Strength detection device for plastic product production
By implementing adaptive closed-loop control in melt filament traction strength testing during plastic product manufacturing, the problems of non-isothermal cooling and insufficient repeatability in melt traction strength testing are solved, achieving stability and comparability, and providing reliable strength characterization results.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- FOSHAN LISHENG PLASTIC PROD CO LTD
- Filing Date
- 2026-02-06
- Publication Date
- 2026-05-12
AI Technical Summary
In the production of plastic products, existing technologies for melt traction strength testing suffer from several drawbacks. Non-isothermal cooling and environmental heat exchange conditions affect the comparability of test results. The sensitivity of traction distance and extrusion rate leads to insufficient repeatability, making it difficult to reliably extract characteristic parameters of melt strength.
By conducting online testing in melt filament drawing detection, adaptive closed-loop control is performed using data on traction force, traction speed, and traction distance to detect the boundary of the stable drawing zone and the critical inflection point, and the tensile viscosity is inverted to output standardized melt strength indicators.
This improves the stability and repeatability of melt strength testing, obtains comparable and reusable strength characterization results, and provides a reliable basis for online closed-loop control and process optimization.
Smart Images
Figure CN122016470A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of material physical property testing and analysis technology, and more specifically, to a strength testing device for the production of plastic products. Background Technology
[0002] In the extrusion molding process of plastic products, the stretching stability of the melt after exiting the die directly affects quality issues such as filament breakage, necking, thickness fluctuations, and surface defects. Therefore, it is necessary to conduct online testing of the melt's stretching capacity and strength characteristics. In 2023, Liu Shuang published an article in the journal *Acta Polymerica Sinica* on the application of rheological techniques in polymer characterization: tensile rheological testing. This article introduces a common engineering method for evaluating the strength of traction-type melts: the extruded melt filaments are stretched at progressively increasing speeds or stretch ratios, and the force-stretch ratio curve is recorded as the stretching force changes with the stretching speed or stretch ratio. Strength indicators are then output at the break points or characteristic points of the curve. For example... Figure 2 As shown, the Rheotens stretching test belongs to a typical traction-based evaluation framework, which characterizes the stretching behavior and strength of the melt by stretching the melt filament and measuring the stretching force.
[0003] On the other hand, in 2013, Xu Xiaoyong published "Modeling and Design of Thin Film Tension Control System" in the Chinese Journal of Mechanical Engineering, proposing that in thin film or strip production lines, such as... Figure 3 As shown, tension measurement and tension control systems have been used for closed-loop tension control in the traction section. However, the goal of such systems is usually to maintain the tension at a set value, rather than directly solving the problems of extracting melt stretching curve features and cross-condition comparability testing.
[0004] Existing online applications of traction-based melt strength analysis still face three main shortcomings: First, the non-isothermal cooling and hardening effect of melt filaments during air stretching amplifies the traction force due to environmental heat exchange conditions, resulting in a lack of a unified and comparable benchmark for test results under different environments and stretching distances. Second, melt strength is highly sensitive to stretching distance and extrusion rate. Stretch speed scans with fixed step lengths or fixed acceleration rates often fail to stably cover the transition boundary between the "stable stretching zone" and the "unstable stretching zone" under different operating conditions, leading to insufficient repeatability when using only the fracture point or single-point traction force as an indicator. Third, online control requires stable output of transferable characteristic parameters, especially the boundary of the stable stretching zone, critical inflection points, and their corresponding transient tensile viscosity or equivalent strength. However, fixed scanning strategies are sparsely sampled near inflection points and are sensitive to noise, making it difficult to stably extract these characteristic quantities.
[0005] Therefore, there is an urgent need for a strength testing device for extrusion production lines that upgrades the traction speed scanning stage to an adaptive closed-loop scanning based on online variable point detection. This allows physical property data such as traction force to drive the updating of scanning parameters and feature inversion in a progressive data flow manner, thereby obtaining comparable and reusable melt strength test results. Summary of the Invention
[0006] To overcome the aforementioned deficiencies in the prior art, this invention provides a strength testing device for plastic product manufacturing. This device performs online testing and analysis based on physical data such as traction force, traction speed, and traction distance during melt filament stretching testing. It also implements adaptive closed-loop control during the traction speed scanning stage to obtain the boundary of the stable stretching zone and critical inflection point. Furthermore, it inverts the tensile viscosity to output standardized melt strength indicators and confidence levels, thereby solving the problems mentioned in the background art.
[0007] To achieve the above objectives, the present invention provides the following technical solution: A strength testing device for the production of plastic products, comprising: The melt filament forming assembly is connected to the die of the extrusion equipment to output continuous melt filaments.
[0008] The traction component scans the traction speed of the molten filament.
[0009] The measuring component outputs traction force timing data.
