Precision plastic mold low stress injection molding precision processing method and system

Abstract

The present application relates to the technical field of intelligent manufacturing equipment industry, in particular to a precision processing method and system for low-stress injection molding of precise plastic molds, comprising the following steps: obtaining wall thickness data to generate a mutation section, reconstructing a filling curve to generate an adjustment track, extending an isobaric formation buffer control section, setting a linkage window to generate a pressure relief record, and matching precision requirements to generate a molding result. In the present application, the dynamic response correction of the cavity wall thickness change area is used to achieve accurate matching of the injection filling timing, the pressure distribution is adjusted by linking the injection filling trend and the structure change trend, the pressure buffer area is constructed in the structure discontinuous area to realize isobaric transition, the local pressure relief rhythm in the mold core retraction process is dynamically controlled by identifying the pressure stagnation position in the cooling stage, and the complete evaluation closed loop is constructed by combining the size resilience and stress distribution of the pressure relief area, which effectively suppresses the local stress concentration problem caused by structure mutation and improves the precision of the injection molding process.

Description

Technical Field

[0001] This invention relates to the field of intelligent manufacturing equipment technology, and in particular to a precision processing method and system for low-stress injection molding of precision plastic molds. Background Technology

[0002] The field of intelligent manufacturing equipment technology specifically involves precision control in the injection molding process of plastic products. The core technology in this area lies in using numerical control (NC) technology, process simulation and analysis, and closed-loop control theory to adjust various physical parameters of the injection molding machine and mold system. Its overall technical structure mainly includes: analyzing stress, temperature, and flowability using computer-aided engineering software; executing preset injection molding process curves using a NC system; collecting data in real time through pressure sensors; and finally, having the control system drive the actuators to adjust injection pressure, mold cavity pressure, venting pressure, or hot runner pressure to ensure molding accuracy. Regarding the pressure fluctuations and unevenness in the plastic mold injection molding process mentioned above, traditional pressure control methods involve the injection molding machine's central controller outputting control signals to the hydraulic system based on preset process parameters such as injection speed, holding pressure, and time. This hydraulic system adjusts the flow and pressure of hydraulic oil by driving servo valves or proportional valves, thereby driving the screw to complete the injection and holding pressure actions of molten plastic. In this process, a pressure sensor is usually installed at the hydraulic circuit or nozzle position of the injection molding machine. The sensor will collect a single-point pressure signal and feed it back to the central controller. The controller will perform single-loop PID calculation based on the deviation between the feedback signal and the set value, and adjust the opening of the servo valve or proportional valve to indirectly regulate the overall pressure of the injection molding system.

[0003] In existing low-stress injection molding processes using plastic molds, injection pressure control mainly relies on preset process curves and single-point pressure feedback signals. When encountering complex mold cavity structures or areas with abrupt changes in wall thickness, pressure response lag or overshoot is prone to occur. Single-loop PID regulation is insufficient to adapt to pressure changes during dynamic filling, often resulting in local overpressure or underpressure in practical applications, which in turn leads to problems such as product dimensional deviations and stress concentration. For example, in injection molding of products with multi-segment gradually changing wall thickness, deformation and warping often occur due to the lack of regional pressure coordination mechanisms. The lack of a refined control path for the injection behavior of complex structures limits the overall precision control capability. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and to propose a precision processing method for low-stress injection molding of precision plastic molds.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a precision processing method for low-stress injection molding of precision plastic molds, comprising the following steps:

[0006] S1: Obtain the wall thickness step scan data of the inner wall of the injection section of the plastic mold, read the wall thickness values ​​of adjacent points to calculate the difference, and filter the structural areas where the difference changes beyond the change threshold to generate the wall thickness change section of the injection section.

[0007] S2: Based on the sudden change in wall thickness of the injection molding section, extract the corresponding section's starting pressure response node and the actual filling start point, calculate the time difference and compare it with the internally set reference filling cycle, reconstruct the corresponding injection molding stage filling curve, and generate the filling section timing adjustment trajectory.

[0008] S3: Based on the timing adjustment trajectory of the filling segment, extract the wall thickness distribution trend of the corresponding mold cavity area, identify the target area that changes from a wall thickness greater than the average wall thickness of the cross section to a wall thickness less than the average wall thickness, extend the isobaric time period to the target area and unify the pressure gradient to form an isobaric buffer, and obtain the thickness transition buffer control segment.

[0009] S4: Read the structural data of the closed end of the mold cavity during the subsequent cooling stage of the thick-thin transition section buffer control section, identify the pressure retention area and set a linkage release window on the surface. When the mold core retraction trend is lower than the slope of the pressure rise curve at the closed end, the linkage release window is triggered to open and close, and a local pressure relief record of the mold cavity terminal is generated.

[0010] S5: After the completion of the local pressure relief record at the end of the mold cavity, the dimensional springback data and regional stress distribution data of the injection molded product are statistically analyzed. The dimensional deviation range is compared and the stress distribution breadth is checked to match the precision requirements and generate the low-stress injection molding result of the precision plastic mold.

[0011] As a further aspect of the present invention, the wall thickness abrupt change zone of the injection molding section includes a wall thickness change threshold zone, a structural difference response zone, and a cross-zone wall thickness abrupt change point; the timing adjustment trajectory of the filling section includes a pressure response correction band, a filling cycle adjustment line, and a curve reconstruction node; the thickness transition buffer control section includes an isobaric extension zone, a unified pressure gradient zone, and a buffer transition interface; the local pressure relief record at the mold cavity terminal includes a pressure release point, a linkage window opening and closing trajectory, and a mold core response hysteresis band; and the low-stress injection molding result of the precision plastic mold includes a dimensional springback control zone, a regional stress uniform distribution zone, and a springback and stress tolerance matching domain.

[0012] As a further aspect of the present invention, the step of obtaining the abrupt change in wall thickness of the injection molding section specifically comprises:

[0013] S111: Obtain the wall thickness step scan data of the inner wall of the injection section of the plastic mold, and read the wall thickness values ​​of adjacent measurement points in the obtained scan data one by one, calculate the wall thickness difference sequence between adjacent points, analyze the numerical offset change between all difference items in the sequence and their previous items, count the offset between adjacent differences, and generate a wall thickness difference offset sequence matrix.

[0014] S112: Based on the wall thickness difference offset sequence matrix, using the injection molding section structural interval as the distinguishing standard, extract the corresponding difference offset data in each structural interval, calculate the numerical range difference between the maximum and minimum offset values ​​in each structural interval, and construct an interval change set according to the injection molding section arrangement order of all interval range differences to generate a set of wall thickness difference change ranges between structural sections.

[0015] S113: Based on the range of wall thickness difference between the structural segments, each range of change is compared with the preset wall thickness difference threshold. The structural positions corresponding to the intervals with values ​​greater than the wall thickness difference threshold are recorded. All structural regions that meet the conditions are aggregated and sorted to obtain the wall thickness change abrupt section of the injection molding segment.

[0016] As a further aspect of the present invention, the step of obtaining the timing adjustment trajectory of the filling segment specifically comprises:

[0017] S211: Based on the sudden change in wall thickness of the injection molding section, extract the time-series data frames recorded in the pressure acquisition nodes and filling sensing nodes in each corresponding section, retrieve the pressure response data change point at the starting position of the section and the resin front advancement starting point index corresponding to the filling position, parse the two time-series index values ​​into actual time points, calculate the time difference between the two, and establish the filling start time difference of the injection molding section.

[0018] S212: Based on the filling start time difference of the injection segment and combined with the reference filling cycle benchmark value, determine whether the time difference is greater than the upper limit threshold or less than the lower limit threshold of the filling cycle. If it is satisfied, determine that the corresponding segment has a cycle advance or lag trend, and obtain the filling cycle offset judgment identifier set.

