Intelligent thickness adjustment method for zinc oxide varistor wet extrusion film punch forming

Abstract

The application relates to the technical field of resistor manufacturing, and discloses an intelligent adjustment method for the thickness of a zinc oxide voltage-dependent resistor wet extrusion film stamping forming, which comprises the following steps: firstly, shear rate and stress data are collected, and rheological parameters of slurry are obtained by fitting based on a power-law fluid model; secondly, a pumping slip compensation model is constructed in combination with a target wet film thickness and real-time back pressure, a corrected metering pump command rotating speed is calculated in real time, and non-linear slip flow in the pump caused by the shear thinning characteristics of the slurry is actively compensated; then, the metering pump is driven to run at the corrected metering pump command rotating speed, and the extruded wet film is stamped into a green body; and finally, the actual thickness of the green body is detected, quality is determined in combination with a dynamic error threshold, and unqualified products are removed. The application eliminates flow errors caused by non-Newtonian fluid characteristics by constructing a pumping slip compensation model, and improves the consistency of the green body thickness of the voltage-dependent resistor under different production speeds and the reliability of resistor manufacturing.

Description

Technical Field

[0001] This invention relates to the field of resistor manufacturing technology, specifically to an intelligent method for adjusting the thickness of zinc oxide varistors during wet extrusion stamping. Background Technology

[0002] Zinc oxide varistors, as a typical voltage-limiting protection device, are widely used for overvoltage protection in power systems, consumer electronics, and automotive electronics. Their core manufacturing process involves mixing zinc oxide powder with other metal oxide additives, followed by molding and sintering to create a ceramic chip. With the miniaturization and lower voltage trends in electronic devices, the demand for medium- and low-voltage (thin-film) varistors is increasing daily.

[0003] While dry powder pressing is a mature traditional manufacturing process, it is prone to defects such as uneven density and delamination when preparing large-area, ultra-thin green films, and its production efficiency is relatively low. To address these issues, a novel wet extrusion stamping process has emerged. This process prepares zinc oxide powder into a slurry with a certain degree of fluidity, which is then extruded through a precision metering pump to form a wet film at the die, followed by stamping. This process offers significant advantages such as high production efficiency, good film density, and suitability for thin-film production. However, current wet extrusion stamping control typically assumes a linear relationship between the metering pump speed and output flow rate, simply increasing the pump speed linearly to improve production efficiency. However, this control strategy often fails to guarantee the uniformity and stability of the wet film thickness in practical applications because it ignores the rheological properties of the slurry. Specifically: Zinc oxide slurry is a typical high-solids suspension, exhibiting significant non-Newtonian fluid characteristics and shear-thinning properties, meaning its apparent viscosity decreases sharply with increasing shear rate. Wet extruders are typically equipped with precision gear metering pumps for feeding. Although gear pumps are theoretically positive displacement pumps with a linear relationship between flow rate and rotational speed, under high pressure differentials, slip flow (i.e., internal leakage) inevitably exists at the gear gaps within the pump. Therefore, in actual production, when the extrusion speed is increased to improve output, the metering pump speed increases, leading to a higher shear rate within the pump and at the die. According to the shear-thinning characteristic, the slurry viscosity decreases non-linearly at this point. This decrease in viscosity reduces resistance at the pump gaps, resulting in a non-linear increase in slip flow. If the control system only increases the speed according to a linear relationship between rotational speed and flow rate, the actual effective flow rate extruded from the die will be lower than expected (because some slurry leaks internally within the pump), resulting in a thinner wet film thickness. This directly leads to larger dimensional deviations in the final sintered resistor, reducing the precision of resistor manufacturing. Therefore, there is an urgent need for an intelligent adjustment method for the thickness of zinc oxide varistors in wet extrusion stamping that can combine non-Newtonian fluid rheological models to provide real-time intelligent compensation for pumping slip. Summary of the Invention

[0004] To address the problems in related technologies, this invention provides an intelligent method for adjusting the thickness of wet extrusion stamping of zinc oxide varistors, thereby overcoming the aforementioned technical problems in existing related technologies.

[0005] To solve the aforementioned technical problem, the present invention is achieved through the following technical solution: In a first aspect, embodiments of the present invention provide an intelligent adjustment method for the thickness of wet extrusion forming of zinc oxide varistor, specifically including: collecting shear rate and shear stress data, and fitting the rheological parameters of zinc oxide slurry based on a power-law fluid model; based on the rheological parameters, the set target wet film thickness, the real-time back pressure, and the conveyor belt running linear speed, combined with the flow characteristics of non-Newtonian fluid in the pump and the die, establishing a pumping slip compensation model including slip flow compensation, and calculating the corrected metering pump command speed; driving the metering pump to run at the corrected metering pump command speed, forming the extruded wet film into a varistor preform, and detecting the actual thickness of the varistor preform; calculating the thickness error based on the actual thickness of the varistor preform and the target thickness, and determining the quality of the varistor preform based on a dynamic error threshold, and rejecting unqualified products.

