Preparation method of rare earth ceramic pigment for building wall surface

Abstract

The invention is applicable to the field of preparation of rare earth ceramic pigments, and provides a preparation method of a rare earth ceramic pigment for building wall surfaces, which comprises the following steps: S1, weighing industrial neodymium oxide and aluminum oxide in equal proportion, adding water, mixing and grinding to obtain slurry A; s2, weighing yttrium oxide and aluminum hydroxide in equal proportion, adding water and chromium sesquioxide, and mixing and grinding to obtain slurry B; s3, mixing the slurry A obtained in the step S1 and the slurry B obtained in the step S2 to obtain slurry C; and S4, the slurry C is poured into a drying cylinder to be dried, a stirring mechanism is arranged in the drying cylinder to stir and heat the slurry C, and a spiral conveying mechanism in the drying cylinder drives the slurry C to be vertically conveyed. The problems that in a traditional drying process, due to the fact that the conveying speed is not matched with the heating uniformity, the drying efficiency is low, and materials are heated unevenly are solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of rare earth ceramic colorant preparation, and particularly relates to a preparation method of a rare earth ceramic colorant for building wall surfaces. BACKGROUND

[0002] In the field of building ceramic colorants, rare earth elements (such as neodymium and yttrium) are of great concern due to their unique color stability. However, the existing production process has significant defects: Raw material mixing problem: the density difference between industrial neodymium oxide (density 7.24 g / cm³) and aluminum oxide (density 3.95 g / cm³) is large, and traditional one-time mixing and grinding easily leads to sedimentation and stratification, resulting in uneven color development of the colorant after calcination.

[0003] Dry process control is rough: the fixed speed of the screw conveying mechanism cannot adapt to different slurry states (such as fluctuations in solid content and differences in particle distribution), resulting in mismatched heating times for materials in the drying cylinder. Overheating in some areas causes clumping, while low-temperature areas retain moisture, affecting the efficiency of subsequent calcination.

[0004] Low hot air utilization efficiency: conventional horizontal guide plates only change the falling direction and cannot form a dispersed material curtain, limiting the contact area between hot air and materials, and increasing drying energy consumption.

[0005] Although existing patents use vibration to assist drying, they do not solve the problem of multi-parameter coupling control, especially the lack of dynamic synergistic optimization of slurry physical properties, stirring intensity, and wind conditions. SUMMARY

[0006] The purpose of the embodiments of the present application is to provide a preparation method of a rare earth ceramic colorant for building wall surfaces, aiming to solve the problem of multi-parameter coupling control in existing patents, especially the lack of dynamic synergistic optimization of slurry physical properties, stirring intensity, and wind conditions.

[0007] The present application is implemented as follows: a preparation method of a rare earth ceramic colorant for building wall surfaces, comprising the following steps: S1: mixing and grinding industrial neodymium oxide and aluminum oxide in equal proportions with water to obtain slurry A; S2: mixing and grinding yttrium oxide and aluminum hydroxide with water and chromium trioxide to obtain slurry B; S3: mixing the slurry A obtained in S1 and the slurry B obtained in S2 to obtain slurry C; S4: pour the slurry C into the drying cylinder, the drying cylinder is provided with a stirring mechanism to stir and heat the slurry C, and a spiral conveying mechanism in the drying cylinder vertically conveys the slurry C, the upper end of the outer sleeve of the spiral conveying mechanism is provided with a guide plate, which can guide and disperse the slurry C when the slurry C is conveyed to a certain height, and the air drying mechanism in the drying cylinder air dries the falling slurry C; the drying cylinder is provided with a conveying speed optimization system, which can optimize the vertical conveying speed of the spiral conveying mechanism; S5: high-temperature calcination of the dried material, and grinding after cooling to room temperature to obtain a rare earth ceramic pigment finished product.

[0008] Further technical solutions, in S3, the molar ratio of neodymium oxide in the slurry A to the slurry B is 1:1.2.

[0009] Further technical solutions, the spiral conveying mechanism of the conveying speed optimization system optimizes the vertical conveying speed in the following manner: According to the solid content of the slurry C, the diameter particle distribution range between each solid raw material in the slurry C, and the density distribution range between each solid raw material, a slurry C state evaluation model is constructed, and a slurry C state evaluation coefficient is output; According to the stirring speed, heating temperature and vibration frequency of the stirring mechanism, a stirring state evaluation model is constructed, and a stirring state evaluation coefficient is output; According to the air flow speed, air flow temperature and inclination angle of the guide plate of the air drying mechanism, an air force state evaluation model is constructed, and an air force state evaluation coefficient is output; According to the slurry C state evaluation coefficient, the stirring state evaluation coefficient and the air force state evaluation coefficient, a heat uniformity evaluation model is constructed, and a heat uniformity evaluation coefficient of the slurry C is output; According to the initial power of the spiral conveying mechanism and the heat uniformity evaluation coefficient, a conveying rate adjustment model is constructed, and a target power of the spiral conveying mechanism is output.

