Graphene conductive paste viscosity detection device and detection method thereof

Abstract

The application is suitable for the technical field of conductive paste viscosity detection, and provides a graphene conductive paste viscosity detection equipment and a detection method thereof.The equipment comprises a tank body, a stirring mechanism, a multi-sensing detection assembly, a signal acquisition module and a controller.The stirring mechanism comprises a stirring motor, the output end of the stirring motor is connected with a transmission structure, the transmission structure is drivingly connected with a stirring shaft, the stirring shaft is a hollow shaft body, an installation shaft is coaxially nested in the stirring shaft, the installation shaft is a fixed shaft body which does not rotate with the stirring shaft, and the two together form a coaxial double-shaft detection integrated structure, and a detection window is formed in the shaft body sidewall of the stirring shaft.Through the double-shaft detection integrated structure of the coaxially nested rotary stirring shaft and the fixed installation shaft, the non-contact detection design makes the sensor not contact with the paste, reduces the strong abrasion of the graphene powder and the corrosion of the organic solvent, and meanwhile, the paste flow field is not damaged and the dispersion effect is not affected.

Description

Technical Field

[0001] This invention relates to the field of conductive paste viscosity testing technology, and more specifically, to a graphene conductive paste viscosity testing device and its testing method. Background Technology

[0002] Graphene conductive pastes, with their excellent conductivity, flexibility, and processing performance, have become fundamental materials in the fields of new energy and electronic information. In the preparation of graphene conductive pastes, viscosity is a crucial process indicator that determines the paste's coating performance, film uniformity, conductivity, and batch stability. It requires precise and real-time control during the stirring and dispersion process. This viscosity is the apparent viscosity, which refers to the ratio of shear stress to shear rate under specific shear rate and temperature conditions for graphene conductive pastes, a non-Newtonian pseudoplastic fluid.

[0003] Currently, the industry generally adopts offline sampling and testing methods, which involves taking samples from the mixing and dispersing equipment after it has been shut down, and then using a laboratory rotational rheometer to test the apparent viscosity.

[0004] The existing sampling and testing methods suffer from strong lag and cannot provide real-time feedback on the rheological state of the slurry during the stirring and dispersion process. This can easily lead to problems such as over-dispersion causing damage to the graphene sheet structure or insufficient dispersion causing slurry agglomeration, affecting the final product performance. In addition, the sampling and testing process requires frequent shutdowns for sampling and manual adjustments, resulting in poor real-time performance, low production efficiency, and poor batch consistency of the slurry. To address these issues, a viscosity testing device and method for graphene conductive slurry are proposed. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a viscosity testing device and method for graphene conductive slurry.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A graphene conductive slurry viscosity testing device includes: a tank, a stirring mechanism, a multi-sensor detection component, a signal acquisition module, and a controller.

[0008] The tank is used to contain the graphene conductive slurry to be tested, and the stirring mechanism is located inside the tank to stir the slurry inside the tank.

[0009] The stirring mechanism includes a stirring motor, the output end of which is connected to a transmission structure, and the transmission structure is connected to a stirring shaft.

[0010] The stirring shaft is a hollow shaft body, and a mounting shaft is coaxially nested inside it. The mounting shaft is a fixed shaft body that does not rotate with the stirring shaft. Together, they form a coaxial double-layer shaft detection integrated structure.

[0011] The stirring shaft has a detection window on its side wall.

[0012] The input terminal of the signal acquisition module is electrically connected to the multi-sensor detection component and the speed encoder that works in conjunction with the stirring motor drive, and the output terminal of the signal acquisition module is electrically connected to the controller. The controller has a built-in multi-parameter coupled apparent viscosity and solid content prediction model based on non-Newtonian fluid rheology, which is used to calculate the apparent viscosity and solid content of graphene conductive slurry in real time.

[0013] The invention is further configured such that: the controller also has a built-in process threshold early warning module and a closed-loop control module. The output of the closed-loop control module is electrically connected to the stirring motor, the feeding actuator matched with the feed inlet, and the temperature control system matched with the tank, respectively. It can adjust the stirring speed, dispersion time, material ratio and slurry temperature according to the real-time calculated apparent viscosity and solid content data, so as to realize closed-loop production of slurry stirring, detection and control.

[0014] The present invention is further configured such that: a feed inlet is provided at the top of the tank, the feed inlet is connected to the interior of the tank, and the feed inlet is a closed channel for feeding slurry raw materials.

[0015] An observation port is provided on the opposite side of the feed inlet. The observation port is a transparent and sealed structure used to observe the slurry mixing and production status inside the tank.

[0016] The bottom of the tank is provided with a discharge port, which is connected to the inside of the tank and is used to discharge the prepared conductive slurry.

[0017] The present invention is further configured such that: the stirring mechanism further includes a first fixing structure, the first fixing structure is sealed and fixedly installed on the top of the tank, and a sealing protective shell is fixedly connected to the top of the first fixing structure.

[0018] The stirring motor is fixedly installed on one side of the housing, and a cable take-up box with a sealed structure is provided on the top of the housing. The signal acquisition module is housed inside the cable take-up box.

[0019] The stirring shaft passes through the interior of the first fixed structure and is rotatably connected to the first fixed structure via a bearing.

[0020] The present invention is further configured such that: the stirring mechanism further includes a shear stress sensor, a flow rate and solid content integrated sensor, and a temperature sensor, wherein the shear stress sensor, the flow rate and solid content integrated sensor, and the temperature sensor are all fixed to the outer side wall of the mounting shaft and correspond to the position of the detection window, and the shear stress sensor, the flow rate and solid content integrated sensor, and the temperature sensor together constitute a multi-sensor detection component.

[0021] The shear stress sensor, the integrated flow rate and solid content sensor, and the temperature sensor are arranged at equal intervals along the circumferential direction of the mounting axis. The circumferential angle between adjacent sensors is 120°, and the detection centers of all sensors are at the same axial height, corresponding to the same slurry detection area of ​​the detection window.

[0022] The present invention is further configured such that: an agitator adapted to the slurry is fixedly provided on the outer wall of the agitator shaft, the agitator is located below the detection window, a second fixing structure is provided at the lower end of the agitator shaft, the second fixing structure is fixedly installed inside the tank, and the lower end of the agitator shaft is rotatably connected to the second fixing structure.

[0023] The invention is further configured such that: the transmission structure is housed inside the housing and includes a drive gear, which is coaxially and fixedly connected to the output end of the stirring motor. A driven gear is meshed below the drive gear.

[0024] A connecting piece is coaxially fixedly connected to the bottom of the driven gear, and an adapter is coaxially fixedly connected to the bottom of the connecting piece. The adapter is coaxially fixedly connected to the top of the stirring shaft.

[0025] The mounting shaft is coaxially inserted through the central through hole of the driven gear, the connecting piece, the adapter, and the stirring shaft. The mounting shaft is rotatably engaged with the driven gear and the stirring shaft through bearings. The top of the mounting shaft is fixedly connected to the top wall of the housing.

[0026] The present invention is further configured such that: the second fixing structure includes a second fixing tube, the second fixing tube is coaxially sleeved on the outer side of the lower end of the stirring shaft, and the inner wall of the second fixing tube and the outer wall of the stirring shaft are rotatably engaged by a bearing.

[0027] The lower end of the mounting shaft passes through the central through hole of the stirring shaft and is then coaxially and fixedly connected to the inner wall of the second fixing tube.

[0028] The outer wall of the second fixed tube is fixedly connected with three sets of radially extending second fixed brackets, and the ends of the second fixed brackets are fixedly installed on the inner wall of the tank.

[0029] A detection method for a graphene conductive paste viscosity testing device, using the aforementioned graphene conductive paste viscosity testing device, includes the following steps:

[0030] S1. Model pre-calibration and establishment.

[0031] S11. Prepare multiple sets of graphene conductive paste standard samples with different solid contents and different dispersions, and obtain the true values ​​of apparent viscosity and solid content of each set of samples under different working conditions using standard testing equipment.

[0032] S12. Place the standard sample in the testing equipment and simultaneously collect the slurry shear stress, flow rate, acoustic impedance, temperature, rotation speed and ultrasonic echo characteristic parameters at different stirring speeds and temperatures. Establish a multi-parameter coupled apparent viscosity and solid content prediction model based on non-Newtonian fluid rheology through a fitting algorithm and store it in the controller.