[0006] As a preferred embodiment of the intelligent adjustment method for the thickness of the zinc oxide varistor wet extrusion stamping process described in this invention, the rheological parameters include the flow behavior index. and consistency coefficient Its expression is: ; in, For the target wet film thickness, The coating width of the die head. The linear speed of the conveyor belt. This represents the theoretical displacement per revolution of the metering pump. For die head clearance, The geometric shear factor of the die head. The geometric slip coefficient of the pump body. This is back pressure.

[0007] As a preferred embodiment of the intelligent adjustment method for the thickness of the zinc oxide varistor wet extrusion stamping process described in this invention, the calculation formula for the die geometric shear factor is as follows: ,in This is a liquidity behavior index.

[0008] As a preferred embodiment of the intelligent adjustment method for the thickness of the zinc oxide varistor wet extrusion stamping process described in this invention, the method for obtaining the pump body geometric slip coefficient is as follows: controlling the metering pump at a constant test speed. Run the program and wait for the flow to stabilize before proceeding within the calibration time window. Inside, continuous collection Each mold head back pressure data point (in ), calculate the average actual volumetric flow rate within the time window and effective pressure driving factors Based on the average slip within the time window Reverse calibration is performed by combining rheological parameters and die geometry parameters. In a preferred embodiment of the intelligent adjustment method for the thickness of wet extrusion stamping of zinc oxide varistors according to the present invention, the determination of the green body quality includes: setting a target thickness. Based on the measured actual thickness of the varistor preform Calculate the thickness error of the resistive preform. Set error threshold and thickness error With error threshold Compare; if The product is deemed qualified; if Products are deemed unqualified and removed from the scrap area.

[0009] As a preferred embodiment of the intelligent adjustment method for the thickness of the zinc oxide varistor wet extrusion stamping process described in this invention, the error threshold is... based on Principles are dynamically set: Collect the most recent data. Measured thickness of a qualified embryo sample Calculate the average thickness and thickness standard deviation The error threshold is calculated. .

[0010] Secondly, embodiments of the present invention provide an intelligent adjustment system for the thickness of wet extrusion stamping of zinc oxide varistors, comprising: a rheological characteristic calibration module, used to control the metering pump to perform variable speed testing during the production preparation stage, and to obtain the rheological parameters of the slurry based on the collected data; a slip compensation calculation module, used to receive the target wet film thickness and real-time back pressure signal, combine with the rheological parameters, construct a pumping slip compensation model, and calculate the corrected metering pump command speed in real time; a drive control module, used to receive the command speed and control the operation of the precision metering pump, as well as control the conveyor belt speed and the stamping mechanism action; and a quality monitoring and feedback module, used to collect the green film thickness through an online thickness gauge, combine with an error threshold to determine the quality of the varistor green film, and output a qualified signal or a rejection instruction according to the determination result.

[0011] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the intelligent adjustment method for the thickness of wet extrusion stamping of zinc oxide varistors as described in the first aspect of the present invention.

[0012] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the intelligent adjustment method for the thickness of wet extrusion stamping of zinc oxide varistors as described in the first aspect of the present invention.

[0013] The present invention has the following beneficial effects: 1. This invention constructs a pump slip compensation model that incorporates production conditions and nonlinear compensation. This model can calculate and quantify the slip flow rate caused by increased extrusion speed and decreased viscosity in real time. Based on the calculation results, it automatically increases the commanded rotational speed of the metering pump to physically compensate for flow losses within the pump. This control method eliminates the implicit errors caused by non-Newtonian fluid characteristics, ensuring that the effective flow rate extruded from the die remains stable at different production speeds, thereby guaranteeing the consistency of the varistor preform thickness.

[0014] 2. This invention collects thickness data from historical qualified samples and calculates the standard deviation, based on... The principle is to dynamically generate error judgment thresholds. This mechanism can automatically adapt to minor normal fluctuations in the production process, identify and reject genuine sudden abnormal products. Compared with the traditional fixed threshold method, this strategy can prevent qualified products from being mistakenly judged as defective products, and ensure that the green blanks entering the sintering process meet strict geometric requirements, which helps to improve the reliability of varistor manufacturing.

