Pvc injection hook forming device and control method thereof

Abstract

The application is suitable for the technical field of injection hook forming, and particularly relates to a PVC injection hook forming device and a control method thereof. The method comprises the following steps: acquiring running parameter data of the PVC injection hook forming device in real time; acquiring forming state data of the PVC injection hook after being stripped from a mold cavity; obtaining a hook tip profile curvature change rate of a hook tip part of the PVC injection hook, and a temperature difference gradient between a hook tip root and a top part based on the forming state data; constructing a coupling relationship matrix of a first feature deviation and a second feature deviation based on the first feature deviation of the hook tip profile curvature change rate and a preset curvature change rate standard value, and the second feature deviation of the temperature difference gradient between the hook tip root and the top part and a preset temperature difference gradient standard value; and dynamically allocating a control priority based on the coupling relationship matrix, and controlling corresponding running parameter data in the running parameter data. The embodiment of the application can solve the problem that the prior art only controls the overall quality of the PVC injection hook, and lacks a design for guaranteeing the quality of the hook tip.

Description

Technical Field

[0001] This application belongs to the field of injection molding technology, and particularly relates to a PVC injection molding device and its control method. Background Technology

[0002] PVC (polyvinyl chloride) is a highly malleable and cost-effective synthetic resin material widely used in injection molding. PVC injection hooks are functional products with hook-like structures manufactured through injection molding. Due to their reliable connection and fixing properties, they are widely used in various fields such as Velcro, medical device accessories, industrial connectors, and electronic component positioning. PVC injection hook molding technology refers to the process of heating and melting PVC raw materials into a molten state, injecting it into a specialized mold cavity, and then completing the hook-like structure formation through processes such as pressure holding and cooling solidification. This technology has now been industrialized and can be used for mass production of PVC injection hook products.

[0003] However, existing PVC injection hook molding technology, in applications such as textile accessories, medical consumables, and packaging fixation where stringent requirements are placed on the puncture performance and structural stability of the hook tip, suffers from a lack of quality assurance design for the hook tip, as it only controls the overall quality of the PVC injection hook. This results in poor consistency in the sharpness, puncture strength, and structural stability of the produced hook tips, which in turn leads to hook tip failure in actual use scenarios such as high-frequency punctures and repeated load-bearing fixation, making it difficult to meet the stable requirements of the core functions of the hook tip in demanding application scenarios. Summary of the Invention

[0004] This application provides a PVC injection hook molding device and its control method, which can solve the problem that existing PVC injection hook molding technology only controls the overall quality of PVC injection hooks and lacks quality assurance design for the hook tip.

[0005] In a first aspect, embodiments of this application provide a PVC injection hook molding debugging and control method, applied to a PVC injection hook molding device, the method comprising:

[0006] During the PVC injection hook molding process, the operating parameter data of the PVC injection hook molding device are acquired in real time; wherein, the operating parameter data includes barrel temperature data, injection pressure data, holding time data, and mold cooling water flow rate data;

[0007] Obtain molding state data after the PVC injection hook is peeled off from the mold cavity;

[0008] Based on the molding state data, the change rate of the hook tip profile curvature and the temperature gradient between the root and the top of the hook tip are obtained.

[0009] Based on the first characteristic deviation between the curve change rate of the hook tip profile and the preset standard value of the curve change rate, and the second characteristic deviation between the temperature difference gradient between the root and the top of the hook tip and the preset standard value of the temperature difference gradient, a coupling relationship matrix between the first characteristic deviation and the second characteristic deviation is constructed.

[0010] Based on the coupling relationship matrix, the control priority is dynamically allocated to control the corresponding operating parameter data in the operating parameter data; wherein, the corresponding operating parameter data is at least one of the barrel temperature data, the injection pressure data, the holding time data, and the mold cooling water flow rate data.

[0011] The technical solutions described in this application embodiment have at least the following technical effects:

[0012] The PVC injection hook molding debugging and control method provided in this application first acquires the operating parameter data of the PVC injection hook molding device in real time during the PVC injection hook molding process, providing accurate, comprehensive and real-time data support for subsequent targeted adjustment; then, it acquires the molding state data of the PVC injection hook after it is peeled from the mold cavity, which can obtain complete state information of the molded product, laying a reliable data foundation for the calculation of key quantitative indicators of the hook tip; then, based on the molding state data, it obtains the hook tip contour curvature change rate and the temperature difference gradient between the hook tip root and the top, which can accurately quantify the molding quality and temperature distribution characteristics of the core functional area of ​​the hook tip, and achieve... Targeted analysis of hook tip quality is performed; then, based on the first characteristic deviation of the hook tip profile curvature change rate and the preset curvature change rate standard value, and the second characteristic deviation of the temperature difference gradient between the hook tip root and top and the preset temperature difference gradient standard value, a coupling relationship matrix between the first and second characteristic deviations is constructed. By establishing a correlation model between the two characteristic deviations, the limitations of single characteristic control can be overcome, providing a scientific basis for multi-parameter collaborative control; finally, based on the coupling relationship matrix, the control priority is dynamically allocated, and the corresponding operating parameter data in the operating parameter data is controlled, which can achieve precise and orderly control of process parameters, reduce quality fluctuations caused by blind parameter adjustment, and improve debugging efficiency and the scientific nature of control. This method addresses core quality risks such as puncture failure and stress cracking caused by deviations in hook tip contour curvature and temperature gradients before the PVC injection hook molding device is put into formal production and operation. It also resolves issues of blind debugging caused by mismatched combinations of key molding influencing parameters and chaotic control priorities. This avoids situations where batches of products are eliminated due to substandard molding quality, production debugging cycles are lengthy, and raw material and energy costs increase after formal production and operation. At the same time, it solves the problem that existing technologies only control the overall quality of PVC injection hooks and lack specific quality assurance for the hook tip. It effectively improves the sharpness, puncture strength, and structural stability of the hook tip, meeting the stable requirements of the core functions of the hook tip in high-requirement application scenarios such as textile accessories and medical consumables.

[0013] Secondly, embodiments of this application provide a PVC injection hook molding debugging and control system, applied to a PVC injection hook molding device, for implementing the PVC injection hook molding debugging and control method described in the first aspect above. The PVC injection hook molding debugging and control system includes:

[0014] The first acquisition unit is used to acquire the operating parameter data of the PVC injection hook molding device in real time during the PVC injection hook molding process; wherein, the operating parameter data includes barrel temperature data, injection pressure data, holding time data, and mold cooling water flow rate data;

[0015] The second acquisition unit is used to acquire molding state data after the PVC injection hook is peeled off from the mold cavity;

[0016] The unit is used to obtain, based on the molding state data, the hook tip profile curvature change rate and the temperature gradient between the hook tip root and the top of the PVC injection hook.

[0017] The construction unit is used to construct a coupling relationship matrix between the first feature deviation and the second feature deviation based on the first feature deviation between the curve change rate of the hook tip profile and the preset standard value of the curve change rate, and the second feature deviation between the temperature difference gradient between the root and the top of the hook tip and the preset standard value of the temperature difference gradient.

[0018] The control unit is used to dynamically allocate control priorities based on the coupling relationship matrix and control the corresponding operating parameter data in the operating parameter data; wherein, the corresponding operating parameter data is at least one of the barrel temperature data, the injection pressure data, the holding time data, and the mold cooling water flow rate data.

[0019] Thirdly, embodiments of this application provide a PVC injection hook molding apparatus, including a PVC injection hook molding debugging and control system. The PVC injection hook molding debugging and control system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method described in any of the first aspects above.

[0020] It is understood that the beneficial effects of the second and third aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a PVC injection hook molding debugging and control method according to an embodiment of this application;

[0023] Figure 2 This is a schematic diagram of the implementation process of step S300 in the PVC injection hook molding debugging control method provided in an embodiment of this application;

[0024] Figure 3 This is a schematic diagram of the implementation process of step S400 in the PVC injection hook molding debugging control method provided in an embodiment of this application;

[0025] Figure 4 This is a schematic diagram of the implementation process of step S500 in the PVC injection hook molding debugging control method provided in an embodiment of this application;

[0026] Figure 5 This is a schematic diagram of the PVC injection hook molding debugging control system provided in the embodiments of this application;

[0027] Figure 6 This is a schematic diagram of the PVC injection hook molding device provided in the embodiments of this application. Detailed Implementation

[0028] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0029] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0030] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0031] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0032] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0033] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0034] In related technologies, existing PVC injection hook molding technology, in application scenarios such as textile accessories, medical consumables, and packaging fixation, which have stringent requirements for hook tip puncture performance and structural stability, has the problem that it only controls the overall quality of PVC injection hooks and lacks quality assurance design for hook tips. This results in poor consistency in the sharpness, puncture strength, and structural stability of the produced hook tips, which in turn makes hook tips prone to failure in actual use scenarios such as high-frequency punctures and repeated load-bearing fixation, making it difficult to meet the stable requirements of the core functions of hook tips in high-requirement application scenarios.