[0019] S213: Based on the segments determined to be offset in the filling beat offset determination identifier set, perform the adjustment of the pressure start node timestamp of the corresponding segment according to the offset direction, and perform time-series interpolation reconstruction operation on the adjusted pressure start node and the remaining data points in the original filling curve to rearrange the complete filling curve point set of the segment and obtain the filling segment time-series adjustment trajectory.

[0020] As a further aspect of the present invention, the step of obtaining the thick-thin transition section buffer control segment specifically includes:

[0021] S311: Based on the filling segment timing adjustment trajectory, establish a corresponding time axis for the filling stage for each node segment of the mold cavity region. Perform wall thickness data extraction operation on all node times on the time axis to obtain the wall thickness value sequence of all sampling points on the cross section of the mold cavity at the corresponding time point. Calculate the average wall thickness of the current cross section and compare the local wall thickness value of each sampling point with the average value. Filter the point combinations where the local wall thickness value changes from being greater than the average wall thickness to being less than the average wall thickness, and establish a wall thickness downward transition trend set.

[0022] S312: Based on the combination of concentrated marker points of the downward transition trend of the wall thickness, determine the distribution segment of the spatial position in the mold cavity structure, and extend the time window sequentially towards the filling direction of the area where the point is located. According to the pressure value distribution corresponding to each unit sampling point on the time axis of the original filling segment, set a continuous isobaric maintenance window and complete the coverage mark on the time axis to form a one-to-one mapping between the structural segment and the time period, and obtain the isobaric extension control interval.

[0023] S313: Based on all marked structural segments and time ranges in the isobaric extension control interval, perform the corresponding time period reconstruction operation, set the pressure to maintain a pressure change gradient of zero in the extension segment and perform edge transition processing, unify the pressure value of all internal nodes to the upstream end pressure value of the cross section, and obtain the thick-thin transition buffer control segment.

[0024] As a further aspect of the present invention, the step of obtaining the partial depressurization record of the mold cavity terminal specifically includes:

[0025] S411: Based on the thick-thin transition buffer control segment, read the cooling stage data frame on the subsequent time axis, extract the structural mesh in the closed end of the mold cavity layer by layer, obtain all wall thickness sampling points in the closed area and establish a wall thickness distribution sequence according to their arrangement number along the main filling direction, calculate the wall thickness difference between adjacent sampling points in sequence and calculate the average, set the local section with the average difference higher than the wall thickness gradient difference threshold as the section to be identified, and generate the end wall thickness gradient difference section identification matrix;

[0026] S412: Based on the end wall thickness gradient difference section identification matrix, extract the cavity pressure curve at each moment in the corresponding structural section and establish a pressure fluctuation array synchronously with time. Select the pressure retention judgment area, set the linkage release window on the corresponding cavity surface through spatial coordinate mapping, and generate a pressure retention mapping window table.

[0027] S413: Based on each linkage window area in the pressure retention mapping window table, calculate the core retraction displacement trend value and the slope of the corresponding closed end pressure curve at each moment during the cooling stage, calculate the linkage response error factor of each window node, and if the linkage response error factor is lower than the response trigger threshold, activate the linkage release window and record the start and end times of opening and closing, and establish a local pressure relief record of the mold cavity terminal.

[0028] As a further aspect of the present invention, the calculation formula for the linkage response error factor is as follows:

[0029] ;

[0030] in, Indicates the first Linkage response error factor at each linked window node This indicates the core shrinkage trend value. This represents the slope of the pressure curve. This represents the sum of squared errors at all nodes.

[0031] As a further aspect of the present invention, the steps for obtaining the low-stress injection molding results of the precision plastic mold are specifically as follows:

[0032] S511: Based on the local pressure relief record of the mold cavity terminal, collect the three-dimensional dimensional coordinates of each structural section in the free state after the injection molded product has cooled down, and match them one by one with the standard geometric data of the mold cavity design. Extract the directional offset of each reference point and calculate the spatial vector magnitude. Construct a dimensional springback vector field for the entire product range. Perform maximum, mean and standard deviation extraction operations on all springback vector values, and compare them point by point with the set dimensional deviation tolerance. Filter all springback anomaly points that exceed the tolerance range and generate a dimensional springback deviation distribution matrix.

[0033] S512: Based on the size rebound deviation distribution matrix, filter out the deviation anomaly point areas, perform internal residual stress data extraction operation on the remaining areas, establish an equally spaced node grid, extract the principal stress tensor at each node and convert it into equivalent stress value, perform regional mean and standard deviation calculation on all node stress values, if the local node stress offset is greater than the stress uniformity tolerance, mark the node as a stress anomaly point, and judge the spatial distribution continuity to obtain the area range where all stresses meet the tolerance conditions, and establish the effective coverage parameter of uniform stress.

[0034] S513: Based on the size rebound deviation distribution matrix and the effective coverage rate parameter of uniform stress, perform joint judgment on the proportion of abnormal points and the stress uniformity rate respectively. When the proportion of deviation points is less than the threshold of the proportion of size deviation abnormal points and the uniform coverage rate is higher than the lower limit threshold of the stress uniformity coverage rate, it is determined that the structure and molding process of the injection molded product meet the low stress rebound condition, the corresponding mold number and molding parameters are recorded, and the low stress injection molding result of precision plastic mold is generated.

[0035] A precision processing system for low-stress injection molding of precision plastic molds, including:

[0036] The wall thickness difference identification module is used to perform S1: acquire the wall thickness step scan data of the inner wall of the injection section of the plastic mold, read the wall thickness values ​​of adjacent points to calculate the difference, and filter the structural areas where the difference changes beyond the change threshold to generate the wall thickness change section of the injection section.

[0037] The pressure timing adjustment module is used to execute S2: Based on the sudden change in wall thickness of the injection molding section, extract the starting pressure response node of the corresponding section and the actual filling start point, calculate the time difference and compare it with the internally set reference filling cycle, reconstruct the filling curve of the corresponding injection molding stage, and generate the filling segment timing adjustment trajectory.

[0038] The transition zone pressure stabilization module is used to execute S3: based on the timing adjustment trajectory of the filling segment, extract the wall thickness distribution trend of the corresponding mold cavity area, identify the target area that changes from greater than the average wall thickness of the cross section to less than the average wall thickness, extend the isobaric time period to the target area and unify the pressure gradient to form an isobaric buffer, and obtain the thick and thin transition segment buffer control segment.

[0039] The linkage pressure relief triggering module is used to execute S4: read the structural data of the closed end of the mold cavity in the subsequent cooling stage of the thick-thin transition section buffer control section, identify the pressure retention area and set the linkage release window on the surface. When the mold core retraction trend is lower than the slope of the pressure rise curve of the closed end, the linkage release window is triggered to open and close, and a local pressure relief record of the mold cavity terminal is generated.

[0040] The accuracy verification module is used to execute S5: statistically analyze the dimensional springback data and regional stress distribution data of the injection molded product after the completion of the local pressure relief record at the end of the mold cavity, perform dimensional deviation range comparison and stress distribution breadth inspection, match precision requirements, and generate low-stress injection molding results of precision plastic mold.

[0041] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0042] In this invention, precise matching of the filling sequence during the injection molding stage is achieved by dynamically correcting the response of the cavity wall thickness variation zone. The pressure distribution is adjusted by linking the injection filling trend with the structural change trend. A pressure buffer zone is constructed in the structural discontinuity area to achieve equal pressure transition. The local pressure relief rhythm during the core retraction process is dynamically controlled by identifying the stagnation position during the cooling stage. A complete evaluation closed loop is constructed by combining the dimensional springback and stress uniformity of the pressure relief area. The precision control capability is improved with filling coordination, pressure relief, and molding stability as the core, effectively suppressing the problem of local stress concentration caused by structural abrupt changes, and significantly improving the internal stress distribution and dimensional consistency during the injection molding process. Attached Figure Description

[0043] Figure 1 This is a flowchart of the main steps of the present invention;

[0044] Figure 2 This is a flowchart illustrating the process of obtaining the abrupt change in wall thickness in the injection molding section of this invention.

