A titanium dioxide intelligent grinding control method and device

Abstract

The present application provides a titanium dioxide intelligent grinding control method and device, which relates to the field of grinding control technology, including: receiving grinding machine control parameters and grinding environment control parameters; obtaining particle dispersion quality coefficient; obtaining standard titanium dioxide particle CIE Lab color space; performing particle color prediction, obtaining comparison titanium dioxide particle CIE Lab color space; obtaining particle color quality coefficient; when the particle dispersion quality coefficient meets the dispersion quality coefficient threshold, and the particle color quality coefficient meets the color quality coefficient threshold, the titanium dioxide grinding equipment is initialized according to the grinding machine control parameters and the grinding environment control parameters. The present application can solve the technical problems in the prior art that the grinding cannot be pre-judged, and adjustments are made when quality problems occur, resulting in large raw material consumption and poor grinding quality, and achieve the technical effect of ensuring the stability of the grinding process and the consistency of product quality.

Description

Technical Field

[0001] The present application relates to the field of grinding control technology, and in particular to an intelligent grinding control method and device for titanium dioxide. Background Art

[0002] Titanium dioxide (TiO2) is a white pigment widely used in coatings, plastics, papermaking, cosmetics and other fields. Its quality directly affects the performance of the final product. Grinding is one of the key steps in the production process of titanium dioxide. The purpose is to grind the rough particles into a suitable particle size range to ensure its hiding power and glossiness in the application.

[0003] Traditional titanium dioxide grinding control methods mainly rely on manual experience and simple mechanical control, lacking real-time monitoring and feedback adjustment during the grinding process. Since the particle size and color of titanium dioxide are very sensitive to grinding conditions (such as temperature, pH value, grinding media, etc.), it is difficult for traditional methods to accurately control these parameters, resulting in large fluctuations in the quality of the final product. Especially in large-scale production, it is impossible to adjust process parameters in time to cope with raw material fluctuations and changes in equipment performance. Problems often need to be discovered in subsequent quality inspections and then remedied, which reduces production efficiency.

[0004] In summary, the prior art has the technical problem that it is impossible to predict the grinding in advance and to make adjustments when quality problems occur, resulting in large consumption of raw materials and poor grinding quality. Summary of the invention

[0005] The purpose of this application is to provide an intelligent grinding control method and device for titanium dioxide, so as to solve the technical problems in the prior art that grinding cannot be predicted in advance and adjustments are made when quality problems occur, resulting in large raw material consumption and poor grinding quality.

[0006] In view of the above problems, the present application provides an intelligent grinding control method and device for titanium dioxide.

[0007] In the first aspect, the present application provides an intelligent grinding control method for titanium dioxide, which is implemented by an intelligent grinding control device for titanium dioxide, including: receiving grinding mechanical control parameters and grinding environment control parameters from titanium dioxide grinding equipment, wherein the grinding environment control parameters include grinding temperature control timing information and grinding pH value control timing information; predicting particle dispersion according to the grinding mechanical control parameters, the grinding temperature control timing information and the grinding pH value control timing information, and obtaining a particle dispersion quality coefficient; obtaining a CIE Lab color space of standard titanium dioxide particles; predicting particle color according to the grinding temperature control timing information and the particle dispersion quality coefficient, and obtaining a CIE Lab color space of comparative titanium dioxide particles; and predicting particle color according to the CIELab color space of the standard titanium dioxide particles and the CIE Lab color space is analyzed to obtain the particle color quality coefficient; when the particle dispersion quality coefficient meets the dispersion quality coefficient threshold, and the particle color quality coefficient meets the color quality coefficient threshold, the titanium dioxide grinding equipment is initialized according to the grinding machine control parameters and the grinding environment control parameters, and then trial production is carried out. When the trial production verification is passed, mass production is started.