[0015] 3. Before formal production, this invention employs a multi-stage variable shear rate test and utilizes a power-law fluid model to fit and calibrate the flow behavior index and consistency coefficient of the slurry. This process not only obtains key physical parameters characterizing the shear thinning degree of the slurry (flow behavior index and consistency coefficient), providing a physical benchmark for constructing a pumping slip compensation model, but also helps eliminate uncertainties in rheological properties caused by batch-to-batch slurry formulation differences or environmental temperature fluctuations, thus avoiding unstable molding quality.

[0016] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For those skilled in the art, the drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 The present invention provides a flowchart of an intelligent method for adjusting the thickness of a zinc oxide varistor through wet extrusion and stamping.

[0019] Figure 2 This is a schematic diagram of a module for an intelligent adjustment system for the thickness of a zinc oxide varistor wet extrusion stamping process, provided by the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example

[0021] In the existing wet extrusion stamping process, zinc oxide slurry is a typical high-solids-content non-Newtonian fluid, which exhibits shear thinning. During high-speed extrusion, the slip flow rate (leakage) inside the metering pump fluctuates nonlinearly with the shear rate. This means that relying solely on linear pump speed control cannot guarantee the consistency of the wet film thickness, thereby reducing the precision of resistor manufacturing.

[0022] To solve the above technical problems, such as Figure 1 As shown, Embodiment 1 of the present invention provides an intelligent adjustment method for the thickness of wet extrusion stamping of zinc oxide varistors. Specifically, Embodiment 1 takes a 10D471K type medium and low voltage varistor production line of an electronic component factory as an example: a high-precision wet extrusion machine (equipped with a precision gear metering pump) is provided on site, and zinc oxide ceramic slurry containing PVA binder is used.

[0023] In the specific implementation of Example 1: First, shear rate and shear stress data are collected, and the rheological parameters of zinc oxide slurry are obtained by fitting a power-law fluid model. This method eliminates the uncertainty of rheological characteristics caused by batch formulation differences or ambient temperature fluctuations in the slurry by constructing a digital mapping of the non-Newtonian fluid characteristics of the slurry during the production preparation stage, providing a reliable physical benchmark for subsequent accurate calculation of slip flow. Second, based on the rheological parameters, the set target wet film thickness, and real-time production conditions, combined with the flow characteristics of non-Newtonian fluid in the pump and die head, a pumping slip compensation model including slip flow compensation is established, and the corrected metering pump command speed is calculated. This method uses a physical model to perform real-time calculation of the rheological behavior of non-Newtonian fluid, quantifies and actively compensates for the implicit error caused by the nonlinear increase in leakage flow in the metering pump due to shear thinning characteristics, overcomes the defect of traditional linear control strategies leading to wet film thinning under high-speed production conditions, and achieves accurate control of wet film thickness at different production speeds. Then, the metering pump is driven to operate at the corrected metering pump command speed to press the extruded wet film into a varistor preform, and the actual thickness of the varistor preform is detected. This method obtains thickness data that reflects the true geometric state of the preform through online real-time monitoring, providing a direct basis for quality judgment. Finally, the thickness error is calculated based on the actual thickness of the varistor preform and the target thickness, and the quality of the varistor preform is judged based on a dynamic error threshold, with defective products being rejected. This method utilizes statistical principles to automatically adapt to small normal fluctuations in the production process, identify and reject sudden defective products with abnormal thickness, prevent misjudgment of qualified products, and ensure that the preforms entering the sintering process all meet strict geometric requirements, thereby improving the reliability of varistor manufacturing.

[0024] Furthermore, to better illustrate the technical solution of Embodiment 1 of the present invention, a detailed description is provided of the intelligent adjustment method for the thickness of the wet extrusion stamping of the zinc oxide varistor, specifically including the following: S1. Perform slurry rheological property calibration, which includes the following sub-steps: S11. Before formal production, the extruder undergoes multi-stage variable shear rate testing. The system controls the metering pump to operate at three preset speed points: low, medium, and high, and collects corresponding shear rate and shear stress data through an online viscometer.

[0025] S12. The system fits the rheological parameters of zinc oxide slurry based on a power-law fluid model. and The fitting model is based on the following physical relationships: ; In the formula, For shear stress, This is the consistency coefficient. For shear rate, This is the flow behavior index. For zinc oxide slurry, when It exhibits characteristics of a pseudoplastic fluid.