[0045] Figure 3 This is a flowchart of the process for obtaining the timing adjustment trajectory of the filling segment in this invention;

[0046] Figure 4 This is a flowchart of the process for obtaining the thick-thin transition section buffer control section of the present invention;

[0047] Figure 5 This is a flowchart of the process for obtaining local pressure relief records at the end of the mold cavity in this invention;

[0048] Figure 6 This is a flowchart illustrating the process of obtaining the low-stress injection molding results of precision plastic molds according to the present invention. Detailed Implementation

[0049] 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.

[0050] 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.

[0051] Please see Figure 1The precision processing method for low-stress injection molding of precision plastic molds includes the following steps:

[0052] S1: Obtain the wall thickness step scan data of the inner wall of the injection section of the plastic mold, read the wall thickness values ​​of adjacent points to calculate the difference, and perform cross-region comparison in units of the structural interval of the injection section to identify the range of wall thickness difference between each section, and filter out structural areas where the range of difference exceeds the change threshold to generate the injection section wall thickness abrupt change section.

[0053] S2: Based on the sudden change in wall thickness in the injection molding section, extract the starting pressure response node and the actual filling start point of the corresponding section, calculate the time difference between the two and compare it with the internally set reference filling cycle to determine whether there is an advance or lag trend. If so, move the pressure start node forward or backward, reconstruct the filling curve of the corresponding injection molding stage, and generate the timing adjustment trajectory of the filling section.

[0054] S3: Based on the timing adjustment trajectory of the filling segment, extract the wall thickness distribution trend of the corresponding mold cavity area, identify the target area that changes from a wall thickness greater than the average wall thickness of the cross section to a wall thickness less than the average wall thickness, extend the isobaric time period to the target area and unify the pressure gradient to form an isobaric buffer, and obtain the thickness transition buffer control segment.

[0055] S4: Read the structural data of the closed end of the mold cavity during the subsequent cooling stage of the thick and thin transition section buffer control section, count the end gradient difference area of ​​the wall thickness structure in the closed area, identify the pressure retention area and set the linkage release window on the surface. When the mold core retraction trend is lower than the slope of the pressure rise curve at the closed end, the linkage release window is triggered to open and close the entire process, and a local pressure relief record of the mold cavity end is generated.

[0056] S5: After the local pressure relief record of the mold cavity terminal is completed, the dimensional springback data and regional stress distribution data of the injection molded product are statistically analyzed. The dimensional deviation range is compared and the stress distribution range is checked. If they are all within the standard springback range and the uniform distribution tolerance range, the molding process is judged to meet the precision requirements, and the low-stress injection molding result of precision plastic mold is generated.

[0057] The wall thickness abrupt change zone in the injection molding section includes the wall thickness change threshold zone, the structural difference response zone, and the cross-zone wall thickness abrupt change point. The timing adjustment trajectory in the filling section includes the pressure response correction zone, the filling cycle adjustment line, and the curve reconstruction node. The thickness transition buffer control section includes the isobaric extension zone, the unified pressure gradient zone, and the buffer transition interface. The local pressure relief record at the end of the mold cavity includes the pressure release point, the opening and closing trajectory of the linkage window, and the mold core response hysteresis zone. The low-stress injection molding results of precision plastic molds include the dimensional springback control zone, the regional stress uniform distribution zone, and the springback and stress tolerance matching domain.

[0058] Please see Figure 2 Step S1 is as follows:

[0059] S111: Obtain the wall thickness step scan data of the inner wall of the injection section of the plastic mold, and read the wall thickness values ​​of adjacent measurement points in the obtained scan data one by one, calculate the wall thickness difference sequence between adjacent points, analyze the numerical offset change between all difference items in the sequence and their previous items, count the offset between adjacent differences, and generate a wall thickness difference offset sequence matrix.

[0060] When acquiring the wall thickness step-length scanning data of the inner wall of the injection section of a plastic mold, several scanning points are first set at different positions in the mold cavity, for example, 20 points are evenly distributed along the longitudinal direction of the mold cavity, with a point spacing of 1.0 mm. The wall thickness value of each scanning point is obtained by a laser rangefinder or an ultrasonic thickness gauge, in mm. For example, the measured values ​​at points 1 to 5 are 3.42, 3.47, 3.51, 3.55, and 3.63 mm, respectively, forming a wall thickness measurement sequence {3.42, 3.47, 3.51, 3.55, 3.63}. Then, the difference is calculated for adjacent point pairs using a formula. Perform calculations, where For the wall thickness value at the i-th point, the difference sequence {0.05, 0.04, 0.04, 0.08} is obtained. Then, the offset change between adjacent differences is calculated, and the following steps are performed: The offset of adjacent differences is calculated to obtain the offset sequence {0.01, 0.00, 0.04}. For example, an offset of 0.04 mm between the 3rd and 4th measuring points indicates a change in the wall thickness growth rate. For ease of overall analysis, all... Arranged in matrix form according to the scan point number, the matrix dimension is (number of measurement points – 2) × 2, where the first column is the scan point number and the second column is the offset value.

[0061] Table 1 Wall Thickness Offset Sequence Matrix

[0062] Measurement point number Offset value (mm) 1 0.01 2 0.00 3 0.04

[0063] As shown in Table 1, the offset values ​​exhibit a local upward trend, indicating that the thickness variation of the mold cavity inner wall exists within a non-linear range. In implementation, when the offset value... A thickness difference ≥0.03mm is considered an abnormal wall thickness variation zone. This threshold is determined based on the mold design tolerance of 0.02mm and the equipment measurement error of ±0.01mm, with a combined upper limit of 0.03mm used as the critical value. If multiple sets of data meet the condition, these measurement points are grouped into the same interval to form a two-dimensional matrix dataset. After calculation and matrix reconstruction, the final wall thickness difference offset sequence matrix is ​​obtained.

[0064] S112: Based on the wall thickness difference offset sequence matrix, using the injection molding section structural interval as the distinguishing standard, extract the corresponding difference offset data in each structural interval, calculate the numerical range difference between the maximum and minimum offset values ​​in each structural interval, and construct the interval change set according to the injection molding section arrangement order to generate the wall thickness difference change range set between structural sections.

[0065] Based on the data grouping in the wall thickness difference offset sequence matrix, the injection molding section is first divided into three segments: A, B, and C, according to the structural intervals. For example, segment A corresponds to scanning points 1–6, segment B to 7–13, and segment C to 14–20. A subset of offset values ​​is extracted within each segment. The difference between the maximum and minimum offset values ​​is calculated for each interval using a formula. Perform calculations, where Let $\mathbf{j}$ be the range of differences in the $j$-th structural interval. For example, given the offset value set of segment A: ${0.01, 0.02, 0.04, 0.03, 0.05, 0.02}, calculate... Segment B consists of {0.02, 0.01, 0.02, 0.01, 0.01, 0.02, 0.03}, therefore... Segment C consists of {0.05, 0.04, 0.03, 0.02, 0.06, 0.05, 0.04}, therefore... Then, the R values ​​of each interval were arranged into a set according to the injection molding segment order. In practice, to verify the rationality of the data, the same interval was scanned three times, and the difference in the offset range was no more than ±0.005 mm, indicating that the results were stable. For ease of comparison, the standard for the range of variation was defined as follows: when R∈[0, 0.02) mm, it is a stable region; when R∈[0.02, 0.05) mm, it is a transition region; and when R≥0.05 mm, it is a region of abrupt change. In this example, segments A and C are in the transition region, and segment B is in the stable region. Through the above process, a set of variation ranges of wall thickness difference between structural segments is formed, which is used to subsequently identify regions of abrupt change in wall thickness.