[0033] S2. In-situ synchronous detection of the mixing process.

[0034] S21. Start the testing equipment. The stirring motor drives the stirring shaft to rotate through the transmission structure, stirring and dispersing the graphene conductive slurry in tank 1.

[0035] S22. A multi-sensor detection assembly fixed on a stationary mounting shaft performs non-contact in-situ detection of the slurry during the stirring process through a detection window on the side wall of the stirring shaft. It simultaneously acquires real-time characteristic signals of the slurry's shear stress, flow rate, acoustic impedance, temperature, and ultrasonic echo, and simultaneously acquires the real-time rotational speed of the stirring shaft through a speed encoder.

[0036] S3. Multi-parameter synchronous acquisition and preprocessing.

[0037] S31. The signal acquisition module uses a unified clock trigger unit to synchronously acquire signals from multiple sensing components and the speed encoder.

[0038] S32. Perform multi-stage filtering on the acquired raw signal to remove electromagnetic interference and mechanical vibration noise, and obtain the preprocessed effective characteristic parameters.

[0039] S4. Real-time calculation of apparent viscosity and solid content.

[0040] The controller inputs the pre-processed effective characteristic parameters into the pre-established multi-parameter coupled apparent viscosity and solid content prediction model, completes real-time error compensation through the built-in temperature and rotation speed dual-dimensional correction terms, and calculates and outputs the real-time apparent viscosity and solid content of the graphene conductive slurry.

[0041] S5, closed-loop process control.

[0042] The controller compares the real-time calculated apparent viscosity and solid content data with the preset process thresholds. Based on the comparison results, it sends control commands to the stirring motor, feeding actuator, and temperature control system to automatically adjust the stirring process parameters and material ratio, thereby realizing closed-loop production of slurry stirring, detection, and control.

[0043] The present invention is further configured such that: in step S4, the multi-parameter coupled apparent viscosity and solid content prediction model includes an apparent viscosity prediction model constructed based on the power-law fluid constitutive equation and a solid content prediction model constructed based on the ultrasonic impedance method.

[0044] The apparent viscosity prediction model incorporates temperature and flow rate correction terms, as well as temperature and rotation speed dual-dimensional correction terms. It uses shear stress, shear rate, real-time temperature, real-time flow rate, and real-time rotation speed of the stirring shaft as inputs to calculate the real-time apparent viscosity of the slurry.

[0045] The solid content prediction model has a built-in temperature correction term and uses ultrasonic impedance, ultrasonic echo amplitude and real-time temperature as inputs to calculate the real-time solid content of the slurry.

[0046] Both the apparent viscosity prediction model and the solid content prediction model were obtained by pre-calibration and fitting using standard samples of graphene conductive slurry.

[0047] In summary, this application includes at least one of the following beneficial technical effects:

[0048] (1) By adopting a double-layer shaft detection integrated structure with a coaxial nested rotating stirring shaft and a fixed installation shaft, the outer stirring shaft undertakes the stirring torque function, and the inner fixed installation shaft provides a mounting carrier for the sensor. This non-contact detection design prevents the sensor from contacting the slurry, reduces the strong abrasion of graphene powder and the corrosion of organic solvents, and does not damage the slurry flow field or affect the dispersion effect.

[0049] (2) Based on the non-Newtonian pseudoplastic fluid law of graphene conductive slurry, the present invention constructs an equation and establishes a multi-parameter coupled apparent viscosity and solid content prediction model of shear stress, shear rate, flow velocity, solid content and temperature. It has a built-in real-time correction term for temperature and velocity, which can be adapted to the shear thinning characteristics and strong temperature sensitivity of graphene slurry, thereby improving the detection accuracy and stability.

[0050] (3) This invention can be directly integrated into the graphene conductive slurry preparation and dispersion process to achieve in-situ, real-time and lag-free apparent viscosity detection during stirring. It does not require stopping the machine to take samples, which reduces the possibility of over-dispersion or under-dispersion in traditional processes, reduces slurry contamination and solvent evaporation during sampling, and improves the stability of slurry performance.

[0051] (4) By integrating the detection system with the stirring drive, temperature control and batching system, the stirring process parameters and material ratio can be automatically adjusted according to the real-time detection data, realizing closed-loop production of stirring, detection and control at the same time, without manual intervention, greatly reducing labor costs, and the detection data can be stored and traced throughout the process. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of the overall structure of a graphene conductive slurry apparent viscosity testing device according to the present invention.

[0053] Figure 2 for Figure 1 Isometric side view.

[0054] Figure 3 for Figure 1 The front view.

[0055] Figure 4 This is a schematic diagram of the stirring mechanism in this invention.

[0056] Figure 5 for Figure 4 The front view.

[0057] Figure 6 for Figure 5 A magnified structural diagram of area A in the middle.

[0058] Figure 7 This is a schematic diagram of the structure of the multi-sensor detection component in this invention.

[0059] Figure 8 This is a flowchart of the viscosity detection method for graphene conductive paste in this invention.

[0060] Figure 9 This is a block diagram of the process threshold early warning and closed-loop control system in this invention.

[0061] Explanation of reference numerals in the attached drawings: 1. Tank body;

[0062] 2. Stirring mechanism; 21. Stirring motor; 22. Housing; 23. Cable take-up box; 24. First fixing structure; 25. Transmission structure; 251. Driving gear; 252. Driven gear; 253. Connecting part; 254. Adaptor; 28. Stirring shaft; 29. ​​Detection window; 201. Stirring paddle; 202. Second fixing structure; 2021. Second fixing pipe; 2022. Second fixing frame; 203. Shear stress sensor; 204. Integrated flow rate and solid content sensor; 205. Temperature sensor;

[0063] 3. Feed inlet; 4. Observation port; 5. Discharge outlet. Detailed Implementation

[0064] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0065] It should be noted that, unless otherwise specified, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0066] Please see Figures 1-9 The present invention provides the following technical solutions:

[0067] Example 1, see Figure 1 A graphene conductive slurry viscosity testing device includes: a tank 1, a stirring mechanism 2, a multi-sensor detection component, a signal acquisition module, and a controller.

[0068] Tank 1 is used to contain the graphene conductive slurry to be tested. Stirring mechanism 2 is located inside tank 1 and is used to stir the slurry inside tank 1.

[0069] See Figure 1 and Figure 2 The top of the tank body 1 is provided with a feed inlet 3, which is connected to the interior of the tank body 1. The feed inlet 3 is a closed channel for feeding slurry raw materials.

[0070] See Figure 1 and Figure 2 An observation port 4 is provided on the opposite side of the feed inlet 3. The observation port 4 is a transparent and sealed structure, used to observe the mixing and production of the slurry inside the tank 1.

[0071] See Figure 1 and Figure 3 The bottom of the tank 1 is provided with a discharge port 5, which is connected to the inside of the tank 1 and is used to discharge the prepared conductive slurry.

[0072] Among them, tank 1 is a vertical closed stainless steel reactor, equipped with a jacketed temperature control system, which can control the temperature of the slurry to meet the dispersion process requirements of graphene conductive slurry.

[0073] A feed inlet 3 is provided on the top left side of the tank body 1. The feed inlet 3 is equipped with a pneumatic sealing ball valve and is connected to an automatic feeding system to realize automatic feeding of materials. An observation port 4 is provided on the top right side of the tank body 1. The observation port 4 is a tempered glass sealing structure and equipped with LED lighting to clearly observe the stirring status of the slurry inside the tank body 1. A discharge port 5 is provided at the bottom center of the tank body 1. The discharge port 5 is equipped with a discharge ball valve to discharge the prepared slurry.

[0074] This testing equipment can be applied to the micron / nano dispersion process in the preparation of graphene conductive slurry, enabling real-time online detection of apparent viscosity throughout the dispersion process.

[0075] See Figure 2 The stirring mechanism 2 is installed at the top center of the tank 1 and includes a stirring motor 21, a shell 22, a first fixing structure 24, a transmission structure 25, a stirring shaft 28, a mounting shaft 27, and a second fixing structure 202.