[0026] For example, in this embodiment 1, multiple sets of shear rate and shear stress data collected in step S11 are received. ,in ( (Number of test points). Set the shear rate range as... In order to cover the expected range of production conditions, the following settings can be configured: This is 0.8 times the die head shearing rate corresponding to the lowest planned output of the production line. The shear rate of the die head is 1.2 times the maximum planned output of the production line. To obtain the power-law model parameters for the zinc oxide slurry, the system performs the following specific fitting process: Step 1: Based on the power-law fluid constitutive equation Taking the natural logarithm of both sides transforms the nonlinear equation into a linear equation: ; make , , Then the above equation is transformed into a standard linear regression model. .

[0027] Step 2: The system uses the least squares method to minimize the sum of squared errors and calculates the slope. (i.e., the liquidity behavior index) and intercept The specific calculation formula is as follows: ; ; in, , indicating the first The natural logarithm of the shear rate during the test; , indicating the first The natural logarithm of the shear stress during the test.

[0028] Step 3: Based on the calculated intercept The consistency coefficient is obtained by inverse solving. : ; At the same time, the system calculates the coefficient of determination. To verify the goodness of fit, the calculation formula is as follows: ; in, For all observation data The arithmetic mean; The predicted value for each test point.

[0029] If The fitting result is deemed valid, and the calculated result is... and The value is stored in the controller's register as a reference physical constant for calculating the slip flow rate in subsequent steps; if If the system determines that the current slurry rheological properties are unstable or that it is a non-power-law fluid, it will issue an alarm prompting manual intervention.

[0030] For example, the system collected five sets of data, and through logarithmic transformation and regression calculation, obtained the slope of the regression line. ,intercept Thus, calculate Simultaneously calculate This indicates that the batch of zinc oxide slurry conforms to the characteristics of a power-law fluid and that the parameters are valid.

[0031] In this embodiment 1, by performing rheological data acquisition and power-law model parameter identification under multiple operating conditions during the production preparation stage, a digital mapping of the non-Newtonian fluid properties of zinc oxide slurry was achieved. This process not only obtained key physical parameters characterizing the shear thinning degree of the slurry (flow behavior index) and consistency coefficient This provides a physical benchmark for the subsequent construction of a pumping slip compensation model and effectively eliminates the uncertainty of rheological properties caused by batch formulation differences of slurry or fluctuations in ambient temperature.

[0032] S2. Establish a pump slip compensation model that includes production conditions and nonlinear compensation, and calculate the corrected metering pump command speed. This includes the following sub-steps: S21, Theoretical discharge flow rate of the metering pump Equal to the actual effective flow rate at the die head outlet Plus the slip flow generated by pressure backflow within the pump ,Right now The theoretical flow rate is directly proportional to the rotational speed. (in, (This refers to the theoretical displacement per revolution of the metering pump).

[0033] S22. According to the non-Newtonian correction of Poiseuille's law in fluid mechanics, slip flow rate. With back pressure and the apparent viscosity of the slurry Related: (in Here, represents the pump body's geometric slip coefficient, indicating the equivalent slip rotational speed under unit rheological stress factor. Considering the shear-thinning properties of the slurry, the apparent viscosity... It is a function that varies with shear rate: The shear rate at the die head. Approximate expression (in The linear speed of the conveyor belt. For die head clearance, Substituting the geometric shear factor of the die head into the slip formula, the slip flow rate is derived. .

[0034] S23, the target wet film volume ( ) as effective traffic By combining the above equations, a pumping slip compensation model is constructed, and the required command speed of the metering pump is obtained by inverse solving. The final formula is as follows: ; in, For the target wet film thickness, The coating width of the die head. This is the consistency coefficient. This is the flow behavior index. The formula indicates that when production speeds up (increases), due to... The apparent viscosity in the denominator decreases sharply, leading to an increase in the slip term. The system then calculates a larger value based on this. It automatically compensates for increased internal pump leakage due to decreased viscosity.

[0035] For example, the extrusion die used in this embodiment is a rectangular slit die, and its flow channel width is... Much larger than the lip-mouth gap According to the theory of non-Newtonian fluid flow in a slit (Rabinowitsch-Mooney equation), the wall shear rate... With average flow velocity and mobility behavior index The relationship is: ; Compare the shear rate formula in step S22 It can be deduced that The theoretical calculation formula is: ; For example, in this embodiment The calculation yields: .

[0036] Furthermore, the pump body geometric slip coefficient The dynamic time-domain integration method is used to obtain the result, as follows: First, a high-frequency pressure sensor is configured (sampling frequency...). Precision Collect the back pressure of the mold head; use precision A precision electronic scale is used to measure the extrusion volume. The metering pump is then controlled to maintain a constant test speed. Run; after the flow stabilizes, set the calibration time window. ( (In the time window) Inside, the system continuously collects data. Back pressure data points (in ); Synchronous measurement time window Total mass of internally extruded slurry Calculate the average actual volumetric flow rate within the time window. For the nonlinear response of non-Newtonian fluid slip to pressure, the effective pressure driving factor is calculated. ; based on average slip within the time window Combined with rheological parameters ( ) and die head geometric parameters ( ), calibrated in reverse by the following formula : ; Substituting the above effective pressure driving factors The calculation formula is: .