[0008] In the second aspect, the present application also provides an intelligent titanium dioxide grinding control device for executing an intelligent titanium dioxide grinding control method as described in the first aspect, including: a parameter receiving module, for receiving grinding mechanical control parameters and grinding environment control parameters from titanium dioxide grinding equipment, wherein the grinding environment control parameters include grinding temperature control timing information and grinding pH value control timing information; a particle dispersion prediction module, for predicting particle dispersion according to the grinding mechanical control parameters, the grinding temperature control timing information and the grinding pH value control timing information, and obtaining a particle dispersion quality coefficient; a standard color space acquisition module, for obtaining a standard titanium dioxide particle CIE Lab color space; a particle color prediction module, for predicting particle color according to the grinding temperature control timing information and the particle dispersion quality coefficient, and obtaining a comparison titanium dioxide particle CIE Lab color space; a particle color quality analysis module, for predicting particle color according to the standard titanium dioxide particle CIE Lab color space and the comparison titanium dioxide particle CIE Lab color space is analyzed to obtain the particle color quality coefficient; an equipment initialization module is used to initialize the titanium dioxide grinding equipment according to the grinding machine control parameters and the grinding environment control parameters when the particle dispersion quality coefficient meets the dispersion quality coefficient threshold and the particle color quality coefficient meets the color quality coefficient threshold, and then conduct trial production; when the trial production verification is passed, mass production begins.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] 1. Receive grinding machine control parameters and grinding environment control parameters from titanium dioxide grinding equipment, wherein the grinding environment control parameters include grinding temperature control timing information and grinding pH value control timing information; predict particle dispersion according to the grinding machine control parameters, the grinding temperature control timing information and the grinding pH value control timing information to obtain a particle dispersion quality coefficient; obtain a standard titanium dioxide particle CIE Lab color space; predict particle color according to the grinding temperature control timing information and the particle dispersion quality coefficient to obtain a comparison titanium dioxide particle CIE Lab color space; analyze according to the standard titanium dioxide particle CIE Lab color space and the comparison titanium dioxide particle CIE Lab color space to obtain a particle color quality coefficient; when the particle dispersion quality coefficient meets the dispersion quality coefficient threshold and the particle color quality coefficient meets the color quality coefficient threshold, conduct trial production after initializing the titanium dioxide grinding equipment according to the grinding machine control parameters and the grinding environment control parameters, and start mass production after the trial production verification is passed. By receiving the grinding machine control parameters and environmental control parameters in real time, the particle dispersion is predicted, the particle dispersion quality coefficient is calculated, the color is predicted by combining the dispersion quality coefficient and temperature control information, and compared and analyzed with the standard color space to obtain the particle color quality coefficient. When the dispersion and color quality both reach the threshold, the grinding equipment is initialized according to these parameters to achieve the technical effect of ensuring the stability of the grinding process and the consistency of product quality.

[0011] 2. When the particle dispersion quality coefficient does not meet the dispersion quality coefficient threshold, or / and the particle color quality coefficient does not meet the color quality coefficient threshold, multi-sample point optimization is performed on the grinding machine control parameters and the grinding environment control parameters to obtain updated grinding machine control parameters and updated grinding environment control parameters; the titanium dioxide grinding equipment is initialized according to the updated grinding machine control parameters and the updated grinding environment control parameters, and the grinding process is dynamically adjusted and optimized to ensure that the particle dispersion and color quality of the titanium dioxide meet the expected standards, thereby improving the consistency and stability of the product and ensuring the technical effect of the grinding quality of the titanium dioxide.

[0012] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0014] Figure 1 A schematic diagram of a process for intelligent grinding control of titanium dioxide in this application;

[0015] Figure 2 This is a structural schematic diagram of an intelligent grinding control device for titanium dioxide in this application.

[0016] Description of reference numerals:

[0017] Parameter receiving module 11, particle dispersion prediction module 12, standard color space acquisition module 13, particle color prediction module 14, particle color quality analysis module 15, equipment initialization module 16. DETAILED DESCRIPTION

[0018] This application provides an intelligent grinding control method and device for titanium dioxide, which solves the technical problem in the prior art that the grinding cannot be pre-judged and adjustments are made when quality problems occur, resulting in large raw material consumption and poor grinding quality. By receiving the grinding machine control parameters and environmental control parameters in real time, the particle dispersibility is predicted, the particle dispersion quality coefficient is calculated, the color is predicted by combining the dispersion quality coefficient and temperature control information, and the particle color quality coefficient is obtained by comparison and analysis with the standard color space. When the dispersibility and color quality both reach the threshold, the grinding equipment is initialized according to these parameters, so as to achieve the technical effect of ensuring the stability of the grinding process and the consistency of product quality.

[0019] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0020] For example, please refer to the attached Figure 1 The present application provides a titanium dioxide intelligent grinding control method, which is applied to a titanium dioxide intelligent grinding control device, wherein the titanium dioxide intelligent grinding control device is connected to a titanium dioxide grinding device for communication, and specifically comprises the following steps:

[0021] Step 1: Receive grinding machine control parameters and grinding environment control parameters from titanium dioxide grinding equipment, wherein the grinding environment control parameters include grinding temperature control timing information and grinding pH value control timing information.