[0010] Further technical solutions, the maximum diameter particle difference between each solid raw material is divided by a set diameter particle difference upper limit value to obtain a diameter particle distribution index of the solid raw material; the maximum density difference between each solid raw material is divided by a set density difference upper limit value to obtain a density distribution index of the solid raw material; The slurry C state evaluation model is: ; Wherein is a solid content correction coefficient, is a distribution range weight coefficient, and is greater than , is the solid content of the slurry , dimensionless, The particle size distribution index of the solid raw material, The density distribution index of the fixed raw material, The slurry The state evaluation coefficient.

[0011] Further technical solutions, the real-time rotating speed of the stirring mechanism is divided by the upper limit value of the stirring speed of the stirring mechanism to obtain the stirring speed index; the real-time heating temperature of the stirring mechanism is divided by the upper limit value of the heating temperature of the stirring mechanism to obtain the stirring temperature index; the vibration assembly is arranged in the stirring mechanism, the real-time vibration frequency of the vibration assembly is divided by the upper limit value of the vibration frequency of the vibration assembly to obtain the vibration frequency index; The stirring state evaluation model is: ; Among them And The speed weight coefficient, the temperature weight coefficient and the frequency weight coefficient respectively; The stirring speed index, The stirring temperature index, The vibration frequency index, The stirring state evaluation coefficient.

[0012] Further technical solutions, the real-time blowing speed of the air-drying mechanism is divided by the upper limit value of the blowing speed of the air-drying mechanism to obtain the airflow speed index; the blowing temperature of the air-drying mechanism is divided by the upper limit value of the blowing temperature of the air-drying mechanism to obtain the airflow temperature index; the difference between the inclination angle (0-90 degrees) of the guide plate and the 45-degree angle is taken as the absolute value and divided by the 45-degree angle to obtain the inclination angle index; The wind power state evaluation model is: ; Among them The speed-temperature coupling coefficient, The angle reference coefficient, The angle deviation penalty coefficient, The airflow speed index, The airflow temperature index, The inclination angle index of the guide plate, The wind power state evaluation coefficient.

[0013] Further technical solutions, the heating uniformity evaluation model is: ; Among them The slurry State leading weight, The stirring state leading weight, The wind power state leading weight, The synergistic enhancement coefficient, is a slurry state evaluation coefficient, stirring state evaluation coefficient, is a wind state evaluation coefficient, is a heating uniformity evaluation coefficient.

[0014] Further technical solutions, the conveying rate adjustment model is: ; wherein is an initial power, is a heating uniformity evaluation coefficient, is a reference uniformity, is a uniformity response sensitivity, is a power adjustment amplitude coefficient, is a target power.

[0015] Compared with the prior art, the beneficial effects of the present application are: The present application effectively suppresses the stratification phenomenon of the mixed slurry, and ensures the uniform distribution of rare earth elements and carriers through staged mixing. The combination of dynamic stirring and adjustable conveying speed avoids local overheating or moisture residue during drying, and the dispersed material curtain formed by the inclined guide plate significantly improves the hot air penetration efficiency. The final ceramic colorant presents stable color uniformity after calcination, while the drying energy consumption is reasonably controlled.

[0016] The present application solves the problem of uneven heating of slurry caused by insufficient adaptability of stirring intensity, temperature and vibration parameters in traditional process. By converting the dynamic parameters of stirring speed, temperature and vibration frequency into normalized indexes, and combining logarithmic and square operations to enhance the sensitivity of key parameters, the stirring state evaluation coefficient can reflect the matching degree of equipment operation state and slurry characteristics in real time, thereby avoiding local overheating or insufficient mixing.

[0017] The present application solves the problem of uneven dispersion of slurry C caused by insufficient contact between drying air flow and falling material curtain in traditional process, effectively improving the interaction efficiency of material and air flow during drying. By standardizing the air flow speed and temperature parameters, the interference of equipment specification difference on wind power evaluation is avoided, ensuring the comparability of parameters under different working conditions. After introducing the angle deviation penalty mechanism, the system can consider the influence of guide plate angle deviation on material dispersion trajectory, and compensate for the angle deviation by adjusting the wind power parameters, preventing local accumulation or uneven dispersion of materials.

[0018] The present application solves the problems of low drying efficiency and uneven heating of materials caused by mismatching of conveying speed and heating uniformity in traditional drying process. By dynamically adjusting the power of the screw conveying mechanism, the conveying speed of slurry C in the drying cylinder and the heating uniformity of slurry C are real-time adapted, ensuring the uniformity of material dispersion. Attached Figure Description