[0035] To address the aforementioned issues, this application provides a PVC injection hook molding device and its control method. In this method, firstly, during the PVC injection hook molding process, the operating parameter data of the PVC injection hook molding device are acquired in real time, providing accurate, comprehensive, and real-time data support for subsequent targeted adjustments. Secondly, the molding state data of the PVC injection hook after it has been peeled from the mold cavity is acquired, allowing for the acquisition of complete state information of the molded product, laying a reliable data foundation for calculating key quantitative indicators of the hook tip. Then, based on the molding state data, the hook tip contour curvature change rate and the temperature gradient between the hook tip root and top are obtained, enabling precise quantification of the molding quality and temperature distribution characteristics of the core functional area of ​​the hook tip, achieving targeted analysis of the hook tip quality. Then, based on the first characteristic deviation between the rate of change of curvature of the hook tip profile and the preset standard value of the rate of change of curvature, and the second characteristic deviation between the temperature gradient between the root and the top of the hook tip and the preset standard value of the temperature gradient, a coupling relationship matrix between the first and second characteristic deviations is constructed. By establishing a correlation model between the two characteristic deviations, the limitations of single characteristic control can be overcome, providing a scientific basis for multi-parameter coordinated control. Finally, based on the coupling relationship matrix, the control priority is dynamically allocated, and the corresponding operating parameter data in the operating parameter data is controlled. This can achieve precise and orderly control of process parameters, reduce quality fluctuations caused by blind parameter adjustment, and improve debugging efficiency and the scientific nature of control. This method addresses core quality risks such as puncture failure and stress cracking caused by deviations in hook tip contour curvature and temperature gradients before the PVC injection hook molding device is put into formal production and operation. It also resolves issues of blind debugging caused by mismatched combinations of key molding influencing parameters and chaotic control priorities. This avoids situations where batches of products are eliminated due to substandard molding quality, production debugging cycles are lengthy, and raw material and energy costs increase after formal production and operation. At the same time, it solves the problem that existing technologies only control the overall quality of PVC injection hooks and lack specific quality assurance for the hook tip. It effectively improves the sharpness, puncture strength, and structural stability of the hook tip, meeting the stable requirements of the core functions of the hook tip in high-requirement application scenarios such as textile accessories and medical consumables.

[0036] The PVC injection hook molding debugging and control method provided in this application embodiment can be applied to a PVC injection hook molding device. In this case, the PVC injection hook molding device is the executing subject of the PVC injection hook molding debugging and control method provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of PVC injection hook molding device.

[0037] It can be understood that a PVC injection hook molding device is an automated injection molding equipment used to mold PVC raw materials into PVC injection hook products with specific hook-shaped structures (including hook tip, hook body, and hook foot) through injection molding processes such as melting and plasticizing, high-pressure injection, pressure holding and shrinkage compensation, and cooling and solidification. It is widely used in the mass production of textile accessories, daily necessities, medical consumables, and other fields. For example, a PVC injection hook molding device may include: an injection molding unit, a precision mold unit, an online detection unit, a parameter control and execution unit, and a PVC injection hook molding debugging and control system.

[0038] The injection molding unit is the core power and plasticizing unit for PVC injection molding, responsible for melting, metering, high-pressure injection, and pressure holding for shrinkage compensation of PVC raw materials. The injection molding unit may include a hopper, barrel, screw assembly, injection cylinder, heating coils, temperature sensors, pressure sensors, and a pressure holding valve assembly. The hopper is installed at the top of the barrel (for storing PVC raw materials). The barrel adopts a segmented structure (heating coils are installed in the front, middle, and rear sections respectively). Temperature sensors are embedded in each section of the barrel (to collect barrel temperature data in real time). The screw assembly is installed inside the barrel (to melt and plasticize the PVC raw materials through rotation). The injection cylinder is connected to the tail of the screw assembly (to provide injection power). The pressure sensor is installed in the injection cylinder's hydraulic circuit (to collect injection pressure data). The pressure holding valve assembly is linked to the injection cylinder's hydraulic circuit (to maintain the holding pressure). The pressure holding valve assembly integrates a time relay (to record the holding time data). During operation, PVC raw material enters the barrel from the hopper, is heated and melted by heating coils in various sections, and the rotating screw pushes the molten PVC raw material to the metering front end of the barrel. After the PVC injection hook molding debugging control system issues a command, the injection cylinder drives the screw to advance rapidly, injecting the molten PVC raw material into the cavity of the precision mold unit at a preset pressure. After injection, the pressure holding valve group is activated to maintain the preset pressure holding time and fill the gaps caused by the cooling and shrinkage of the PVC raw material. At the same time, temperature sensors, pressure sensors, and time relays collect barrel temperature, injection pressure, and pressure holding time data in real time, and feed them back to the PVC injection hook molding debugging control system to provide raw data for subsequent deviation analysis and parameter adjustment.

[0039] The precision mold unit is the molding carrier of the PVC injection hook, directly determining the outline shape, dimensional accuracy, and core structure of the hook tip. The precision mold unit can include a fixed mold, a moving mold, a dedicated cavity for the hook tip, an ejection mechanism, guide pillars and bushings, and mold cooling water channels. The fixed mold is fixed to the mounting panel of the PVC injection hook molding device. The moving mold is connected to the clamping mechanism of the injection molding unit via a mold frame (to achieve mold opening and closing). The dedicated cavity for the hook tip is machined on the mating surface of the fixed and moving molds (the cavity outline is machined according to the PVC injection hook design drawings, with a focus on optimizing the cavity accuracy at the hook tip piercing end to reduce molding burrs). The ejection mechanism is installed inside the moving mold (including ejector pins, ejector rod fixing plates, and return springs; the ejector pins correspond to the non-stressed area of ​​the hook tip). Guide pillars and bushings are installed at the four corners of the mold (to ensure coaxiality when the fixed and moving molds open and close). The mold cooling water channels are embedded inside the fixed and moving molds (the pipes conform to the cavity outline, especially the hook tip area, to ensure uniform cooling). During operation, after the molten PVC material is injected into the special cavity for the hook tip, circulating cooling water is introduced into the mold cooling water circuit to accelerate the cooling and solidification of the material. After molding is completed, the mold locking mechanism drives the moving mold to retract, and the ejection mechanism, driven by a spring or injection cylinder, ejects the PVC injection hook from the cavity to ensure complete peeling of the product.

[0040] The online inspection unit is installed on the ejector side (downstream of the demolding port) of the precision mold unit to collect real-time molding status data (hook tip molding image, thermal distribution data) after the PVC injection hook is peeled off. The online inspection unit may include a vision inspection component, an infrared thermal distribution detection component, and a conveying and positioning mechanism. The conveying and positioning mechanism is installed directly below the demolding port to accurately transport and position the ejected PVC injection hook to the inspection station. The conveying and positioning mechanism includes a belt conveyor, a positioning block, and a photoelectric sensor. The belt conveyor is horizontally arranged directly below the demolding port, the positioning block is installed at the inspection station at the end of the belt conveyor, and the photoelectric sensor is fixed to the entrance side of the inspection station by a bracket.

[0041] The vision inspection component is installed directly above the inspection station to capture a complete image of the hook tip. The vision inspection component includes an industrial camera, a ring-shaped supplementary light source, and an image acquisition card. The industrial camera is mounted on a bracket, with its lens vertically aligned with the hook tip area of ​​the inspection station. The ring-shaped supplementary light source surrounds the bottom of the lens. The image acquisition card is integrated into the signal output terminal of the industrial camera. The infrared thermal distribution detection component is installed to one side of the vision inspection component to collect the hook tip thermal distribution data. The infrared thermal distribution detection component includes an infrared thermal imager, an ambient temperature compensation sensor, and a data transmission module. The infrared thermal imager is fixed with an independent bracket, its lens facing the hook tip area of ​​the inspection station. The ambient temperature compensation sensor is installed on the side of the infrared thermal imager's body, and the data transmission module is integrated inside the infrared thermal imager's housing. During operation, the PVC injection hook is precisely delivered to the inspection station via a conveying and positioning mechanism, triggering a detection signal from a photoelectric sensor. A ring-shaped supplementary light source is activated, and an industrial camera captures a complete image of the hook tip (covering the puncture end and the connection point with the hook body). The image is transmitted via an image acquisition card to the PVC injection hook molding and debugging control system for subsequent noise reduction, contour extraction, and curvature change rate calculation. Simultaneously, an infrared thermal imager collects heat distribution data of the hook tip, and an ambient temperature compensation sensor synchronously collects the ambient temperature of the inspection area. The PVC injection hook molding and debugging control system calibrates the heat distribution data based on the ambient temperature, reducing errors in temperature gradient calculation caused by environmental interference.

[0042] The parameter control execution unit is an actuator that receives commands from the PVC injection hook molding debugging control system and dynamically adjusts operating parameters. It can precisely adjust the barrel temperature, injection pressure, holding time, and mold cooling water flow rate. The parameter control execution unit may include a temperature control module, a pressure control module, a holding time control module, and a cooling water flow rate control module. The temperature control module (SCR power regulator, temperature controller) is linked with the heating coil and temperature sensor of the injection molding unit (receiving commands from the PVC injection hook molding debugging control system to adjust the heating coil power and achieve precise control of the barrel temperature). The pressure control module (proportional relief valve, solenoid directional valve) is connected to the oil circuit of the injection cylinder (adjusting the injection pressure). The holding time control module (programmable time relay) is linked with the holding valve group (adjusting the holding duration). The cooling water flow rate control module (solenoid flow valve, water flow sensor) is connected to the mold cooling water circuit of the precision mold unit (adjusting the cooling water circulation speed). During operation, the PVC injection hook molding debugging control system issues commands to the corresponding control modules according to the control priority assigned by the coupling relationship matrix. For example, when the curvature-related parameter group needs to be adjusted, the temperature control module adjusts the barrel heating power and the pressure control module adjusts the injection pressure; when the temperature difference-related parameter group needs to be adjusted, the pressure holding time control module adjusts the pressure holding time and the cooling water flow rate control module adjusts the opening of the electromagnetic flow valve. During the control process, the sensors of each module collect the adjusted parameter data in real time and feed it back to the PVC injection hook molding debugging control system to form a closed-loop control system.

