Production monitoring system for functional water-based paint

Abstract

The invention relates to the technical field of visual monitoring of water-based paint production, in particular to a production monitoring system for functional water-based paint, which comprises a data access module for acquiring and storing bubble half-life period, high-temperature area ratio, carbon nanotube length-diameter ratio retention rate and inlet and outlet pressure value in real time; the slurry mixing module is used for determining whether the premixed slurry reaches the standard or not based on the bubble half-life period; the mixed analysis module is used for determining the influence degree of the carbon nano tube based on a shearing safety coefficient; the parameter adjusting module responds to the shearing safety coefficient and determines whether the dispersion state is qualified or not based on the length-diameter ratio retention rate of the carbon nanotubes; the production adjustment module is used for responding to the unqualified dispersion state, determining whether a dispersing agent is supplemented or not according to the state evaluation value and the bubble evaluation value, and determining the compensation amount of the carbon nano tube based on the length-diameter ratio retention rate of the carbon nano tube; and the filtering and canning module is used for determining whether to start secondary filtering and execute canning based on the filtering pressure difference value. The production quality of the water-based paint is improved.

Description

Technical Field

[0001] This invention relates to the field of visual monitoring technology for water-based coating production, and more particularly to a production monitoring system for functional water-based coatings. Background Technology

[0002] Functional waterborne conductive coatings, especially high-performance products using nanomaterials such as carbon nanotubes and graphene as conductive fillers, have significant application value in fields such as electronic shielding, antistatic agents, and flexible circuits. The quality of their core conductivity directly depends on whether the nano-conductive fillers can form a complete and efficient conductive network within the coating. The formation of this network requires not only excellent properties of the filler itself but also extreme precision in protecting the integrity of the filler's microstructure during the production process.

[0003] Quality control in the production process of water-based coatings mainly relies on manual experience, offline sampling and testing, and simple feedback control based on single process parameters. Especially in the dispersion process involving conductive nanofillers such as carbon nanotubes and graphene, traditional methods often fail to achieve real-time, online protection and control of their microstructural integrity due to the extreme sensitivity of nanomaterials to shear forces, localized overheating, and interfacial states. Common problems include: Subjective determination of the premixing endpoint: The premixing endpoint relies on manual observation of liquid surface foam or empirical timing, making it difficult to quantify the mixing uniformity. Insufficient mixing can easily cause filler agglomeration, while excessive mixing can introduce too many bubbles or prematurely damage the nanofiller structure.

[0004] Thermal and mechanical coupling damage during dispersion is difficult to monitor: During high-speed dispersion, local high temperature and high shear are prone to occur in the blade wake region, which increases the risk of carbon nanotube fracture under the synergistic effect. Existing methods are mostly limited to monitoring the overall temperature or motor load, and cannot identify the spatial distribution of high temperature areas, resulting in monitoring blind spots.

[0005] The assessment of the structural integrity of nanofillers is lagging: the dispersion state and aspect ratio of fillers such as carbon nanotubes are mostly determined by offline scanning electron microscopy analysis after production. The results lag behind the production line process, making real-time intervention impossible and easily leading to batch-specific functional failures.

[0006] Compensation by compensators relies on existing experience: Existing technologies often add dispersants or fillers in fixed proportions, lacking a precise and dynamic compensation mechanism based on the actual degree of damage, which can easily lead to inaccurate compensation amounts and affect product performance.

[0007] Chinese Patent Publication No. CN118409552A discloses a predictive control system and method for water-based coating production, specifically relating to the field of artificial intelligence algorithms. This invention employs an advanced Actor-Critic neural network model, which can adaptively learn and optimize multiple key parameters in the water-based coating production process. Through machine learning algorithms, the system can automatically adjust control strategies to adapt to the dynamic changes in the production process, reducing reliance on manual calibration and maintenance.

[0008] Therefore, the aforementioned predictive control system and method for water-based coating production has the following problems: While macroscopic process parameters such as reaction temperature and stirring speed can be optimized by establishing an objective function model, there is a lack of real-time monitoring and assessment of the microscopic level of shear damage and local overheating risk of water-based coatings.

[0009] It relies on offline data and model predictions, and lacks the ability to perceive and control the production process in real time and online. Summary of the Invention

[0010] Therefore, the present invention provides a production monitoring system for functional waterborne coatings to overcome the problem in the prior art that it is difficult to monitor and intelligently control the damage to nanofillers caused by thermal and mechanical coupling in the production of functional waterborne coatings.