[0019] Figure 1 A schematic diagram of the preparation method of rare earth ceramic pigments for building walls; Figure 2 A flowchart illustrating the process of optimizing the conveying speed system. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0021] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0022] like Figure 1 The image shows a method for preparing rare earth ceramic pigments for building walls, provided by an embodiment of the present invention, comprising the following steps: S1: Weigh out industrial neodymium oxide and aluminum oxide in equal proportions, add water, mix and grind to obtain slurry A; S2: Weigh out yttrium oxide and aluminum hydroxide in equal proportions, add water and chromium trioxide, mix and grind to obtain slurry B; S3: Mix the slurry A obtained from S1 and the slurry B obtained from S2 to obtain slurry C; S4: Pour slurry C into the drying cylinder for drying. The drying cylinder is equipped with a stirring mechanism to stir and heat the slurry C. The screw conveyor mechanism in the drying cylinder drives the slurry C to be conveyed vertically. The upper end of the outer sleeve of the screw conveyor mechanism is inclined with a guide plate. After the slurry C is conveyed to a certain height, the guide plate can guide and disperse the slurry C. At this time, the air drying mechanism in the drying cylinder air dries the falling slurry C. The drying cylinder is equipped with a conveying speed optimization system, which can optimize the vertical conveying speed of the screw conveyor mechanism. S5: The dried material is calcined at high temperature and then cooled to room temperature before being ground and pulverized to obtain the rare earth ceramic pigment product.

[0023] In this embodiment, the stirring mechanism refers to a mechanical stirring device with a heating function, specifically a paddle-type stirrer combined with an electric heating element, used to maintain slurry flow and transfer heat. The screw conveyor mechanism refers to a vertical conveying device with screw blades, specifically a metal screw rod driven by a variable frequency motor, used to control the upward speed of the slurry. The guide plate refers to an inclined material guide plate, specifically a stainless steel plate fixed at an angle to the outlet side of the sleeve, used to convert the vertically conveyed slurry into a dispersed downward state. The conveying speed optimization system refers to a control system that adjusts the conveying power based on sensor data, specifically a PLC controller connected to a torque sensor and a motor frequency converter, used to dynamically match the conveying speed with drying requirements.

[0024] Specifically, neodymium oxide and alumina are first mixed to form slurry A, and yttrium oxide and aluminum hydroxide are mixed to form slurry B. This stepwise grinding reduces the risk of sedimentation and stratification due to density differences. During the secondary mixing of slurries A and B, chromium trioxide, acting as a colorant, is already uniformly dispersed in slurry B, preventing localized enrichment caused by subsequent additions. A stirring mechanism inside the drying drum continuously agitates the slurry to prevent agglomeration due to heat. A screw conveyor lifts the slurry to the guide plate, and the inclined plate surface creates a thin film of slurry, increasing the contact surface area with hot air. A conveyor speed optimization system adjusts the screw conveyor power according to the real-time drying status to ensure that the material's residence time in the drying drum matches the hot air conditions.

[0025] Compared to existing technologies, traditional processes, which mix multiple raw materials at once, lead to stratification due to density differences. A step-by-step mixing strategy, however, reduces the overall density gradient by pre-mixing raw materials with similar properties. Existing drying equipment, using a fixed conveyor speed, cannot adapt to the drying requirements of different slurry states. This solution dynamically adjusts the conveyor speed to ensure real-time adaptation of material dispersion to hot air conditions. Conventional guide plates are mostly horizontal baffles, only changing the direction of material descent, while inclined guide plates, through their angle design, generate centrifugal dispersion, improving heat exchange efficiency.

[0026] Through the above technical solution, this application effectively suppresses the stratification phenomenon of the mixed slurry, and ensures the uniform distribution of rare earth elements and carriers through staged mixing. The combination of dynamic stirring and adjustable conveying speed avoids local overheating or moisture residue during the drying process, and the dispersion curtain formed by the inclined guide plate significantly improves the hot air penetration efficiency. The final ceramic pigment exhibits stable color uniformity after calcination, while the drying energy consumption is reasonably controlled.

[0027] In a preferred embodiment of the present invention, in S3, the molar ratio of neodymium oxide in slurry A to slurry B is 1:1.2.

[0028] like Figure 2 As shown, in a preferred embodiment of the present invention, the conveying speed optimization system optimizes the vertical conveying speed of the screw conveyor mechanism in the following way: Based on the solid content of slurry C, the particle size distribution range among the solid raw materials in slurry C, and the density distribution range among the solid raw materials, a state evaluation model for slurry C is constructed, and the state evaluation coefficient of slurry C is output. A stirring state evaluation model is constructed based on the stirring speed, heating temperature, and vibration frequency of the stirring mechanism, and stirring state evaluation coefficients are output. A wind force state evaluation model is constructed based on the airflow velocity, airflow temperature and tilt angle of the guide plate of the air drying mechanism, and the wind force state evaluation coefficient is output. A heating uniformity evaluation model is constructed based on the slurry C state evaluation coefficient, stirring state evaluation coefficient, and wind force state evaluation coefficient, and the heating uniformity evaluation coefficient of slurry C is output. A conveying rate adjustment model is constructed based on the initial power and heating uniformity evaluation coefficient of the screw conveyor mechanism, and the target power of the screw conveyor mechanism is output.

[0029] In this embodiment, the slurry C-state evaluation model refers to a computational model that assesses the slurry C-stratification trend through solid content and particle characteristic parameters. The stirring state evaluation model refers to an evaluation system that quantifies the dynamic effect of stirring. The wind force state evaluation model refers to a computational model that assesses the matching degree between air-drying conditions and material dispersion. The heating uniformity evaluation model refers to a heat transfer efficiency evaluation model that comprehensively considers the interaction of multiple factors. The conveying rate adjustment model refers to a control algorithm that dynamically adjusts power based on uniformity.