[0076] See Figure 2 The first fixing structure 24 is sealed and fixedly installed on the top of the tank body 1, and a sealed protective shell 22 is fixedly connected to the top of the first fixing structure 24.

[0077] See Figure 2 The stirring motor 21 is fixedly installed on one side of the housing 22. The top of the housing 22 is provided with a take-up box 23 with a sealed structure, and the signal acquisition module is housed inside the take-up box 23.

[0078] The first fixing structure 24 is a flange-type bearing seat, which is fixed to the center flange at the top of the tank body 1 by bolts. The top of the first fixing structure 24 is fixedly connected to a sealing protective shell 22 by bolts.

[0079] The stirring motor 21 is a variable frequency speed control servo motor, which is fixedly installed on the right side of the housing 22 by a flange; the top of the housing 22 is fixed with a take-up box 23 with a sealing cover plate by bolts, and the signal acquisition module is housed inside the take-up box 23 to reduce the pollution of dust and slurry splash.

[0080] The output end of the stirring motor 21 is connected to a transmission structure 25, and the transmission structure 25 is connected to the stirring shaft 28.

[0081] The stirring shaft 28 is a hollow shaft body, and a mounting shaft 27 is coaxially nested inside it. The mounting shaft 27 is a fixed shaft body that does not rotate with the stirring shaft 28. Together, they form a coaxial double-layer shaft detection integrated structure. A detection window 29 is opened on the side wall of the stirring shaft 28.

[0082] The specific structure of transmission structure 25 is as follows:

[0083] See Figure 4 and Figure 5 The transmission structure 25 is housed inside the housing 22 and includes a drive gear 251, which is coaxially and fixedly connected to the output end of the stirring motor 21. A driven gear 252 is meshed below the drive gear 251.

[0084] See Figure 6A connecting piece 253 is coaxially fixedly connected to the bottom of the driven gear 252, and an adapter 254 is coaxially fixedly connected to the bottom of the connecting piece 253. The adapter 254 is coaxially fixedly connected to the top of the stirring shaft 28.

[0085] See Figures 4-6 The mounting shaft 27 is coaxially inserted through the center through hole of the driven gear 252, the connecting piece 253, the adapter 254 and the stirring shaft 28. The mounting shaft 27 is rotatably engaged with the driven gear 252 and the stirring shaft 28 through bearings. The top of the mounting shaft 27 is fixedly connected to the top wall of the housing 22.

[0086] The drive gear 251 is coaxially connected to the output end of the stirring motor 21, and the driven gear 252 is meshed below the drive gear 251 to meet the stirring requirements of the slurry. The bottom of the driven gear 252 is coaxially fixed with a connector 253 by bolts, and the bottom of the connector 253 is coaxially fixed with an adapter 254 by splines. The lower end of the adapter 254 is coaxially welded and fixed to the top end of the stirring shaft 28.

[0087] In specific operation, when the stirring motor 21 starts, it drives the driving gear 251 to rotate, which in turn drives the driven gear 252 to rotate through gear meshing. The driven gear 252 transmits the rotational torque synchronously to the stirring shaft 28 through the coaxially fixed connecting piece 253 and adapter 254, thereby achieving stable rotation of the stirring shaft 28. The gear transmission can improve the precise control of the stirring speed, enhance the accuracy of shear rate calculation, and thus improve the accuracy of apparent viscosity detection.

[0088] The outer hollow stirring shaft 28 independently undertakes the function of stirring torque transmission, and drives the rotation through the transmission structure to realize the stirring of slurry; the inner mounting shaft 27 remains stationary and is dedicated to the installation of detection components and signal transmission. The two are coaxially nested and do not interfere with each other, so as to realize the synchronous operation of the stirring process and the detection process, and achieve the technical goal of in-situ real-time detection.

[0089] The stirring shaft 28 passes through the interior of the first fixed structure 24 and is rotatably connected to the first fixed structure 24 via a bearing.

[0090] See Figure 7 The stirring mechanism 2 also includes a shear stress sensor 203, a flow rate and solid content integrated sensor 204, and a temperature sensor 205. The shear stress sensor 203, the flow rate and solid content integrated sensor 204, and the temperature sensor 205 are all fixed to the outer wall of the mounting shaft 27 and correspond to the position of the detection window 29. The shear stress sensor 203, the flow rate and solid content integrated sensor 204, and the temperature sensor 205 together constitute a multi-sensor detection component.

[0091] See Figure 7The shear stress sensor 203, the flow rate and solid content integrated sensor 204, and the temperature sensor 205 are arranged at equal intervals along the circumference of the mounting axis 27. The circumferential angle between adjacent sensors is 120°, and the detection centers of all sensors are at the same axial height, corresponding to the same slurry detection area of ​​the detection window 29.

[0092] The detection window 29 is fitted with a single-crystal sapphire bushing flush with the outer wall of the stirring shaft 28. The bushing is 2mm thick and has an acoustic impedance of 43×10⁻⁶. 6 Pa·s / m, visible light transmittance ≥85%; the inner wall of the stirring shaft 28 and the outer wall of the mounting shaft 27 are filled with polytetrafluoroethylene heat insulation and vibration damping material to reduce the interference of stirring friction heat and mechanical vibration on the sensor; the detection ends of the shear stress sensor 203, the integrated flow rate and solid content sensor 204, and the temperature sensor 205 are all tightly fitted to the inner surface of the single crystal sapphire bushing, and the gap between the fittings is filled with a signal transmission coupling agent matching the corresponding sensor, and the signal lines of all sensors are led upward through the mounting shaft 27, the specific positions of the signal lines are as follows. Figure 7 The circles in the diagram are connected to the sensors respectively.

[0093] The shear stress sensor is a piezoresistive planar shear stress sensor with a range of 0~1kPa and an accuracy of ±0.2%FS. The sensing surface is completely in contact with the inner surface of the sapphire bushing, and the gap is filled with high thermal conductivity silicone grease to improve the transmission efficiency of shear stress. It can collect the shear stress signal generated by the slurry flow in real time.

[0094] The integrated ultrasonic sensor for flow rate and solid content uses a pulsed ultrasonic Doppler sensor with a center frequency of 2MHz, a flow rate range of 0~5m / s, a solid content detection range of 0~30%, and an accuracy of ±2%FS. Its probe end face is attached to the inner surface of the sapphire bushing, and the gap is filled with ultrasonic coupling agent, which can simultaneously acquire the flow rate, ultrasonic impedance, and ultrasonic echo amplitude characteristic signals of the slurry.

[0095] The temperature sensor uses a Class A PT100 platinum resistance sensor with a temperature measurement range of 0~100℃ and an accuracy of ±0.15℃. Its probe is set close to the inner surface of the sapphire bushing to improve the real-time performance and accuracy of temperature detection.

[0096] The three sensors are arranged at equal intervals and staggered around the mounting axis 27, which reduces signal interference between sensors and allows all sensors to detect the same area of ​​slurry. This reduces parameter mismatch caused by flow field phase difference and improves the consistency and accuracy of detection data.

[0097] Shear stress sensor 203 collects the shear stress generated on the shaft wall during slurry flow, providing a reference parameter for apparent viscosity calculation; flow velocity and solid content integrated sensor 204 simultaneously collects the slurry flow velocity, acoustic impedance, and ultrasonic echo characteristics, providing auxiliary verification parameters for apparent viscosity calculation, and simultaneously realizing the synchronous detection of solid content; temperature sensor 205 collects the real-time temperature of the slurry to evaluate the interference of temperature on apparent viscosity detection.

[0098] During the specific testing process, the detection heads of the three sensors are all facing the detection window 29, so that during the stirring process, the sensors can sense the dynamic slurry flowing through the window through the rotating stirring shaft 28. The internal cavity of the mounting shaft 27 is equipped with a sealing baffle above the sensor installation position to isolate the gas in the tank 1 from the upper take-up box 23. All sensor signal lines pass through the inside of the mounting shaft 27 and are led upward to the take-up box 23 at the top of the housing 22, where they are connected to the internal signal acquisition module.