[0011] To achieve the above objectives, the present invention provides a production monitoring system for functional water-based coatings, comprising: The data storage module is used to collect and store the bubble half-life, high-temperature region percentage, carbon nanotube aspect ratio retention rate, and inlet and outlet pressure values ​​within a preset collection range and duration. A slurry mixing module is used to determine whether the mixed slurry in the premixing tank meets the standards based on the bubble half-life and to determine the bubble evaluation value; The mixing analysis module is used to calculate the shear safety factor based on the bubble evaluation value and the high temperature region proportion value to determine the degree of influence of dispersion stirring on carbon nanotubes in the mixed slurry, so as to determine the state evaluation value; The parameter adjustment module, which responds to the state evaluation value, is used to determine whether the dispersion state of the carbon nanotubes in the mixed slurry is qualified based on the carbon nanotube aspect ratio retention rate. The production adjustment module responds to the unqualified dispersion state of the carbon nanotubes by determining whether to add a preset dose of dispersant based on the state evaluation value and the bubble evaluation value, and determines the compensation amount of the carbon nanotubes based on the carbon nanotube aspect ratio retention rate, so that the mixture of the compensator addition and mixing enters the filter state. The filtration and filling module, in response to the state of the mixed slurry to be filtered, calculates the filtration pressure difference based on the inlet and outlet pressure values ​​to determine whether to activate secondary filtration and fill the mixed coating.

[0012] Furthermore, the slurry mixing module determines that the mixed slurry in the premixing tank meets the standard based on the fact that the bubble half-life is less than a preset bubble half-life, and identifies it as the first bubble evaluation value, wherein, The first bubble evaluation value is the ratio of the preset bubble half-life to the bubble half-life.

[0013] Furthermore, if the bubble half-life of the slurry mixing module is greater than or equal to a preset bubble half-life, it is determined that the mixed slurry in the premixing tank does not meet the standard, and this is identified as a second bubble evaluation value. The second bubble evaluation value is the ratio of the preset bubble half-life to the bubble half-life plus the difference between the bubble half-life and the preset bubble half-life divided by the preset bubble half-life.

[0014] Furthermore, the mixing analysis module, based on the fact that the shear safety factor is less than a preset shear safety factor, determines that the degree of influence of dispersion stirring on carbon nanotubes is unqualified, and determines the state evaluation value as the second state evaluation value, wherein... The second state evaluation value is the ratio of the shear safety factor to the preset shear safety factor minus the difference between the preset shear safety factor and the shear safety factor divided by the preset shear safety factor.

[0015] Furthermore, the mixing analysis module, based on the shear safety factor being greater than or equal to a preset shear safety factor, determines that the degree of influence of dispersion stirring on carbon nanotubes is acceptable, and determines the state evaluation value as the first state evaluation value, wherein... The first state evaluation value is the ratio of the shear safety factor to the preset shear safety factor.

[0016] Furthermore, the parameter adjustment module determines that the dispersion state of the carbon nanotubes in the mixed slurry is qualified based on the carbon nanotube aspect ratio retention rate being greater than or equal to the preset carbon nanotube aspect ratio retention rate.

[0017] Furthermore, in response to the state evaluation value being the second state evaluation value, the parameter adjustment module determines that the dispersion state of the carbon nanotubes in the mixed slurry is unqualified based on the fact that the carbon nanotube aspect ratio retention rate is less than the preset carbon nanotube aspect ratio retention rate.

[0018] Furthermore, the production adjustment module determines to replenish a preset dose of dispersant based on the state evaluation value as the second state evaluation value and the bubble evaluation value as the second bubble evaluation value, wherein, The preset dosage is 0.1% of the mixed slurry mass, and the compensation amount of carbon nanotubes is negatively correlated with the carbon nanotube aspect ratio retention rate.

[0019] Furthermore, the filtration and filling module determines that the mixed slurry will not be filtered twice and performs filling based on the filtration pressure difference value being less than or equal to a preset filtration pressure difference value.

[0020] Furthermore, the filter filling module determines that secondary filtration of the mixed slurry is required based on the filtration differential pressure value being greater than the preset filtration differential pressure value.

[0021] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention achieves intelligent control of the production quality of water-based coatings through multi-module collaboration. The slurry mixing module calculates the bubble half-life based on liquid surface images, improving the objective judgment of the premixing uniformity endpoint. The mixing analysis module, based on the shear safety factor, realizes early warning of the risk of thermomechanical damage to carbon nanotubes during high-speed dispersion, avoiding potential structural damage to carbon nanotubes. The parameter adjustment module, based on the carbon nanotube aspect ratio retention rate, reduces the lag in the assessment of carbon nanotube structural quality. The production adjustment module intelligently decides and calculates the compensation amount of dispersant and carbon nanotubes, realizing on-demand compensation of the compensation agent. The filtration and bottling module adaptively activates secondary filtration based on the filtration pressure difference value, ensuring the purity of the water-based coating, thereby improving the quality reliability of functional water-based coatings.

[0022] Furthermore, this invention improves the accuracy of premixing endpoint determination by using a slurry mixing module to determine premixing compliance based on bubble half-life and generate bubble evaluation values. Based on whether the mixed slurry in the premixing tank meets the standards, the first bubble evaluation value and the second bubble evaluation value are calculated, which improves the sensitivity of early warning of mixing quality deterioration, avoids insufficient or excessive mixing due to human misjudgment, reduces the quality risk caused by uneven slurry, and thus improves the reliability of the premixing process.