[0030] Compared to existing technologies, traditional drying equipment typically uses a fixed-speed screw conveyor mechanism, which cannot respond to changes in the physical properties of slurry C. This solution, however, constructs a multi-parameter coupled real-time evaluation system. When neodymium oxide and alumina exhibit sedimentation tendencies due to density differences, it can automatically reduce the conveying speed to extend the dispersion time. Furthermore, when the viscosity of slurry C is affected by fluctuations in solid content, impacting its flowability, the vibration frequency of the stirring mechanism and the conveying power can be simultaneously adjusted to achieve coordinated control.

[0031] Through the above technical solution, this application effectively solves the problem of component segregation caused by material stratification during the drying process of rare earth pigments. When sedimentation occurs due to density differences in the mixed slurry of raw materials such as neodymium oxide and alumina, the residence time of the raw materials in the dispersion area is extended by adjusting the conveying speed. Simultaneously, it overcomes the technical defect of insufficient contact between hot air and the falling raw material curtain in traditional methods. Furthermore, the nonlinear power adjustment mechanism avoids the problem of slurry C accumulation caused by sudden speed changes, ensuring that the high-viscosity slurry C maintains a continuous and uniform material curtain morphology during the drying process.

[0032] In a preferred embodiment of the present invention, the particle size distribution index of the solid raw materials is obtained by dividing the maximum particle size difference between each solid raw material by a set upper limit value for particle size difference; the density distribution index of the solid raw materials is obtained by dividing the maximum density difference between each solid raw material by a set upper limit value for density difference. The C-state evaluation model for slurry is as follows: ; in This is the solid content correction factor. The distribution range weighting coefficient is denoted by , and All are greater than 0. For slurry Medium solids content, dimensionless. The particle size distribution index of solid raw materials. To fix the density distribution index of the raw materials, For slurry State evaluation coefficient.

[0033] In this embodiment, the solid content is the weight of each solid raw material divided by the weight of slurry C. The solid content of slurry C can be calculated based on the amount of each solid raw material and water added. The particle size distribution index characterizes the degree of particle size difference by the difference between the maximum particle size difference between each raw material and a set upper limit for particle size difference. The particle size can be measured using a laser particle size analyzer. The density distribution index reflects the influence of raw material density differences on stratification by the ratio of the maximum density difference to a set upper limit for density difference. The density of each raw material can be measured using a densitometer. Solid content correction coefficient. The effect of equilibrium solid concentration on dispersibility can be specifically determined experimentally by calibrating correction parameters for different solid contents. Distribution range weighting coefficient. To enhance the negative effects of particle size and density differences on slurry condition, the weight ratios can be determined through multi-factor orthogonal experiments.

[0034] Specifically, the slurry C-state evaluation model achieves dynamic control of drying parameters by quantifying the impact of differences in the physical properties of solid raw materials on mixing uniformity. Particle size distribution index. In the calculation, Presenting a positive value, The larger the density distribution index, the greater the dispersion of particle size; In the calculation, At the right time, A higher value reflects a stronger tendency for raw material stratification. The slurry C-state evaluation model combines the reciprocal of the solids content with a solids content correction coefficient. Multiplication reflects the negative impact of increased solids content on the C-state stability of the slurry. (Denominator term) The impact of particle size and density differences on slurry stability was comprehensively evaluated using a weighted summation method. The introduction of this method avoids calculation errors caused by a denominator of zero. The C-state evaluation model outputs the C-state evaluation coefficients for the slurry. It is positively correlated with the uniformity of slurry C, providing a quantitative basis for subsequent conveying speed adjustment.

[0035] Compared to existing technologies, traditional methods rely solely on visual inspection or simple viscosity tests to determine slurry condition, failing to quantitatively assess the impact of raw material physical property differences on the drying process. This solution establishes a mathematical model incorporating particle size distribution index and density distribution index to precisely capture the cumulative effect of particle size and density differences on slurry stratification tendency, enabling accurate adjustment of drying parameters.

[0036] Through the above technical solution, this application effectively solves the problem of uneven dispersion of solid raw materials in mixed slurry due to differences in particle size and density. By calculating the solid content, particle size distribution index, and density distribution index, the initial state of slurry C is evaluated, thereby improving the overall heating uniformity of the slurry during the drying process.

[0037] In a preferred embodiment of the present invention, the stirring speed index is obtained by dividing the real-time rotational speed of the stirring mechanism by the upper limit of the stirring speed of the stirring mechanism; the stirring temperature index is obtained by dividing the real-time heating temperature of the stirring mechanism by the upper limit of the heating temperature of the stirring mechanism; a vibration component is provided in the stirring mechanism, and the vibration frequency index is obtained by dividing the real-time vibration frequency of the vibration component by the upper limit of the vibration frequency of the vibration component. The stirring state evaluation model is as follows: ; in as well as These are the speed weighting coefficient, temperature weighting coefficient, and frequency weighting coefficient, respectively. as well as All are greater than 0. This refers to the stirring speed index. This refers to the stirring temperature index. The vibration frequency index, This is the coefficient for evaluating the stirring state.