[0099] An agitator 201 adapted to the slurry is fixedly installed on the outer wall of the agitator shaft 28. The agitator 201 is located below the detection window 29. A second fixing structure 202 is provided at the lower end of the agitator shaft 28. The second fixing structure 202 is fixedly installed inside the tank body 1. The lower end of the agitator shaft 28 is rotatably connected to the second fixing structure 202.

[0100] The stirring paddle 201 rotates with the stirring shaft 28 to forcibly stir the slurry in the tank 1, so that the slurry in the tank 1 forms a uniform and stable flow field, and the slurry flow field parameters at the detection window 29 are stable and the detection accuracy is controllable. The stirring paddle 201 is set below the detection window 29, so that the detection window 29 is located in the circulating flow above the paddle blade, which can reduce the direct interference of the stirring paddle 201 on the local flow field at the detection window 29. At the same time, the overall macroscopic convection circulation in the tank makes the slurry in the sensor area representative.

[0101] The specific structure of the second fixing structure 202 is as follows:

[0102] See Figure 5 The second fixing structure 202 includes a second fixing tube 2021, which is coaxially sleeved on the outer side of the lower end of the stirring shaft 28. The inner wall of the second fixing tube 2021 and the outer wall of the stirring shaft 28 are rotatably fitted by bearings.

[0103] See Figure 5 The lower end of the mounting shaft 27 passes through the central through hole of the stirring shaft 28 and is coaxially fixedly connected to the inner wall of the second fixed tube 2021.

[0104] See Figure 5The outer wall of the second fixed pipe 2021 is fixedly connected with three sets of radially extending second fixed brackets 2022, and the ends of the second fixed brackets 2022 are fixedly installed on the inner wall of the tank body 1.

[0105] The second fixing tube 2021 is coaxially sleeved on the outer side of the lower end of the stirring shaft 28, and the two are rotatably fitted by a deep groove ball bearing; the lower end of the mounting shaft 27 passes through the central through hole of the stirring shaft 28 and is coaxially fixed with the inner wall of the second fixing tube 2021; the end of the second fixing bracket 2022 is fixed to the inner side wall of the tank 1 by bolts, providing bottom support for the stirring shaft 28 and the mounting shaft, reducing the possibility of radial swaying during stirring, and reducing the interference of mechanical vibration on the detection accuracy of the sensor.

[0106] The input end of the signal acquisition module is electrically connected to the multi-sensor detection component and the speed encoder that works in conjunction with the stirring motor 21, and the output end of the signal acquisition module is electrically connected to the controller.

[0107] The signal acquisition module is a multi-channel industrial-grade data acquisition card. Its input end is electrically connected to the multi-sensor detection components and the speed encoder. The speed encoder is an incremental photoelectric encoder, which is coaxially mounted on the output shaft end of the stirring motor 21. The data acquisition card has a built-in unified clock trigger unit, which can realize hardware synchronous sampling of all sensors and encoders and can filter out interference noise in the signal. The output end of the signal acquisition module is electrically connected to the controller.

[0108] The apparent viscosity controller is an industrial-grade PLC controller with a built-in multi-parameter coupled apparent viscosity and solid content prediction model based on non-Newtonian fluid rheology. This model can integrate and process signals such as shear stress, flow rate, temperature, and rotation speed in real time to calculate the current apparent viscosity and solid content of the slurry. It is equipped with an external industrial touch screen that can display the slurry's apparent viscosity, solid content, temperature, and rotation speed data in real time.

[0109] Example 2: The structure described in Example 1 enables the detection of the apparent viscosity of graphene conductive slurry during the micron / nano dispersion process. Furthermore, multiple sensing components are used to assist in data correction, resulting in more accurate calculated apparent viscosity data. Building upon Example 1, it is also necessary to configure the early warning and closed-loop control of the detection equipment, ensuring that the detected data is applied to the execution components, thereby improving the precision of graphene conductive slurry preparation.

[0110] To enable early warning and closed-loop control of the testing equipment, the controller also has a built-in process threshold early warning and closed-loop control system. The system includes a process threshold early warning module and a closed-loop control module. The output of the closed-loop control module is electrically connected to the stirring motor 21, the feeding actuator of the feed inlet 3, and the temperature control system of the tank 1, respectively. It can adjust the stirring speed, dispersion time, material ratio and slurry temperature according to the real-time calculated apparent viscosity and solid content data to realize closed-loop production of slurry stirring, testing and control.

[0111] See Figure 9 The specific implementation steps are as follows:

[0112] First, the underlying implementation architecture of the control system.

[0113] The entire process threshold early warning and closed-loop control system is built with a three-layer architecture, which includes a perception layer, a control layer, and an execution layer.

[0114] The sensing layer includes a multi-sensor detection component, a speed encoder, and a signal acquisition module. It collects parameters such as apparent viscosity, solid content, temperature, and stirring speed of the slurry in real time, and uploads them to the controller after completing signal preprocessing.

[0115] The control layer consists of a built-in process threshold early warning module and a closed-loop control module in the controller, which completes parameter comparison, early warning triggering, control command calculation, and logic interlock control.

[0116] The execution layer includes a stirring motor 21, a feeding actuator for the feed inlet 3, and a temperature control system for the tank 1. It receives control commands from the controller, executes corresponding actions, and completes the adjustment of process parameters.

[0117] The closed-loop logic of the industrial threshold early warning and closed-loop control system is as follows: real-time parameter acquisition, model calculation, threshold comparison, early warning triggering, control command output, actuator action, secondary parameter acquisition and verification, and closed-loop convergence. It achieves fully automated production without manual intervention.

[0118] Second, the specific implementation and triggering process of the process threshold early warning module.

[0119] The early warning module is the pre-triggered unit for closed-loop control and also undertakes the function of production safety interlocking. The specific implementation steps are as follows:

[0120] Step 1: Presetting and writing process thresholds.

[0121] Before slurry production, threshold presets are completed on the controller's human-machine interface (e.g., an external industrial touchscreen) based on the graphene conductive slurry's formulation, target performance, and process type. Thresholds are divided into two categories: basic process thresholds and safety interlock thresholds. Examples of preset parameters are as follows:

[0122] Table 1 Example of Preset Parameters

[0123]

[0124] Meanwhile, the preset parameter sampling period is 100ms under normal operating conditions, and shortened to 50ms during the control process to meet the requirements of control response speed.

[0125] Step 2: Real-time parameter comparison and early warning level classification.

[0126] The controller compares the real-time calculated apparent viscosity, solid content, temperature, and rotational speed data with preset thresholds cycle by cycle, and classifies them into three warning levels according to the degree of deviation. Different warning levels correspond to different actions. The specific settings for the three warning levels are shown in the table below:

[0127] Table 2 Comparison of Three-Level Early Warning System

[0128]

[0129] Step 3: Record the entire process of early warning data.

[0130] All warning trigger times, parameter values, deviation values, and executed actions are automatically stored in the controller's local database, and historical curves can be retrieved at any time, enabling full-process data traceability in production.

[0131] Third, the control logic and full-process implementation steps of the closed-loop control module.

[0132] The closed-loop control module is implemented using an incremental PID control algorithm, which reduces the possibility of overshoot and oscillation during the control process, and ensures that the slurry process parameters converge smoothly to the target range. The specific implementation steps are as follows:

[0133] Step 1: Confirm the triggering conditions for regulation.

[0134] When the controller triggers a level-two warning, the closed-loop control module automatically starts and simultaneously completes the pre-verification:

[0135] The multi-sensor detection components were confirmed to be working properly, with the deviation between the two sets of parameters (calculated shear stress value and calculated ultrasonic parameter value) ≤5%, and no data anomalies.

[0136] The actuators (stirring motor 21, feeding actuator, temperature control system) were confirmed to be communicating normally and there were no fault alarms.

[0137] Lock the current process step (micron dispersion or nano dispersion), call the corresponding process control parameters and PID coefficients to avoid cross-process mis-control.

[0138] It should be noted that before the equipment is put into production, the PID parameters of the closed-loop control module need to be engineered. The critical proportionality method or the decay curve method can be used to tune the PID parameters suitable for the apparent viscosity, solid content, and temperature loops for the different process characteristics of micron-dispersion and nano-dispersion processes. The tuned parameter set is then stored in the controller and automatically called up with each process.