[0023] Furthermore, the hybrid analysis module improves the spatial identification capability of overheating risk in the dispersion blade wake region based on the proportion of the high-temperature region, avoiding misjudgment of the overall heat load based on a single temperature measurement point. According to the shear force safety factor, it solves the monitoring blind spot of carbon nanotube fracture due to the synergistic effect of shear force and local overheating during high-speed dispersion, realizes the synergistic evaluation of mixing quality and heat dissipation efficiency, changes the passive mode of relying on post-event detection of carbon nanotube damage, reduces the risk of functional filler failure due to improper process, and ensures the reliability of the conductivity and other functions of water-based coatings.

[0024] Furthermore, this invention, through the parameter adjustment module responding to the state evaluation value to trigger electron microscopy detection, changes the traditional mode of offline, destructive sampling inspection for each batch of slurry, avoids production interruptions caused by invalid detection, reduces the production cost of water-based slurry, and transforms the structural monitoring of carbon nanotubes from post-event sampling inspection to online verification. Based on the comparison between the aspect ratio retention rate of carbon nanotubes and the preset aspect ratio retention rate of carbon nanotubes, it is determined whether carbon nanotubes have broken or been damaged during dispersion. Even if they appear to be dispersed in the slurry macroscopically, they have lost the high aspect ratio structure required as a functional filler, preventing functional failure caused by carbon nanotube breakage and a decrease in aspect ratio, ensuring the functionality of water-based coatings, and thus improving the production quality and economic benefits of water-based coatings.

[0025] Furthermore, the present invention uses the production adjustment module to jointly determine whether to trigger the replenishment of a preset dose of dispersant based on the state evaluation value and the bubble evaluation value, thus avoiding the ineffective addition of dispersant. It calculates the precise compensation amount of carbon nanotubes based on the carbon nanotube aspect ratio retention rate, thereby realizing the quantitative replenishment of carbon nanotubes according to the degree of damage. The filter filling module decides whether to activate secondary filtration based on the filtration pressure difference value, ensuring the purity of the water-based coating, avoiding unnecessary filtration losses and production delays, and ensuring the functional reliability and quality consistency of each batch of water-based coating. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the module connection for a production monitoring system for functional water-based coatings according to an embodiment of the present invention; Figure 2 This is a logic diagram illustrating whether the mixed slurry in the premixing tank meets the standards in an embodiment of the present invention. Figure 3 A logic diagram for determining whether the degree of influence of dispersion stirring on carbon nanotubes is acceptable in an embodiment of the present invention; Figure 4 To determine whether the dispersion state of carbon nanotubes in the mixed slurry is qualified for the embodiments of the present invention; Figure 5 This is an equipment connection diagram of the production monitoring system according to an embodiment of the present invention; In the diagram, 11-Premixing tank; 111-Premixing tank body; 112-Premixing agitator blade; 113-High-definition industrial camera; 12-High-speed disperser; 121-High-speed dispersion tank body; 122-High-speed dispersion blade; 123-Thermal infrared camera; 13-Slurry transfer tank; 131-Transfer tank body; 132-Low-speed agitator; 133-Compensator feeding port; 14-Filtration equipment; 141-Bag filter body; 142-Inlet pressure sensor; 143-Outlet pressure sensor; 144-Backup filter switching valve; 15-Filling machine; 151-Filling platform; 152-Quantitative filling head; 153-High-precision filling scale; 154-Filling controller. Detailed Implementation

[0027] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0028] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0029] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0030] Please see Figure 1 and Figure 5 As shown, Figure 1 This is a schematic diagram of the module connections for a production monitoring system for functional water-based coatings according to an embodiment of the present invention. Figure 5 This is a schematic diagram of the connection of the water-based coating production equipment according to an embodiment of the present invention.

[0031] This invention provides a production monitoring system for functional water-based coatings, comprising: The data storage module is used to collect and store the bubble half-life, high-temperature region percentage, carbon nanotube aspect ratio retention rate, and inlet and outlet pressure values ​​within a preset collection range and duration. The slurry mixing module, which is connected to the data storage module, is used to determine whether the mixed slurry in the premixing tank meets the standard based on the bubble half-life, and to determine the bubble evaluation value; A mixing analysis module, which is connected to the data storage module and the slurry mixing module respectively, is used to calculate the shear safety factor based on the bubble evaluation value and the high temperature region ratio value to determine the degree of influence of dispersion and stirring on carbon nanotubes in the mixed slurry, so as to determine the state evaluation value. The parameter adjustment module is connected to the data storage module and the hybrid analysis module respectively. In response to the state evaluation value, it is used to determine whether the dispersion state of carbon nanotubes in the hybrid slurry is qualified based on the carbon nanotube aspect ratio retention rate of the hybrid slurry. The production adjustment module is connected to the slurry mixing module, the mixing analysis module, and the parameter adjustment module respectively. In response to the unqualified dispersion state of the carbon nanotubes, it determines whether to add a preset dose of dispersant based on the state evaluation value and the bubble evaluation value, and determines the compensation amount of carbon nanotubes based on the carbon nanotube aspect ratio retention rate, so that the mixture of compensator addition and mixing enters the filtration state. The filtration and filling module is connected to the data storage module and the production adjustment module respectively. In response to the filtration status of the mixed slurry, it calculates the filtration pressure difference based on the inlet and outlet pressure values ​​to determine whether to activate secondary filtration and fill the mixed coating.