[0043] The PVC injection molding and debugging control system is the core control and data processing unit of the PVC injection molding and debugging device. It is electrically connected to the injection molding unit, precision mold unit, online detection unit, and parameter control execution unit. The PVC injection molding and debugging control system can be, for example, a PLC controller, an industrial panel PC, or an embedded controller.

[0044] To better understand the PVC injection hook molding debugging and control method provided in the embodiments of this application, the specific implementation process of the PVC injection hook molding debugging and control method provided in the embodiments of this application will be described by way of example below.

[0045] Figure 1 This illustration shows a schematic flowchart of a PVC injection hook molding debugging and control method provided in an embodiment of this application. The PVC injection hook molding debugging and control method includes:

[0046] S100 acquires real-time operating parameter data of the PVC injection hook molding device during the PVC injection hook molding process; the operating parameter data includes barrel temperature data, injection pressure data, holding time data, and mold cooling water flow rate data.

[0047] The PVC injection hook molding process refers to the complete process of PVC raw material undergoing melting and plasticization, high-pressure injection, pressure holding and shrinkage compensation, cooling and solidification, and finally peeling off from the mold cavity to form a PVC injection hook. The PVC injection hook molding device is an automated injection molding equipment used to realize the PVC injection hook molding process, including an injection molding unit, a precision mold unit, an online detection unit, and a PVC injection hook molding debugging and control system. Operating parameter data are quantified data of key process parameters affecting the quality of PVC injection hook molding. Barrel temperature data are the quantified values ​​of the actual temperature of each section of the barrel (front, middle, and rear sections), directly affecting the molten state of the PVC raw material. Injection pressure data are the quantified values ​​of the actual pressure when the injection cylinder pushes the molten PVC raw material into the mold cavity, determining the cavity filling effect. Holding time data are the quantified values ​​of the duration for which the holding pressure valve group maintains the preset pressure after injection, used to fill the gaps caused by the cooling and shrinkage of the PVC raw material. Mold cooling water flow rate data are the quantified values ​​of the actual flow rate of cooling water flowing through the mold cooling water path, affecting the cooling and solidification speed of the PVC raw material.

[0048] For example, temperature data of the barrel can be continuously collected at preset time intervals by temperature sensors embedded in each section of the barrel, injection pressure data can be continuously collected at preset time intervals by pressure sensors installed in the oil circuit of the injection cylinder, holding time data can be continuously collected at preset time intervals by time relays integrated in the holding pressure valve group, and mold cooling water flow rate data can be continuously collected at preset time intervals by water flow rate sensors in the mold cooling water circuit.

[0049] S200: Obtain molding status data after the PVC injection hook is detached from the mold cavity.

[0050] It can be understood that the mold cavity is a sealed space within a precision mold unit, formed after the fixed mold and moving mold are closed. Its contour perfectly matches the design shape of the PVC injection hook, and it is used to contain molten PVC raw material and allow it to cool and solidify into the target product shape. Molding state data reflects the molding quality after the PVC injection hook is peeled off. For example, it may include visual data showing the hook tip contour and thermal distribution data showing the hook tip temperature distribution.

[0051] For example, the PVC injection hooks stripped from the mold cavity can be first transported to the inspection station by the conveying and positioning mechanism. When the PVC injection hook triggers the photoelectric sensor, the conveying and positioning mechanism stops running and completes the positioning. The PVC injection hook molding and debugging control system then triggers the vision inspection component and the infrared thermal distribution detection component of the online inspection unit to start synchronously. The industrial camera of the vision inspection component captures the hook tip molding image and transmits it through the image acquisition card. The infrared thermal imager of the infrared thermal distribution detection component collects the hook tip thermal distribution data and transmits it through the data transmission module. The molding image and hook tip thermal distribution data are then sent to the PVC injection hook molding and debugging control system in real time.

[0052] S300, based on molding state data, obtains the change rate of hook tip profile curvature of the hook tip portion of the PVC injection hook, and the temperature gradient between the root and top of the hook tip.

[0053] It is understandable that the hook tip is the key area for the piercing function of a PVC injection hook, including the piercing end (the end that directly contacts the object being pierced) and the transition area between the hook tip and the hook body. The hook tip profile curvature variation rate is the degree of fluctuation in curvature values ​​at various feature sampling points along the hook tip profile. It is used to quantify the regularity of the hook tip profile; the curvature value characterizes the degree of bending at a point on the curve, and the degree of fluctuation is obtained through specific calculations, directly affecting the sharpness of the hook tip's piercing. The hook tip root is the force transition area at the connection point between the hook tip and the hook body, and is the starting point for the transmission of piercing force. The hook tip tip top is the piercing functional area of ​​the hook tip's piercing end, and is the part where the piercing action is directly performed. The temperature gradient between the hook tip root and tip is the average temperature difference between the corresponding areas at the hook tip root and tip. It is used to quantify the uniformity of temperature distribution after the hook tip cools. The uniformity of temperature distribution affects the structural stability of the PVC injection hook, preventing stress cracking caused by excessive temperature differences.

[0054] S400, based on the first feature deviation between the curve change rate of the hook tip profile and the preset standard value of the curve change rate, and the second feature deviation between the temperature difference gradient between the root and the top of the hook tip and the preset standard value of the temperature difference gradient, constructs a coupling relationship matrix between the first feature deviation and the second feature deviation.

[0055] It is understandable that the preset curvature change rate standard value is a qualified benchmark value for the hook tip contour curvature change rate set through extensive testing and verification based on the application scenarios, puncture performance requirements, and industry quality standards of PVC injection hooks. It is used to measure whether the actual hook tip contour regularity meets the puncture sharpness requirements. The first characteristic deviation is the difference between the actual hook tip contour curvature change rate and the preset curvature change rate standard value. The sign of the difference reflects the direction of deviation from the standard, and the absolute value reflects the degree of deviation. The preset temperature gradient standard value is a qualified benchmark value determined through material thermal stability testing and structural strength testing based on the material characteristics, structural strength requirements, and industry quality standards of PVC injection hooks, to prevent stress cracking caused by excessive temperature differences. The second characteristic deviation is the difference between the actual temperature gradient between the hook tip root and top and the preset temperature gradient standard value. The sign of the difference reflects the direction of deviation from the standard, and the absolute value reflects the degree of deviation. The coupling relationship matrix is ​​a two-dimensional data matrix used to establish the correlation and correspondence between the first and second characteristic deviations, providing core data support for subsequent dynamic allocation and control priorities.

[0056] S500 dynamically allocates control priorities based on the coupling relationship matrix, and controls the corresponding operating parameter data in the operating parameter data; wherein, the corresponding operating parameter data is at least one of the following: barrel temperature data, injection pressure data, holding pressure time data, and mold cooling water flow rate data.

[0057] It can be understood that the control priority is a ranking of the urgency of adjusting operating parameter data, used to clarify the order in which different operating parameter data are controlled. The corresponding operating parameter data refers to the operating parameter data that is directly related to the first characteristic deviation or the second characteristic deviation, and whose adjustment can effectively correct the corresponding deviation. Specifically, it includes at least one of the following: barrel temperature data, injection pressure data, holding time data, and mold cooling water flow rate data.

[0058] By employing steps S100 to S500, and quantifying two key indicators—the rate of change of the hook tip contour curvature and the temperature gradient between the root and top of the hook tip—potential defects in hook tip forming quality are accurately captured. Furthermore, by linking the failure risks of these two key indicators through a coupling matrix, dynamic allocation of control priorities, and targeted adjustment of relevant operating parameter data, specialized assurance of hook tip quality is achieved. This effectively solves the problem of existing technologies lacking specialized quality assurance for the hook tip, significantly improving the sharpness, puncture strength, and structural stability of the hook tip, and meeting the stable requirements of core hook tip functions in high-demand application scenarios such as textile accessories and medical consumables.

[0059] As an optional embodiment of this application, please refer to Figure 2 S300, based on molding state data, obtains the hook tip profile curvature change rate and temperature gradient between the hook tip root and tip of the PVC injection hook, including:

[0060] S310 performs noise reduction processing on the molded image, removing the interference of residual impurities from the injection molding on the complete contour, and obtains the noise-reduced molded image.

[0061] It can be understood that the molded image is the visual data acquired in S200, covering the complete outline of the hook tip piercing end and the connection end between the hook tip and the hook body in the molded state data. Residual impurities from injection molding are PVC debris, dust, and other impurities that may adhere to the hook tip surface or mold cavity during the injection molding process, which can cause the outline of the molded image to be unclear. A complete outline is the contour line that fully reflects the shape of the hook tip piercing end and the connection end between the hook tip and the hook body. The noise-reduced molded image is image data where the hook tip outline is clearly distinguishable after noise reduction processing and removal of impurity interference.

[0062] For example, the residual impurity pixels with abnormal gray values ​​in the molding image can be identified first, and then these residual impurity pixels can be smoothed by a filtering algorithm while preserving the edge features of the hook tip contour to avoid loss of contour information. Finally, a denoised molding image with a clear hook tip contour can be obtained. For example, Gaussian filtering, median filtering and other image denoising algorithms can be used, and the appropriate filtering parameters can be selected according to the degree of impurity interference.

[0063] S320 preprocesses the denoised image, extracts the outline of the hook tip, and retains the key contour features that affect the sharpness of the hook tip piercing end.

[0064] It is understandable that preprocessing involves enhancing the contrast and strengthening the edges of the denoised image to improve the accuracy of contour extraction. Extracting the hook tip contour involves separating the hook tip area from the background area in the preprocessed image, obtaining a continuous line that only reflects the shape of the hook tip. Key contour features refer to the contour structures in the hook tip piercing end that directly affect the sharpness of the piercing, such as the straight segment of the piercing blade, the inflection point of the hook tip contour, and the transition arc between the blade and the hook body.