[0139] Step 2: Calculate the target value and deviation.

[0140] The controller determines the target center value of the parameters based on the preset process threshold. The target center value of the basic process threshold is the arithmetic mean of the upper and lower limits of the corresponding parameters. At the same time, it calculates the deviation between the real-time value and the target value, which is used as the input value of the PID algorithm.

[0141] Step 3: PID algorithm calculation and control command output.

[0142] The controller uses an incremental PID algorithm to calculate the control increment of the corresponding actuator based on the deviation and outputs a standard industrial control signal.

[0143] To avoid detection distortion caused by fluctuations in the slurry flow field, all control actions are performed in a step-by-step, gradual manner. After each adjustment, a waiting time for the flow field to stabilize is set before a second detection and verification is conducted. Large-scale adjustments to parameters in a single instance are prohibited.

[0144] Step 4: Execution process for precise control of sub-parameters

[0145] For the three parameters of apparent viscosity, solid content, and temperature, independent control links are set up to ensure that they do not interfere with each other. The specific execution process is as follows:

[0146] The first step is the closed-loop control process for apparent viscosity.

[0147] Apparent viscosity is an indicator of the degree of dispersion of graphene slurry, and corresponds to adjustments in stirring speed and dispersion time. Specific steps are as follows:

[0148] State 1: When the real-time apparent viscosity is higher than the target upper limit (i.e., insufficient dispersion).

[0149] Single adjustment step size: The stirring speed is increased by 10% of the current speed.

[0150] The single lifting range must simultaneously meet the following conditions: not exceeding 10% of the equipment's rated speed, and the upper limit of a single lifting range not exceeding 100 rpm. If both conditions are met, the smaller value between the two shall be taken.

[0151] Adjust the waiting time for the flow field in the tank 1 to stabilize after adjustment, and re-collect the apparent viscosity data of the slurry. If the apparent viscosity is still higher than the upper limit, repeat the above step size adjustment until the rotational speed reaches the rated upper limit of this process. If the apparent viscosity still does not meet the standard after the rotational speed reaches the upper limit, the controller automatically extends the dispersion duration and sets the extension step size until the apparent viscosity drops back to the target range.

[0152] State 2: When the real-time apparent viscosity is lower than the target lower limit (i.e., over-dispersed).

[0153] Single adjustment step size: The reduction amplitude of the stirring rotational speed is 10% of the current rotational speed, and the maximum single reduction amplitude does not exceed 20% of the current rotational speed. After adjustment, wait for the flow field in the corresponding tank 1 to stabilize, and re-collect the apparent viscosity data. If the apparent viscosity is still lower than the lower limit, the controller immediately triggers a first-level shutdown instruction to suspend the dispersion process and simultaneously push an alarm message to the operator to avoid excessive damage to the graphene sheet layer structure, resulting in a decrease in the conductivity of the slurry.

[0154] Secondly is the closed-loop control process of the solid content.

[0155] The solid content directly determines the accuracy of the final formula of the slurry. For the material addition adjustment of the corresponding feeding actuator, the solvent metering pump and the powder screw feeder supporting the feeding port 3 are both electrically connected to the closed-loop control module of the controller and can receive instructions to complete precise feeding. The specific steps are as follows:

[0156] State 1: When the real-time solid content is higher than the target upper limit.

[0157] The controller calculates the mass of the solvent to be added based on the effective volume of the tank 1, the current solid content, and the target solid content. Adopt a multi-time micro-addition strategy. The single addition amount does not exceed 40% of the total addition amount, the cumulative addition amount of three times does not exceed 100% of the total addition amount, the first addition amount does not exceed 40% of the total addition amount, the second addition amount does not exceed 60% of the remaining amount to be added, and the third addition amount is the remaining amount to be added.

[0158] Output an instruction to the solvent metering pump to add the corresponding solvent according to the calculated value. During the addition process, the stirring motor 21 maintains the current rotational speed to ensure rapid and uniform mixing of the solvent and the slurry. After a single addition is completed, wait for the mixing stabilization time of the tank 1 volume, and re-collect the solid content data. If it is still higher than the upper limit, repeat the above addition process until the solid content meets the standard.

[0159] State 2: When the real-time solid content is lower than the target lower limit.

[0160] The controller calculates the mass of graphene powder or binder powder to be additionally supplemented; it is also executed in three times, and the single addition amount does not exceed 40% of the total addition amount; an instruction is output to the powder screw feeder to supplement the corresponding powder according to the calculated value, and the stirring speed is increased by 10% during the addition process to avoid powder agglomeration; after the single addition is completed, wait for the mixing stabilization time of the volume of tank 1, and re-collect the solid content data until the solid content drops back to the target range.

[0161] It should be noted that before calculating the additional amount, the controller will combine the data of the shear stress sensor 203 to judge whether the current flow field is stable. If the flow field fluctuates greatly (such as the shear stress fluctuation exceeds the set threshold), the regulation will be suspended, and after the flow field is stable, the judgment and execution will be carried out again. At the same time, a multiple micro-addition strategy is adopted, and the calculated total addition amount is divided into two to three executions. After each addition, the effect is verified until the standard is reached.

[0162] Then is the temperature closed-loop regulation process.

[0163] Temperature is the correction term for apparent viscosity detection and affects the slurry dispersion effect at the same time. For the adjustment of the temperature control system supporting tank 1, the temperature control unit with both cold and heat for tank 1 is electrically connected to the closed-loop regulation module of the controller and can receive instructions to adjust the flow rate and temperature of the refrigerant or heat medium. The specific steps are as follows:

[0164] When the real-time temperature is higher or lower than the target range.

[0165] The controller outputs a standard signal to the temperature control unit to adjust the opening of the inlet valve of the refrigerant or heat medium. The single adjustment step is 5% of the full stroke of the valve, and the single maximum adjustment amplitude does not exceed 20% of the full stroke; wait for 10 s after the adjustment, and re-collect the slurry temperature data until the temperature is stable within the target range; the whole process of temperature regulation is linked with the apparent viscosity calculation model to update the temperature correction term in real time to avoid the error of apparent viscosity detection caused by temperature fluctuation.

[0166] The whole process of temperature regulation is linked with the apparent viscosity calculation model to update the temperature correction term in real time to avoid the error of apparent viscosity detection caused by temperature fluctuation.

[0167] Step Five: Verification of Regulation Effect and Closed-Loop Convergence.

[0168] After each regulation action is completed, the controller re-collects the slurry parameters through the multi-sensor detection component to complete two verifications:

[0169] Deviation verification: Confirm whether the parameter deviation amount is reduced. If the deviation continues to expand, immediately suspend the current regulation logic and trigger a three-level warning to avoid slurry scrapping.

[0170] Compliance verification: Confirm whether the parameters have fallen back to the basic process threshold range. If the parameters are stable within the target range for three consecutive sampling cycles, the control is deemed complete, the closed-loop control module stops running, and parameter monitoring resumes normal operation.

[0171] Step 6: Record data during the control process.

[0172] The trigger time, deviation, control command, parameter changes after execution, and final result of all control actions are automatically stored in the database to generate control logs, which can be retrieved and traced at any time.

[0173] Fourth, emergency control and safety interlock procedures for abnormal operating conditions.

[0174] To address any abnormal situations during the production process, an independent emergency control procedure is established to ensure equipment and production safety, as detailed below:

[0175] When sensor data is abnormal, if the deviation between the calculated shear stress value and the calculated ultrasonic parameter value exceeds 5% for three consecutive sampling cycles, the sensor is determined to be abnormal, a level 3 warning is immediately triggered, closed-loop control is suspended, the stirring motor 21 is reduced to idle speed, an alarm message is pushed to the operator, automatic control actions are prohibited, and misoperation is avoided.

[0176] When parameters are severely out of tolerance, and the parameters exceed the safety interlock threshold, an emergency interlock will be triggered immediately: the feed valve will be closed, the stirring motor 21 will be reduced to idle speed, the temperature control system will enter the heat preservation state, and an emergency alarm message will be pushed. After confirmation by the operator, an emergency shutdown can be triggered to avoid equipment damage.