[0037] Finally, fault tolerance is assessed, and the collected data is calculated. coefficient of variation of back pressure data For example, if (Preset threshold) indicates excessive back pressure fluctuation and unstable calibration environment. If the value is invalid, the flow path needs to be checked and recalibrated; otherwise, the current value is valid. The value is valid.

[0038] Example of results: In this embodiment 1, the test rotation speed is set. The back pressure was measured. The average actual volumetric flow rate was measured after 60 seconds of weighing. Equivalent to The displacement; then the slip speed equivalent Metering pump single-cycle displacement Die head width Die head clearance Die head geometric shear factor rheological parameters , Substitute into the above formula and calculate the result. .

[0039] Based on this, in this embodiment 1, a target wet film thickness is set. ), conveyor belt speed Metering pump single-cycle displacement Pump body geometric slip coefficient Real-time back pressure of the die head was collected. The system calculates the current shear rate-related terms: Calculate the instantaneous apparent viscosity term: Calculate the slip drive term: Calculate the slip compensation speed: The final output is the corrected metering pump command speed. .

[0040] In the example above, by basing the target wet film thickness With the linear speed of the conveyor belt The calculated linear theoretical rotational speed, compared with the slurry power-law fluid model and real-time back pressure The reverse-derived slip compensation speed is superimposed and corrected to obtain the corrected metering pump command speed. This method utilizes a physical model to perform real-time calculations of the rheological behavior of non-Newtonian fluids, quantifying and compensating for the implicit errors caused by higher speeds, lower viscosity, and greater leakage. The aim is to address the problem of nonlinearly increasing leakage flow in the metering pump due to the shear thinning characteristics of zinc oxide slurry at high shear rates, resulting in the actual extrusion flow rate of the die being lower than the theoretically expected value. This effectively overcomes the shortcomings of traditional linear control strategies that neglect rheological characteristics under high-speed production conditions, leading to thinner wet film thickness. Thus, it achieves precise control of the wet film thickness of the zinc oxide varistor at different production speeds.

[0041] S3, Execute the revised metering pump command speed. The process involves wet film stamping, specifically including the following sub-steps: S31, The drive control module receives the corrected metering pump speed command. The precision gear metering pump is controlled to operate at a constant speed. Driven by the metering pump, zinc oxide slurry is extruded into the die. The extruded wet film is conveyed to the stamping station via a conveyor belt, where it is directly stamped into a circular varistor preform in a wet state.

[0042] S32. After stamping, the actual thickness of the varistor blank is detected using an online laser thickness gauge. .

[0043] S4. Determine the actual thickness of the varistor preform. Whether it is qualified includes the following steps: S41, Set target thickness Calculate the thickness error of the resistive preform. .

[0044] S42. Set the error threshold . If , determine that the product is qualified; if , determine that the product is unqualified and reject it to the waste area.

[0045] Exemplarily, in this Embodiment 1, the error threshold is dynamically set based on the following principle: The system collects the thickness data of the recently e.g., stamped green compacts in real time, and calculates its standard deviation where is the measured thickness of the recently qualified green compact samples, and is the average thickness of the recently samples. In order to avoid frequent false alarms while ensuring the product yield, set the error threshold . For example, during the stable operation stage of the system, if the measured standard deviation of the thickness is measured, then set the dynamic error threshold . If exceeds this value during subsequent inspections, it is determined as a sudden abnormality and rejection is executed; otherwise, it is determined that the product is qualified. It should be noted that if the number of valid samples is insufficient or the calculated dynamic threshold exceeds the preset reasonable protection range, the system will automatically switch to the preset fixed limit error threshold for quality determination to prevent misjudgment caused by statistical distortion.

[0046] In this Embodiment 1, by collecting historical sample data in real time and calculating the standard deviation of the thickness , a dynamic error threshold setting mechanism based on the principle is constructed to determine the product quality. This dynamic determination mechanism can identify and reject the green compacts with abnormal thickness, thereby ensuring that each varistor green compact entering the sintering process meets strict geometric dimension requirements, thus improving the precision of resistor manufacturing.