[0066] S113: Based on the range of wall thickness difference between structural sections, each range of change is compared with the preset wall thickness difference threshold. The structural positions corresponding to the intervals with values ​​greater than the wall thickness difference threshold are recorded. All structural regions that meet the conditions are aggregated and sorted to obtain the wall thickness change abrupt section of the injection molding section.

[0067] Based on the range of wall thickness difference between structural sections, each R value is set, and a threshold for wall thickness difference variation is defined. The threshold value was determined based on the flow stability test of the injection molded material. The test measured melt pressure fluctuations under different wall thickness gradients. The results showed that when the wall thickness change exceeded 0.035 mm, the pressure fluctuation increase exceeded 5%, therefore this value was taken as the stability critical line. A comparison operation was performed for each structural segment, using a logical judgment formula. Make a judgment, among which This serves as the status identifier for the structural segments. Substituting the aforementioned data: Segment A R_A = 0.04mm > 0.035mm, Segment B R_B = 0.02mm ≤ 0.035mm, Segment C R_C = 0.04mm > 0.035mm, we obtain S = {1, 0, 1}. Status 1 represents a sudden change in wall thickness in this segment, and its structural location is recorded as the abrupt change region. If the status of two consecutive detection results in the same segment is 1, it is further aggregated and marked as a stable abrupt change region. Finally, all structural segments that meet the conditions are numbered and sorted according to the injection molding segment order to form the dataset {A, C}. This result indicates that abrupt changes in wall thickness occur in segments A and C, and after aggregation and recording, the wall thickness abrupt change segments of the injection molding segment are obtained.

[0068] Please see Figure 3 Step S2 is as follows:

[0069] S211: Based on the sudden change in wall thickness of the injection molding section, extract the time-series data frames recorded in the pressure acquisition nodes and filling sensing nodes in each corresponding section, retrieve the pressure response data change point at the starting position of the section and the resin front advancement starting point index corresponding to the filling position, parse the two time-series index values ​​into actual time points, calculate the time difference between the two, and establish the filling start time difference of the injection molding section.

[0070] Based on the abrupt changes in wall thickness within the injection molding section, the corresponding pressure response node and actual filling start point are first located within each abrupt change section. The pressure response node is acquired by a high-response-rate piezoelectric pressure sensor arranged within the mold cavity. Its data recording format is a two-dimensional data frame composed of a timestamp and the corresponding instantaneous pressure value. For example, if a pressure value suddenly increases from 0.015 MPa to 0.055 MPa at t=0.840s in a certain section, this moment is determined as the pressure initiation node. Simultaneously, the actual filling start point is obtained by using an optical flow front tracking system to determine the time point when the resin flows to the front of the section. Under an image frame rate of 1000fps, the filling front is detected to have reached the front of the section at t=0.895s. The timestamps of the two nodes are recorded as follows: s and s, perform time difference calculation operation The actual filling response delay for this segment is 55ms. To improve data applicability, the same operation is performed on all abrupt segments and the results are aggregated into a structured time difference matrix, as shown below:

[0071] Table 2. Time Difference Record of Wall Thickness Abrupt Change Zone in Injection Molding Section

[0072] Section Number Pressure node time (s) Fill in the start time (s) Startup time difference (s) A1 0.840 0.895 0.055 B3 1.325 1.372 0.047 C2 1.805 1.851 0.046

[0073] As shown in Table 2, all time difference values ​​are positive, indicating that the filling start point is delayed after the pressure response point, reflecting a significant delay in the melt front response. Based on this matrix, the filling start time difference of the injection molding section is established.

[0074] S212: Based on the filling start time difference of the injection molding section and combined with the reference filling cycle benchmark value, determine whether the time difference is greater than the upper limit threshold or less than the lower limit threshold of the filling cycle. If it is satisfied, it is determined that the corresponding section has a trend of advancing or lagging the cycle, and the filling cycle offset judgment identifier set is obtained.

[0075] Based on the time difference values ​​of each segment in the injection molding stage filling start time difference, an internally set reference filling cycle benchmark value is set to 0.050s. On this basis, upper and lower threshold values ​​are set to ±0.005s, with the upper threshold set at 0.055s and the lower threshold at 0.045s. This benchmark value is derived from the statistical average of the filling response time of typical runner regions in 30 different injection molding cycles, with a standard deviation of 0.0046s. A rounding tolerance of ±0.005s is set. Based on these settings, the time difference of each segment in segment 1 is judged sequentially. Define: Segment A1 is 0.055s, which is equal to the upper limit threshold and is considered a critical advance state; segment B3 is 0.047s, which is in the normal range; segment C2 is 0.046s, which is in the normal range. Based on this, construct a mapping judgment logic matrix and mark its mapping state as a Boolean value. If it is in the normal range, it is marked as 0; if it exceeds any threshold, it is marked as 1. For example: A1→1, B3→0, C2→0, which finally forms a Boolean vector {1, 0, 0}. Based on the Boolean marking, establish a mapping between the structural segments and the judgment results to obtain the filling beat offset judgment identifier set.

[0076] S213: Based on the segments identified as offset in the fill beat offset determination identifier set, perform the corresponding segment's pressure start node timestamp addition and subtraction adjustment according to the offset direction, and perform time-series interpolation reconstruction operation on the adjusted pressure start node and the remaining data points in the original fill curve to rearrange the complete fill curve point set of the segment and obtain the fill segment time-series adjustment trajectory.

[0077] Based on the structural segment marked as 1 in the fill beat offset determination indicator set, i.e., segment A1, timing correction is performed on the corresponding pressure start node timestamp. Since it is determined to be "critically early," a delay operation is required. The adjustment step size is set to 0.005s. The original timestamp is linearly corrected according to the error direction; the original value is 0.840s, and the adjusted value is 0.845s. To ensure timing consistency, interpolation calculations are performed on the remaining timestamps in the pressure curve. A new time axis is reconstructed using spline interpolation, ensuring that the reconstructed curve retains the original pressure change trend. Node samples are as follows: Original... The time series {0.800, 0.820, 0.840, 0.860} corresponds to the pressure value series {0.010, 0.012, 0.055, 0.070}. After adjustment, the intermediate node is changed to 0.845. After interpolation, the new time series is {0.800, 0.820, 0.845, 0.860}, and the corresponding pressure values ​​are adjusted to {0.010, 0.012, 0.050, 0.070}. The reconstructed point set is used as an index to rebuild the time series filling dataset, and finally the time series adjustment trajectory of the filling segment is obtained.

[0078] Please see Figure 4 Step S3 is as follows:

[0079] S311: Based on the timing adjustment trajectory of the filling segment, establish a corresponding time axis for the filling stage for each node segment of the mold cavity region. Perform wall thickness data extraction operation on all node times on the time axis to obtain the wall thickness value sequence of all sampling points on the cross section of the mold cavity at the corresponding time point. Calculate the average wall thickness of the current cross section and compare the local wall thickness value of each sampling point with the average value. Select the combination of points where the local wall thickness value changes from being greater than the average wall thickness to being less than the average wall thickness to establish a set of downward transition trends of wall thickness.

