for processing; for example, the heating setpoint is selected for temperature parameters, and the axial load control value is selected for pressure parameters. During the time progression, the extracted data is arranged in timestamp order. Each adjacent data point is traversed and its value is read. The magnitude of each subsequent value is compared with the preceding value. If the value of the subsequent term is greater than that of the preceding term, it is marked as an upward segment; if it is less, it is marked as a downward segment; if they are equal, it is marked as a level segment. This method divides the entire segment into several directional segment groups according to the direction of change. Simultaneously, the start time, end time, and corresponding numerical span of each segment are recorded. The span is determined by the difference between the maximum and minimum values ​​within that segment. For example, if a segment starts at 16.4 and ends at 16.8, and the value rises from 21.5 to 24.0, the direction is upward, and the span is 2.5. If the value falls from 33.2 to 30.0, the direction is downward, and the span is 3.2. If the value remains continuously at 27.1, the direction is level, and the span is 0. A change threshold θv is introduced during processing to eliminate weak fluctuations. If the numerical change is less than θv, it is forcibly classified as flat. θv is set based on sampling accuracy and system noise. If the system noise is ±0.4, then θv can be set to 0.5. For example, a segment with a start value of 48.6 and an end value of 48.9 has a change of 0.3. If the change is less than the threshold, it is classified as a flat segment. All directional segment groups are consecutively numbered, and their parameter names, segment numbers, start and end times, direction categories, numerical start points, numerical end points, and span values ​​are recorded. If a segment contains multiple directional segments, they are arranged sequentially into a direction sequence. The change pattern of the direction sequence is also encoded and identified. For example, "rise-fall-level" is marked as a coded sequence UDF. The entire process must ensure that the start and end times of each segment boundary and response difference time period are strictly consistent, and there are no omissions or repetitions within the segment. Finally, the control path direction trend and numerical span of all parameters in each response difference time period are organized into a unified structure form to form a control path migration record. (After the path record is formed, the evolution trend of different paths is analyzed using the coded structure, and the main control module is linked to dynamically correct the pressure setpoint and heating power target value of the next cycle, so that the control path develops in a convergent state and reduces the accumulation of disturbances.)

[0099] The position of a segment in a fluctuation trend refers to the physical semantic position of the segment in the stress cycle by combining the starting node (peak / valley) of the pressure trend segment with the trend direction (rising / falling / stable), which is used to mark the functional role in the cycle.

[0100] Analyzing the correspondence refers to performing time and direction overlap matching between the clamping path and the workpiece deformation path. If the time intervals intersect and the directions are consistent, a mapping relationship is established.

[0101] Extracting time segments of asynchronous actions refers to identifying action segments where the control action (preheating) and the response behavior (pressing) do not overlap in time;

[0102] The response delay correspondence table records the delay duration between control initiation and feedback response;

[0103] The parameter perturbation behavior fragment sequence set refers to the set of action fragment structures with continuous feedback lag;

[0104] The control path migration record refers to the analysis of the trend and magnitude of parameter changes within the response offset segment, indicating the dynamic evolution of the execution path.

[0105] Please see Figure 7 A process parameter control system for automotive fastener production, comprising:

[0106] The stress fluctuation extraction module acquires the cavity pressure and mold wall temperature data during the forming process of automotive fasteners, extracts the stress peak and valley points in a continuous cycle, divides the pressure fluctuation period, extracts the start and end nodes and change direction of each segment, locates the role of the segment in the fluctuation trend, and obtains a set of stress fluctuation segment labels.

[0107] The deformation path comparison module extracts the clamping trajectory and displacement change path based on the time range in the stress fluctuation section label set, compares the direction switching behavior time, analyzes the corresponding relationship, and obtains the deformation behavior mapping structure table.

[0108] The temperature control behavior screening module extracts the preheating control data and the pressing response time point based on the response time period in the deformation behavior mapping structure table, compares the actions on the time axis, extracts the time segments and control numbers of the asynchronous actions, and obtains the temperature control behavior matching list for the preheating stage.