[0010] The motion parameter acquisition component outputs time-series data of traction distance.
[0011] The strength testing component calculates the transient strain rate and inverses the tensile viscosity, outputting standardized melt strength indices and confidence levels.
[0012] As a further aspect of the present invention, a melt filament forming assembly is connected to the die of an extrusion device to output continuous melt filaments, comprising the following specific contents: the melt filament forming achieves a sealed connection through the die of the extrusion device, enabling the polymer melt within a set melt temperature range to be stably introduced into the forming channel. The melt filament forming assembly internally includes a heat-resistant guide tube and a sizing die. The heat-resistant guide tube is used to smoothly guide the melt from the die downstream and reduce melt retention and backflow; the sizing die is used to constrain the melt outlet geometry to form continuous melt filaments.
[0013] As a further aspect of the present invention, the traction component performs traction speed scanning on the melt filament, including the following specific content: the traction component is disposed on the downstream drawing path of the melt filament forming component, applies controllable traction to the continuously output melt filament and performs traction speed scanning, thereby forming traction speed timing data corresponding to the traction force response.
[0014] As a further aspect of the present invention, the measuring component outputs traction force timing data, including the following specific contents: the measuring component is set on the force transmission path of the melt filament drawing process, and is arranged between the melt filament forming component and the traction component, so that the tensile load generated by the melt filament when it is tractioned by the traction clamping mechanism can be completely transmitted to the measuring component and measured.
[0015] As a further aspect of the present invention, a motion parameter acquisition component outputs traction distance time-series data, including the following specific contents: The motion parameter acquisition component is used to measure the kinematic quantities during the traction speed scanning process and outputs traction distance time-series data synchronized with the scanning process of the traction component. The motion parameter acquisition component includes a distance sensor, which cooperates with the traction distance adjustment mechanism to measure the effective traction distance between the measuring component and the traction clamping mechanism, and outputs traction distance time-series data after the traction distance is adjusted or locked.
[0016] As a further aspect of the present invention, the strength detection component calculates the transient strain rate and inverts the tensile viscosity, outputting a standardized melt strength index and confidence level, including the following specific contents: the strength detection component takes the traction force time series data, traction speed time series data and traction distance time series data as input, and sequentially passes through a signal preprocessing module, an online change point detection module, an adaptive scanning module and a critical inversion module.
[0017] The signal preprocessing module performs signal preprocessing operations. Its inputs are traction force time-series data, traction speed time-series data, and traction distance time-series data synchronously acquired under the sampling clock. Its output is a preprocessed dataset used for online change point detection and subsequent inversion calculation.
[0018] The input to the online change point detection module is the preprocessed dataset, which includes preprocessed traction force time series data, traction speed time series data, and traction distance time series data. The online change point detection module performs transformation discrimination on the statistical characteristics of the preprocessed dataset during the traction speed scanning process.
[0019] The adaptive scanning module converts the scanning process of the traction component into critical section encrypted sampling.
[0020] The critical inversion module takes the encrypted sampling data as input, calculates the transient strain rate and inverts the tensile viscosity based on the extracted critical inflection point, and outputs the standardized solution index and confidence level. This includes: reading a first data segment formed by the encrypted sampling data; extracting candidate critical points using the discrimination signal as an index; and extracting local candidate data segments formed by consecutive windows of a preset fixed length before and after the sampling point; performing a consistency check on the sliding window statistical characteristics of the traction force time series data and the local slope changing with the traction speed time series data within the local candidate data segments to form a critical point feature package; using the critical point feature package as an anchor point, extracting a second data segment covering a fixed time length before and after the candidate critical point from the first data segment; generating a transient strain rate sequence aligned with the candidate critical point; and outputting the transient strain rate scalar at the candidate critical point. The step of generating a transient strain rate sequence aligned with the candidate critical point includes: using the timestamp corresponding to the candidate critical inflection point as the alignment reference, extracting a traction speed time sequence of a preset fixed length before and after the candidate critical point and its synchronous traction distance from the first data segment; performing differential calculation on the traction speed time sequence to obtain the rate of change of speed and smoothing it with a sliding window to suppress noise; then pairing the smoothed rate of change of speed with the corresponding effective traction distance point by point to convert it into a stretching rate per unit length, forming a sequence according to the timestamp order to obtain a transient strain rate sequence aligned with the candidate critical point. Using the traction force time series data and transient strain rate sequence in the second data segment as input, a fixed-length neighboring window is first set with the sampling time of the candidate critical point as the center. Within the neighboring window, non-increasing segments of traction speed, abnormal jump points of traction