[0032] Specifically, this invention achieves intelligent control of waterborne coating production quality through multi-module collaboration. The slurry mixing module calculates the bubble half-life based on liquid surface images, improving the objective judgment of the premixing uniformity endpoint. The mixing analysis module, based on the shear safety factor, provides early warning of the risk of thermomechanical damage to carbon nanotubes during high-speed dispersion, avoiding potential structural damage to carbon nanotubes. The parameter adjustment module, based on the carbon nanotube aspect ratio retention rate, reduces the lag in assessing the structural quality of carbon nanotubes. The production adjustment module intelligently decides and calculates the compensation amount of dispersant and carbon nanotubes, enabling on-demand compensation of the compensating agent. The filtration and bottling module adaptively activates secondary filtration based on the filtration pressure difference, ensuring the purity of the waterborne coating and thus improving the quality reliability of functional waterborne coatings.

[0033] In this embodiment of the invention, the mixed slurry includes, but is not limited to, an aqueous resin matrix, carbon nanotube conductive filler, dispersant, wetting agent, defoamer, leveling agent, and deionized water, wherein the mass fraction of carbon nanotubes is 0.1% to 5%, the aqueous resin is an acrylic emulsion or a polyurethane dispersion, the dispersant is a polymeric dispersant, and the wetting agent is an organosilicon or alkynyl alcohol surfactant.

[0034] Specifically, the water-based coating production line includes a premixing tank 11, a high-speed disperser 12, a slurry transfer tank 13, a filtration device 14, and a filling machine 15.

[0035] In this embodiment of the invention, the premixing tank 11 includes a premixing tank body 111 for containing and initially mixing the slurry, a premixing stirring blade 112 disposed inside the premixing tank body 111, and a high-definition industrial camera 113 disposed on the side wall of the premixing tank body 111 for acquiring time-series images of the liquid surface. The rotational speed of the premixing stirring blade 112 is in the range of 50-300 rpm, which is used to achieve uniform wetting and initial dispersion of the raw materials. The high-definition industrial camera 113 acquires liquid surface images at a fixed frame rate and transmits them to a data storage module.

[0036] In this embodiment of the invention, the high-speed disperser 12 includes a high-speed dispersion tank 121 for receiving premixed slurry, a high-speed dispersion blade 122 disposed inside the high-speed dispersion tank 121, and a thermal infrared camera 123 installed on the side of the high-speed dispersion tank 121 for monitoring the temperature distribution in the blade wake region. The high-speed dispersion blade 122 rotates at a speed of 1000-5000 rpm to perform high-shear dispersion on the mixed slurry. The thermal infrared camera 123 is aimed at the vortex region behind the blade tip to acquire thermal infrared images in real time and transmit them to the data storage module and the mixing analysis module.

[0037] In this embodiment of the invention, the slurry turnover tank 13 includes a tank body 131 for receiving the slurry after high-speed dispersion, a low-speed agitator 132 disposed inside the tank body 131 for mixing the compensating agent, and a compensating agent inlet 133 disposed on the upper part of the tank body and connected to the automatic metering and adding system 134. The low-speed agitator 132 rotates at a speed range of 30-100 rpm to ensure uniform dispersion of the compensating agent. The compensating agent inlet 133 receives the control command from the production adjustment module.

[0038] In this embodiment of the invention, the filtration device 14 includes a bag filter body 141 for filtering out impurities in the slurry, an inlet pressure sensor 142 disposed on the inlet pipe of the filter body 141, an outlet pressure sensor 143 disposed on the outlet pipe, and a standby filter switching valve 144 connected in parallel with the inlet pipe. The inlet pressure sensor 142 and the outlet pressure sensor 143 monitor the pressure values ​​in real time and transmit them to the filter filling module for calculating the filtration pressure difference. The standby filter switching valve 144 responds to the instructions of the filter filling module to realize the automatic switching of the filtration path.

[0039] In this embodiment of the invention, the filling machine 15 includes a filling platform 151 for positioning and carrying packaging barrels, a quantitative filling head 152 disposed above the filling platform, a high-precision filling scale 153 connected to the filling head, and a filling controller 154 for controlling the filling process. The filling controller 154 receives filling instructions from the filter filling module and performs quantitative filling and barrel conveying.

[0040] In this embodiment of the invention, the thermal infrared image inside the high-speed disperser is the thermal infrared image of the vortex and wake region formed behind the blade tip. Due to the strong shearing action and the lag in fluid backflow, the vortex and wake region experience local temperature rise. Monitoring the vortex and wake region helps to identify whether the carbon nanotubes have suffered structural damage due to overheating. The thermal infrared camera has a sampling frequency of not less than 10Hz, a spatial resolution of not less than 320×240 pixels, and a temperature measurement range covering 30℃~120℃ to ensure that the temperature distribution of the slurry during the high-speed dispersion process can be captured.