[0065] For example, the PVC injection hook molding debugging control system can adjust the grayscale contrast and enhance the details of the contour edges of the denoised molding image. Then, it can call the edge detection and contour extraction algorithm to separate the continuous contour lines of the hook tip from the preprocessed molding image. Subsequently, according to the preset key feature recognition rules, it can screen and retain key contour features that affect the sharpness of puncture, such as the straight line segment of the puncture edge of the hook tip, the inflection point of the hook tip contour, and the transition arc between the edge and the hook body. It can also remove the contour details of non-critical areas of the hook body, providing a precise basis for the selection of subsequent sampling points.

[0066] S330, based on the contour line and key contour features, selects feature sampling points on the contour line of the hook tip piercing end and the end where the hook tip connects to the hook body, and calculates the curvature value of the feature sampling points.

[0067] As can be understood, feature sampling points are discrete points selected from the contour line that accurately reflect the curvature of the hook tip contour, and are concentrated at the hook tip piercing end and the junction of the hook tip and the hook body. The curvature value is a quantitative data characterizing the curvature of a point on the contour line. The larger the curvature value, the more obvious the curvature of the contour at that point, directly reflecting the regularity of the hook tip contour.

[0068] S340, the rate of change of curvature of the hook tip profile is obtained based on the fluctuation range of the curvature value.

[0069] As can be understood, fluctuation amplitude refers to the degree of difference between the curvature values ​​of all feature sampling points, reflecting the consistency of the curvature of various parts of the hook tip profile. The rate of change of curvature of the hook tip profile is a quantitative representation of fluctuation amplitude; the smaller the value, the more regular the hook tip profile and the better the puncture sharpness.

[0070] For example, the PVC injection hook molding debugging control system performs statistical analysis on the curvature values ​​of all feature sampling points, calculates the variance or range of the curvature values ​​to obtain the fluctuation range, and then converts the fluctuation range into a quantified hook tip profile curvature change rate according to a preset conversion formula. For example, the hook tip profile curvature change rate can be obtained through the preset conversion formula: hook tip profile curvature change rate = variance of curvature values ​​× proportional coefficient (the proportional coefficient is set according to the molding accuracy requirements of PVC injection hooks and industry standards).

[0071] By employing the above steps S310 to S340, through noise reduction, preprocessing, contour extraction, feature sampling point selection, and curvature value calculation of the formed image, the rate of change of the hook tip contour curvature is accurately obtained. This solves the problem of the lack of specific quantitative detection of the hook tip contour in existing technologies, and can accurately capture subtle deviations in the hook tip contour, providing a basis for subsequent targeted control and effectively ensuring the stability of the hook tip piercing sharpness.

[0072] As an optional embodiment of this application, S300, based on molding state data, obtains the temperature difference gradient between the root and top of the hook tip portion of the PVC injection hook, including:

[0073] The S350 performs environmental temperature compensation calibration on the thermal distribution data to reduce the interference of environmental temperature on the thermal distribution detection results of the hook tip, thus obtaining calibrated thermal distribution data.

[0074] It can be understood that thermal distribution data is quantitative data acquired from the S200, reflecting the temperature distribution in various areas of the hook tip. Ambient temperature compensation calibration is a process of correcting the thermal distribution data by collecting the actual temperature of the testing environment. The calibrated thermal distribution data, after reducing ambient temperature interference, is accurate data that truly reflects the temperature distribution of the hook tip itself.

[0075] For example, the PVC injection hook molding debugging control system first acquires the real-time ambient temperature of the detection area collected by the ambient temperature compensation sensor, and then calls the preset compensation algorithm to subtract the difference between the ambient temperature and the standard ambient temperature from the temperature value of each point in the heat distribution data, thereby removing the influence of ambient temperature fluctuations on the detection results, and finally obtains calibrated heat distribution data that can truly reflect the temperature distribution of the hook tip, thus improving the accuracy of subsequent temperature difference calculations.

[0076] S360, based on calibrated thermal distribution data, divides the area corresponding to the root of the hook tip into two regions: the area corresponding to the root of the hook tip and the area corresponding to the top of the hook tip. The area corresponding to the root of the hook tip is the force transition area at the connection between the hook tip and the hook body, while the area corresponding to the top of the hook tip is the puncture function area at the puncture end of the hook tip.

[0077] It is understandable that the area corresponding to the base of the hook tip is the transition area connecting the hook tip and the hook body, and this area is the force transmission area during piercing. The area corresponding to the top of the hook tip is the foremost piercing execution area of ​​the hook tip, and this area is the piercing function area, which directly affects the piercing effect.

[0078] For example, the PVC injection hook molding debugging control system sets the region division boundary in the calibrated heat distribution data based on the structural design parameters of the PVC injection hook. Taking the midpoint of the connection end between the hook tip and the hook body as the starting point, the region extending to the hook tip piercing end to a preset length is the region corresponding to the top of the hook tip, and the remaining transition region between the hook tip and the hook body is the region corresponding to the root of the hook tip.

[0079] S370, calculate the first average temperature of the area corresponding to the root of the hook tip and the second average temperature of the area corresponding to the tip of the hook tip, respectively.

[0080] It can be understood that the first average temperature is the average temperature of all temperature sampling points in the area corresponding to the base of the hook tip, reflecting the overall temperature level of that area. The second average temperature is the average temperature of all temperature sampling points in the area corresponding to the tip of the hook tip, reflecting the overall temperature level of that area.

[0081] For example, the PVC injection hook molding debugging control system extracts all temperature sampling point data of the corresponding area at the root of the hook tip and the corresponding area at the top of the calibrated heat distribution data, and calculates the first average temperature and the second average temperature by taking the arithmetic mean.

[0082] S380, based on the difference between the first average temperature and the second average temperature, obtains the temperature gradient between the root and the top of the hook tip.

[0083] It can be understood that the temperature gradient between the root and the top of the hook tip is the absolute difference between the first average temperature of the area corresponding to the root of the hook tip and the second average temperature of the area corresponding to the top of the hook tip. It is used to quantify the temperature difference between the root and the top of the hook tip. The larger the difference, the more uneven the temperature distribution of the hook tip, and the more likely it is to crack due to thermal stress.

[0084] For example, the PVC injection hook molding debugging control system calculates the absolute difference between the first average temperature and the second average temperature. This absolute difference is the temperature gradient between the root and the top of the hook tip. This value directly reflects the uniformity of temperature distribution after the hook tip is cooled, providing core data for judging whether there is a risk of stress cracking in the hook tip.

[0085] By employing the above steps S350 to S380, through environmental temperature compensation calibration of thermal distribution data, key area division, and average temperature calculation, the temperature difference gradient between the root and top of the hook tip is accurately obtained. This solves the problem of the lack of specific detection of hook tip temperature distribution in existing technologies, and can promptly detect stress cracking hazards caused by uneven temperature distribution, effectively ensuring the structural stability of the hook tip.

[0086] In one possible implementation, S330, based on the contour line and key contour features, selects feature sampling points on the contour lines of the hook tip piercing end and the end where the hook tip connects to the hook body, and calculates the curvature values ​​of the feature sampling points, including:

[0087] S331, Perform preliminary sampling of the contour line according to the preset sampling interval to form a preliminary sampling point set of the contour line.

[0088] It is understandable that the preset sampling interval is the distance or angular interval between two adjacent sampling points, set according to the accuracy requirements of the hook tip profile. Discretization preliminary sampling is the process of converting the continuous hook tip profile into sampling of multiple discrete points. The preliminary sampling point set of the profile is a set of all discrete points on the profile line covering the hook tip piercing end and the connection end between the hook tip and the hook body, obtained through preliminary sampling, including valid sampling points and redundant sampling points.

[0089] For example, the PVC injection hook molding debugging control system collects data point by point on the contour line at preset distance or angle intervals, discretizing the continuous contour line into multiple preliminary sampling points. All preliminary sampling points together constitute the preliminary sampling point set of the contour line. The preset sampling interval is set to fully cover the contour details, reducing the problem of missing key parts.

[0090] S332. Based on the key contour features, the initial set of contour sampling points is filtered, retaining the contour inflection point of the hook tip piercing end, the sampling points of the transition section of the piercing blade edge, and the sampling points of the force transition section at the connection end between the hook tip and the hook body, while eliminating redundant sampling points caused by image interference, thus obtaining the set of feature sampling points.

[0091] It can be understood that the contour inflection point is the point where the bending direction of the hook tip contour changes. The puncture edge transition section sampling points are located at the puncture edge and its transition point with the hook body. The force-bearing transition section sampling points are the sampling points at the connection point between the hook tip and the hook body, the transition point used to transmit puncture force. Redundant sampling points are invalid sampling points generated due to slight image interference that do not reflect the key contour features of the hook tip. The feature sampling point set is the set of valid sampling points that, after filtering, accurately reflect the key contour features of the hook tip.

[0092] For example, the PVC injection hook molding debugging control system identifies the initial set of sampling points one by one based on the key contour features, determines whether each sampling point is located at the contour inflection point, the puncture edge transition section or the force transition section of the connection end, retains the valid sampling points that meet the conditions, and removes redundant sampling points that deviate from the main contour line due to image interference, and finally forms a set of feature sampling points that can accurately characterize the key contour of the hook tip.

[0093] S333 uses the midpoint between the hook tip and the hook body as the reference point to perform coordinate calibration on each feature sampling point in the feature sampling point set, and determines the precise coordinate value of each feature sampling point.