distance, and outlier points of traction force peaks are identified. The traction force fluctuation level and strain rate fluctuation level are calculated using a sliding window. Continuous sampling point segments with fluctuation levels below a preset threshold and continuously meeting stability requirements are retained. These continuous sampling point segments are defined as inversion windows, and their start and end timestamps and sample index sets are output. Within the inversion window, the traction force time series data is used as the axial load input and normalized by aligning with the real-time cross-sectional area of the melt filament to obtain the tensile stress at the corresponding time as the tensile response time series. The tensile response time series is combined with the transient strain rate to complete the tensile viscosity inversion, obtaining the tensile viscosity result of the candidate critical point and the tensile viscosity sequence within the inversion window. The process of combining tensile response quantity with transient strain rate to complete tensile viscosity inversion and obtain candidate critical point tensile viscosity results and tensile viscosity sequence within the inversion window includes: aligning the tensile response quantity time series and transient strain rate series point by point according to a unified sampling clock; then, filtering the transient strain rate series within the inversion window, removing invalid sampling points, and inverting the tensile response quantity and transient strain rate into tensile viscosity values for the retained sampling points, generating the tensile viscosity sequence within the inversion window point by point; based on this, using the sampling point corresponding to the critical inflection point as an index, reading the tensile viscosity value of that sampling point in the tensile viscosity sequence as the candidate critical point tensile viscosity.Using the candidate critical point tensile viscosity as the primary feature and parameters from the critical point feature package as supplementary inputs, a pre-defined standardized mapping rule is invoked to generate a standardized melt strength index. The standardized mapping rule uses the critical point tensile viscosity as the primary input and reads the traction force value, traction speed value, and traction distance value of the critical point from the critical point feature package. First, the candidate critical point tensile viscosity is benchmarked by traction distance. Then, the benchmarked candidate critical point tensile viscosity is checked for consistency and its amplitude is normalized by combining the critical point traction force and traction speed. Finally, a standardized melt strength index is generated according to a pre-defined fixed output caliber.
[0021] The technical effects and advantages of this invention, a strength testing device for plastic product manufacturing, are as follows: This invention achieves online testing of melt stretching capacity and strength characteristics on the extrusion production line by simultaneously acquiring motion parameters such as the melt filament forming component, the traction component, and traction force / distance. This addresses the monitoring needs for quality issues such as filament breakage, necking, and thickness fluctuations from the source. Its core lies in: after preprocessing the traction force, traction speed, and traction distance data, the strength testing component performs online change point detection based on sliding window statistical characteristics (mean, standard deviation, coefficient of variation, slope). A judgment signal drives the traction speed scan to switch from coarse scanning to critical zone encrypted sampling, thereby stably locating the transition boundary and critical turning point between the "stable stretching zone" and the "unstable stretching zone," improving the stability and repeatability of feature extraction across operating conditions. Based on this, the system calculates transient strain rate and inverts tensile viscosity around the critical inflection point. Furthermore, it generates standardized melt strength index and provides confidence level by benchmarking traction distance, consistency verification and amplitude normalization, thereby obtaining comparable and reusable strength characterization results, providing reliable quantitative basis for online closed-loop control and process optimization. Attached Figure Description
[0022] Figure 1 This is a schematic diagram of a strength testing device for the production of plastic products according to the present invention.
[0023] Figure 2 This is a schematic diagram and explanation of the working principle of an existing filament stretching rheometer.
[0024] Figure 3 This is a schematic diagram illustrating the working principle of an existing drool film winding system.
[0025] Figure 4 This is a schematic diagram of the traction component structure of the present invention.
[0026] Figure 5 This is a schematic diagram of the stable stretching zone, critical inflection point, and unstable stretching zone in the traction force-traction speed curve of this invention.
[0027] In the diagram: Laser, laser measurement device; Force Transducer, force sensor; l(t), length of the sample at time t; The initial length at time t=0; At the appointed time Accumulated Hencky strain; 1. Initial diameter of the neck at t=0; D(t), instantaneous diameter of the neck at t; 2. Melt wire; 3. First traction wheel; 4. Second traction wheel; 5. Variable speed drive mechanism. Detailed Implementation
[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0029] Example 1
[0030] like Figure 1 As shown, the present invention provides a strength testing device for the production of plastic products, comprising: The melt filament forming assembly is connected to the die of the extrusion equipment to output continuous melt filaments 1.
[0031] The traction component scans the traction speed of the molten filament 1.
[0032] The measuring component outputs traction force timing data.
[0033] The motion parameter acquisition component outputs time-series data of traction distance.
[0034] The strength testing component calculates the transient strain rate and inverses the tensile viscosity, outputting standardized melt strength indices and confidence levels.
[0035] Furthermore, the melt filament forming assembly is disposed at the discharge end of the extrusion equipment and is sealed by connecting to the die of the extrusion equipment, so that the polymer melt within the set melt temperature range can be stably introduced into the forming channel.