[0022] Specifically, the titanium dioxide intelligent grinding control device refers to a platform for executing an intelligent titanium dioxide grinding control method, which receives and monitors various key parameters in the grinding process in real time by communicating with the titanium dioxide grinding equipment. First, the grinding machinery control parameters and grinding environment control parameters are received from the titanium dioxide grinding equipment. The grinding machinery control parameters include key parameters related to the mechanical operation of the equipment, such as the feeding speed (the speed at which the titanium dioxide raw material is fed into the titanium dioxide grinding equipment) and the grinding speed (the rotation speed of the titanium dioxide grinding equipment, usually refers to the speed of the grinder spindle). The grinding environment control parameters involve factors that affect the environmental conditions during the grinding process, such as temperature and pH value.

[0023] The grinding environment control parameters include grinding temperature control timing information and grinding pH value control timing information. The grinding temperature control timing information refers to the sequence of temperature changes over time during the grinding process. The grinding pH value control timing information refers to the sequence of pH value changes over time during the entire grinding process.

[0024] Step 2: Predict the particle dispersion according to the grinding machine control parameters, the grinding temperature control timing information and the grinding pH value control timing information to obtain the particle dispersion quality coefficient.

[0025] Specifically, particle dispersibility prediction refers to predicting the physical dispersion effect of titanium dioxide particles. Grinding machinery control parameters, such as feed rate, grinding speed, grinding medium filling rate, etc., determine the operating state of the titanium dioxide grinding equipment and directly affect the physical dispersion effect of titanium dioxide particles. The grinding temperature control timing information and the grinding pH value control timing information respectively record how the temperature and pH value change over time during the grinding process. Environmental factors will affect the chemical stability and dispersibility of titanium dioxide particles during the grinding process. Therefore, the grinding machinery control parameters, the grinding temperature control timing information and the grinding pH value control timing information can be combined for calculation and simulation to predict the dispersion performance of titanium dioxide particles during the grinding process, and finally generate a particle dispersion quality coefficient.

[0026] The particle dispersion quality coefficient is used to quantify the degree of dispersion of particles after grinding. For example, the particle dispersion quality coefficient is calculated to be 0.85 (usually ranging from 0 to 1), which indicates that the particle dispersion is good, but there may still be room for improvement. Through this analysis and prediction, it is possible to determine in advance whether the grinding results meet expectations, so as to decide whether the grinding parameters need to be adjusted to optimize the final quality of titanium dioxide.

[0027] Step 3: Obtain the CIE Lab color space of standard titanium dioxide particles.

[0028] Specifically, CIE Lab color space is an existing color space model used to quantify and describe colors. CIELab color space is a three-dimensional color representation method that includes three parameters: L, a, and b. L represents brightness, from 0 (black) to 100 (white), a represents the position of the color on the red-green axis, with positive values ​​representing red and negative values ​​representing green, and b represents the position of the color on the yellow-blue axis, with positive values ​​representing yellow and negative values ​​representing blue.

[0029] In the specific operation, first, based on historical experience, a standard titanium dioxide sample with qualified grinding quality is obtained, its color information is collected, and it is converted into the CIE Lab color space to generate the CIE Lab color space of the standard titanium dioxide particles. For example, the CIE Lab color space value measured for the standard titanium dioxide sample is L=92, a=0.5, b=1.8, which means that the sample has a higher brightness and a slightly yellowish color. This value will be used as a reference standard for the comparison and evaluation of the color of the titanium dioxide particles produced in the subsequent grinding process.

[0030] After obtaining the CIE Lab color space of standard titanium dioxide particles, the color of the ground titanium dioxide can be compared with the standard to evaluate the color consistency and quality of the particles during the grinding process, ensuring that the color of the final product meets the expected standards and guarantees the grinding quality.

[0031] Step 4: Predict the color of particles according to the grinding temperature control timing information and the particle dispersion quality coefficient to obtain a CIE Lab color space for comparing titanium dioxide particles.

[0032] Specifically, the grinding temperature control timing information and the particle dispersion quality coefficient jointly affect the final color of the titanium dioxide particles. For example, if the temperature is high and the dispersion quality coefficient is low during the grinding process, the color of the titanium dioxide may be yellowish or uneven. Based on the grinding temperature control timing information and the particle dispersion quality coefficient, the expected color of the titanium dioxide particles is calculated by a pre-trained color prediction model. Assuming that in a specific grinding process, the grinding temperature control timing information shows that the temperature gradually rises from 30°C to 70°C, and the particle dispersion quality coefficient is 0.78, which indicates that the particles are well dispersed but the temperature is high. It can be predicted that the CIE Lab color space of the titanium dioxide particles is L*=89, a*=0.7, b*=2.0, which means that the brightness of the particles is high, but the color is slightly yellow.