[0094] It is understandable that the midpoint between the hook point and the hook body is a reference point used for coordinate positioning, determined according to the hook point's structural design. Coordinate calibration involves comparing and correcting the original coordinates of the feature sampling points with the reference point coordinates to reduce minor offsets during the sampling process. Precise coordinate values ​​are the calibrated coordinate data that accurately reflect the actual position of the feature sampling points on the hook point's contour.

[0095] For example, the PVC injection hook molding debugging control system first determines the midpoint of the connection between the hook tip and the hook body on the outline as a reference point, and establishes a two-dimensional coordinate system (with the reference point as the origin, the horizontal direction pointing to the hook tip piercing end as the positive X-axis, and the vertical upward direction as the positive Y-axis). Then, it substitutes the original coordinates of each feature sampling point in the feature sampling point set into a preset calibration formula, and corrects it in combination with the reference point coordinates to reduce sampling deviation, finally obtaining the accurate coordinate value of each feature sampling point. For example, through the preset calibration formula: accurate coordinate value (X 精 Y 精 ) = Original coordinates (X) 原 Y 原 - Original coordinates of the reference point (X) 基 Y 基 This yields precise coordinate values, where the original coordinates of the reference point are the actual coordinates collected at the reference point during sampling.

[0096] S334. For each feature sampling point in the feature sampling point set, select the adjacent previous feature sampling point and the adjacent next feature sampling point on the contour line for each feature sampling point. Calculate the associated parameters based on the precise coordinate values ​​of each feature sampling point, the adjacent previous feature sampling point, and the adjacent next feature sampling point to obtain the curvature value of the feature sampling point.

[0097] It can be understood that "adjacent preceding feature sampling point" and "adjacent following feature sampling point" refer to the two most immediate preceding and following valid feature sampling points on the contour line for each feature sampling point. Associated parameters are intermediate parameters used to derive curvature values, calculated based on the precise coordinates of each feature sampling point, its adjacent preceding feature sampling point, and its adjacent following feature sampling point. These parameters include line segment length and vector angle.

[0098] For example, the PVC injection hook molding debugging control system finds the adjacent previous and adjacent next feature sampling points on the contour line for each feature sampling point in the feature sampling point set, extracts the precise coordinate values ​​of the three points, calculates the circumcircle radius of the triangle formed by the three points, and then calculates the curvature value of the feature sampling point according to the reciprocal relationship between curvature and circumcircle radius.

[0099] By adopting the above steps S331 to S334, through preliminary sampling, precise screening, coordinate calibration and curvature calculation of the contour line, the curvature value of the accurate feature sampling point is obtained, which solves the problems of inaccurate sampling point selection and large curvature calculation error in the existing technology. It provides reliable data support for the accurate calculation of the curvature change rate of the hook tip contour, and further ensures the detection accuracy of the hook tip piercing sharpness.

[0100] As an optional embodiment of this application, please refer to Figure 3 S400, based on the first feature deviation between the rate of change of curvature of the hook tip profile and the preset standard value of the rate of change of curvature, and the second feature deviation between the temperature gradient between the root and the tip of the hook tip and the preset standard value of the temperature gradient, a coupling relationship matrix between the first feature deviation and the second feature deviation is constructed, including:

[0101] S410, based on the puncture performance test data and stress cracking test data of PVC injection hooks, determine the puncture failure risk weight corresponding to the first characteristic deviation and the stress cracking failure risk weight corresponding to the second characteristic deviation.

[0102] It is understandable that puncture performance test data is quantitative data obtained from puncture tests on PVC injection hooks, including puncture force, puncture success rate, and puncture life, used to reflect the reliability of the hook tip's puncture function. Stress cracking test data is quantitative data obtained from stress loading tests on PVC injection hooks, including crack resistance and cracking time, used to reflect the stability of the hook tip structure. The puncture failure risk weight is a quantitative coefficient characterizing the degree of influence of the first characteristic deviation on puncture failure; a larger weight indicates a more significant impact of this deviation on puncture failure. The stress cracking failure risk weight is a quantitative coefficient characterizing the degree of influence of the second characteristic deviation on stress cracking failure; a larger weight indicates a more significant impact of this deviation on stress cracking failure.

[0103] For example, PVC injection hook samples with different first and second characteristic deviations were selected and subjected to puncture performance tests and stress cracking tests, respectively. The failure probability and failure loss under different deviation values ​​were statistically analyzed. Then, the impact of puncture failure risk and stress cracking failure risk was quantitatively evaluated using the analytic hierarchy process (AHP) to determine the puncture failure risk weight and stress cracking failure risk weight. Since puncture failure directly leads to the loss of product function, the puncture failure risk weight is higher than the stress cracking failure weight, so that the weight allocation fits the actual use needs of the product.

[0104] S420 is a molding quality standard based on PVC injection hooks, which divides the deviation level range of the first characteristic deviation and the deviation level range of the second characteristic deviation. The deviation level range includes the range of slight deviation, the range of moderate deviation, and the range of severe deviation.

[0105] It is understandable that the molding quality standard is a qualified standard for hook tip molding based on the application scenarios, industry specifications, and customer needs of PVC injection hooks. The deviation level range of the first characteristic deviation is divided into different ranges according to the absolute value of the first characteristic deviation, used to distinguish the severity of the deviation's impact on puncture performance. The deviation level range of the second characteristic deviation is divided into different ranges according to the absolute value of the second characteristic deviation, used to distinguish the severity of the deviation's impact on stress cracking risk. The slight deviation range is the range with small deviations and minimal impact on quality; the moderate deviation range is the range with moderate deviations and some impact on quality; and the severe deviation range is the range with large deviations and significant impact on quality.

[0106] For example, based on the molding quality standard of PVC injection hooks, a first threshold and a second threshold are set. The first threshold is less than the second threshold. The first characteristic deviation and the second characteristic deviation are divided into three intervals: the deviation absolute value is less than the first threshold, which is the slight deviation interval; the deviation between the first threshold and the second threshold is the moderate deviation interval; and the deviation greater than the second threshold is the severe deviation interval. The first threshold and the second threshold are determined through a large number of experiments to accurately distinguish the impact of different deviation degrees on quality.

[0107] S430, based on the risk weight of puncture failure and the risk weight of stress cracking failure, formulates deviation coupling association rules. The deviation coupling association rules are the comprehensive failure risk levels corresponding to the combination of the deviation level interval of the first characteristic deviation and the deviation level interval of the second characteristic deviation. The comprehensive failure risk levels include low risk level, medium risk level and high risk level.

[0108] It is understandable that the deviation coupling correlation rule is a rule that clarifies the correspondence between different combinations of first and second characteristic deviation levels and the comprehensive failure risk level. The comprehensive failure risk level is a comprehensive assessment of the hook tip forming quality risk level by combining the puncture failure risk weight, the stress cracking failure risk weight, and the deviation level ranges of the first and second characteristic deviations. A low risk level corresponds to a situation with minor quality hazards and no need for emergency treatment; a medium risk level corresponds to a situation with moderate quality hazards and the need for routine treatment; and a high risk level corresponds to a situation with significant quality hazards and the need for emergency treatment.

[0109] S440, based on the deviation coupling association rule, generates the coupling relationship matrix between the first feature deviation and the second feature deviation.

[0110] It can be understood that the coupling relationship matrix uses the deviation level range of the first characteristic deviation as rows and the deviation level range of the second characteristic deviation as columns. The matrix cells are filled with a two-dimensional data matrix of the corresponding comprehensive failure risk level, which is used to intuitively present the risk level corresponding to different deviation combinations and provide a clear basis for the allocation of control priorities.

[0111] For example, a 3×3 two-dimensional matrix is ​​constructed using the slight, moderate, and severe deviation ranges of the first characteristic deviation as the rows of the matrix and the slight, moderate, and severe deviation ranges of the second characteristic deviation as the columns of the matrix. Then, according to the deviation coupling association rules defined in S430, the comprehensive failure risk level corresponding to each deviation level combination is filled into the corresponding cell of the matrix, and finally a coupling relationship matrix that can intuitively query the risk level of the deviation combination is generated.

[0112] By adopting the above steps S410 to S440, determining the failure risk weight, dividing the deviation level interval, formulating coupling association rules and generating a coupling relationship matrix, a precise correlation between the first and second characteristic deviations and the comprehensive failure risk is established. This solves the problem that existing technologies only control single deviations and lack comprehensive risk assessment, and provides a scientific risk basis for hook tip special quality control.

[0113] In one possible implementation, S430, based on the puncture failure risk weight and the stress cracking failure risk weight, formulates a deviation coupling association rule, including:

[0114] S431, determine the key molding influencing parameters of PVC injection hooks during the molding process. The key molding influencing parameters include PVC raw material batch, molding temperature range, and holding pressure time range.

[0115] It is understandable that key molding influencing parameters refer to process parameters that significantly affect the first characteristic deviation, the second characteristic deviation, and the overall failure risk during PVC injection molding. PVC raw material batches refer to different production batches of PVC raw materials; the melt index, purity, and other material properties of different batches of PVC raw materials may vary, thus affecting molding quality. Molding temperature range refers to the temperature range of the barrel heating process, directly affecting the molten state of the PVC raw material. Holding pressure time range refers to the time range of the holding pressure process, affecting the molding accuracy after the PVC raw material cools and shrinks.

[0116] For example, through orthogonal experimental design, multiple potential influencing parameters in the PVC injection hook molding process (such as PVC raw material batch, molding temperature, holding time, cooling water flow rate, etc.) are selected. The first and second characteristic deviation data under different combinations of potential influencing parameters are tested respectively. Through variance analysis, parameters that have a significant impact on the deviation are screened out. Finally, the PVC raw material batch, molding temperature range, and holding time range are determined as key molding influencing parameters.