[0047] Embodiment 2 This is the second embodiment of the present invention. As Figure 2 shown, based on Embodiment 1, this embodiment also discloses an intelligent adjustment system for the thickness of zinc oxide varistor wet extrusion film stamping, specifically including: a rheological property calibration module, a slip compensation calculation module, a drive control module, and a quality monitoring and feedback module.

[0048] The system further includes a data acquisition unit, which is connected to an on-line viscometer, a pressure sensor, and a laser thickness gauge, and is used to obtain shear stress, die back pressure, and green compact thickness data in real time.

[0049] The system also includes a stamping unit for stamping the wet film extruded by the metering pump into a varistor preform.

[0050] The rheological property calibration module is used to control the metering pump to perform multi-stage variable shear rate tests during the production preparation stage, collect shear rate and shear stress data, and fit the rheological parameters (flow behavior index) of the zinc oxide slurry based on a power-law fluid model. and consistency coefficient This allows for the establishment of a digital mapping of the non-Newtonian fluid properties of the slurry.

[0051] The slip compensation calculation module is used to receive the target wet film thickness and die back pressure signal in real time, construct a pumping slip compensation model by combining rheological parameters, and calculate the corrected metering pump command speed in real time. This is to quantify and compensate for the nonlinear slip flow rate within the pump caused by shear-thinning characteristics.

[0052] The drive control module is used to receive instruction speed and control the operation of the precision metering pump, while coordinating the conveyor belt speed to ensure a precise match between the slurry extrusion flow rate and the transmission speed.

[0053] The quality monitoring and feedback module is used to collect the thickness of the green embryo using an online thickness gauge and to calculate the thickness based on statistical principles. The principle is to determine the dynamic error threshold, and output a qualified signal or control the rejection mechanism to perform rejection action based on the judgment result, so as to realize closed-loop control of product quality.

[0054] In the specific implementation of Implementation 2 above, the system uses a rheological characteristic calibration module to "profile" the physical properties of the zinc oxide slurry. Production only begins when the fitted determination coefficient meets the requirements. This method eliminates the uncertainty in rheological properties caused by batch differences in raw materials or fluctuations in ambient temperature. Secondly, through a slip compensation calculation module, the system uses a physical model to calculate in real time the increased internal leakage flow due to viscosity reduction under high-speed extrusion conditions. This method overcomes the defect of traditional linear control strategies causing wet film thinning at high speeds, achieving active compensation for the rheological behavior of non-Newtonian fluids. Finally, the drive control module precisely executes the corrected metering pump speed command. This ensures that the effective flow rate of the die extrusion remains stable at all times. Finally, the quality monitoring and feedback module uses dynamically generated error thresholds. Acceptance testing of varistor blanks; this method can prevent qualified products from being mistakenly judged as defective products, and ensure that each blank meets strict geometric requirements, thereby improving the precision of resistor manufacturing.

[0055] This embodiment also provides a computer device applicable to the intelligent adjustment method for the thickness of wet extrusion stamping of zinc oxide varistors, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the intelligent adjustment method for the thickness of wet extrusion stamping of zinc oxide varistors as proposed in the above embodiment.

[0056] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0057] To further verify the effectiveness of the embodiments of the present invention, especially to verify the adjustment accuracy of the pumping slip compensation model under high-speed production conditions, comparative experiments are conducted below for comparison and demonstration: A commercially available precision wet extrusion machine was selected as the research object, and the same batch of zinc oxide ceramic slurry was used for production testing. Before the experiment, the rheological properties of the slurry were calibrated, and the fitted rheological parameters were: consistency coefficient Mobility Behavior Index The experiment set a target wet film thickness. for (Right now ), Die head coating width for Theoretical displacement per revolution of metering pump for .

[0058] To ensure the scientific rigor and comparability of the experiment, two experimental groups with different control strategies were set up, operating under the same high-speed production conditions (conveyor belt linear speed). Run under: Control group (using traditional linear control): Pump speed is calculated solely based on the geometric volumetric flow rate formula, without introducing slip compensation, and the theoretical speed is calculated. It remains constant throughout the entire process; Experimental group (using the intelligent adjustment method of Embodiment 1 of the present invention): Enable the pumping slip compensation model, and the system continuously collects the die back pressure in real time , dynamically calculates the slip flow rate in combination with rheological parameters, and outputs the corrected command speed of the metering pump .