[0080] Based on the timing adjustment trajectory of the filling segment, the start and end range of the time period corresponding to each cavity structure region is first marked in the constructed time series. Then, according to the segment division, the preset wall thickness measurement point group within the scanning structure is called. The cross-sectional wall thickness array is constructed by the sampled wall thickness data of the cavity cross section at each moment within the time period. For example, if 10 frames are sampled in segment A from 0.900 to 0.940 seconds, and each frame contains wall thickness data of 12 points on the cross section, the average wall thickness value of the cross section is calculated by performing mean calculation on the wall thickness sequence. If the wall thickness of the 12 points in the first frame is {3.2, 3.3, 3.4, 3.5, 3.6, 3.5, 3.3, 3.1, 2.9, 2.8, 2.6, 2.5}, its average wall thickness is... At each moment, the wall thickness of each measuring point is compared with the average value. The number and location of points where the local wall thickness is greater than the average wall thickness are recorded. When a point is greater than the average value in the previous moment and turns to less than the average value in the next moment, it is marked as a transition point. The trend of change in subsequent moments is continuously monitored. If the trend remains unchanged, it is determined to be a stable transition point. All points that meet the condition of "turning from greater than the average value to less than the average value" are indexed by timestamp and spatial location. Finally, the marked points of all structural sections are summarized to generate a set of wall thickness downward transition trends.

[0081] S312: Based on the combination of concentrated marker points of the downward transition trend of wall thickness, determine the distribution segment of spatial location in the mold cavity structure, and extend the time window sequentially towards the filling direction of the area where the point is located. According to the pressure value distribution corresponding to each unit sampling point on the time axis of the original filling segment, set a continuous isobaric maintenance window and complete the coverage mark on the time axis to form a one-to-one mapping between structural segments and time periods, and obtain the isobaric extension control interval.

[0082] Based on the coordinates of the points recorded in the concentrated transition trend of the wall thickness, they are first indexed and mapped to the three-dimensional structural mesh of the mold cavity. The geometric unit number to which the point belongs and its downstream mesh connection information are extracted. Starting from the timestamp of the point, the extension is carried out sequentially according to the time axis with a step size of 0.005 seconds, for a maximum of 5 sampling steps, forming an initial extension window. Then, based on the original pressure trajectory data within this time period, the pressure value sequence of all nodes in the extension segment is extracted. For example, if the pressure of the current transition point is 24.5 MPa, the pressure of subsequent sampling nodes is {24.3, 24.2, 24.0, 23.8, 23.7}. Deviation calculation is performed and it is determined whether it is within ±0.5 MPa. If this condition is met, the extension segment can be defined as an isobaric segment. Then, a mapping pair is constructed between the structural segment number and the time period and stored in the control dataset, indicating that the pressure change within this segment can remain stable. The above process is repeated to obtain the isobaric extension segments of all downward transition points and recorded in the control interval table, as shown in the table:

[0083] Table 3 Record Table of Isobaric Extension Control Zone

[0084] Structure number Start time (s) End time (s) Extension length (s) A-05 0.910 0.935 0.025 B-03 1.105 1.125 0.020 C-07 1.302 1.327 0.025

[0085] As shown in Table 3, some structural sections successfully constructed extended control sections that meet the ±0.5MPa isobaric condition, ultimately forming isobaric extended control intervals.

[0086] S313: Based on all marked structural sections and time ranges in the isobaric extension control interval, perform the corresponding time period reconstruction operation, set the pressure to keep the pressure change gradient to zero in the extension section and perform edge transition processing, unify the pressure value of all internal nodes to the upstream end pressure value of the cross section, and obtain the thick-thin transition section buffer control section.

[0087] Based on the structural segment numbers and their start and end times recorded in the isobaric extension control interval, the corresponding time period nodes in the original pressure trajectory are located, and all pressure values ​​within that segment are extracted for reconstruction. First, the upstream endpoint pressure of each extension segment is determined as the target constant pressure value for the entire extension segment. For example, if the pressure at the node before a certain extension segment is 23.8 MPa, then all nodes within the extension segment are assigned a value of 23.8 MPa. To eliminate the disturbance caused by edge fluctuations to structural control, a 0.005-second transition zone is set at each end of the extension segment. The transition pressure values ​​are smoothed using linear decreasing and linear increasing methods within this interval, respectively. For example, the pressure value sequence of the initial boundary transition zone can be set as {24.0, 23.9, 23.8}, and the transition zone of the termination boundary can be set as {23.8, 23.9, 24.0}. After completing the edge correction, the extension segment is merged with the original trajectory and the original value segment is replaced. A two-dimensional pressure patch is constructed by combining the node pressure array and the time axis. This patch is the pressure distribution result of the buffer segment in the target area, and finally, the thick and thin transition segment buffer control segment is obtained.

[0088] Please see Figure 5 Step S4 is as follows:

[0089] S411: Based on the thick-thin transition buffer control segment, read the cooling stage data frame on the subsequent time axis, extract the structural mesh in the closed end of the mold cavity layer by layer, obtain all wall thickness sampling points in the closed area and establish a wall thickness distribution sequence according to their arrangement number along the main filling direction, calculate the wall thickness difference between adjacent sampling points in sequence and calculate the average, set the local section with the average difference higher than the wall thickness gradient difference threshold as the section to be identified, and generate the end wall thickness gradient difference section identification matrix;

[0090] Based on the thick-thickness transition buffer control section, the structural frame data of the mold cavity covered by the cooling stage is first obtained in chronological order according to the time axis. In each structural frame, the 3D mesh information of the closed end region of the mold cavity is extracted, the boundary node range of the closed area is defined, and a numbered index is established. Then, the corresponding wall thickness value is extracted for each node, and the wall thickness data vector is reconstructed according to the main filling direction sequence. Next, the structural end section identification operation is performed, setting this section as the last 10% length interval and filtering out all node sequences located within this interval. A one-dimensional wall thickness gradient array is constructed based on the node sequence number. The wall thickness values ​​between adjacent nodes are differentially calculated, and the average difference of the section is used as the judgment criterion. If the wall thickness difference of a node is greater than the set wall thickness gradient difference threshold of 0.25mm, the mesh where the node is located is marked as a structural gradient abrupt change region. This standard is used to complete the gradient filtering of the end nodes of the entire closed section. All regions that meet the conditions are numbered, and a mapping matrix is ​​established for subsequent operations. To verify the rationality of the set values, wall thickness samples of three different closed end sections of the mold cavity are introduced for calculation, and the following statistical table is constructed:

[0091] Table 4. Example of Calculating the Difference in Wall Thickness at Closed Ends

[0092] Section Number Node 1 wall thickness (mm) Node 2 wall thickness (mm) Difference (mm) Is it marked? A01 2.95 2.60 0.35 yes A02 3.10 2.90 0.20 no A03 3.00 2.70 0.30 yes

[0093] As shown in Table 4, nodes with a wall thickness difference greater than 0.25 mm are identified as candidate marking regions, thereby generating an end wall thickness gradient difference segment identification matrix.

[0094] S412: Based on the identification matrix of the end wall thickness gradient difference section, extract the cavity pressure curve of each moment in the corresponding structural section and establish a pressure fluctuation array synchronously according to time. Select the fluctuation area in each section where the pressure is continuously higher than the regional average by 20% and the duration exceeds 0.02s as the pressure retention judgment area. Set the linkage release window on the corresponding cavity surface through spatial coordinate mapping to generate a pressure retention mapping window table.

[0095] Based on the identification matrix of the end wall thickness gradient difference section, the time-series data node of each marked structural unit is located and the cavity pressure value recorded during the cooling stage is extracted synchronously. An array of pressure curves that evolve over time is constructed. Then, a 20% offset threshold is extracted according to the overall average of each curve. This value is set as the judgment benchmark. For example, if the average pressure is 21.5 MPa, the upper limit of the judgment threshold is 25.8 MPa. High-pressure sections with a continuous duration of more than 0.02s in each section are filtered and their start time index is recorded. Then, this time period is mapped to the cavity surface through spatial projection and a linkage release window logic mask is established for it. Finally, the spatial projection position of each section and the time index are combined to form a surface mapping record structure and uniformly summarized into a pressure retention mapping window table.