[0177] When the actuator malfunctions, the controller immediately suspends control actions and triggers a level-three warning when it detects that the actuator is unresponsive or communication is interrupted. At the same time, it records the fault information to avoid safety accidents caused by continuous output of control commands.

[0178] Example 3, see reference Figure 8 A detection method for a graphene conductive slurry viscosity testing device, using the graphene conductive slurry viscosity testing device as described above, is applied to the micron / nano dispersion process in the preparation of graphene conductive slurry, realizing real-time online detection throughout the dispersion process. The method specifically includes the following steps:

[0179] S1. Model pre-calibration and establishment.

[0180] S11. Prepare multiple sets of graphene conductive paste standard samples with different solid contents and different dispersions, and obtain the true values ​​of apparent viscosity and solid content of each set of samples under different working conditions using standard testing equipment.

[0181] Ten sets of graphene conductive paste standard samples were prepared with solid contents of 1%, 2%, 3%, 4%, 5%, 6%, 8%, 10%, 15%, and 20%, respectively, covering the solid content range of the entire process of graphene conductive paste, with 4%-6% being the core production process range. Each set of samples was dispersed for four durations of 5 min, 15 min, 30 min, and 60 min, respectively, under the same stirring equipment and rated speed as in actual production, resulting in 40 sets of standard samples with different dispersion.

[0182] Using a standard rotational rheometer, the apparent viscosity of each sample was measured within the shear rate range of 10s⁻¹ to 1000s⁻¹ at temperatures of 25℃, 30℃, 35℃, and 40℃. This shear rate range matches the shear rate range under the stirring conditions of this equipment. The true solid content of each sample was measured using the vacuum drying method, and a database of true values ​​for standard samples was established.

[0183] S12. Place the standard sample in the testing equipment and simultaneously collect the slurry shear stress, flow rate, acoustic impedance, temperature, rotation speed and ultrasonic echo characteristic parameters at different stirring speeds and temperatures. Establish a multi-parameter coupled apparent viscosity and solid content prediction model based on non-Newtonian fluid rheology through a fitting algorithm and store it in the controller.

[0184] During the testing of standard samples, the shear rate and temperature conditions of the rotational rheometer correspond one-to-one with the stirring speed and temperature conditions of the testing equipment, ensuring the consistency of the characteristic parameters with the true values ​​under the operating conditions and reducing the fitting error caused by the deviation of the operating conditions.

[0185] Forty sets of standard samples were placed into the testing equipment in sequence. Under the stirring speed of 100rpm, 200rpm, 300rpm, 400rpm, 500rpm and 600rpm, the characteristic parameters of shear stress, flow rate, ultrasonic impedance, temperature, rotation speed and ultrasonic echo amplitude were collected simultaneously to form a characteristic dataset that matches the true value. The least squares method was used to perform multivariate nonlinear fitting to establish a multi-parameter coupled prediction model of apparent viscosity and solid content.

[0186] The zero-point calibration and range calibration of the equipment are completed using standard viscosity oil. After calibration, the model is stored in the PLC controller. At the same time, process thresholds and early warning parameters are preset on the human-machine interface of the controller to complete the engineering tuning of the PID coefficient of the closed-loop control module.

[0187] Before the equipment is put into production, the PID parameters of the closed-loop control module need to be engineered. Using the decay curve method, the PID parameters suitable for the apparent viscosity, solid content, and temperature loops are tuned separately for the different process characteristics of micron dispersion and nano dispersion processes.

[0188] The apparent viscosity control loop has a proportionality of 20% to 40%, an integral time of 60 to 120 seconds, and a derivative time of 5 to 15 seconds; the solid content control loop has a proportionality of 30% to 50%, an integral time of 120 to 180 seconds, and a derivative time of 0 seconds; the temperature control loop has a proportionality of 40% to 60%, an integral time of 180 to 300 seconds, and a derivative time of 10 to 20 seconds. The calibrated parameter set is stored in the controller and automatically recalled during each process.

[0189] S2. In-situ synchronous detection of the mixing process.

[0190] S21. Start the testing equipment. The stirring motor 21 drives the stirring shaft 28 to rotate through the transmission structure 25, and stirs and disperses the graphene conductive slurry in the tank 1.

[0191] According to the formula, graphene powder, dispersant, solvent and binder are put into tank 1 through feed port 3. The stirring motor 21 is started and the stirring shaft 28 is driven to rotate through the transmission structure 25 to stir and disperse the slurry. The speed of the micron dispersion process is set to 300 rpm and the speed of the nano dispersion process is set to 500 rpm. The temperature control system of tank 1 stabilizes the temperature of the slurry at 30±0.5℃.

[0192] S22. The multi-sensor detection assembly fixed on the stationary mounting shaft 27 performs non-contact in-situ detection of the slurry during the stirring process through the detection window 29 on the side wall of the stirring shaft 28. It simultaneously acquires the real-time characteristic signals of the slurry's shear stress, flow rate, acoustic impedance, temperature, and ultrasonic echo, and simultaneously acquires the real-time rotational speed of the stirring shaft 28 through the speed encoder.

[0193] The multi-sensor detection component, fixed on the stationary mounting shaft 27, performs non-contact in-situ detection of the slurry during the stirring process through the sapphire bushing of the detection window 29. It simultaneously acquires the real-time characteristic signals of the slurry's shear stress, flow rate, ultrasonic impedance, temperature, and ultrasonic echo. The speed encoder simultaneously acquires the real-time rotational speed of the stirring shaft 28 and converts it into the shear rate at the detection window 29.

[0194] The controller calculates the shear rate in real time based on the rotational speed of the stirring shaft 28 fed back by the speed encoder and the parameters at the detection window 29, which serves as the key input parameter for the model.

[0195] The signal acquisition module synchronously acquires signals from all sensors and speed encoders, and after preprocessing, uploads them to the controller. The controller then synchronously activates the process threshold early warning module to begin real-time parameter comparison.

[0196] During the slurry mixing and dispersion process, non-contact in-situ detection is achieved through a multi-sensor detection component fixed on the stationary mounting shaft 27. This eliminates the need to stop the machine for sampling, eliminates detection lag, and allows for the real-time acquisition of slurry characteristic parameters, accurately reflecting the changes in the slurry's rheological state during the mixing process.

[0197] S3. Multi-parameter synchronous acquisition and preprocessing.

[0198] S31. The signal acquisition module uses a unified clock trigger unit to synchronously acquire signals from multiple sensing components and the speed encoder.

[0199] The sampling time synchronization accuracy is ≤1ms; the sampling frequency of each sensor is set as follows: shear stress sensor 203 is 5kHz, ultrasonic sensor is 1kHz, temperature sensor 205 is 1kHz, and speed encoder is 10kHz; under normal operating conditions, the signal acquisition module performs anti-aliasing low-pass filtering on the multi-channel raw data and then downsamples and synchronizes it, outputting synchronization characteristic data with a sampling period of 100ms; during the control process, the downsampling output period is shortened to 50ms to meet the control response speed requirements.

[0200] S32. Perform multi-stage filtering on the acquired raw signal to remove electromagnetic interference and mechanical vibration noise, and obtain the preprocessed effective characteristic parameters.

[0201] The acquired raw signal is sequentially subjected to Kalman filtering, followed by 50Hz power frequency notch filtering and then 100Hz low-pass filtering to remove high-frequency noise from mechanical vibration. Finally, adaptive Kalman filtering is performed to remove random noise from the signal, and the preprocessed effective characteristic parameters are obtained and uploaded to the PLC controller.

[0202] A unified clock trigger unit enables hardware synchronous acquisition of multiple parameters, ensuring consistent sampling times for all feature parameters and reducing model solution errors caused by parameter asynchrony. Multi-stage filtering removes interference noise from the signal, improving the accuracy of effective feature parameters.

[0203] S4. Real-time calculation of apparent viscosity and solid content.

[0204] The controller inputs the pre-processed effective characteristic parameters into the pre-established multi-parameter coupled apparent viscosity and solid content prediction model, completes real-time error compensation through the built-in temperature and rotation speed dual-dimensional correction terms, and calculates and outputs the real-time apparent viscosity and solid content of the graphene conductive slurry.