[0041] In this embodiment of the invention, the compensating agent is carbon nanotubes or a dispersant. The dispersant is a polymeric dispersant, such as sodium polyacrylate, polycarboxylate, or modified polyether polymeric surfactants. Its molecular structure contains anchoring groups and solvation chains, which can be effectively adsorbed onto the surface of carbon nanotubes, improving their dispersion stability in aqueous systems. The dispersant is added in liquid form and injected through a precision metering pump to ensure rapid mixing with the mixed slurry.

[0042] In this embodiment of the invention, the original image of the carbon nanotubes was obtained by sampling scanning electron microscopy of the carbon nanotube raw material used in the preparation of water-based coatings. No less than 100 complete carbon nanotubes were randomly selected, and the arithmetic mean of the measured length and diameter was used as the initial average aspect ratio.

[0043] In this embodiment of the invention, the preset acquisition range is set to cover 80% of the diameter of the center area of ​​the liquid surface in the premixing tank for the liquid surface time sequence image acquisition area; the thermal infrared image acquisition range covers a 20cm×20cm area behind the rotating plane of the high-speed disperser blades; the pressure sensor is installed at the center of the inlet and outlet pipelines of the filtration equipment; the preset acquisition duration is set to 60s for the liquid surface time sequence image acquisition starting from the end of stirring; the thermal infrared image is continuously acquired during the high-speed dispersion stage; and the pressure value sampling interval is 1s.

[0044] Please see Figure 2 As shown, it is a logic judgment diagram for determining whether the mixed slurry in the premixing tank meets the standard in an embodiment of the present invention.

[0045] Specifically, the slurry mixing module calculates the bubble half-life based on the liquid surface time sequence image, and determines whether the mixed slurry in the premixing tank meets the standard by comparing the result with the preset bubble half-life, and determines the bubble evaluation value. If the bubble half-life is less than the preset bubble half-life, then the mixed slurry in the premix tank is determined to meet the standard and is determined as the first bubble evaluation value; If the bubble half-life is greater than or equal to the preset bubble half-life, the mixed slurry in the premix tank is determined to be substandard and is identified as the second bubble evaluation value.

[0046] In this embodiment of the invention, the calculation process of the bubble half-life is as follows: taking the moment when the stirring blade in the premixing tank stops rotating as the initial time, and continuously collecting time-series images of the liquid surface for a preset acquisition duration, performing binarization processing on each frame of the time-series images of the liquid surface in the premixing tank to distinguish the bubble region from the liquid background, and calculating the percentage of pixel area At occupied by the bubble region in each frame of the image, where t is the time counted from the initial time, and the percentage of bubble area corresponding to the initial time is denoted as A0. The time point t1 / 2 corresponding to the first drop of the percentage of pixel area At occupied by the bubble region from the initial time to 0.5A0 is the bubble half-life to be calculated.

[0047] In this embodiment of the invention, the preset bubble half-life ranges from [5s, 40s], preferably set to 15s, but the above value is not limited to this, and those skilled in the art can adjust the value according to actual needs.

[0048] In this embodiment of the invention, the first bubble evaluation value is the ratio of the preset bubble half-life to the bubble half-life, and the second bubble evaluation value is the result of the ratio of the preset bubble half-life to the bubble half-life plus the difference between the bubble half-life and the preset bubble half-life divided by the preset bubble half-life.

[0049] Specifically, this invention improves the accuracy of premixing endpoint determination by using a slurry mixing module to determine premixing compliance based on bubble half-life and generate bubble evaluation values. Based on whether the mixed slurry in the premixing tank meets the standards, the first bubble evaluation value and the second bubble evaluation value are calculated, which improves the sensitivity of early warning of mixing quality deterioration, avoids insufficient or excessive mixing due to human misjudgment, reduces the quality risk caused by uneven slurry, and thus improves the reliability of the premixing process.

[0050] Please see Figure 3 As shown, it is a logic judgment diagram for determining whether the degree of influence of dispersion and stirring on carbon nanotubes is qualified in an embodiment of the present invention.

[0051] Specifically, the mixing analysis module determines the proportion of the high-temperature region in the wake area of ​​the mixed slurry where the blade tip of the high-speed disperser passes through the thermal infrared image, calculates the shear safety factor based on the bubble evaluation value and the proportion of the high-temperature region, and determines the degree of influence of dispersion and stirring on carbon nanotubes by comparing the result with the preset shear safety factor, so as to determine the state evaluation value. If the shear safety factor is greater than or equal to the preset shear safety factor, then the degree of influence of dispersion and stirring on carbon nanotubes is determined to be qualified, and the state evaluation value is determined to be the first state evaluation value. If the shear safety factor is less than the preset shear safety factor, then the degree of influence of dispersion and stirring on carbon nanotubes is determined to be unqualified, and the state evaluation value is determined to be the second state evaluation value.