[0059] During the experiment, simulate the pressure fluctuations in the production site and continuously collect the operation data at 15 time nodes. The comparison of the command speeds output by the two control strategies under different real-time back pressures is shown in Table 1

[0060] Table 1 Time Node Real-time back pressure ΔP (MPa) <![CDATA[Control group commanded speed N linear (r / sp)]]> <![CDATA[Experimental group - Slip compensation amount N sliip (r / s)]]> <![CDATA[Experimental group - Command speed N cmd (r / s)]]> T1 2.00 6.00 0.70 6.70 T2 2.05 6.00 0.74 6.74 T3 1.95 6.00 0.66 6.66 T4 2.10 6.00 0.78 6.78 T5 2.02 6.00 0.71 6.71 T6 1.99 6.00 0.69 6.69 T7 2.00 6.00 0.70 6.70 T8 1.96 6.00 0.67 6.67 T9 2.01 6.00 0.71 6.71 T10 2.02 6.00 0.72 6.72 T11 1.97 6.00 0.68 6.68 T12 1.99 6.00 0.69 6.69 T13 1.97 6.00 0.68 6.68 T14 1.99 6.00 0.69 6.69 T15 2.00 6.00 0.70 6.70 As can be seen from Table 1, under high-speed conditions, due to the shear-thinning characteristics of the zinc oxide slurry, there is a significant slip flow rate in the pump. The control group ignored this non-linear error and always operated at the theoretical speed . While the experimental group automatically superimposed the compensation speed through model calculation, and the command speed was dynamically adjusted with the fluctuation of the back pressure , reflecting the intelligence of this method

[0061] Subsequently, the wet films extruded by the two groups were stamped into green compacts, and their actual thicknesses were detected using an online laser thickness gauge. Set the thickness qualification determination threshold to the target value (that is, is regarded as qualified). The thickness and quality determination results of the green compacts produced at the corresponding time nodes are shown in Table 2

[0062] Table 2 Time Node Control group - actual thickness (μm) Control group - thickness error (μm) Control group results Experimental group - actual thickness (μm) Experimental group - thickness error (μm) Results of the experimental group T1 291.50 -8.50 qualified 300.20 +0.20 qualified T2 284.80 -15.20 Unqualified 300.50 +0.50 qualified T3 293.20 -6.80 qualified 299.40 -0.60 qualified T4 279.90 -20.10 Unqualified 300.80 +0.80 qualified T5 296.80 -3.20 qualified 300.10 +0.10 qualified T6 298.11 -1.89 qualified 300.23 +0.23 qualified T7 291.75 -8.25 qualified 299.66 -0.34 qualified T8 297.43 -2.57 qualified 300.1 +0.10 qualified T9 290.66 -9.34 qualified 300.47 +0.47 qualified T10 292.2 -7.80 qualified 299.68 -0.32 qualified T11 292.93 -7.07 qualified 300.02 +0.02 qualified T12 292.83 -7.17 qualified 300.11 +0.11 qualified T13 292.84 -7.16 qualified 299.87 -0.13 qualified T14 296.78 -3.22 qualified 299.7 -0.30 qualified T15 295.24 -4.76 qualified 299.55 -0.45 qualified As can be seen from the detection data in Table 2, due to the lack of compensation for the internal leakage of the pump in the control group, the actual extrusion flow rate was seriously insufficient, resulting in an average thickness of the green compacts of only about 292.46 , which is lower than the target value of 300 . In contrast, the actual thickness of the green compacts in the experimental group was stable around 300 , and the maximum absolute error was only 0.8 , fully meeting the quality requirements, and all samples were qualified. This shows that the intelligent adjustment method described in the present invention not only corrects the systematic flow deviation but also effectively suppresses the thickness dispersion caused by pressure fluctuations

[0063] Finally, comprehensively analyze the statistical characteristics of the two groups of experimental data, and the results are shown in Table 3

[0064] Table 3 Evaluation indicators Control group (traditional linear control) Experimental group (the intelligent adjustment method of this invention) Improvement effect description Average thickness (μm) 292.46 300.03 The thickness deviation of approximately 7.57 μm was corrected. Thickness standard deviation (σ) 4.81 0.39 Consistency improved by approximately 12 times pass rate 86.67% 100% The pass rate has been greatly improved. Experimental data shows that although traditional control methods can achieve a pass rate of approximately 86.67% after incorporating manual experience corrections, significant quality risks still exist in high-speed production, failing to meet the requirements of precision manufacturing. In contrast, in the experimental group with pre-tested results, the intelligent adjustment method proposed in this invention increased the pass rate to 100%, significantly outperforming traditional control methods. Furthermore, it demonstrates a significant advantage in thickness consistency, effectively solving the thickness control problem in the wet extrusion process of zinc oxide varistors.