[0205] By using a pre-established prediction model, combined with temperature and rotation speed correction terms, the apparent viscosity and solid content of the slurry can be calculated in real time. This model can fully adapt to the shear thinning characteristics and strong temperature sensitivity of graphene non-Newtonian fluids, ensuring the accuracy of the test results.

[0206] In step S4, the multi-parameter coupled apparent viscosity and solid content prediction model includes an apparent viscosity prediction model based on the power-law fluid constitutive equation and a solid content prediction model based on the ultrasonic impedance method. The expression of the multi-parameter coupled apparent viscosity and solid content prediction model is as follows:

[0207] Based on the first embodiment, the stirring shaft 28 drives the stirring paddle 201 to rotate, thereby forming a stable flow field at the detection window 29 position to adapt to the establishment of the prediction model.

[0208] Apparent viscosity prediction model:

[0209]

[0210] Where η is the apparent viscosity and K is the consistency coefficient. Where is the shear rate, and n is the flow behavior exponent. , These are the pre-calibrated coefficients of the apparent viscosity prediction model. For slurry flow rate, As the reference slurry flow rate, It is a two-dimensional correction term for temperature and speed. For slurry temperature, As the reference slurry temperature, This refers to the real-time rotational speed of the stirring shaft.

[0211] K is related to the real-time temperature of the slurry. The pre-calibration function related to the real-time solid content C was obtained by fitting it through rheological testing of standard samples.

[0212] n is the real-time temperature of the slurry. A pre-calibration function related to the real-time solid content C was obtained by fitting the rheological test of standard samples, which is adapted to the non-Newtonian fluid characteristics of graphene conductive paste.

[0213] Under the baseline operating conditions, , The values ​​were obtained through multivariate nonlinear fitting of standard samples, and their ranges are as follows: , .

[0214] The expression is:

[0215]

[0216] Where b1, b2, and b3 are pre-calibrated correction coefficients, b1∈[−0.03,−0.015], b2∈[0.0008,0.0015], and b3∈[−0.0001,−0.00005], and n0 is the reference speed, taken as 300 rpm. The correction terms are obtained by fitting test data of standard samples at different temperatures and speeds, and are used to compensate for the detection error caused by fluctuations in operating conditions.

[0217] The formula for calculating the shear rate is as follows:

[0218]

[0219] in, To detect the real-time shear rate of the slurry in the detection area; denoted as _r_, where _r_ is the real-time rotational speed of the stirring shaft 28, _r_ is the outer radius of rotation of the stirring shaft 28 at the detection window, and _h_ is the radial clearance between the outer wall of the detection window 29 and the inner wall of the tank 1.

[0220] The apparent viscosity prediction model incorporates temperature and flow rate correction terms, as well as temperature and rotation speed correction terms. It takes shear stress, shear rate, real-time temperature, real-time flow rate, and real-time rotation speed of the stirring shaft 28 as inputs, covering various factors affecting the apparent viscosity of graphene slurry and improving the accuracy of apparent viscosity calculation. The temperature and rotation speed correction terms can compensate for detection errors caused by changes in operating conditions in real time, further improving detection accuracy.

[0221] The solid content prediction model is based on the principle of ultrasound, where A is the ultrasonic echo amplitude (synchronously acquired by the integrated flow velocity and solid content sensor 204). The expression for the solid content prediction model is:

[0222] Solid content prediction model:

[0223]

[0224] Where C represents the solid content. For ultrasonic acoustic impedance, This refers to the amplitude of the ultrasonic echo. Based on solid content, As the reference acoustic impedance, As the reference echo amplitude, For slurry temperature, As the reference slurry temperature, c represents the coefficients of the pre-calibrated solids content prediction model.

[0225] c is obtained by multivariate nonlinear fitting of standard samples, with values ​​ranging from k1∈[0.8,1.2], k2∈[0.3,0.6], k3∈[-0.02,-0.01], to c∈[-0.5,0.5].

[0226] The solids content prediction model has a built-in temperature correction term. It can calculate the solids content of the slurry by taking ultrasonic impedance, ultrasonic echo amplitude, and real-time temperature as inputs, and realize the simultaneous detection of apparent viscosity and solids content.

[0227] During the calculation process, a multi-parameter weighted fusion algorithm is used to cross-validate the detection data. The cross-validation logic is as follows:

[0228] Apparent viscosity cross-validation: The first path, shear stress rheological solution value (weight 60%), serves as the core benchmark, adapting to the core definition of viscosity for non-Newtonian fluids; the second path, ultrasonic parameter solution verification value (weight 30%), serves as auxiliary verification to reduce interference from flow field fluctuations; the third path, temperature and speed correction terms (weight 10%), serves as error compensation to adapt to operating condition fluctuations. The weight allocation has been verified with 40 sets of standard samples, and the relative error of the detection is ≤ ±3%.

[0229] Solid content cross-validation: The first channel ultrasonic impedance method solution value (70% weight) is the core benchmark, which conforms to the industry standard for ultrasonic testing of solid content; the second channel rheological property correlation solution value (30% weight) is used for auxiliary verification to avoid sensor drift. When the relative deviation of the two-channel verification exceeds 5% and continues for 3 sampling cycles, an abnormal alarm is triggered.

[0230] The multi-parameter weighted fusion algorithm achieves cross-validation of detection data by setting corresponding weights for different parameters. It can effectively identify sensor drift and failure issues, trigger abnormal alarms, reduce the possibility of detection data distortion, and improve the stability and reliability of continuous equipment operation.

[0231] S5, closed-loop process control.

[0232] The controller compares the real-time calculated apparent viscosity and solid content data with the preset process thresholds. Based on the comparison results, it sends control commands to the stirring motor 21, the feeding actuator, and the temperature control system to automatically adjust the stirring process parameters and material ratio, thereby realizing closed-loop production of slurry stirring, detection, and control.

[0233] S51. The controller compares the real-time calculated apparent viscosity and solid content data with the preset process threshold.

[0234] S52. When the data triggers the secondary warning (control warning) defined in Embodiment 2, the controller starts the built-in closed-loop control module.

[0235] S53. The module sends instructions to the stirring motor 21, the feeding actuator, and the temperature control system respectively according to the control logic detailed in Embodiment 2, and automatically adjusts the stirring speed, material ratio and slurry temperature.

[0236] S54. During the control process, steps S2-S4 are repeated to verify the control effect in real time until the parameters stabilize within the target range, thus achieving closed-loop production of slurry mixing, detection, and control. All early warning and control data are recorded and stored according to the requirements in Example 2.

[0237] Obviously, the embodiments described above are merely some, not all, embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention.

Claims

1. A viscosity testing device for graphene conductive paste, characterized in that: include: Tank body (1), stirring mechanism (2), multi-sensor detection component, signal acquisition module, controller; The tank (1) is used to contain the graphene conductive slurry to be tested, and the stirring mechanism (2) is located inside the tank (1) and is used to stir the slurry inside the tank (1). The tank (1) is provided with a feed inlet (3) at the top and a discharge outlet (5) at the bottom. The stirring mechanism (2) includes a stirring motor (21), the output end of which is connected to a transmission structure (25), and the transmission structure (25) is connected to a stirring shaft (28). The stirring shaft (28) is a hollow shaft body, and an installation shaft (27) is coaxially nested inside it. The installation shaft (27) is a fixed shaft body that does not rotate with the stirring shaft (28). Together, they form a coaxial double-layer shaft detection integrated structure. The stirring shaft (28) has a detection window (29) on its side wall. The stirring mechanism (2) also includes a shear stress sensor (203), a flow rate and solid content integrated sensor (204), and a temperature sensor (205). The shear stress sensor (203), the flow rate and solid content integrated sensor (204), and the temperature sensor (205) are arranged at equal intervals along the circumferential direction of the mounting axis (27). The circumferential angle between adjacent sensors is 120°, and the detection centers of all sensors are at the same axial height, corresponding to the same slurry detection area of ​​the detection window (29). The input end of the signal acquisition module is electrically connected to the multi-sensor detection component and the speed encoder that drives the stirring motor (21), and the output end of the signal acquisition module is electrically connected to the controller. The controller has a built-in multi-parameter coupled apparent viscosity prediction model and solid content prediction model based on non-Newtonian fluid rheology, which are used to calculate the apparent viscosity and solid content of graphene conductive paste in real time. Apparent viscosity prediction model: Where η is the apparent viscosity and K is the consistency coefficient. Where is the shear rate, and n is the flow behavior exponent. , These are the pre-calibrated coefficients of the apparent viscosity prediction model. For slurry flow rate, As the reference slurry flow rate, It is a two-dimensional correction term for temperature and speed. For slurry temperature, As the reference slurry temperature, This refers to the real-time rotational speed of the stirring shaft; The expression is: in, These are the pre-calibrated correction coefficients. The reference speed; Solid content prediction model: Where C represents the solid content. For ultrasonic acoustic impedance, This refers to the amplitude of the ultrasonic echo. Based on solid content, As the reference acoustic impedance, As the reference echo amplitude, c represents the pre-calibrated coefficients of the solid content prediction model; The controller also has a built-in process threshold early warning module and a closed-loop control module. The output of the closed-loop control module is electrically connected to the stirring motor (21), the feeding actuator of the feed inlet (3), and the temperature control system of the tank (1), respectively. It can adjust the stirring speed, dispersion time, material ratio and slurry temperature according to the real-time calculated apparent viscosity and solid content data, so as to realize the closed-loop production of slurry stirring, detection and control.