[0117] S432, based on key forming influence parameters, sets a working condition adaptation factor, which is used to correct the ratio of puncture failure risk weight to stress cracking failure risk weight.

[0118] It is understandable that the working condition adaptation factor is a quantitative coefficient set according to different combinations of key molding influence parameters (i.e. different molding working conditions). It is used to adjust the actual proportion of the puncture failure risk weight and the stress cracking failure risk weight under different working conditions, so that the risk assessment is more in line with the actual situation of the current molding working conditions.

[0119] For example, for different combinations of PVC raw material batches, molding temperature ranges, and holding time ranges, the actual probability of puncture failure and stress cracking failure under different conditions is statistically analyzed through experiments. Based on the ratio of the probability of puncture failure to the probability of stress cracking failure, a corresponding condition adaptation factor is set. The condition adaptation factor is a coefficient greater than 0 and less than 2. When the probability of puncture failure is higher under a certain condition, the condition adaptation factor is tilted towards the risk weight of puncture failure, and vice versa.

[0120] S433, based on the working condition adaptation factor, adjust the actual proportion of the puncture failure risk weight and the stress cracking failure risk weight to obtain the adjusted puncture failure risk weight and the adjusted stress cracking failure risk weight.

[0121] It is understandable that the adjusted puncture failure risk weight is calculated by combining the original puncture failure risk weight determined in S410 with the working condition adaptation factor, and is adapted to the current working condition. The adjusted stress cracking failure risk weight is calculated by combining the original stress cracking failure risk weight determined in S410 with the working condition adaptation factor, and is adapted to the current working condition. The sum of the proportions of the adjusted puncture failure risk weight and the adjusted stress cracking failure risk weight remains 1.

[0122] For example, a preset weight adjustment formula is used (e.g., adjusted puncture failure risk weight = original puncture failure risk weight × working condition adaptation factor; adjusted stress cracking failure risk weight = 1 - adjusted puncture failure risk weight). Based on the working condition adaptation factor corresponding to the current molding working condition, the original puncture failure risk weight and stress cracking failure risk weight are adjusted to obtain the adjusted puncture failure risk weight and adjusted stress cracking failure risk weight adapted to the current working condition, so that the weight ratio can accurately reflect the actual impact of the two types of failure risks under the current working condition.

[0123] S434, based on the adjusted puncture failure risk weight and the adjusted stress cracking failure risk weight, combined with the deviation level range of the first characteristic deviation and the deviation level range of the second characteristic deviation, formulates the deviation coupling association rule for each working condition. The deviation coupling association rule for each working condition corresponds to the comprehensive failure risk level under different combinations of key forming influence parameters.

[0124] It is understandable that the deviation coupling correlation rule for different working conditions is a rule that corresponds the deviation level combination and the comprehensive failure risk level for different combinations of key forming influence parameters (different working conditions). Each working condition corresponds to a set of exclusive rules, making risk assessment more accurate.

[0125] By adopting the above steps S431 to S434, by determining key molding influencing parameters, setting working condition adaptation factors, adjusting risk weights, and formulating working condition association rules, the problem that the fixed rules of the existing technology are not suitable for different molding working conditions is solved, so that the hook tip quality risk assessment can accurately match the actual molding working conditions.

[0126] In one possible implementation, S434, based on the adjusted puncture failure risk weight and the adjusted stress cracking failure risk weight, and combining the deviation level range of the first characteristic deviation and the deviation level range of the second characteristic deviation, formulates deviation coupling association rules for different working conditions, including:

[0127] S4341, calculate the interaction coefficients among the key forming influence parameters. The interaction coefficients are used to characterize the degree of linkage influence of different combinations of key forming influence parameters on the failure sensitivity of the first characteristic deviation and the second characteristic deviation.

[0128] The interaction coefficient is understood to quantify the interaction between different key molding influencing parameters and their synergistic impact on the first and second characteristic deviations and failure sensitivity. Failure sensitivity refers to the sensitivity of the first and second characteristic deviations to changes in key molding influencing parameters. The degree of synergistic impact is the comprehensive influence on failure risk when multiple key molding influencing parameters act together; a larger absolute value of the interaction coefficient indicates a more significant synergistic impact among the key molding influencing parameters.

[0129] For example, the response surface methodology is used to statistically analyze the first and second characteristic deviation data under different combinations of key forming influence parameters, and a multiple regression model of deviation and parameter combination is established. The coefficient of the interaction term of each parameter in the multiple regression model is the interaction coefficient between parameters. The interaction coefficient is used to quantify the degree of linkage influence of different combinations of key forming influence parameters on the sensitivity of deviation failure.

[0130] S4342, based on the interaction coefficient and the adjusted puncture failure risk weight and the adjusted stress cracking failure risk weight, corrects the deviation combination threshold corresponding to each comprehensive failure risk level, and obtains the corrected deviation combination threshold.

[0131] It is understandable that the deviation combination threshold is the critical score value for judging the comprehensive failure risk level corresponding to the deviation level combination. The corrected deviation combination threshold is a critical value adjusted by combining the interaction coefficient, the adjusted puncture failure risk weight, and the adjusted stress cracking failure risk weight, which can more accurately reflect the critical state of failure risk under parameter linkage.

[0132] For example, the interaction coefficients calculated by S4341 and the adjusted weights are substituted into a preset threshold correction formula to adjust the deviation combination thresholds corresponding to the original comprehensive failure risk levels. When the interaction coefficients between key forming influence parameters are large, the deviation combination thresholds are appropriately adjusted to adapt to the changes in failure risk brought about by the linkage of key forming influence parameters, so that the corrected deviation combination thresholds can accurately distinguish different risk levels. For example, the preset threshold correction formula is: Corrected deviation combination threshold = Original deviation combination threshold × [1 + Interaction coefficient × (Adjusted puncture failure risk weight × First characteristic deviation level coefficient + Adjusted stress cracking failure risk weight × Second characteristic deviation level coefficient)], where the original deviation combination threshold is the initial critical score corresponding to a specific deviation level combination (such as slight first characteristic deviation + moderate second characteristic deviation); the first / second characteristic deviation level coefficients are quantitative values ​​set according to the deviation level (slight = 1, moderate = 2, severe = 3), used to distinguish the degree of influence of different deviation levels.

[0133] S4343, for different combinations of key forming influence parameters, combined with the corrected deviation combination threshold, refine the deviation coupling association rules for each working condition, obtain the refined deviation coupling association rules for each working condition, and clarify the comprehensive failure risk level corresponding to the combination of the deviation level range of the first characteristic deviation and the deviation level range of the second characteristic deviation under each type of key forming influence parameter combination.

[0134] For example, for each combination of key forming influence parameters (each working condition), the comprehensive risk score of different combinations of first and second characteristic deviation levels is recalculated using the corrected deviation combination threshold as the judgment standard. Based on the correspondence between the comprehensive risk score and the corrected deviation combination threshold, the comprehensive failure risk level corresponding to the key forming influence parameter combination is clarified, and the critical conditions in the deviation coupling association rules of the sub-working conditions are refined, so that the deviation coupling association rules of the sub-working conditions are more in line with the actual failure risk law under the linkage of key forming influence parameters.

[0135] S4344 performs a feasibility check on the deviation coupling association rules of the refined sub-working conditions, eliminates the deviation coupling association rules of the refined sub-working conditions that do not conform to the actual molding failure law of PVC injection hooks, and obtains the final deviation coupling association rules of the sub-working conditions.

[0136] It is understandable that feasibility verification is the process of verifying the accuracy of rules through experiments or actual production data. Actual molding failure patterns are the true correspondence between deviation combinations and failure scenarios exhibited by PVC injection hooks during the actual molding process. The final deviation coupling correlation rules for each working condition are verified rules that are consistent with the actual failure patterns and possess feasibility.

[0137] For example, PVC injection hook samples with different combinations of key molding influencing parameters are selected, and the comprehensive failure risk level corresponding to each deviation combination is predicted according to the refined deviation coupling association rules for each working condition. At the same time, actual molding failure tests are conducted on these PVC injection hook samples, and the actual failure situation is recorded. The prediction results are compared with the actual test results, and the refined deviation coupling association rules for each working condition that exceed the allowable range are eliminated. The refined deviation coupling association rules for each working condition that are consistent with the actual failure law are retained to obtain the final deviation coupling association rules for each working condition.

[0138] By adopting the above steps S4341 to S4344, calculating parameter interaction coefficients, correcting deviation combination thresholds, refining rules, and conducting feasibility verification, the problems of existing technical rules not considering the influence of parameter interaction and insufficient feasibility are solved. This makes the deviation coupling association rules for different working conditions more accurate and more in line with the actual forming situation, providing a more reliable risk judgment basis for hook tip special quality control under different working conditions.

[0139] As an optional embodiment of this application, please refer to Figure 4 S500 dynamically allocates control priorities based on the coupling relationship matrix, controlling the corresponding operating parameter data in the operating parameter data, including:

[0140] S510, Division steps: Based on the comprehensive failure risk level in the coupling relationship matrix, divide the control priority intervals corresponding to the control priorities. The control priority intervals include emergency control intervals, regular control intervals, and observation and standby intervals. The emergency control interval corresponds to the high risk level, the regular control interval corresponds to the medium risk level, and the observation and standby interval corresponds to the low risk level.

[0141] It is understandable that the control priority range is divided according to the comprehensive failure risk level, corresponding to different levels of urgency for adjustment. The emergency control range corresponds to the high-risk level and requires immediate parameter adjustment; the routine control range corresponds to the medium-risk level and requires parameter adjustment according to the routine procedure; and the observation and standby range corresponds to the low-risk level and requires no adjustment but only monitoring.