[0065] In summary, this invention, by constructing a pump slip compensation model incorporating rheological parameters and real-time operating conditions, can accurately calculate the corrected metering pump command speed in real time. Experimental data shows that even under high-speed production conditions where shear thinning is highly likely to occur, this invention can ensure a high degree of consistency and accuracy in the thickness of the varistor green sheet, overcoming the problems of thinning and unevenness that occur with speed increases in traditional control methods, thus improving the reliability and yield of resistor manufacturing.

[0066] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0067] The preferred embodiments of the invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention.

Claims

1. A method for intelligently adjusting the thickness of zinc oxide varistors in wet extrusion and stamping processes, characterized in that, include: Shear rate and shear stress data were collected, and the rheological parameters of zinc oxide slurry were obtained by fitting based on a power-law fluid model. Based on rheological parameters, the set target wet film thickness, real-time back pressure and conveyor belt running linear speed, and combined with the flow characteristics of non-Newtonian fluid in the pump and the die head, a pumping slip compensation model including slip flow compensation is established, and the corrected metering pump command speed is calculated. The metering pump is driven to run at the modified metering pump command speed to press the extruded wet film into a varistor preform and to detect the actual thickness of the varistor preform. The thickness error is calculated based on the actual thickness of the varistor blank and the target thickness, and the quality of the varistor blank is determined based on the dynamic error threshold. Defective products are rejected.

2. The intelligent adjustment method for the thickness of zinc oxide varistors in wet extrusion stamping according to claim 1, characterized in that, The rheological parameters include flow behavior indices. and consistency coefficient Its expression is: In the formula, For shear stress, This is the consistency coefficient. For shear rate, This is a liquidity behavior index.

3. The intelligent adjustment method for the thickness of zinc oxide varistors in wet extrusion stamping according to claim 2, characterized in that, The formula for calculating the corrected metering pump command speed is as follows: ； in, For the target wet film thickness, The coating width of the die head. The linear speed of the conveyor belt. This represents the theoretical displacement per revolution of the metering pump. For die head clearance, The geometric shear factor of the die head. The geometric slip coefficient of the pump body. This is back pressure.

4. The intelligent adjustment method for the thickness of zinc oxide varistors in wet extrusion stamping according to claim 3, characterized in that, The formula for calculating the geometric shear factor of the die head is: ,in This is a liquidity behavior index.

5. The intelligent adjustment method for the thickness of zinc oxide varistors in wet extrusion stamping according to claim 4, characterized in that, The method for obtaining the pump body geometric slip coefficient is as follows: control the metering pump at a constant test speed. Run the program and wait for the flow to stabilize before proceeding within the calibration time window. Inside, continuous collection Each mold head back pressure data point (in ), calculate the average actual volumetric flow rate within the time window and effective pressure driving factors Based on the average slip within the time window Reverse calibration is performed by combining rheological parameters and die geometry parameters. 。 6. The intelligent adjustment method for the thickness of zinc oxide varistors in wet extrusion stamping according to claim 1, characterized in that, The determination of embryo quality includes: setting a target thickness. Based on the measured actual thickness of the varistor preform Calculate the thickness error of the resistive preform. Set error threshold and thickness error With error threshold Compare; if The product is deemed qualified; if Products are deemed unqualified and removed from the scrap area.

7. The intelligent adjustment method for the thickness of zinc oxide varistors in wet extrusion stamping according to claim 6, characterized in that, The error threshold based on Principles are dynamically set: Collect the most recent data. Measured thickness of a qualified embryo sample Calculate the average thickness and thickness standard deviation The error threshold is calculated. .

8. An intelligent adjustment system for the thickness of a zinc oxide varistor wet extrusion stamping process, employing the intelligent adjustment method for the thickness of a zinc oxide varistor wet extrusion stamping process as described in any one of claims 1 to 7, characterized in that, include: The rheological property calibration module is used to control the metering pump to perform variable speed tests during the production preparation stage, and to obtain the rheological parameters of the slurry based on the collected data. The slip compensation calculation module is used to receive the target wet film thickness and real-time back pressure signal, combine rheological parameters, construct a pumping slip compensation model, and calculate the corrected metering pump command speed in real time. The drive control module is used to receive command speed and control the operation of the precision metering pump, as well as control the conveyor belt speed and the action of the stamping mechanism; The quality monitoring and feedback module is used to collect the thickness of the green body through an online thickness gauge, determine the quality of the varistor green body by combining the error threshold, and output a qualified signal or rejection instruction based on the determination result.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the intelligent adjustment method for the thickness of wet extrusion stamping of zinc oxide varistors according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the intelligent adjustment method for the thickness of the zinc oxide varistor wet extrusion stamping as described in any one of claims 1 to 7.

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