[0038] In this embodiment, the stirring speed index refers to the ratio of real-time rotational speed to the maximum allowable rotational speed of the equipment, reflecting how close the current stirring intensity is to the equipment's limits. Specifically, it can be implemented using a speed sensor and controller to avoid excessively high speeds leading to increased energy consumption or excessively low speeds leading to insufficient mixing. The stirring temperature index refers to the ratio of real-time temperature to the maximum allowable temperature of the equipment, quantifying the impact of temperature on slurry flowability. Specifically, it can be implemented using thermocouples and a temperature control module to prevent temperature exceeding limits from causing component denaturation. The vibration frequency index refers to the ratio of real-time vibration frequency to the maximum allowable frequency of the equipment, characterizing the auxiliary effect of vibration on particle dispersion. Specifically, it can be implemented using a vibration sensor and a frequency regulator to avoid insufficient frequency causing material agglomeration. The logarithmic term in the stirring state evaluation model... Converting temperature to a thermodynamic temperature scale enhances sensitivity in high-temperature ranges; square term This amplifies the contribution of high-frequency vibrations to the dispersion effect.

[0039] Specifically, the stirring speed index dynamically determines whether the stirring intensity is within a reasonable range by monitoring the ratio of the rotation speed to its upper limit in real time. For example, it automatically reduces the speed when it approaches the upper limit to avoid overloading the equipment. The stirring temperature index normalizes real-time temperature data and combines it with a logarithmic function transformation, making the impact of temperature changes on the model output more significant at high temperatures. For example, when the temperature approaches the upper limit, the stirring state evaluation model will prioritize reducing the heating power to prevent local overheating. The vibration frequency index amplifies the effect of high-frequency vibration through square operations. For example, when the vibration frequency increases, its promoting effect on particle dispersion will be more significantly reflected in the evaluation coefficients. By combining and adjusting the speed weight coefficient, temperature weight coefficient, and frequency weight coefficient, the stirring state evaluation model can dynamically balance stirring intensity, heat transfer efficiency, and vibration dispersion effect. For example, when the viscosity of slurry C is high, the vibration weight can be increased to enhance the dispersion effect.

[0040] Compared to existing technologies, traditional processes improve drying results by simply adjusting the stirring speed or temperature, without considering the synergistic effect between vibration and parameters. For example, existing technologies may only start and stop the heating device based on a temperature threshold, while this solution achieves multi-parameter coupled control by quantifying the dynamic relationship between stirring speed, temperature, and vibration, thereby more accurately optimizing the uniformity of slurry heating.

[0041] Through the above technical solution, this application solves the problem of uneven slurry heating caused by insufficient adaptability of stirring intensity, temperature, and vibration parameters in traditional processes. By converting the dynamic parameters of stirring speed, temperature, and vibration frequency into normalized exponents, and combining logarithmic and square operations to enhance the sensitivity of key parameters, the stirring state evaluation coefficient can reflect the degree of matching between the equipment operating state and the slurry characteristics in real time, thereby avoiding local overheating or insufficient mixing. For example, when the viscosity of slurry C is high, the stirring state evaluation model enhances the vibration dispersion effect by increasing the weight of the vibration frequency exponent, preventing uneven drying caused by particle agglomeration; when the temperature is close to the safe threshold, the stirring state evaluation model reduces the heating power in a timely manner by improving the sensitivity of the temperature logarithmic term, ensuring the stability of the composition.

[0042] In a preferred embodiment of the present invention, the airflow velocity index is obtained by dividing the real-time blowing speed of the air-drying mechanism by the upper limit of the blowing speed of the air-drying mechanism; the airflow temperature index is obtained by dividing the blowing temperature of the air-drying mechanism by the upper limit of the blowing temperature of the air-drying mechanism; and the tilt angle index is obtained by taking the absolute value of the difference between the tilt angle (0-90 degrees) of the guide plate and the 45-degree angle and dividing it by the 45-degree angle. The wind state evaluation model is as follows: ; Where is the velocity-temperature coupling coefficient. As the angular reference coefficient, The penalty coefficient for angle deviation, as well as All are greater than 0. The airflow velocity index, The airflow temperature index. The tilt angle index of the guide plate. This is the wind force condition evaluation coefficient.

[0043] In this embodiment, the airflow velocity index is calculated by normalizing the ratio of real-time airflow velocity to the maximum wind speed of the equipment. This can be achieved using a combination of an airflow sensor and a controller, eliminating interference from different equipment specifications in wind speed assessment. The airflow temperature index is calculated by normalizing the ratio of real-time temperature to the maximum allowable temperature of the equipment. This can be achieved using a thermocouple and a temperature controller, balancing the dual impact of temperature on drying rate and material thermal stability. The tilt angle index is calculated by normalizing the deviation of the actual guide plate angle from the standard 45-degree angle. The guide plate tilt angle can be obtained based on the equipment model parameters, and the tilt angle index quantifies the degree of deviation in the material dispersion trajectory. The velocity-temperature coupling coefficient reflects the synergistic effect of airflow velocity and temperature on drying efficiency. This can be obtained through experimental or production data calibration, and is used to enhance heat transfer efficiency under high temperature and high wind speed conditions.