[0052] In this embodiment of the invention, the process of determining the proportion of the high-temperature region is as follows: based on the thermal infrared image of the high-speed disperser during operation, the blades at known positions are image-calibrated in a stationary state. The trail area swept by the blade tip in the image is determined as the analysis region. The high-temperature threshold of the mixed slurry is set according to the thermal stability of carbon nanotubes and process requirements. All pixels in the analysis region with a temperature greater than or equal to the high-temperature threshold are identified and counted. The proportion of the high-temperature region is the ratio of all pixels in the analysis region with a temperature greater than or equal to the high-temperature threshold to all pixels in the analysis region.

[0053] In this embodiment of the invention, the temperature range of the high-temperature alarm threshold is [50℃, 65℃], preferably set to 55℃, but the above value is not limited to this, and those skilled in the art can also adjust the value according to actual needs.

[0054] In this embodiment of the invention, the shear safety factor is the ratio of the bubble evaluation value to the proportion of the high-temperature region.

[0055] In this embodiment of the invention, the preset shear safety factor ranges from [2, 10], and is preferably set to 5. However, the above value is not limited to this, and those skilled in the art can adjust the value according to actual needs.

[0056] In this embodiment of the invention, the first state evaluation value is the ratio of the shear safety factor to the preset shear safety factor, and the second state evaluation value is the result of the ratio of the shear safety factor to the preset shear safety factor minus the difference between the preset shear safety factor and the preset shear safety factor divided by the preset shear safety factor.

[0057] Specifically, based on the state evaluation value of the mixing analysis module as the first state evaluation value, the mixture is triggered to enter the filtration equipment to generate water-based coating and then bottle it.

[0058] Specifically, the hybrid analysis module improves the spatial identification capability of overheating risk in the dispersion blade wake region based on the proportion of the high-temperature region, avoiding misjudgment of the overall heat load based on a single temperature measurement point. According to the shear force safety factor, it solves the monitoring blind spot of carbon nanotube fracture due to the synergistic effect of shear force and local overheating during high-speed dispersion, realizes the synergistic evaluation of mixing quality and heat dissipation efficiency, changes the passive mode of relying on post-event detection of carbon nanotube damage, reduces the risk of functional filler failure due to improper process, and ensures the reliability of the conductivity and other functions of water-based coatings.

[0059] Please see Figure 4 As shown, this is an embodiment of the present invention for determining whether the dispersion state of carbon nanotubes in the mixed slurry is qualified.

[0060] Specifically, the parameter adjustment module responds to the state evaluation value, determines the carbon nanotube aspect ratio retention rate based on the scanning electron microscope image of the mixed slurry, and compares it with the preset carbon nanotube aspect ratio retention rate to determine whether the dispersion state of the carbon nanotubes in the mixed slurry is qualified. If the carbon nanotube aspect ratio retention rate is greater than or equal to the preset carbon nanotube aspect ratio retention rate, then the dispersion state of the carbon nanotubes in the mixed slurry is determined to be qualified. If the carbon nanotube aspect ratio retention rate is less than the preset carbon nanotube aspect ratio retention rate, then the dispersion state of the carbon nanotubes in the mixed slurry is determined to be unqualified.

[0061] In this embodiment of the invention, the parameter adjustment module triggers precise detection of the structural integrity of carbon nanotubes based on the state evaluation value of the mixing analysis module as the second state evaluation value. The principle is that carbon nanotubes, as functional fillers in water-based coatings, have an aspect ratio that is a key structural parameter determining the final electrical and thermal conductivity properties of the coating. During high-speed dispersion, excessive shear force and localized high temperature can easily cause carbon nanotubes to break, reducing their aspect ratio and thus impairing the coating's intended function.

[0062] In this embodiment of the invention, the process of acquiring the scanning electron microscope (SEM) image of the mixed slurry is as follows: 10 ml of the mixed slurry is taken from the outlet of the high-speed disperser, diluted and dispersed with deionized water, dried, sputter-coated with gold, and then placed under a scanning electron microscope to acquire at least 5 SEM images.

[0063] In this embodiment of the invention, the process for determining the aspect ratio retention rate of carbon nanotubes is as follows: at least 50 complete carbon nanotubes are randomly selected from scanning electron microscope images, their average length and average diameter are measured, and the average aspect ratio of the carbon nanotubes is calculated. The aspect ratio retention rate of carbon nanotubes is determined by the ratio of the average aspect ratio of the carbon nanotubes to the initial average aspect ratio of the raw materials used to prepare this batch of carbon nanotubes.

[0064] In this embodiment of the invention, the range of the preset carbon nanotube aspect ratio retention rate is [80%, 95%], preferably set to 85%, but the above value is not limited to this, and those skilled in the art can also adjust the value according to actual needs.