[0036] The melt filament forming assembly includes, in sequence, a heat-resistant guide tube and a sizing die. The heat-resistant guide tube smoothly guides the melt from the die downstream and reduces melt retention and backflow. The sizing die constrains the melt outlet geometry to form a continuous melt filament 1. The outlet diameter of the sizing die is set within the range of 0.5–5.0 mm, and the outlet edge has a chamfered structure to reduce the probability of melt adhesion and buildup at the outlet, thereby improving the continuity and stability of filament forming.
[0037] With the above structure, the melt filament forming component can continuously output a continuous flow of melt filaments during the extrusion production process, providing a stable test object for the downstream traction component.
[0038] Furthermore, the traction component is disposed on the downstream drawing path of the melt filament forming component, and applies controllable traction to the continuously output melt filament 1 and performs traction speed scanning, thereby forming traction speed timing data corresponding to the traction force response.
[0039] like Figure 4 As shown, the traction assembly includes a molten filament 1, a first traction wheel 2, a second traction wheel 3, a variable speed drive mechanism 4, and a traction clamping mechanism (not shown in the figure). The variable speed drive mechanism 4 is composed of a servo motor and its driver or a variable frequency motor and its inverter, which can realize the continuously adjustable output of traction speed according to the speed command issued by the strength detection component, and convert the speed control command into the actual traction speed response. The traction clamping mechanism is used to truly transmit the traction speed of the molten filament 1 to the filament body. Its structure can adopt one of the following: a counter-rotating traction wheel, a crawler traction belt, or a pressure roller traction structure. It provides a stable clamping force through a clamping mechanism to avoid slippage, so that the traction speed scanning process is repeatable. The traction speed scanning includes at least two basic forms: stepped speed sequence and linear ramp speed sequence. The stepped speed sequence achieves discrete excitation of different traction speed points through segmented constant speed and pauses, while the linear ramp speed sequence achieves continuous excitation through linearly increasing speed over time. Both are used to form traction force-traction speed or traction ratio curves. During traction speed scanning, the traction component synchronously records the traction speed at a sampling frequency of 50–2000Hz and aligns it with the traction force time-series data. The maximum traction speed is set to a range of 10–600 m / min to adapt to different material and production line speed levels, and the traction distance is set to a range of 0.05–1.50m to adapt to different equipment layouts and clamping positions.
[0040] Furthermore, the measuring component is positioned on the force transmission path during the drawing process of the melt filament 1, and is arranged between the melt filament forming component and the drawing component, so that the tensile load generated by the melt filament 1 when it is drawn by the drawing clamping mechanism can be completely transmitted to the measuring component and measured.
[0041] The measuring component can be implemented using a tensile weighing sensor, a strain gauge force sensor, or a moment balance beam structure. Its measuring range is set to 0–50N or 0–200N, and its resolution is set to 0.01–0.1N to adapt to different material melt strength levels and different traction speed scanning conditions.
[0042] The measurement component converts the traction load into an electrical signal output, forming traction force timing data.
[0043] Furthermore, the motion parameter acquisition component is used to measure the kinematic quantities during the traction speed scanning process and output traction distance time-series data synchronized with the scanning process of the traction component. The motion parameter acquisition component includes a distance sensor, which cooperates with the traction distance adjustment mechanism to measure the effective traction distance between the measuring component and the traction clamping mechanism, and outputs traction distance time-series data after traction distance adjustment or locking.
[0044] Furthermore, the strength detection component takes the traction force time series data, traction speed time series data and traction distance time series data as inputs, and passes them sequentially through the signal preprocessing module, the online change point detection module, the adaptive scanning module and the critical inversion module.
[0045] The signal preprocessing module performs signal preprocessing operations. Its inputs are traction force time-series data, traction speed time-series data, and traction distance time-series data synchronously acquired under the sampling clock. Its output is a preprocessed dataset used for online change point detection and subsequent inversion calculations. Specifically, the signal preprocessing module first performs denoising and smoothing on the traction force time-series data. Kalman filtering or Savitzky-Golay smoothing can be used to suppress high-frequency noise and preserve inflection point and slope abrupt change information. The filtering window is set to 5–200 sampling points. Simultaneously, the signal preprocessing module performs timestamp alignment and outlier removal on the traction speed and traction distance time-series data to ensure a one-to-one correspondence between the three data streams, thus forming a preprocessed dataset as direct input for online change point detection.