[0096] S413: Based on the linkage window regions in the pressure retention mapping window table, the core retraction displacement trend value and the slope of the corresponding closed end pressure curve are calculated at each moment during the cooling stage, using the following formula:

[0097] ;

[0098] The linkage response error factor of each window node is calculated. If the linkage response error factor is lower than the response trigger threshold, the linkage release window is activated and the start and end times of opening and closing are recorded to establish a local pressure relief record for the mold cavity terminal; among which, Indicates the first Linkage response error factor at each linked window node This indicates the core shrinkage trend value. This represents the slope of the pressure curve. This represents the sum of squared errors at all nodes;

[0099] Based on the spatial and temporal information of all surface windows in the pressure retention mapping window table, the core retraction trend value and its corresponding closed-end pressure curve slope value within each time segment are paired one-to-one, and a difference normalization operation is performed. This is then compared with the linkage response trigger threshold of 0.12. If the error factor... If the value is below the threshold, the corresponding window will be set to "linkage on state" and its opening and closing timestamps will be recorded in the window linkage logic controller. The linkage state of all windows that meet the conditions in the entire cycle will be extracted and archived, and finally the local pressure relief record of the mold cavity terminal will be obtained.

[0100] The following is a practical example: Within a certain linkage window period, five time nodes are collected. The sequence of core retraction trend values ​​is {1.05, 0.92, 1.10, 0.87, 1.00} mm / s², and the corresponding pressure slope sequence is {1.00, 0.90, 1.15, 0.89, 1.05} MPa / s. Then, for the third node, we have:

[0101] ;

[0102] ;

[0103] The molecular part is ;

[0104] Then calculate the denominator:

[0105] ;

[0106] ;

[0107] ;

[0108] Substitute into the formula:

[0109] ;

[0110] Since 0.549 > 0.12, it indicates that the node does not meet the linkage triggering condition and will not perform window linkage action;

[0111] Then calculate for the second node:

[0112] ;

[0113] ;

[0114] Molecules are ;

[0115] The denominator is still 0.0911, then:

[0116] ;

[0117] If it's still greater than 0.12, exclude it and continue the evaluation; if a node exists... If the window is "open", its timestamp is recorded and the window is marked as "open" after the corresponding time period ends, thus forming the time sequence data of the depressurization process.

[0118] The above formula The operational logic can be explained in two parts: First, the numerator part Indicates the first The instantaneous response difference between the core retraction trend value and the slope of the closed-end pressure curve at each time point is used to measure the offset intensity of the linkage response at that point by taking the absolute value to eliminate the directional influence and retaining only the degree of difference between the two. The square root of the sum of the squares of the differences between the core trend values ​​and pressure slopes among all nodes in the entire time series is essentially the root mean square error term for the entire observation interval. Its function is to standardize the current node's offset to the overall response level for comparison, improving the sensitivity of anomaly identification and the accuracy of local judgment. The summation operation reflects the global accumulation effect of errors over multiple time points, the squaring operation increases the contribution weight of the large error value, and the square root restores the dimensions to the same order of magnitude as the numerator, ensuring the mathematical comparability of the ratio. This ratio is the normalized error magnitude between the current node's linkage response and the overall deviation distribution. When... A value close to 0 indicates that the node's linkage response is highly synchronized. If the value deviates significantly, it indicates that its local behavior is significantly inconsistent with the overall trend. Therefore, this ratio can be used as a direct basis for judging whether to activate the linkage release window.

[0119] The linkage response error factor quantifies the degree of synchronous deviation between the core retraction trend and the slope of the internal pressure change at a single time point. It is a normalized measure of response difference, its core significance being to reflect the coordination between the core motion response and the dynamic accumulation of internal pressure exhibited by local structural units during the cooling phase. A smaller factor value indicates a more consistent core retraction trend with the local pressure curve change trend, and a more sufficient linkage response. Conversely, a larger value indicates a lag in core response or unreleased pressure accumulation at that structural location, serving as a basis for identifying potential pressure retention risk zones. Therefore, the linkage response error factor not only reflects the deviation magnitude of the pressure-structure response relationship between local nodes but also provides a quantifiable criterion for the subsequent opening and closing control of the linkage window.

[0120] Please see Figure 6 The S5 steps are as follows:

[0121] S511: Based on the local pressure relief record of the mold cavity terminal, the three-dimensional dimensional coordinates of each structural section in the free state after the injection molded product has cooled are collected and matched one by one with the standard geometric data of the mold cavity design. The directional offset of each reference point is extracted and the spatial vector magnitude is calculated. The dimensional springback vector field of the entire product range is constructed. The maximum value, mean and standard deviation of all springback vector values ​​are extracted and compared with the set dimensional deviation tolerance point by point. All springback anomaly points exceeding the tolerance range are filtered out and the dimensional springback deviation distribution matrix is ​​generated.

[0122] Based on the local pressure relief record at the end of the mold cavity, a 3D laser scanning model of the injection-molded product under no-load conditions after cooling is called. Spatial reconstruction is performed on the obtained point cloud, and the corresponding nodes in the three axes are mapped according to the CAD reference model of the mold cavity. The coordinate offsets in the X, Y, and Z directions are extracted from the corresponding points in the structure to construct the 3D springback vector of each node. Then, the Euclidean norm is used to calculate the springback vector. The springback modulus is calculated as the node size springback value. A size springback array construction operation is performed on all nodes. For example, if a node's coordinate offset is (0.09, -0.04, 0.08) mm, then its springback modulus is... The maximum, mean, and standard deviation of all springback values ​​are calculated to obtain the overall dimensional springback statistics of the structure. The upper and lower limits of the deviation tolerance are set at ±0.15mm. Based on these tolerance limits, the value range of each node is judged. If the springback value of a node is higher than 0.15mm or lower than -0.15mm, it is determined to be an out-of-tolerance node. Its spatial index and springback value are recorded in the anomaly array. The number of out-of-tolerance nodes and their spatial distribution trend are then statistically analyzed to generate a dimensional springback deviation distribution matrix. Typical sample data are as follows:

[0123] Table 5 Sample Table of Springback Deviation of Injection Molded Products

[0124] Node number X offset (mm) Y offset (mm) Z-offset (mm) Springback value (mm) Judgment Result P101 0.08 0.06 -0.09 0.132 qualified P108 -0.11 0.10 0.12 0.194 Out of tolerance P115 0.04 -0.05 0.07 0.094 qualified

[0125] As shown in Table 5, only node P108 was identified as an anomaly because it exceeded the set tolerance threshold, while the rest met the design tolerance range. Therefore, it was determined that the overall control status of its spatial rebound entered the data comparison stage.

[0126] S512: Based on the size rebound deviation distribution matrix, filter out the deviation anomaly point areas, perform internal residual stress data extraction operation on the remaining areas, establish an equally spaced node grid, extract the principal stress tensor at each node and convert it into equivalent stress value, perform regional mean and standard deviation calculation on all node stress values, if the local node stress offset is greater than the stress uniformity tolerance, mark the node as a stress anomaly point, and judge the continuity of spatial distribution to obtain the area range where all stresses meet the tolerance conditions, and establish the effective coverage parameter of uniform stress.

[0127] Based on the dimensional springback deviation distribution matrix, nodes marked as abnormal are filtered out, and the remaining valid node set is constructed. For each node, an equally spaced spatial index grid with a 5mm grid spacing is created. The residual stress tensor is extracted from the molding condition sensing system. Stress transformation is performed using the principal stress values ​​of each node in three directions, and its equivalent stress value sequence is calculated. For example, if the principal stresses of a node are σx=3.5MPa, σy=2.8MPa, and σz=1.2MPa, then its equivalent stress is... MPa, constructing a one-dimensional stress vector from the equivalent stress values ​​of all nodes, calculating the mean μ and standard deviation σ of this vector to obtain the overall stress state of the region, and setting the stress offset tolerance to 0.4 MPa, taking the absolute value of the difference between the stress value of each node and the mean, if it is greater than 0.4 MPa, it is marked as a stress anomaly point. Then, the ratio of the number of non-anomaly nodes to the total number of all effective nodes is calculated, converted into a percentage and recorded as the effective coverage rate parameter of uniformly distributed stress. If the coverage rate is ≥90%, the stress distribution is reasonable; otherwise, it is a region of uneven structural stress. For example, in the example, there are a total of 500 nodes, of which 43 are marked as anomalies, the effective coverage rate is 90%. .