2. The graphene conductive slurry viscosity testing device according to claim 1, characterized in that: The feed inlet (3) is connected to the interior of the tank (1), and the feed inlet (3) is a closed channel for feeding slurry raw materials; An observation port (4) is provided on the opposite side of the feed inlet (3). The observation port (4) is a transparent and sealed structure, used to observe the slurry mixing and production inside the tank (1). The discharge port (5) is connected to the interior of the tank (1) and is used to discharge the prepared conductive slurry.

3. The graphene conductive slurry viscosity testing device according to claim 1, characterized in that: The stirring mechanism (2) further includes a first fixing structure (24), which is sealed and fixedly installed on the top of the tank (1), and a sealed protective shell (22) is fixedly connected to the top of the first fixing structure (24). The stirring motor (21) is fixedly installed on one side of the housing (22), and a take-up box (23) with a sealing structure is provided on the top of the housing (22). The signal acquisition module is housed inside the take-up box (23). The stirring shaft (28) passes through the interior of the first fixed structure (24) and is rotatably connected to the first fixed structure (24) via a bearing.

4. The graphene conductive slurry viscosity testing device according to claim 1, characterized in that: The shear stress sensor (203), the flow rate and solid content integrated sensor (204), and the temperature sensor (205) are all fixed on the outer wall of the mounting shaft (27) and correspond to the position of the detection window (29). The shear stress sensor (203), the flow rate and solid content integrated sensor (204), and the temperature sensor (205) together constitute a multi-sensor detection component.

5. The graphene conductive paste viscosity testing device according to claim 4, characterized in that: The outer wall of the stirring shaft (28) is fixedly provided with a stirring paddle (201) adapted to the slurry. The stirring paddle (201) is located below the detection window (29). The lower end of the stirring shaft (28) is provided with a second fixing structure (202). The second fixing structure (202) is fixedly installed inside the tank (1). The lower end of the stirring shaft (28) is rotatably connected to the second fixing structure (202).

6. The graphene conductive slurry viscosity testing device according to claim 5, characterized in that: The transmission structure (25) is housed inside the housing (22) and includes a drive gear (251). The drive gear (251) is coaxially and fixedly connected to the output end of the stirring motor (21). A driven gear (252) is meshed below the drive gear (251). The driven gear (252) is coaxially fixedly connected to the bottom of a connecting piece (253), and the connecting piece (253) is coaxially fixedly connected to the bottom of an adapter (254). The adapter (254) is coaxially fixedly connected to the top of the stirring shaft (28). The mounting shaft (27) is coaxially inserted through the central through hole of the driven gear (252), the connecting piece (253), the adapter (254) and the stirring shaft (28). The mounting shaft (27) is rotated with the driven gear (252) and the stirring shaft (28) through bearings. The top of the mounting shaft (27) is fixedly connected to the top wall of the housing (22).

7. The graphene conductive paste viscosity testing device according to claim 6, characterized in that: The second fixing structure (202) includes a second fixing tube (2021), which is coaxially sleeved on the outer side of the lower end of the stirring shaft (28). The inner wall of the second fixing tube (2021) and the outer wall of the stirring shaft (28) are rotatably fitted by bearings. The lower end of the mounting shaft (27) passes through the central through hole of the stirring shaft (28) and is coaxially fixedly connected to the inner wall of the second fixing tube (2021). The outer wall of the second fixed tube (2021) is fixedly connected with three sets of radially extending second fixed brackets (2022), and the ends of the second fixed brackets (2022) are fixedly installed on the inner wall of the tank (1).

8. A method for detecting the viscosity of graphene conductive paste using a viscosity testing device, comprising the graphene conductive paste viscosity testing device as described in any one of claims 1-7, characterized in that: Includes the following steps: S1. Model pre-calibration and establishment; S11. Prepare multiple sets of graphene conductive paste standard samples with different solid contents and different dispersions, and obtain the true values ​​of apparent viscosity and solid content of each set of samples under different working conditions using standard testing equipment. S12. Place the standard sample in the testing equipment and simultaneously collect the characteristic parameters of slurry shear stress, flow rate, acoustic impedance, temperature, rotation speed and ultrasonic echo amplitude at different stirring speeds and temperatures. Establish a multi-parameter coupled apparent viscosity and solid content prediction model based on non-Newtonian fluid rheology through a fitting algorithm and store it in the controller. S2. In-situ synchronous detection of the mixing process; S21. Start the testing equipment. The stirring motor (21) drives the stirring shaft (28) to rotate through the transmission structure (25) to stir and disperse the graphene conductive slurry in the tank (1). S22. The multi-sensor detection assembly fixed on the stationary mounting shaft (27) performs non-contact in-situ detection of the slurry during the stirring process through the detection window (29) on the side wall of the stirring shaft (28), and simultaneously acquires the real-time characteristic signals of the slurry's shear stress, flow rate, acoustic impedance, temperature, and ultrasonic echo amplitude, and simultaneously acquires the real-time rotational speed of the stirring shaft (28) through the speed encoder. S3. Multi-parameter synchronous acquisition and preprocessing; S31. The signal acquisition module uses a unified clock triggering unit to synchronously acquire signals from multiple sensing components and the speed encoder in hardware. S32. Perform multi-stage filtering on the acquired raw signal to filter out electromagnetic interference and mechanical vibration noise in the signal, and obtain the pre-processed effective characteristic parameters. S4. Real-time calculation of apparent viscosity and solid content; The controller inputs the pre-processed effective characteristic parameters into the pre-established multi-parameter coupled apparent viscosity and solid content prediction model, and completes real-time error compensation through the built-in temperature and rotation speed dual-dimensional correction terms, and calculates and outputs the real-time apparent viscosity and solid content of the graphene conductive slurry. S5, closed-loop process control; The controller compares the real-time calculated apparent viscosity and solid content data with the preset process threshold. Based on the comparison results, it sends control commands to the stirring motor (21), the feeding actuator, and the temperature control system to automatically adjust the stirring process parameters and material ratio, thereby realizing closed-loop production of slurry stirring, detection, and control.

9. The detection method of the graphene conductive paste viscosity detection device according to claim 8, characterized in that: In step S4, the multi-parameter coupled apparent viscosity and solid content prediction model includes an apparent viscosity prediction model based on the power-law fluid constitutive equation and a solid content prediction model based on the ultrasonic impedance method. The apparent viscosity prediction model has built-in temperature and flow rate correction terms and temperature and rotation speed dual-dimensional correction terms. It uses shear stress, shear rate, real-time temperature, real-time flow rate and real-time rotation speed of stirring shaft (28) as inputs to calculate the real-time apparent viscosity of slurry. The solid content prediction model has a built-in temperature correction term and uses ultrasonic impedance, ultrasonic echo amplitude and real-time temperature as inputs to calculate the real-time solid content of the slurry. Both the apparent viscosity prediction model and the solid content prediction model were obtained by pre-calibration and fitting using standard samples of graphene conductive slurry.

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