[0044] Specifically, during the descent of slurry C, the airflow velocity and temperature of the drying mechanism are monitored in real time and converted into dimensionless exponents, making the wind force parameters comparable under different operating conditions. The difference between the guide plate tilt angle and the standard angle is processed by absolute value and divided by 45 degrees to convert it into a tilt angle exponent in the range of 0-1. In the wind force state evaluation model, the velocity-temperature coupling term reflects the synergistic effect of the two on the drying rate through a product, while the angle deviation term uses an exponential function to nonlinearly penalize the degree of deviation.

[0045] Compared to existing technologies, traditional methods only dry materials by fixing wind speed and temperature, without considering the synergistic effect of these two factors on material dispersion, and cannot quantify the impact of angular deviation on drying efficiency. This solution establishes an evaluation model that includes a speed-temperature coupling term and an angular deviation penalty term, enabling multi-dimensional dynamic evaluation of wind parameters. In particular, it enhances the sensitivity of angular deviation to wind distribution through an exponential function.

[0046] Through the above technical solutions, this application solves the problem of uneven dispersion of slurry C caused by insufficient contact between the drying airflow and the falling material curtain in traditional processes, effectively improving the interaction efficiency between materials and airflow during the drying process. By standardizing the processing of airflow velocity and temperature parameters, the interference of equipment specification differences on wind force assessment is avoided, ensuring the comparability of parameters under different operating conditions. After introducing an angle deviation penalty mechanism, the system can consider the impact of guide plate angle deviation on the material dispersion trajectory and compensate for angle deviation by adjusting wind force parameters, preventing local accumulation or uneven dispersion of materials. The setting of the velocity-temperature coupling term enhances the heat transfer efficiency under high temperature and high wind speed conditions, improving the drying rate while avoiding surface agglomeration and internal moisture residue.

[0047] As a preferred embodiment of the present invention, the heating uniformity evaluation model is as follows: ; in The C state of the slurry is the dominant weight. The mixing state is the dominant weight. Wind force condition is the dominant weight. For the synergistic enhancement coefficient, as well as All are greater than 0. The C-state evaluation coefficient of the slurry. This is the coefficient for evaluating the stirring state. This is the wind force condition evaluation coefficient. This is the evaluation coefficient for heating uniformity.

[0048] In this embodiment, the slurry C state evaluation coefficient is a quantitative index reflecting the dispersion state of solid components in slurry C, used to characterize the influence of slurry C composition differences on heating uniformity. The stirring state evaluation coefficient is a dynamic parameter reflecting the mixing effect of the stirring mechanism on slurry C, used to characterize the degree to which mechanical stirring promotes heat transfer efficiency. The airflow state evaluation coefficient is a comprehensive parameter reflecting the air-drying mechanism's dispersion and heat exchange capacity of slurry C, used to characterize the regulating effect of airflow conditions on drying uniformity. The synergistic enhancement coefficient is a proportional parameter used to adjust the intensity of multi-factor interactions. Specifically, it can be achieved by calibrating the contribution of each coefficient product term to heating uniformity under different operating conditions through experiments or production experience, used to capture the nonlinear synergistic effect between slurry C state, stirring intensity, and airflow conditions.

[0049] Specifically, the C-state evaluation coefficient of the slurry quantifies the dispersion stability of solid particles in the slurry by combining the solid content correction coefficient with the inverse relationship between solid content and particle size distribution index and density distribution index. When the solid content is low and the particle size or density difference is small, the C-state evaluation coefficient of the slurry increases, indicating that the slurry itself is more easily heated uniformly. The stirring state evaluation coefficient is calculated by combining speed, temperature, and vibration parameters to reflect the enhancing effect of mechanical stirring on the internal heat conduction of the slurry. When the stirring speed is matched with the temperature and there is high-frequency vibration, the stirring state evaluation coefficient increases, indicating that the stirring process effectively promotes heat diffusion. The wind force state evaluation coefficient is calculated by multiplying the airflow speed and temperature, as well as the exponential decay of the guide plate angle deviation penalty term, to comprehensively evaluate the dispersion and coverage ability of the airflow on the falling slurry. The heating uniformity evaluation model linearly superimposes the above three coefficients and introduces the product term of the three as a synergistic correction term. The linear superposition part independently reflects the basic contribution of each factor, while the product term dynamically amplifies or suppresses the coupling effect of multiple factors. For example, when there are large differences in slurry composition, the product of a lower slurry C-state evaluation coefficient and the stirring and wind force coefficients can significantly improve the synergistic effect, thereby more accurately characterizing the changes in heating uniformity under complex working conditions.