[0065] Specifically, this invention, through the parameter adjustment module responding to the state evaluation value to trigger electron microscopy detection, changes the traditional mode of offline, destructive sampling inspection for each batch of slurry, avoids production interruptions caused by invalid detection, reduces the production cost of water-based slurry, and transforms the structural monitoring of carbon nanotubes from post-event sampling inspection to online verification. Based on the comparison between the aspect ratio retention rate of carbon nanotubes and the preset aspect ratio retention rate of carbon nanotubes, it is determined whether carbon nanotubes have broken or been damaged during dispersion. Even if they appear to be dispersed in the slurry macroscopically, they have lost the high aspect ratio structure required as a functional filler, preventing functional failure caused by carbon nanotube breakage and a decrease in aspect ratio, ensuring the functionality of water-based coatings, and thus improving the production quality and economic benefits of water-based coatings.

[0066] Specifically, in response to the unqualified dispersion state of the carbon nanotubes, the production adjustment module determines whether to add a preset dose of dispersant based on the state evaluation value and the bubble evaluation value, and determines the compensation amount of the carbon nanotubes based on the carbon nanotube aspect ratio retention rate, so that the mixture of the compensator addition and mixing enters the filter-ready state. If the state evaluation value is the second state evaluation value and the bubble evaluation value is the second bubble evaluation value, then it is determined to supplement the preset dose of dispersant; If the state evaluation value is the first state evaluation value or the bubble evaluation value is the first bubble evaluation value, then it is determined that no dispersant should be added.

[0067] In this embodiment of the invention, the preset dosage is preferably set to 0.05% to 0.3% of the mass of the mixed slurry, and more preferably to 0.1% of the mass of the mixed slurry. However, the above values ​​are not limited to these, and those skilled in the art can adjust the values ​​according to actual needs.

[0068] In this embodiment of the invention, the compensation amount of the carbon nanotubes is the product of the original amount of carbon nanotubes added in the batch of slurry formulation and 1 minus the carbon nanotube aspect ratio retention rate.

[0069] In this embodiment of the invention, after the production adjustment module determines the type and dosage of the compensator, it generates a feeding control instruction containing the compensator name, the compensator mass and the target container, and sends the control instruction to the automatic metering and adding system of the production line.

[0070] In this embodiment of the invention, the automatic metering and adding system responds to the control command by controlling a precision loss-in-weight scale to quantitatively inject a determined mass of dispersant and carbon nanotubes into a slurry transfer tank located before the filtration process. After the addition of the compensating agent is completed, the stirring blades of the slurry transfer tank are activated to circulate and stir for 3 to 5 minutes to ensure that the compensating agent is uniformly dispersed in the mixed slurry. After the mixing time is reached, the system automatically determines that the mixed slurry has completed the compensation process and updates the status to the state of awaiting filtration.

[0071] Specifically, the filter filling module responds to the state of the mixed slurry to be filtered by calculating the filtration pressure difference value based on the inlet and outlet pressure values ​​of the mixed slurry entering and exiting the filter equipment to determine whether to activate secondary filtration and fill the mixed coating. If the filtration differential pressure is less than or equal to the preset filtration differential pressure, then the mixed slurry will not be used for secondary filtration and will be bottled. If the filtration differential pressure value is greater than the preset filtration differential pressure value, then the mixed slurry will be used for secondary filtration.

[0072] In this embodiment of the invention, the filtration pressure difference is the difference between the pressure value at the inlet of the filtration device and the pressure value at the outlet of the filtration device.

[0073] In this embodiment of the invention, the preset filter pressure difference value is in the range of [0.1 MPa, 0.3 MPa], preferably set to 0.2 MPa, but the above value is not limited to this, and those skilled in the art can adjust the value according to actual needs.

[0074] In this embodiment of the invention, when the filtration and filling module determines that secondary filtration is to be activated, it generates a control command to switch to the backup filtration path. The control command controls the backup filter switching valve on the production pipeline to switch, guiding the filtered mixed slurry to the parallel backup filtration device. The mixed slurry is switched to flow to the backup filtration device, the inlet pressure monitoring of the backup filtration device is activated, and the real-time filtration pressure difference is recalculated. The filtration cycle is carried out in the backup filtration device until the filtration pressure difference is stable and less than or equal to the preset filtration pressure difference value. The system determines that secondary filtration is completed and the mixed slurry has reached the cleanliness level suitable for filling.

[0075] In this embodiment of the invention, the filling process is as follows: the filter filling module generates a filling permission instruction and sends it to the filling machine. The filling permission instruction triggers the filling machine to prepare, including positioning the empty packaging barrel and the filling head. The system monitors the weight feedback of the filling scale in real time, performs quantitative filling, and after the filled packaging barrel is sealed, it is moved out of the workstation by the conveyor belt. At the same time, the system updates the production batch record and marks the completion of the production of this batch of water-based coatings.