[0046] The input to the online change point detection module is the preprocessed dataset, which includes preprocessed traction force time-series data, traction speed time-series data, and traction distance time-series data. During the traction speed scan, the online change point detection module performs a transformation judgment on the statistical characteristics of the preprocessed dataset. This transformation judgment uses the preprocessed dataset as the sole input and sets a sliding window of a preset fixed length (e.g., the window length is the number of sampling points and is updated in a certain step). The signal preprocessing module synchronously outputs the sliding window statistical features, which include the traction force mean, traction force standard deviation, traction force coefficient of variation, and traction force slope. The traction force mean is obtained by the arithmetic mean of the traction force samples within the sliding window, and is used to characterize the average tensile load level under the corresponding traction state of the window; the traction force standard deviation is calculated by the dispersion of the traction force samples within the sliding window relative to the mean of the window, and is used to characterize the traction force fluctuation amplitude; the traction force coefficient of variation is calculated by the ratio of the traction force standard deviation of the sliding window to the traction force mean of the window, and is used to measure the relative intensity of fluctuation in a dimensionless manner under different traction force levels and facilitate cross-working condition comparison; within the sliding window, the traction force and the timestamp are subjected to first-order difference or linear fitting to obtain the slope of the traction force change over time. During the traction speed scanning process, the online change point detection module updates the above-mentioned sliding window statistical features window by window with a fixed length sliding window and simultaneously checks whether the speed scan is in an effective increasing segment (i.e., the traction speed within the window is monotonically increasing and the traction distance is within the allowable range without obvious jumps). When the following conditions are met, the determination signal of the change judgment is 0, that is, the stretching state of the melt filament 1 is in the stable stretching zone (the stretching state of the melt filament 1 being in the stable stretching zone specifically means that during the traction speed scanning process, the melt filament 1 can still be continuously stretched in an approximately uniform manner: the outer edge of the filament...). The diameter changes little over time, the traction path is stable and does not jitter, and the traction force signal shows small fluctuations and no sudden jumps within a short time window. As the traction speed gradually increases, the traction force shows a smooth and predictable change, possibly rising slowly or remaining relatively stable within a certain range, indicating that the viscoelastic response of the melt and the cooling and solidification process have not yet caused local instability, and the material is still under controllable stretching conditions. Within the window, the coefficient of variation of the traction force is consistently lower than the preset stability threshold, the average traction force changes smoothly and slowly with the traction speed, and the change in the traction force slope between adjacent windows does not exceed the preset slope fluctuation threshold. When the judgment signal is 0, the coarse scanning parameters are maintained, that is, a large speed step size and a short dwell time are maintained to efficiently cover the traction speed range. At the same time, continuous windows that meet the stability conditions are merged into a stable stretching zone, and its start and end speed intervals, the average traction force of the stable segment, and the fluctuation level are recorded as the stable stretching zone identification results.The transition judgment signal is 1 when any of the following transition conditions occur, indicating that the drawing state of the melt filament 1 has transitioned from the stable drawing region to the unstable drawing region: 1. Under the premise of continuously increasing drawing speed, the confirmed stable drawing region is used as the "stable segment baseline". The average drawing force and the trend of drawing force change within the stable segment baseline are used as references. When the average drawing force within 5 consecutive sliding windows is higher than the stable segment baseline level, and the deviation increases continuously as the window progresses; 2. The drawing force fluctuation level increases significantly within 5 consecutive windows and exceeds the stable threshold and shows an upward trend, indicating that necking, local unevenness, or oscillation has begun to occur in the drawing process. Figure 5 The diagram illustrates that during the traction speed scan, the response of the traction force to changes in traction speed can be divided into a "stable drawing zone" and an "unstable drawing zone." Within the stable drawing zone, the traction force exhibits a smooth and relatively stable change with increasing speed, indicating that the drawing process of the melt filament 1 is in a controllable and repeatable stable state. As the scan progresses, when the fluctuation level or slope of the traction force curve undergoes a sudden change and crosses the judgment threshold, the corresponding position is marked as a critical inflection point, which is the boundary between the stable and unstable drawing zones.
[0047] When the determination signal for the transition is 1, the stretching state of the melt filament changes from the stable stretching region to the unstable stretching region. The adaptive scanning module converts the scanning process of the traction component into a critical region (the critical region refers to the boundary between the stable stretching region and the unstable stretching region) encrypted sampling: the current traction speed is frozen and a short dwell time is set to continuously collect the traction force timing at the same speed point to confirm the continuity of the transition and suppress false triggering. The speed resolution is improved by reducing the subsequent speed step size, the scanning acceleration is reduced to weaken the dynamic disturbance caused by the speed transition, and the dwell time at each speed point is extended to obtain a sufficient length of traction force for statistical determination, thereby forming multi-resolution encrypted sampling data in the critical region.