[0050] Compared to existing technologies, traditional methods typically control the drying process using only a single parameter or static threshold, such as monitoring only the slurry moisture content or setting a fixed stirring speed. Existing technologies lack multi-dimensional dynamic coupling analysis of slurry composition, mechanical stirring, and wind conditions, resulting in low heat transfer efficiency during the drying process. This solution constructs a comprehensive evaluation model combining linear superposition and nonlinear synergy, achieving synergistic optimization of slurry characteristics, equipment operating parameters, and environmental conditions. In particular, the introduction of a three-factor product term as a synergistic correction term dynamically captures the interaction of various parameters under different operating conditions.

[0051] Through the above technical solution, this application solves the problem of drying stratification caused by differences in slurry composition and eliminates local overheating or under-drying caused by mismatch between stirring intensity and wind force parameters. By dynamically evaluating the heating uniformity under the coupled effects of multiple factors, it provides a precise basis for real-time adjustment of the screw conveyor speed, ensuring that slurries with different properties can obtain an optimized drying path. This heating uniformity evaluation model effectively improves the thermal energy utilization rate of the rare earth pigment drying process, avoids energy waste caused by parameter solidification in traditional methods, and ensures the color uniformity of the finished pigment after calcination.

[0052] As a preferred embodiment of the present invention, the conveying rate adjustment model is as follows: ; in For initial power, This is the coefficient for evaluating the uniformity of heating. As a baseline uniformity, For uniformity response sensitivity, This is the power regulation amplitude coefficient. All are greater than 0. Target power.

[0053] In this embodiment, the initial power This refers to the basic operating power of the screw conveyor mechanism without dynamic adjustment. It can be achieved through preset motor drive parameters to maintain the basic material conveying rate within the drying drum. The heating uniformity evaluation coefficient is a quantitative index calculated comprehensively based on slurry state, stirring intensity, and wind force parameters. It reflects the degree of heating uniformity of the slurry during the drying process. The benchmark uniformity refers to the preset target value for heating uniformity, which can be set through experimental data or process standards and serves as a reference for power adjustment. The uniformity response sensitivity is a parameter indicating the degree of influence of heating uniformity deviation on power adjustment. It can be adjusted by... This is achieved by controlling the response speed of the target power as uniformity changes. The power adjustment amplitude coefficient refers to the maximum allowable range parameter for power adjustment, which can be specifically limited... The range of values ​​is implemented to prevent power from exceeding the device's safety threshold.

[0054] Specifically, this technical solution dynamically correlates heating uniformity with conveying power through a nonlinear function. The initial power serves as an adjustment benchmark. When the heating uniformity evaluation coefficient deviates from the benchmark value, a hyperbolic tangent function maps the difference into a smooth power adjustment, avoiding sudden power changes caused by linear adjustment. The uniformity response sensitivity parameter controls the amplification factor of the deviation value, ensuring that small deviations trigger only slight power adjustments, while large deviations are limited by the saturation characteristics of the function. The power adjustment amplitude coefficient further limits the maximum adjustment range, ensuring equipment operational stability. Thus, the screw conveyor mechanism can adaptively adjust the conveying speed according to the real-time heating status. When the heating uniformity of slurry C is lower than the benchmark uniformity, the further the uniformity deviates from the benchmark, the higher the conveying speed of the screw conveyor mechanism, thereby improving the mixing degree of slurry C and enhancing its heating uniformity.

[0055] Compared to existing technologies, traditional drying processes use a fixed-power driven screw conveyor, which cannot adjust the conveying speed according to the material's state, making it difficult to simultaneously achieve drying efficiency and uniformity. This solution, however, establishes a dynamic correlation model between heating uniformity and target power, enabling real-time optimization of the conveying rate. Existing technologies that simply increase stirring intensity or extend drying time not only increase energy consumption but may also exacerbate material stratification. This solution, by quantitatively evaluating the heating state and precisely adjusting the power, improves drying efficiency while avoiding energy waste.

[0056] Through the above technical solution, this application solves the problems of low drying efficiency and uneven material heating caused by the mismatch between conveying speed and heating uniformity in traditional drying processes. By dynamically adjusting the power of the screw conveyor mechanism, the conveying speed of slurry C in the drying cylinder is matched with the heating uniformity of slurry C in real time, ensuring uniform material dispersion. At the same time, the nonlinear characteristics of the hyperbolic tangent function effectively suppress power abrupt changes, ensuring a stable and controllable conveying process, and providing a material basis for uniform drying in subsequent calcination processes.