[0142] For example, the PVC injection hook molding debugging control system establishes a unique correspondence between high-risk levels and emergency control intervals in the coupling relationship matrix, a unique correspondence between medium-risk levels and regular control intervals, and a unique correspondence between low-risk levels and observation / standby intervals. This clarifies the urgency of parameter adjustments corresponding to different risk levels, completes the division of control priority intervals, and ensures precise matching between priorities and risk levels.

[0143] S520, Grouping steps: Group the running parameter data to obtain the curvature-related parameter group and the temperature difference-related parameter group. The curvature-related parameter group includes barrel temperature data and injection pressure data, while the temperature difference-related parameter group includes holding time data and mold cooling water flow rate data.

[0144] It can be understood that the curvature-related parameter set is a combination of operating parameters that directly affects the rate of change of the curvature of the hook tip profile (the first characteristic deviation) and can effectively correct the first characteristic deviation after adjustment. The temperature difference-related parameter set is a combination of operating parameters that directly affects the temperature difference gradient between the root and tip of the hook tip (the second characteristic deviation) and can effectively correct the second characteristic deviation after adjustment.

[0145] For example, the PVC injection hook molding debugging control system clarifies the correlation between operating parameter data and deviations based on the molding process principle and test data: the barrel temperature and injection pressure directly affect the melting state of PVC raw materials and the cavity filling effect, which in turn affect the rate of change of hook tip contour curvature, so they are classified into the curvature-related parameter group; the holding time and mold cooling water flow rate directly affect the cooling and shrinkage process of PVC raw materials, which in turn affect the hook tip temperature distribution and temperature gradient, so they are classified into the temperature difference-related parameter group, thus completing the grouping.

[0146] S530, Control steps: According to the control priority range, prioritize synchronous control of the curvature-related parameter group or temperature difference-related parameter group corresponding to the emergency control range, then synchronously control the curvature-related parameter group or temperature difference-related parameter group corresponding to the normal control range, and maintain the current operating status of the curvature-related parameter group or temperature difference-related parameter group corresponding to the observation standby range.

[0147] Synchronous control can be understood as simultaneously coordinating the adjustment of all parameters within the same parameter group to ensure that the adjustment directions of each parameter are consistent and the effects are synergistic. Maintaining the current operating state means temporarily not adjusting the parameters, but only continuously monitoring the changes in the deviations of the first and second characteristics.

[0148] For example, the PVC injection hook molding debugging control system queries the coupling relationship matrix based on the current deviation combination to obtain the corresponding control priority range. If it is an emergency control range, it immediately issues a synchronous control command to the parameter group (curvature-related parameter group or temperature difference-related parameter group) corresponding to the emergency control range to coordinate and adjust the parameters in the parameter group. If it is a normal control range, it synchronously controls the corresponding parameter group in an orderly manner according to the preset process. If it is an observation standby range, it does not adjust the corresponding parameter group, but only continuously receives the deviation monitoring data from the online detection unit.

[0149] S540, Retesting Steps: After completing one round of regulation, retest the first characteristic deviation and the second characteristic deviation to obtain retested deviation data. Based on the retested deviation data, query the coupling relationship matrix and calibrate the regulation priority range. If the retested deviation data is still within the deviation range corresponding to the original regulation priority range, repeat the synchronous regulation action of the regulation steps until the retested deviation data falls into the deviation range corresponding to the observation standby range, and then stop regulation.

[0150] It can be understood that one round of regulation refers to the complete process of adjusting parameters according to the requirements of S530. Retesting refers to re-collecting molding state data through the online detection unit and recalculating the deviations of the first and second characteristics. The retested deviation data is the latest deviation data obtained after the retest. The calibration of the regulation priority interval is determined by re-querying the coupling relationship matrix based on the retested deviation data to establish a new regulation priority interval. The original regulation priority interval is the regulation priority interval before this round of regulation. The deviation range corresponding to the observation standby interval refers to the deviation range where both the first and second characteristic deviations are within the slight deviation range, corresponding to a low-risk level.

[0151] For example, after completing one round of parameter adjustment, the PVC injection hook molding debugging control system triggers the online detection unit to re-acquire the molding image and heat distribution data of the hook tip, recalculate the re-measured first characteristic deviation and re-measured second characteristic deviation, i.e., the re-measured deviation data, and query the coupling relationship matrix based on the re-measured deviation data to determine a new control priority range; if the new control priority range is still the original control priority range, the synchronous control action of S530 is repeated; if the new control priority range is the observation standby range, or the re-measured deviation data falls into the deviation range corresponding to the observation standby range, the control is stopped.

[0152] By adopting the above steps S510 to S540, through dividing the control priority range, grouping the operating parameter data, synchronously controlling according to priority, and conducting closed-loop retesting, precise and dynamic control based on risk level is achieved. This solves the problems of fixed control priority, lack of targeting, and closed-loop correction in existing technologies, and effectively improves the sharpness, puncture strength, and structural stability of the hook tip.

[0153] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0154] Corresponding to the PVC injection hook molding debugging and control method described in the above embodiments, this application also provides a PVC injection hook molding debugging and control system. Each module of this device can realize each step of the PVC injection hook molding debugging and control method. Figure 5 The diagram shows a structural block diagram of the PVC injection hook molding debugging control system provided in the embodiment of this application. For ease of explanation, only the parts related to the embodiment of this application are shown.

[0155] Reference Figure 5 The system includes:

[0156] The first acquisition unit is used to acquire the operating parameter data of the PVC injection hook molding device in real time during the PVC injection hook molding process; wherein, the operating parameter data includes barrel temperature data, injection pressure data, holding time data and mold cooling water flow rate data;

[0157] The second acquisition unit is used to acquire molding state data after the PVC injection hook is peeled off from the mold cavity;

[0158] The unit is used to obtain the rate of change of hook tip profile curvature and the temperature gradient between the root and the tip of the hook tip based on the molding state data.

[0159] The construction unit is used to construct a coupling relationship matrix between the first feature deviation and the second feature deviation based on the first feature deviation between the curve change rate of the hook tip profile and the preset standard value of the curve change rate, and the second feature deviation between the temperature difference gradient between the root and the top of the hook tip and the preset standard value of the temperature difference gradient.

[0160] The control unit is used to dynamically allocate control priorities based on the coupling relationship matrix and control the corresponding operating parameter data in the operating parameter data; wherein the corresponding operating parameter data is at least one of the following: barrel temperature data, injection pressure data, holding time data, and mold cooling water flow rate data.

[0161] It should be noted that the information interaction and execution process between the above systems / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0162] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0163] This application also provides a PVC injection hook molding device. Figure 6 This is a schematic diagram of the structure of a PVC injection hook molding device provided in one embodiment of this application. Figure 6 As shown, the PVC injection hook molding apparatus 6 of this embodiment includes: at least one processor 60 ( Figure 6 Only one is shown in the image), at least one memory 61 ( Figure 6 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the PVC injection hook molding device 6 to perform the steps in any of the above-described PVC injection hook molding debugging and control method embodiments, or causes the PVC injection hook molding device 6 to perform the functions of each module / unit in the above-described device embodiments.

[0164] Exemplarily, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 62 in the PVC injection hook molding apparatus 6.

[0165] The PVC injection hook molding device 6 may include an injection molding unit, a precision mold unit, an online detection unit, a parameter control and execution unit, and a PVC injection hook molding debugging and control system. The PVC injection hook molding debugging and control system of this PVC injection hook molding device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 6 This is merely an example of the PVC injection hook molding device 6 and does not constitute a limitation on the PVC injection hook molding device 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0166] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0167] In some embodiments, the memory 61 may be an internal storage unit of the PVC injection molding device 6, such as a hard disk or memory of the PVC injection molding device 6. In other embodiments, the memory 61 may be an external storage device of the PVC injection molding device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the PVC injection molding device 6. Further, the memory 61 may include both internal storage units and external storage devices of the PVC injection molding device 6. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0168] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0169] This application provides a computer program product that, when run on a PVC injection hook molding device, causes the PVC injection hook molding device to perform the steps in any of the above-described method embodiments.

[0170] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to the PVC injection hook molding debugging control system / PVC injection hook molding device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, such as a USB flash drive, a portable hard drive, a magnetic disk, or an optical disk.

[0171] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0172] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0173] In the embodiments provided in this application, it should be understood that the disclosed PVC injection hook molding debugging control system / PVC injection hook molding device and method can be implemented in other ways. For example, the embodiments of the PVC injection hook molding debugging control system / PVC injection hook molding device described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0174] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0175] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for debugging and controlling PVC injection hook molding, characterized in that, The method, applied to a PVC injection hook molding apparatus, includes: During the PVC injection hook molding process, the operating parameter data of the PVC injection hook molding device are acquired in real time; wherein, the operating parameter data includes barrel temperature data, injection pressure data, holding time data, and mold cooling water flow rate data; Obtain molding state data of the PVC injection hook after it is peeled from the mold cavity; the molding state data includes molding image and heat distribution data of the hook tip, and the molding image covers the complete outline of the hook tip piercing end and the hook tip connecting to the hook body; Based on the molding state data, the change rate of the hook tip profile curvature and the temperature gradient between the root and the top of the hook tip are obtained. Based on the first characteristic deviation between the curve change rate of the hook tip profile and the preset standard value of the curve change rate, and the second characteristic deviation between the temperature difference gradient between the root and the top of the hook tip and the preset standard value of the temperature difference gradient, a coupling relationship matrix between the first characteristic deviation and the second characteristic deviation is constructed. Based on the coupling relationship matrix, the control priority is dynamically allocated to control the corresponding operating parameter data in the operating parameter data; wherein, the corresponding operating parameter data is at least one of the barrel temperature data, the injection pressure data, the holding time data, and the mold cooling water flow rate data; The process of constructing a coupling matrix between the first feature deviation and the second feature deviation based on the first feature deviation of the hook tip contour curvature change rate and a preset standard value of curvature change rate, and the second feature deviation of the temperature difference gradient between the hook tip root and tip and a preset standard value of temperature difference gradient, includes: Based on the puncture performance test data and stress cracking test data of the PVC injection hook, determine the puncture failure risk weight corresponding to the first characteristic deviation and the stress cracking failure risk weight corresponding to the second characteristic deviation. Based on the molding quality standard of the PVC injection hook, the deviation level range of the first characteristic deviation and the deviation level range of the second characteristic deviation are respectively divided. The deviation level range includes a slight deviation range, a moderate deviation range, and a severe deviation range. Based on the puncture failure risk weight and the stress cracking failure risk weight, a deviation coupling association rule is formulated. The deviation coupling association rule is the comprehensive failure risk level corresponding to the combination of the deviation level range of the first characteristic deviation and the deviation level range of the second characteristic deviation. The comprehensive failure risk level includes low risk level, medium risk level and high risk level. Based on the aforementioned deviation coupling association rule, a coupling relationship matrix between the first feature deviation and the second feature deviation is generated.