[0109] The response delay extraction module extracts the power adjustment and load action time based on the preheating stage temperature control behavior matching list, compares the temperature response sequentially, identifies continuous delay behavior, and obtains a set of parameter disturbance behavior fragment sequences.

[0110] The parameter offset tracking module extracts control commands and feedback data based on the numbering of the parameter disturbance behavior fragment sequence set, tracks the offset direction within the cycle, extracts the corresponding execution process, and obtains the migration record of the control path.

[0111] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for controlling process parameters in automotive fastener manufacturing, characterized in that, Includes the following steps: S1: Obtain mold cavity pressure and mold wall temperature data during the forming process of automotive fasteners, extract stress peak and valley points in continuous cycles, divide pressure fluctuation periods, extract the start and end nodes and change direction of each segment, locate the role of the segment in the fluctuation trend, and obtain a set of stress fluctuation segment labels. S2: Based on the set of stress fluctuation segment labels, extract the clamping trajectory and displacement change path, compare the direction switching behavior time, and analyze the corresponding relationship to obtain the deformation behavior mapping structure table; S3: Based on the deformation behavior mapping structure table, extract the preheating control data and the pressing response time point, compare the actions on the time axis, extract the time segments and control numbers of the asynchronous actions, and obtain the preheating stage temperature control behavior matching list. S4: Based on the preheating stage temperature control behavior matching list, extract the power adjustment and load action time, compare the temperature response in sequence, identify continuous delayed behavior, and obtain a set of parameter disturbance behavior fragment sequences. S5: Based on the parameter disturbance behavior segment sequence set, extract control commands and feedback data, track the offset direction within the cycle, extract the corresponding execution process, and obtain the migration record of the control path.

2. The method for controlling automotive fastener manufacturing process parameters according to claim 1, characterized in that, The stress fluctuation zone label set includes start node, end node, pressure trend, change direction, and fluctuation trend position. The deformation behavior mapping structure table includes the starting and ending points of compression, deformation direction path, direction consistency status, and time overlap range. The preheating stage temperature control behavior matching list includes control action sequence number, control action time segment, and time overlap judgment result. The parameter disturbance behavior segment sequence set includes operation response delay segment number, temperature control action start point, and temperature feedback response point. The control path migration record includes control input data, feedback data, response difference time point, and parameter state offset direction.

3. The method for controlling automotive fastener manufacturing process parameters according to claim 1, characterized in that, The stress peak and valley points refer to the highest and lowest points within the pressure cycle of the mold cavity. The pressing trajectory refers to the actual movement path and direction change of the pressing mechanism during the forming process.

4. The method for controlling automotive fastener manufacturing process parameters according to claim 1, characterized in that, The displacement change path refers to the direction of displacement and the trajectory of deformation process generated by the workpiece during the clamping process; The continuous delay behavior refers to a continuous abnormal response in which the control action has occurred but the feedback is continuously delayed.

5. The method for controlling automotive fastener manufacturing process parameters according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Acquire the continuous output data of the stress and temperature sensors in the mold cavity within a specified time period, extract the periodic stress peak and valley positions from the pressure curve, and match the corresponding time points with the pressure values ​​one by one to obtain a stress peak and valley data reference set. S102: Based on the stress peak and valley data comparison set, segment the continuous change process between adjacent data points, extract the start and end nodes of each segment, analyze the direction of pressure increase and decrease between nodes, and obtain a segmented set of pressure change trends. S103: Call the pressure change trend segment set, match the start and end nodes of each segment with their corresponding positions in the fluctuation sequence, distinguish the combination relationship between the change direction and the location, and obtain the stress fluctuation segment label set.

6. The method for controlling automotive fastener manufacturing process parameters according to claim 1, characterized in that, The specific steps of S2 are as follows: S201: Based on the time range in the stress fluctuation segment label set, retrieve motion trajectory data and workpiece displacement trend data during the clamping action, extract the starting point of the clamping behavior and the change process of the clamping direction path within the time range, and obtain the clamping action direction path sequence. S202: Based on the pressing action direction path sequence, extract the workpiece displacement trend data within the corresponding time period, and divide the change path into continuous direction segments to obtain the workpiece deformation path sequence segment group. S203: Based on the overlap in time and direction between the pressing action direction path sequence and the workpiece deformation path sequence segment group, compare the directional trend and time position of each segment in the sequence, map the segments with synchronous relationship, and obtain the deformation behavior mapping structure table.