[0048] The critical inversion module takes the encrypted sampling data as input, calculates the transient strain rate and inverts the tensile viscosity based on the extracted critical inflection point, and outputs standardized solution indices and confidence levels, including: 1. Read the first data segment formed by the encrypted sampling data, the first data segment including preprocessed traction force time series data, traction speed time series data and traction distance time series data with timestamp alignment; using the discrimination signal output by the online change point detection module as an index, extract the sampling point corresponding to the moment when the discrimination signal is first set from 0 to 1 as a candidate critical point, and extract the local candidate data segment formed by the continuous preset fixed length window before and after the sampling point; In this embodiment, the fixed-length window is centered on the sampling point, and a segment of data is extracted 0.5s before and 0.5s after the sampling point (total window length 1.0s). To ensure that the window length is consistent under different sampling frequencies (50–2000Hz), the intensity detection component resamples the synchronous dataset to 500Hz before entering the variable point and inversion calculation. Therefore, the above fixed-length window corresponds to 250 sampling points on each side, for a total of 500 sampling points. The selection results of the fixed-length window are shown in Table 1.
[0049] Table 1. Statistical results of the fixed-length window selection verification experiment (500Hz resampling, window symmetrically truncated with the candidate point as the center).
[0050] As shown in Table 2, when the window length on each side is 0.2s and 0.3s, the amount of traction force samples available for statistical determination within the window is insufficient, resulting in a significant increase in the false trigger rate and a large critical point velocity positioning error. When the window length on each side is increased to 0.8s, the false trigger rate and positioning error further decrease, but the trigger delay and calculation time increase simultaneously, and the switching of encrypted sampling in the critical zone becomes slower, which is not conducive to the timely convergence of the online closed loop in the critical neighborhood. When the window length on each side is 0.5s, the false trigger rate drops to 2.0%, the critical point velocity positioning error stabilizes at the level of 2.1m / min, and the trigger delay and calculation time remain within the range that can be used for online control. Therefore, this invention determines the fixed length window to be 0.5s before and after (total 1.0s).
[0051] 2. Within the local candidate data segment, a consistency check is performed on the sliding window statistical characteristics of the traction force time series data and the local slope that changes with the traction speed time series data: Continuous windows that satisfy the discrimination signal of 1 before the candidate critical point are merged into the end of the stable stretching zone, and continuous windows that show a continuous increase in fluctuation level after the candidate critical point are merged into the beginning segment of the unstable stretching zone; when the windows adjacent to the candidate critical point satisfy the condition that the stability segment (the stability segment refers to the effective constraint of the position of the pre-processed traction force time series data, the synchronous traction speed and traction distance, and the effective increment of the traction speed in seconds, the sliding window statistics of the traction force time series data are performed, and the mean, standard deviation, coefficient of variation and traction force slope of each window are calculated; when 5 consecutive adjacent serial ports simultaneously satisfy "fluctuation level is lower than the stability threshold, slope change is smooth and the slope of adjacent windows is...") When the candidate critical point is determined as a critical turning point, and the traction force value, traction speed, and traction distance do not jump within the window, the candidate critical point is determined as a critical turning point. The traction force value, traction speed value, and traction distance value corresponding to the critical turning point are output to form a critical point feature package. The critical turning point is determined by the following conditions: the difference does not exceed the threshold, the average traction force does not have a continuous cumulative drift, and the traction speed increases within the window, and the traction distance does not jump. The determination conditions are: the traction force time series data position is still used as the effective constraint, and the traction speed and traction distance are synchronized. When the traction speed and traction distance continue to increase within the window for 5 consecutive adjacent windows starting from a certain window, the candidate critical point is determined as a critical turning point. The traction force value, traction speed value, and traction distance value corresponding to the critical turning point are output to form a critical point feature package.
[0052] 3. Using the critical point feature packet as an anchor point, extract a second data segment from the first data segment that covers a fixed time length before and after the candidate critical point (the fixed time length is 1.0 s before and after the candidate critical point). Verify the validity of the traction speed time series and traction distance time series in the second data segment to ensure that the speed scan is in the geological segment and the distance data has no jumps. Based on this, using the change of traction speed over time and the corresponding traction distance as input, generate a transient strain rate sequence aligned with the candidate critical point and output the transient strain rate scalar at the candidate critical point.
[0053] The process of generating a transient strain rate sequence aligned with the candidate critical point includes: using the timestamp corresponding to the candidate critical inflection point as the alignment reference, extracting a traction speed time sequence of a preset fixed length before and after the candidate critical point and its synchronous traction distance from the first data segment; performing differential calculation on the traction speed time sequence to obtain the rate of change of speed and smoothing it with a sliding window to suppress noise; then pairing the smoothed rate of change of speed with the corresponding effective traction distance point by point to convert it into a stretching rate per unit length, forming a sequence according to the timestamp order to obtain a transient strain rate sequence aligned with the candidate critical point.