2. The PVC injection hook molding debugging and control method as described in claim 1, characterized in that, Based on the molding state data, the rate of change of the hook tip profile curvature of the PVC injection hook is obtained, including: The denoised image is then processed to remove the interference of residual impurities from the injection molding on the complete contour, resulting in a denoised denoised image. After preprocessing the denoised image, the outline of the hook tip is extracted, and the key outline features that affect the sharpness of the hook tip piercing end are retained. Based on the outline and the key outline features, feature sampling points are selected on the outline of the hook tip piercing end and the hook tip connecting to the hook body, and the curvature value of the feature sampling points is calculated. The rate of change of curvature of the hook tip profile is obtained based on the fluctuation range of the curvature value.

3. The PVC injection hook molding debugging and control method as described in claim 2, characterized in that, Based on the molding state data, the temperature gradient between the hook tip root and the top of the PVC injection hook is obtained, including: After performing environmental temperature compensation calibration on the thermal distribution data to reduce the interference of environmental temperature on the thermal distribution detection results of the hook tip, calibrated thermal distribution data is obtained. Based on the calibrated heat distribution data, the area corresponding to the root of the hook tip and the area corresponding to the top of the hook tip are divided. The area corresponding to the root of the hook tip is the force transition area at the connection end between the hook tip and the hook body, and the area corresponding to the top of the hook tip is the puncture function area of ​​the puncture end of the hook tip. Calculate the first average temperature of the region corresponding to the root of the hook tip and the second average temperature of the region corresponding to the tip of the hook tip, respectively. The temperature gradient between the root and the top of the hook tip is obtained based on the difference between the first average temperature and the second average temperature.

4. The PVC injection hook molding debugging and control method as described in claim 2, characterized in that, The step of selecting feature sampling points on the contour lines of the hook tip piercing end and the hook tip-body connection end based on the contour lines and the key contour features, and calculating the curvature values ​​of the feature sampling points, includes: The contour line is initially sampled by discretization at a preset sampling interval to form a set of initial sampling points for the contour line. Based on the key contour features, the preliminary set of contour sampling points is filtered, retaining the contour inflection point of the hook tip piercing end, the sampling points of the transition section of the piercing blade edge, and the sampling points of the force transition section of the connection end between the hook tip and the hook body, while removing redundant sampling points caused by image interference, to obtain the feature sampling point set. Using the midpoint of the connection between the hook tip and the hook body as a reference point, coordinate calibration is performed on each feature sampling point in the feature sampling point set to determine the precise coordinate value of each feature sampling point; For each feature sampling point in the set of feature sampling points, select the adjacent preceding feature sampling point and the adjacent following feature sampling point on the contour line. Calculate the associated parameters based on the precise coordinate values ​​of each feature sampling point, the adjacent preceding feature sampling point, and the adjacent following feature sampling point to obtain the curvature value of the feature sampling point.

5. The PVC injection hook molding debugging and control method as described in claim 1, characterized in that, The step of formulating deviation coupling association rules based on the puncture failure risk weight and the stress cracking failure risk weight includes: The key molding influencing parameters of the PVC injection hook during the molding process are determined. The key molding influencing parameters include PVC raw material batch, molding temperature range, and holding pressure time range. Based on the key forming influence parameters, a working condition adaptation factor is set, which is used to correct the ratio of the puncture failure risk weight to the stress cracking failure risk weight. Based on the working condition adaptation factor, the actual proportion of the puncture failure risk weight and the stress cracking failure risk weight is adjusted to obtain the adjusted puncture failure risk weight and the adjusted stress cracking failure risk weight. Based on the adjusted puncture failure risk weight and the adjusted stress cracking failure risk weight, and combined with the deviation level range of the first characteristic deviation and the deviation level range of the second characteristic deviation, deviation coupling association rules for different working conditions are formulated. The deviation coupling association rules for different working conditions correspond to the comprehensive failure risk level under different combinations of key forming influence parameters.

6. The PVC injection hook molding debugging and control method as described in claim 5, characterized in that, Based on the adjusted puncture failure risk weight and the adjusted stress cracking failure risk weight, and combining the deviation level range of the first characteristic deviation and the deviation level range of the second characteristic deviation, deviation coupling association rules for different working conditions are formulated, including: Calculate the interaction coefficients among the key molding influence parameters. The interaction coefficients are used to characterize the degree of linkage influence of different combinations of key molding influence parameters on the failure sensitivity of the first feature deviation and the second feature deviation. Based on the interaction coefficient, the adjusted puncture failure risk weight, and the adjusted stress cracking failure risk weight, the deviation combination threshold corresponding to each of the comprehensive failure risk levels is corrected to obtain the corrected deviation combination threshold. For different combinations of key forming influence parameters, and in conjunction with the corrected deviation combination threshold, the deviation coupling association rules for the sub-working conditions are refined to obtain the refined deviation coupling association rules for the sub-working conditions. The comprehensive failure risk level corresponding to the combination of the deviation level range of the first characteristic deviation and the deviation level range of the second characteristic deviation under each type of key forming influence parameter combination is clarified. The feasibility of the refined deviation coupling association rules for each working condition is verified, and the refined deviation coupling association rules for each working condition that do not conform to the actual molding failure law of the PVC injection hook are eliminated to obtain the final deviation coupling association rules for each working condition.

7. The PVC injection hook molding debugging and control method as described in claim 1, characterized in that, The dynamic allocation of control priorities based on the coupling relationship matrix, and the control of the corresponding operating parameter data in the operating parameter data, includes: Division steps: Based on the comprehensive failure risk level in the coupling relationship matrix, the control priority interval corresponding to the control priority is divided. The control priority interval includes an emergency control interval, a regular control interval, and an observation and standby interval. The emergency control interval corresponds to the high risk level, the regular control interval corresponds to the medium risk level, and the observation and standby interval corresponds to the low risk level. Grouping steps: The operating parameter data are grouped to obtain the curvature-related parameter group and the temperature difference-related parameter group. The curvature-related parameter group includes the barrel temperature data and the injection pressure data. The temperature difference-related parameter group includes the holding time data and the mold cooling water flow rate data. Control steps: According to the control priority range, the curvature-related parameter group or the temperature difference-related parameter group corresponding to the emergency control range is controlled synchronously first, and then the curvature-related parameter group or the temperature difference-related parameter group corresponding to the normal control range is controlled synchronously. The curvature-related parameter group or the temperature difference-related parameter group corresponding to the observation standby range is kept in its current operating state. Retesting steps: After completing one round of adjustment, retest the first feature deviation and the second feature deviation to obtain retested deviation data. Based on the retested deviation data, query the coupling relationship matrix and calibrate the adjustment priority interval. If the retested deviation data is still within the deviation range corresponding to the original adjustment priority interval, repeat the synchronous adjustment action of the adjustment steps until the retested deviation data falls into the deviation range corresponding to the observation standby interval, and then stop the adjustment.

8. A PVC injection hook molding debugging and control system, characterized in that, An application to a PVC injection hook molding apparatus, used to implement the PVC injection hook molding debugging and control method as described in any one of claims 1 to 7, wherein the PVC injection hook molding debugging and control system comprises: The first acquisition unit is used to acquire the operating parameter data of the PVC injection hook molding device in real time during the PVC injection hook molding process; wherein, the operating parameter data includes barrel temperature data, injection pressure data, holding time data, and mold cooling water flow rate data; The second acquisition unit is used to acquire molding state data after the PVC injection hook is peeled off from the mold cavity; The unit is used to obtain, based on the molding state data, the hook tip profile curvature change rate and the temperature gradient between the hook tip root and the top of the PVC injection hook. The construction unit is used to construct a coupling relationship matrix between the first feature deviation and the second feature deviation based on the first feature deviation between the curve change rate of the hook tip profile and the preset standard value of the curve change rate, and the second feature deviation between the temperature difference gradient between the root and the top of the hook tip and the preset standard value of the temperature difference gradient. The control unit is used to dynamically allocate control priorities based on the coupling relationship matrix and control the corresponding operating parameter data in the operating parameter data; wherein, the corresponding operating parameter data is at least one of the barrel temperature data, the injection pressure data, the holding time data, and the mold cooling water flow rate data.

9. A PVC injection hook molding device, characterized in that, The system includes a PVC injection hook molding debugging control system, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method as described in any one of claims 1 to 7.

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