7. The method for controlling automotive fastener manufacturing process parameters according to claim 1, characterized in that, The specific steps for S3 are as follows: S301: Based on the response time period in the deformation behavior mapping structure table, extract the temperature control operation data and heat treatment action time axis within the corresponding time range, filter the action data in the preheating stage, and extract the start time and duration of each group of control actions to obtain the preheating stage control action sequence. S302: Based on the preheating stage control action sequence, retrieve the start time of each group of control actions and compare it with the start and end time of the pressing response behavior within the same time range. Separate the corresponding segments of control actions that are not in the same time segment to obtain a set of non-overlapping action time segments. S303: Based on the set of non-overlapping action time periods, extract the corresponding control action number sequence according to the time sequence, remove duplicate numbers, and obtain the preheating stage temperature control behavior matching list.

8. The method for controlling automotive fastener manufacturing process parameters according to claim 1, characterized in that, The specific steps of S4 are as follows: S401: Based on the time segments in the preheating stage temperature control behavior matching list, extract the heating power adjustment action and axial load adjustment action within the time range, extract the start time and corresponding duration of the control action from each set of data, and obtain the control action time frame set. S402: Based on the control action time frame set, extract the feedback time point sequence from the temperature change record within the same time period, compare the chronological relationship between the control action start time point and the temperature feedback occurrence time point in chronological order, and obtain the response delay correspondence table. S403: Based on the response delay correspondence table, identify control behaviors with continuous lag in feedback time points in continuous time segments, extract the action type and start and end positions corresponding to the segments, and obtain a set of parameter disturbance behavior segment sequences.

9. The method for controlling automotive fastener manufacturing process parameters according to claim 1, characterized in that, The specific steps of S5 are as follows: S501: Based on the segment number in the parameter disturbance behavior segment sequence set, retrieve the control command and feedback data of the parameter in the current period, and match the time points of the data sequence in a continuous time period to obtain the control feedback time sequence group. S502: Call the control feedback time series group, compare the time point of the control command action with the time point of the feedback response, divide the continuous region where the data has intervals on the time axis, and obtain the response difference time period set; S503: Based on the set of response difference time periods, track the numerical trend of each group of parameters within the segment, divide the direction trend and span of numerical changes during the time progression, and obtain the migration record of the control path.

10. A control system for automotive fastener manufacturing process parameters, characterized in that, The system is used to implement the automotive fastener manufacturing process parameter control method according to any one of claims 1-9, the system comprising: The stress fluctuation extraction module acquires the cavity pressure and mold wall temperature data during the forming process of automotive fasteners, extracts the stress peak and valley points in a continuous cycle, divides the pressure fluctuation period, extracts the start and end nodes and change direction of each segment, locates the role of the segment in the fluctuation trend, and obtains a set of stress fluctuation segment labels. The deformation path comparison module extracts the clamping trajectory and displacement change path based on the time range in the stress fluctuation segment label set, compares the direction switching behavior time, analyzes the corresponding relationship, and obtains the deformation behavior mapping structure table. The temperature control behavior screening module extracts preheating control data and pressing response time points based on the response time periods in the deformation behavior mapping structure table, compares the actions on the time axis, extracts time segments and control numbers of asynchronous actions, and obtains a preheating stage temperature control behavior matching list. Based on the preheating stage temperature control behavior matching list, the response delay extraction module extracts the power adjustment and load action time, performs sequential comparison of the temperature response, identifies continuous delay behavior, and obtains a set of parameter disturbance behavior fragment sequences. The parameter offset tracking module extracts control commands and feedback data based on the numbering of the parameter disturbance behavior segment sequence set, tracks the offset direction within the period, extracts the corresponding execution process, and obtains the migration record of the control path.

Images