[0128] S513: Based on the dimensional springback deviation distribution matrix and the effective coverage rate parameter of uniform stress, perform joint judgment on the proportion of abnormal points and the stress uniformity rate. When the proportion of deviation points is less than the threshold of the proportion of abnormal points of dimensional deviation and the uniform coverage rate is higher than the lower limit threshold of the stress uniformity coverage rate, it is determined that the structure and molding process of the injection molded product meet the low stress springback condition. Record the corresponding mold number and molding parameters, and generate the low stress injection molding result of the precision plastic mold.

[0129] Based on the dimensional springback deviation distribution matrix and the effective coverage rate parameter of uniform stress, the number of out-of-tolerance nodes and the percentage of effective stress coverage are extracted respectively. The judgment threshold for the former is set at 2.5% of the total number of nodes. If the proportion of out-of-tolerance nodes is less than this threshold, it is acceptable to be considered as a state where the springback dimensional control meets the standard. The threshold for the latter, the uniform stress coverage rate, is set at 90%. If the current node coverage rate is higher than this value, the structural stress distribution is within the tolerance range. The total number of nodes in the current sample is further set to 500. If the number of out-of-tolerance nodes does not exceed 13, the dimensional judgment condition is met. At the same time, if the stress uniform coverage rate is 91.4%, the stress judgment condition is met. When both conditions are met, the molding state of the injection molding structure corresponding to this mold is determined to be a stable state. The mold number, such as M221104, and its corresponding injection pressure value, holding time, cooling time, and other key process parameters are recorded and archived into the mold molding database. Finally, the low-stress injection molding result of precision plastic mold is generated.

[0130] A precision processing system for low-stress injection molding of precision plastic molds, including:

[0131] The wall thickness difference identification module is used to perform S1: acquire the wall thickness step scan data of the inner wall of the injection section of the plastic mold, read the wall thickness values ​​of adjacent points to calculate the difference, and filter the structural areas where the difference changes beyond the change threshold to generate the wall thickness change section of the injection section.

[0132] The pressure timing adjustment module is used to execute S2: Based on the sudden change in wall thickness of the injection molding section, extract the corresponding section's starting pressure response node and the actual filling start point, calculate the time difference and compare it with the internally set reference filling cycle, reconstruct the corresponding injection molding stage filling curve, and generate the filling section timing adjustment trajectory.

[0133] The transition zone pressure stabilization module is used to execute S3: based on the filling segment timing adjustment trajectory, extract the wall thickness distribution trend of the corresponding mold cavity area, identify the target area that changes from greater than the average wall thickness of the cross section to less than the average wall thickness, extend the isobaric time period to the target area and unify the pressure gradient to form an isobaric buffer, and obtain the thick and thin transition segment buffer control segment.

[0134] The linkage pressure relief trigger module is used to execute S4: read the structural data of the closed end of the mold cavity in the subsequent cooling stage of the thick-thin transition section buffer control section, identify the pressure retention area and set the linkage release window on the surface. When the mold core retraction trend is lower than the slope of the pressure rise curve of the closed end, the linkage release window is triggered to open and close, and a local pressure relief record of the mold cavity terminal is generated.

[0135] The accuracy verification module is used to execute S5: statistically analyze the springback data of the injection molded product dimensions and the regional stress distribution data after the completion of the local pressure relief record at the end of the mold cavity, perform dimensional deviation range comparison and stress distribution breadth inspection, match precision requirements, and generate low-stress injection molding results of precision plastic molds.

[0136] 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 precision processing method for low-stress injection molding of precision plastic molds, characterized in that, Includes the following steps: S1: Obtain the wall thickness step scan data of the inner wall of the injection section of the plastic mold, read the wall thickness values ​​of adjacent points to calculate the difference, and filter the structural areas where the difference changes beyond the change threshold to generate the wall thickness change section of the injection section. S2: Based on the sudden change in wall thickness of the injection molding section, extract the corresponding section's starting pressure response node and the actual filling start point, calculate the time difference and compare it with the internally set reference filling cycle, reconstruct the corresponding injection molding stage filling curve, and generate the filling section timing adjustment trajectory. S3: Based on the timing adjustment trajectory of the filling segment, extract the wall thickness distribution trend of the corresponding mold cavity area, identify the target area that changes from a wall thickness greater than the average wall thickness of the cross section to a wall thickness less than the average wall thickness, extend the isobaric time period to the target area and unify the pressure gradient to form an isobaric buffer, and obtain the thickness transition buffer control segment. S4: Read the structural data of the closed end of the mold cavity during the subsequent cooling stage of the thick-thin transition section buffer control section, identify the pressure retention area and set a linkage release window on the surface. When the mold core retraction trend is lower than the slope of the pressure rise curve at the closed end, the linkage release window is triggered to open and close, and a local pressure relief record of the mold cavity terminal is generated. S5: After the completion of the local pressure relief record at the end of the mold cavity, the dimensional springback data and regional stress distribution data of the injection molded product are statistically analyzed. The dimensional deviation range is compared and the stress distribution breadth is checked to match the precision requirements and generate the low-stress injection molding result of the precision plastic mold.

2. The precision processing method for low-stress injection molding of precision plastic molds according to claim 1, characterized in that, The wall thickness abrupt change zone of the injection molding section includes the wall thickness change threshold zone, the structural difference response zone, and the cross-zone wall thickness abrupt change point. The timing adjustment trajectory of the filling section includes the pressure response correction zone, the filling cycle adjustment line, and the curve reconstruction node. The thickness transition buffer control section includes the isobaric extension zone, the unified pressure gradient zone, and the buffer transition interface. The local pressure relief record at the mold cavity terminal includes the pressure release point, the linkage window opening and closing trajectory, and the mold core response hysteresis zone. The low-stress injection molding result of the precision plastic mold includes the dimensional springback control zone, the regional stress uniform distribution zone, and the springback and stress tolerance matching domain.

3. The precision processing method for low-stress injection molding of precision plastic molds according to claim 1, characterized in that, The specific steps for obtaining the abrupt change in wall thickness of the injection molding section are as follows: S111: Obtain the wall thickness step scan data of the inner wall of the injection section of the plastic mold, and read the wall thickness values ​​of adjacent measurement points in the obtained scan data one by one, calculate the wall thickness difference sequence between adjacent points, analyze the numerical offset change between all difference items in the sequence and their previous items, count the offset between adjacent differences, and generate a wall thickness difference offset sequence matrix. S112: Based on the wall thickness difference offset sequence matrix, using the injection molding section structural interval as the distinguishing standard, extract the corresponding difference offset data in each structural interval, calculate the numerical range difference between the maximum and minimum offset values ​​in each structural interval, and construct an interval change set according to the injection molding section arrangement order of all interval range differences to generate a set of wall thickness difference change ranges between structural sections. S113: Based on the range of wall thickness difference between the structural segments, each range of change is compared with the preset wall thickness difference threshold. The structural positions corresponding to the intervals with values ​​greater than the wall thickness difference threshold are recorded. All structural regions that meet the conditions are aggregated and sorted to obtain the wall thickness change abrupt section of the injection molding segment.