[0076] Specifically, the present invention uses the production adjustment module to determine whether to trigger the replenishment of a preset dose of dispersant based on the state evaluation value and the bubble evaluation value, thus avoiding the ineffective addition of dispersant. It calculates the precise compensation amount of carbon nanotubes based on the carbon nanotube aspect ratio retention rate, realizing the quantitative replenishment of carbon nanotubes according to the degree of damage. The filter filling module decides whether to activate secondary filtration based on the filtration pressure difference value, ensuring the purity of water-based coatings, avoiding unnecessary filtration losses and production delays, and ensuring the functional reliability and quality consistency of each batch of water-based coatings.

[0077] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A production monitoring system for functional water-based coatings, characterized in that, include: The data storage module is used to collect and store the bubble half-life, high-temperature region percentage, carbon nanotube aspect ratio retention rate, and inlet and outlet pressure values ​​within a preset collection range and duration. A slurry mixing module is used to determine whether the mixed slurry in the premixing tank meets the standards based on the bubble half-life and to determine the bubble evaluation value; The mixing analysis module is used to calculate the shear safety factor based on the bubble evaluation value and the high temperature region proportion value to determine the degree of influence of dispersion stirring on carbon nanotubes in the mixed slurry, so as to determine the state evaluation value; The parameter adjustment module, which responds to the state evaluation value, is used to determine whether the dispersion state of the carbon nanotubes in the mixed slurry is qualified based on the carbon nanotube aspect ratio retention rate. The production adjustment module responds to the unqualified dispersion state of the carbon nanotubes by determining whether to add a preset dose of dispersant based on the state evaluation value and the bubble evaluation value, and determines the compensation amount of the carbon nanotubes based on the carbon nanotube aspect ratio retention rate, so that the mixture of the compensator addition and mixing enters the filter state. The filtration and filling module, in response to the state of the mixed slurry to be filtered, calculates the filtration pressure difference based on the inlet and outlet pressure values ​​to determine whether to activate secondary filtration and fill the mixed coating.

2. The production monitoring system for functional water-based coatings according to claim 1, characterized in that, The slurry mixing module determines that the mixed slurry in the premixing tank meets the standard based on the fact that the bubble half-life is less than a preset bubble half-life, and identifies it as the first bubble evaluation value. The first bubble evaluation value is the ratio of the preset bubble half-life to the bubble half-life.

3. The production monitoring system for functional water-based coatings according to claim 1, characterized in that, If the bubble half-life of the slurry mixing module is greater than or equal to a preset bubble half-life, it is determined that the mixed slurry in the premixing tank does not meet the standard, and this is identified as a second bubble evaluation value. The second bubble evaluation value is the ratio of the preset bubble half-life to the bubble half-life plus the difference between the bubble half-life and the preset bubble half-life divided by the preset bubble half-life.

4. The production monitoring system for functional water-based coatings according to claim 1, characterized in that, The mixing analysis module, based on the fact that the shear safety factor is less than a preset shear safety factor, determines that the degree of influence of dispersion stirring on carbon nanotubes is unqualified, and determines the state evaluation value as the second state evaluation value, wherein... The second state evaluation value is the ratio of the shear safety factor to the preset shear safety factor minus the difference between the preset shear safety factor and the shear safety factor divided by the preset shear safety factor.

5. The production monitoring system for functional water-based coatings according to claim 1, characterized in that, The mixing analysis module determines that the degree of influence of dispersion stirring on carbon nanotubes is acceptable based on the shear safety factor being greater than or equal to a preset shear safety factor, and determines the state evaluation value as the first state evaluation value. The first state evaluation value is the ratio of the shear safety factor to the preset shear safety factor.

6. The production monitoring system for functional water-based coatings according to claim 1, characterized in that, The parameter adjustment module determines that the dispersion state of carbon nanotubes in the mixed slurry is qualified based on the carbon nanotube aspect ratio retention rate being greater than or equal to the preset carbon nanotube aspect ratio retention rate.

7. The production monitoring system for functional water-based coatings according to claim 4, characterized in that, The parameter adjustment module responds to the state evaluation value as the second state evaluation value, and determines that the dispersion state of the carbon nanotubes in the mixed slurry is unqualified based on the fact that the carbon nanotube aspect ratio retention rate is less than the preset carbon nanotube aspect ratio retention rate.

8. The production monitoring system for functional water-based coatings according to claim 7, characterized in that, The production adjustment module determines the amount of dispersant to be added based on the state evaluation value (second state evaluation value) and the bubble evaluation value (second bubble evaluation value). The preset dosage is 0.1% of the mixed slurry mass, and the compensation amount of carbon nanotubes is negatively correlated with the carbon nanotube aspect ratio retention rate.

9. The production monitoring system for functional water-based coatings according to claim 1, characterized in that, The filtration and filling module determines that secondary filtration of the mixed slurry will not be enabled and performs filling based on the filtration pressure difference value being less than or equal to the preset filtration pressure difference value.

10. The production monitoring system for functional water-based coatings according to claim 1, characterized in that, The filter filling module determines that secondary filtration of the mixed slurry is required based on the filtration differential pressure value being greater than the preset filtration differential pressure value.

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