[0057] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for preparing rare earth ceramic pigments for building walls, characterized in that, Includes the following steps: S1: Weigh out industrial neodymium oxide and aluminum oxide in equal proportions, add water, mix and grind to obtain slurry A; S2: Weigh out yttrium oxide and aluminum hydroxide in equal proportions, add water and chromium trioxide, mix and grind to obtain slurry B; S3: Mix the slurry A obtained from S1 and the slurry B obtained from S2 to obtain slurry C; S4: Pour slurry C into the drying cylinder for drying. The drying cylinder is equipped with a stirring mechanism to stir and heat the slurry C. The screw conveyor mechanism in the drying cylinder drives the slurry C to be conveyed vertically. The upper end of the outer sleeve of the screw conveyor mechanism is inclined with a guide plate. After the slurry C is conveyed to a certain height, the guide plate can guide and disperse the slurry C. At this time, the air drying mechanism in the drying cylinder air dries the falling slurry C. The drying cylinder is equipped with a conveying speed optimization system, which can optimize the vertical conveying speed of the screw conveyor mechanism. S5: The dried material is calcined at high temperature and then cooled to room temperature before being ground and pulverized to obtain the rare earth ceramic pigment product.

2. The method for preparing rare earth ceramic pigments for building walls according to claim 1, characterized in that, In S3, the molar ratio of neodymium oxide in slurry A to that in slurry B is 1:1.

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3. The method for preparing rare earth ceramic pigments for building walls according to claim 1, characterized in that, The conveying speed optimization system optimizes the vertical conveying speed of the screw conveyor mechanism in the following way: Based on the solid content of slurry C, the particle size distribution range among the solid raw materials in slurry C, and the density distribution range among the solid raw materials, a state evaluation model for slurry C is constructed, and the state evaluation coefficient of slurry C is output. A stirring state evaluation model is constructed based on the stirring speed, heating temperature, and vibration frequency of the stirring mechanism, and stirring state evaluation coefficients are output. A wind force state evaluation model is constructed based on the airflow velocity, airflow temperature and tilt angle of the guide plate of the air drying mechanism, and the wind force state evaluation coefficient is output. A heating uniformity evaluation model is constructed based on the slurry C state evaluation coefficient, stirring state evaluation coefficient, and wind force state evaluation coefficient, and the heating uniformity evaluation coefficient of slurry C is output. A conveying rate adjustment model is constructed based on the initial power and heating uniformity evaluation coefficient of the screw conveyor mechanism, and the target power of the screw conveyor mechanism is output.

4. The method for preparing rare earth ceramic pigments for building walls according to claim 3, characterized in that, The particle size distribution index of the solid raw materials is obtained by dividing the maximum particle size difference between each solid raw material by the set upper limit of particle size difference; the density distribution index of the solid raw materials is obtained by dividing the maximum density difference between each solid raw material by the set upper limit of density difference. The C-state evaluation model for slurry is as follows: ； in This is the solid content correction factor. The distribution range weighting coefficient is denoted by , and All are greater than 0. For slurry Medium solids content, The particle size distribution index of solid raw materials. The density distribution index of the fixed raw material, For slurry State evaluation coefficient.

5. The method for preparing rare earth ceramic pigments for building walls according to claim 4, characterized in that, The stirring speed index is obtained by dividing the real-time rotational speed of the stirring mechanism by the upper limit of the stirring speed of the stirring mechanism; the stirring temperature index is obtained by dividing the real-time heating temperature of the stirring mechanism by the upper limit of the heating temperature of the stirring mechanism; the stirring mechanism is equipped with a vibration component, and the vibration frequency index is obtained by dividing the real-time vibration frequency of the vibration component by the upper limit of the vibration frequency of the vibration component. The stirring state evaluation model is as follows: ； in as well as These are the speed weighting coefficient, temperature weighting coefficient, and frequency weighting coefficient, respectively. This refers to the stirring speed index. This refers to the stirring temperature index. The vibration frequency index, This is the coefficient for evaluating the stirring state.

6. The method for preparing rare earth ceramic pigments for building walls according to claim 5, characterized in that, The airflow velocity index is obtained by dividing the real-time blowing speed of the air-drying mechanism by the upper limit of the blowing speed of the air-drying mechanism; the airflow temperature index is obtained by dividing the blowing temperature of the air-drying mechanism by the upper limit of the blowing temperature of the air-drying mechanism; the tilt angle index is obtained by taking the absolute value of the difference between the tilt angle of the guide plate and the 45-degree angle and dividing it by the 45-degree angle. The wind state evaluation model is as follows: ； in The velocity-temperature coupling coefficient, As the angular reference coefficient, The penalty coefficient for angle deviation, The airflow velocity index, The airflow temperature index. The tilt angle index of the guide plate. This is the wind force condition evaluation coefficient.

7. The method for preparing rare earth ceramic pigments for building walls according to claim 6, characterized in that, The evaluation model for heat uniformity is as follows: ； in For slurry State dominates weights. The mixing state is the dominant weight. Wind force condition is the dominant weight. For the synergistic enhancement coefficient, For slurry Status evaluation coefficient This is the coefficient for evaluating the stirring state. This is the wind force condition evaluation coefficient. This is the evaluation coefficient for heating uniformity.

8. The method for preparing rare earth ceramic pigments for building walls according to claim 7, characterized in that, The conveying rate regulation model is as follows: ； in For initial power, This is the coefficient for evaluating the uniformity of heating. As a baseline uniformity, For uniformity response sensitivity, This is the power regulation amplitude coefficient. The target power.

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