[0054] 4. Using the preprocessed traction force time series data and transient strain rate sequence in the second data segment as input, a fixed-length neighboring window is first set with the sampling time of the candidate critical point as the center. Within the neighboring window, non-increasing traction speed segments, abnormal jump points in traction distance, and outlier points of traction force peaks are identified. Then, the traction force fluctuation level and strain rate fluctuation level are calculated using a sliding window. Only continuous sampling point segments with fluctuation levels below a preset threshold and continuously meeting stability requirements are retained. The continuous sampling point segments are defined as inversion windows, and their start and end timestamps and sample index sets are output. Within the inversion window, the traction force time series data is used as the axial load input and normalized by aligning with the real-time cross-sectional area of melt filament 1 to obtain the tensile stress at the corresponding time as the tensile response time series. The tensile response time series is combined with the transient strain rate to complete the tensile viscosity inversion, obtaining the tensile viscosity result of the candidate critical point and the tensile viscosity sequence within the inversion window.
[0055] The process of combining the tensile response quantity with the transient strain rate to complete the tensile viscosity inversion and obtain the candidate critical point tensile viscosity result and the tensile viscosity sequence within the inversion window includes: aligning the tensile response quantity sequence and the transient strain rate sequence point by point according to a unified sampling clock to ensure that the tensile response quantity sequence at each moment is paired with the transient strain rate at the same moment to form an inversion sample; then, filtering the transient strain rate sequence within the inversion window to remove invalid sampling points caused by excessively low strain rates, sudden velocity changes, or missing data, and combining the tensile response quantity and transient strain rate to invert the tensile viscosity value for the retained sampling points according to the defined relationship, thereby generating the tensile viscosity sequence within the inversion window point by point; based on this, using the sampling point corresponding to the critical inflection point as an index, reading the tensile viscosity value of that sampling point in the tensile viscosity sequence as the candidate critical point tensile viscosity.
[0056] Using the candidate critical point tensile viscosity as the primary characteristic and parameters from the critical point feature package as supplementary inputs, a pre-defined standardized mapping rule is invoked to generate a standardized melt strength index. The standardized mapping rule uses the critical point tensile viscosity as the primary input and reads the traction force value, traction speed value, and traction distance value of the critical point from the critical point feature package. First, the candidate critical point tensile viscosity is benchmarked by traction distance to eliminate scale differences caused by different arrangements. Then, the benchmarked candidate critical point tensile viscosity is checked for consistency and its amplitude is normalized by combining the critical point traction force and traction speed. Finally, a standardized melt strength index is generated according to a pre-defined fixed output caliber.
[0057] When the candidate critical point satisfies both the stable segment termination and unstable segment start conditions within the local window, and the number of continuous windows (the number of continuous windows refers to the number of windows that continuously satisfy the same judgment condition after dividing the time series data into sliding windows of fixed length within the local window of encrypted sampling) reaches a set value, and at the same time, the fluctuation index (the fluctuation index is obtained by performing sliding window statistics on the tensile viscosity sequence within the inversion window) and the residual index (the residual index is obtained by calculating the predicted traction force curve using the candidate critical point tensile viscosity combined with transient strain rate and cross-sectional area within the inversion window, comparing the predicted traction force curve with the actual measured traction force time series data point by point to obtain the error sequence; the mean square error obtained by statistically analyzing the error sequence is the residual index) within the inversion window meet the threshold requirements, a high confidence level is assigned (the high confidence level ranges from 0.8 to 1.0).
[0058] The local window is obtained by extracting a segment of encrypted sampled data centered on a candidate critical point: first, the timestamp or velocity point position corresponding to the candidate critical point is determined, and then a continuous data segment is taken forward and backward according to a preset window length (defined by a fixed number of sampling points or a fixed time length) and spliced together to form a local data segment, which is used to verify the changes in statistical characteristics within the candidate critical point domain.
[0059] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
[0060] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A strength testing device for the production of plastic products, characterized in that, include: The melt filament forming assembly is connected to the die of the extrusion equipment to output continuous melt filaments (1). The traction assembly scans the traction speed of the molten filament (1); The measurement component outputs traction force timing data. Motion parameter acquisition component, outputting traction distance time-series data; The strength testing component calculates transient strain rate and inverses tensile viscosity, outputting standardized melt strength index and confidence level; The strength detection component takes traction force time series data, traction speed time series data and traction distance time series data as input, and passes them sequentially through the signal preprocessing module, the online change point detection module, the adaptive scanning module and the critical inversion module. The critical inversion module takes encrypted sampled data as input and calculates transient strain rate based on critical inflection points. This includes: reading a first data segment formed by the encrypted sampled data; extracting candidate critical points using a discrimination signal as an index; and extracting local candidate data segments formed by consecutive windows of a preset fixed length before and after the sampling points. Within the local candidate data segments, the consistency between the sliding window statistical characteristics of the traction force time series data and the local slope changing with the traction speed time series data is checked to form a critical point feature package. Using the critical point feature package as an anchor point, a second data segment covering a fixed time length before and after the candidate critical point is extracted from the first data segment, generating a transient strain rate sequence aligned with the candidate critical point, and outputting the transient strain rate scalar at the candidate critical point.