4. The precision processing method for low-stress injection molding of precision plastic molds according to claim 1, characterized in that, The specific steps for obtaining the timing adjustment trajectory of the filling segment are as follows: S211: Based on the sudden change in wall thickness of the injection molding section, extract the time-series data frames recorded in the pressure acquisition nodes and filling sensing nodes in each corresponding section, retrieve the pressure response data change point at the starting position of the section and the resin front advancement starting point index corresponding to the filling position, parse the two time-series index values ​​into actual time points, calculate the time difference between the two, and establish the filling start time difference of the injection molding section. S212: Based on the filling start time difference of the injection segment and combined with the reference filling cycle benchmark value, determine whether the time difference is greater than the upper limit threshold or less than the lower limit threshold of the filling cycle. If it is satisfied, determine that the corresponding segment has a cycle advance or lag trend, and obtain the filling cycle offset judgment identifier set. S213: Based on the segments determined to be offset in the filling beat offset determination identifier set, perform the adjustment of the pressure start node timestamp of the corresponding segment according to the offset direction, and perform time-series interpolation reconstruction operation on the adjusted pressure start node and the remaining data points in the original filling curve to rearrange the complete filling curve point set of the segment and obtain the filling segment time-series adjustment trajectory.

5. The precision processing method for low-stress injection molding of precision plastic molds according to claim 1, characterized in that, The specific steps for obtaining the thick-thin transition section buffer control segment are as follows: S311: Based on the filling segment timing adjustment trajectory, establish a corresponding time axis for the filling stage for each node segment of the mold cavity region. Perform wall thickness data extraction operation on all node times on the time axis to obtain the wall thickness value sequence of all sampling points on the cross section of the mold cavity at the corresponding time point. Calculate the average wall thickness of the current cross section and compare the local wall thickness value of each sampling point with the average value. Filter the point combinations where the local wall thickness value changes from being greater than the average wall thickness to being less than the average wall thickness, and establish a wall thickness downward transition trend set. S312: Based on the combination of concentrated marker points of the downward transition trend of the wall thickness, determine the distribution segment of the spatial position in the mold cavity structure, and extend the time window sequentially towards the filling direction of the area where the point is located. According to the pressure value distribution corresponding to each unit sampling point on the time axis of the original filling segment, set a continuous isobaric maintenance window and complete the coverage mark on the time axis to form a one-to-one mapping between the structural segment and the time period, and obtain the isobaric extension control interval. S313: Based on all marked structural segments and time ranges in the isobaric extension control interval, perform the corresponding time period reconstruction operation, set the pressure to maintain a pressure change gradient of zero in the extension segment and perform edge transition processing, unify the pressure value of all internal nodes to the upstream end pressure value of the cross section, and obtain the thick-thin transition buffer control segment.

6. The precision processing method for low-stress injection molding of precision plastic molds according to claim 1, characterized in that, The specific steps for obtaining the local depressurization record of the mold cavity terminal are as follows: S411: Based on the thick-thin transition buffer control segment, read the cooling stage data frame on the subsequent time axis, extract the structural mesh in the closed end of the mold cavity layer by layer, obtain all wall thickness sampling points in the closed area and establish a wall thickness distribution sequence according to their arrangement number along the main filling direction, calculate the wall thickness difference between adjacent sampling points in sequence and calculate the average, set the local section with the average difference higher than the wall thickness gradient difference threshold as the section to be identified, and generate the end wall thickness gradient difference section identification matrix; S412: Based on the end wall thickness gradient difference section identification matrix, extract the cavity pressure curve at each moment in the corresponding structural section and establish a pressure fluctuation array synchronously with time. Select the pressure retention judgment area, set the linkage release window on the corresponding cavity surface through spatial coordinate mapping, and generate a pressure retention mapping window table. S413: Based on each linkage window area in the pressure retention mapping window table, calculate the core retraction displacement trend value and the slope of the corresponding closed end pressure curve at each moment during the cooling stage, calculate the linkage response error factor of each window node, and if the linkage response error factor is lower than the response trigger threshold, activate the linkage release window and record the start and end times of opening and closing, and establish a local pressure relief record of the mold cavity terminal.

7. The precision processing method for low-stress injection molding of precision plastic molds according to claim 6, characterized in that, The formula for calculating the linkage response error factor is as follows: ； in, Indicates the first Linkage response error factor at each linked window node This indicates the core shrinkage trend value. This represents the slope of the pressure curve. This represents the sum of squared errors at all nodes.

8. The precision processing method for low-stress injection molding of precision plastic molds according to claim 1, characterized in that, The specific steps for obtaining the low-stress injection molding results of the precision plastic mold are as follows: S511: Based on the local pressure relief record of the mold cavity terminal, collect the three-dimensional dimensional coordinates of each structural section in the free state after the injection molded product has cooled down, and match them one by one with the standard geometric data of the mold cavity design. Extract the directional offset of each reference point and calculate the spatial vector magnitude. Construct a dimensional springback vector field for the entire product range. Perform maximum, mean and standard deviation extraction operations on all springback vector values, and compare them point by point with the set dimensional deviation tolerance. Filter all springback anomaly points that exceed the tolerance range and generate a dimensional springback deviation distribution matrix. S512: Based on the size rebound deviation distribution matrix, filter out the deviation anomaly point areas, perform internal residual stress data extraction operation on the remaining areas, establish an equally spaced node grid, extract the principal stress tensor at each node and convert it into equivalent stress value, perform regional mean and standard deviation calculation on all node stress values, if the local node stress offset is greater than the stress uniformity tolerance, mark the node as a stress anomaly point, and judge the spatial distribution continuity to obtain the area range where all stresses meet the tolerance conditions, and establish the effective coverage parameter of uniform stress. S513: Based on the size rebound deviation distribution matrix and the effective coverage rate parameter of uniform stress, perform joint judgment on the proportion of abnormal points and the stress uniformity rate respectively. When the proportion of deviation points is less than the threshold of the proportion of size deviation abnormal points and the uniform coverage rate is higher than the lower limit threshold of the stress uniformity coverage rate, it is determined that the structure and molding process of the injection molded product meet the low stress rebound condition, the corresponding mold number and molding parameters are recorded, and the low stress injection molding result of precision plastic mold is generated.

9. A precision processing system for low-stress injection molding of precision plastic molds, characterized in that, The system is used to implement the precision processing method for low-stress injection molding of precision plastic molds as described in any one of claims 1-8, including: The wall thickness difference identification module is used to perform S1: acquire the wall thickness step scan data of the inner wall of the injection section of the plastic mold, read the wall thickness values ​​of adjacent points to calculate the difference, and filter the structural areas where the difference changes beyond the change threshold to generate the wall thickness change section of the injection section. The pressure timing adjustment module is used to execute S2: Based on the sudden change in wall thickness of the injection molding section, extract the starting pressure response node of the corresponding section and the actual filling start point, calculate the time difference and compare it with the internally set reference filling cycle, reconstruct the filling curve of the corresponding injection molding stage, and generate the filling segment timing adjustment trajectory. The transition zone pressure stabilization module is used to execute S3: based on the timing adjustment trajectory of the filling segment, extract the wall thickness distribution trend of the corresponding mold cavity area, identify the target area that changes from greater than the average wall thickness of the cross section to less than the average wall thickness, extend the isobaric time period to the target area and unify the pressure gradient to form an isobaric buffer, and obtain the thick and thin transition segment buffer control segment. The linkage pressure relief triggering module is used to execute S4: read the structural data of the closed end of the mold cavity in the subsequent cooling stage of the thick-thin transition section buffer control section, identify the pressure retention area and set the linkage release window on the surface. When the mold core retraction trend is lower than the slope of the pressure rise curve of the closed end, the linkage release window is triggered to open and close, and a local pressure relief record of the mold cavity terminal is generated. The accuracy verification module is used to execute S5: statistically analyze the dimensional springback data and regional stress distribution data of the injection molded product after the completion of the local pressure relief record at the end of the mold cavity, perform dimensional deviation range comparison and stress distribution breadth inspection, match precision requirements, and generate low-stress injection molding results of precision plastic mold.

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