2. The strength testing device for plastic product manufacturing according to claim 1, characterized in that... The step of generating a transient strain rate sequence aligned with the candidate critical point includes: using the timestamp corresponding to the candidate critical inflection point as the alignment reference, extracting a traction speed time sequence of a preset fixed length before and after the candidate critical point and its synchronous traction distance from the first data segment; performing differential calculation on the traction speed time sequence to obtain the rate of change of speed and smoothing it with a sliding window to suppress noise; then pairing the smoothed rate of change of speed with the corresponding effective traction distance point by point to convert it into the stretching rate per unit length, forming a sequence according to the timestamp order to obtain a transient strain rate sequence aligned with the candidate critical point.
3. The strength testing device for plastic product manufacturing according to claim 2, characterized in that... Using the traction force time series data and transient strain rate sequence in the second data segment as input, a fixed-length neighboring window is first set with the sampling time of the candidate critical point as the center. Within the neighboring window, non-increasing traction speed segments, abnormal jump points in traction distance, and outlier points of traction force peaks are extracted. The traction force fluctuation level and strain rate fluctuation level are calculated by sliding window. Continuous sampling point segments with fluctuation levels below the preset threshold and continuous stability requirements are retained. The continuous sampling point segments are defined as inversion windows and their start and end timestamps and sample index sets are output. Within the inversion window, the traction force time series data is used as the axial load input and normalized by aligning with the real-time cross-sectional area of the melt filament (1) to obtain the tensile stress at the corresponding time as the tensile response time series. The tensile response time series is combined with the transient strain rate to complete the tensile viscosity inversion, and the candidate critical point tensile viscosity result and the tensile viscosity sequence within the inversion window are obtained.
4. The strength testing device for plastic product manufacturing according to claim 3, characterized in that, The process of combining tensile response quantity with transient strain rate to complete tensile viscosity inversion and obtain candidate critical point tensile viscosity results and tensile viscosity sequence within the inversion window includes: aligning the tensile response quantity time series and transient strain rate series point by point according to a unified sampling clock; then, filtering the transient strain rate series within the inversion window, removing invalid sampling points, and inverting the tensile response quantity and transient strain rate into tensile viscosity values for the retained sampling points, generating the tensile viscosity sequence within the inversion window point by point; based on this, using the sampling point corresponding to the critical inflection point as an index, reading the tensile viscosity value of that sampling point in the tensile viscosity sequence as the candidate critical point tensile viscosity.
5. The strength testing device for plastic product manufacturing according to claim 4, characterized in that, Using the candidate critical point tensile viscosity as the main feature quantity and the parameters in the critical point feature package as supplementary inputs, a preset standardized mapping rule is invoked to generate a standardized melt strength index.
6. The strength testing device for plastic product manufacturing according to claim 5, characterized in that, The standardized mapping rule takes the critical point tensile viscosity as the main input and reads the traction force value, traction speed value, and traction distance value of the critical point in the critical point feature package. First, the candidate critical point tensile viscosity is benchmarked by traction distance. Then, the benchmarked candidate critical point tensile viscosity is checked for consistency and normalized by combining the critical point traction force and traction speed. Finally, a standardized melt strength index is generated according to a preset fixed output caliber.
7. The strength testing device for plastic product manufacturing according to claim 1, characterized in that... The melt filament forming assembly includes, in sequence, a heat-resistant guide tube and a sizing die.
8. The strength testing device for plastic product manufacturing according to claim 1, characterized in that... The traction assembly includes a variable speed drive mechanism (4) and a traction clamping mechanism. The variable speed drive mechanism (4) is composed of a servo motor and its driver or a variable frequency motor and its inverter. The traction clamping mechanism is one of a counter-rotating traction wheel, a track traction belt or a pressure roller traction structure, and provides clamping force through a clamping mechanism.
9. The strength testing device for plastic product manufacturing according to claim 8, characterized in that... The motion parameter acquisition component includes a distance sensor, which cooperates with the traction distance adjustment mechanism to determine the effective traction distance between the measuring component and the traction clamping mechanism, and outputs traction distance timing data after traction distance adjustment or locking.
10. The strength testing device for plastic product manufacturing according to claim 1, characterized in that... The signal preprocessing module performs noise reduction and smoothing on the traction force time series data using Kalman filtering, and performs timestamp alignment and outlier removal on the traction speed time series data and traction distance time series data.