[0033] The CIE Lab color space of titanium dioxide particles will be used as a basis for comparison with the standard color space. Through such a comparison, it can be determined whether the color of the titanium dioxide particles after grinding meets the expected standards. If the predicted results are significantly different from the CIE Lab color space of the standard titanium dioxide particles, the grinding parameters need to be adjusted to optimize the color and ensure that the color quality of the final product meets the requirements, so that the titanium dioxide grinding process can be more accurately controlled, and finally produce high-quality titanium dioxide products that meet the quality standards.

[0034] Step 5: Analyze the CIE Lab color space of the standard titanium dioxide particles and the CIE Lab color space of the comparison titanium dioxide particles to obtain the particle color quality coefficient.

[0035] Specifically, the particle color quality coefficient is used to quantify the color quality of the titanium dioxide particles after grinding to ensure that they meet the expected standards. First, the CIE Lab color space of the standard titanium dioxide particles and the CIELab color space of the comparison titanium dioxide particles are compared and analyzed, and the CIE Lab color space deviation of the two is calculated. The particle color quality coefficient is generated by the CIE Lab color space deviation. The particle color quality coefficient reflects the degree of closeness of the color of the titanium dioxide particles after grinding to the standard color. The calculation method may include the use of color difference formulas, such as the ΔE formula, which can quantify the difference in color space into a single value. For example, a ΔE calculation result of 1.5 indicates that the color is very close to the standard value and the color quality is high; while a ΔE value of 5.0 may indicate that the color deviation is large and the grinding process parameters need to be adjusted to optimize the color quality.

[0036] Step six: When the particle dispersion quality coefficient meets the dispersion quality coefficient threshold, and the particle color quality coefficient meets the color quality coefficient threshold, the titanium dioxide grinding equipment is initialized according to the grinding machine control parameters and the grinding environment control parameters, and then trial production is carried out. When the trial production verification is passed, mass production is started.

[0037] Specifically, the dispersion quality coefficient threshold and the color quality coefficient threshold are thresholds set by professional and technical personnel in this field based on actual experience when the grinding quality meets the requirements. When the particle dispersion quality coefficient meets the dispersion quality coefficient threshold, and the particle color quality coefficient meets the color quality coefficient threshold, it means that the current grinding quality meets the expected standard. At this time, it is only necessary to initialize the titanium dioxide grinding equipment according to the current grinding machine control parameters and grinding environment control parameters to ensure that the operation state and settings of the titanium dioxide grinding equipment can stably produce titanium dioxide that meets the quality standards. Initialization includes adjusting the operation state and settings of the equipment with the grinding machine control parameters and the grinding environment control parameters to make it enter the best working state. After the equipment is initialized, trial production is carried out. Trial production is to verify whether the quality of titanium dioxide actually produced by the grinding machine control parameters and the grinding environment control parameters meets the expected quality requirements. Trial production usually selects a small batch of raw materials for processing to verify whether the particle dispersibility and color of titanium dioxide meet the dispersion quality coefficient threshold and the color quality coefficient threshold. If they meet, they are qualified, and the qualified rate is calculated. If the qualified rate meets the preset threshold, such as 85%, it is considered that the trial production verification has passed, and mass production can be started. Batch production is the full-scale production stage based on the success of trial production. At this time, the equipment will continue to operate according to the verified parameters to ensure the quality and performance of large quantities of titanium dioxide. Through this coherent process control, from equipment initialization to trial production to batch production, each link is strictly monitored and verified, greatly improving the production efficiency and quality consistency of the product.

[0038] Furthermore, step one of this application includes:

[0039] The titanium dioxide grinding equipment includes a feeding device, a grinding chamber, a medium chamber, and an environmental control component, wherein the environmental control component is used to control the grinding chamber temperature and the grinding chamber pH value, and the medium chamber and the feeding device are connected to the grinding chamber; the feeding speed is received through the feeding device; the grinding rotation speed is received through the grinding chamber; the grinding medium filling rate, the grinding medium size, and the grinding medium hardness are received through the medium chamber; the grinding temperature control timing information and the grinding pH value control timing information are received through the environmental control component; the feeding speed, the grinding rotation speed, the grinding medium filling rate, the grinding medium size, and the grinding medium hardness are added to the grinding mechanical control parameters; the grinding temperature control timing information and the grinding pH value control timing information are added to the grinding environment control parameters.

[0040] Specifically, titanium dioxide grinding equipment consists of multiple key components, including a feeding device, a grinding chamber, a media chamber, and an environmental control component. The coordinated work of these components ensures the high efficiency of the grinding process and the stability of product quality. The feeding device is responsible for feeding the titanium dioxide raw material into the grinding equipment at a controlled speed, which is called the feeding speed. The grinding chamber is the main place for the actual grinding of titanium dioxide, and the grinding speed of the grinding equipment is received through the grinding chamber. The media chamber is used to store and manage grinding media. The grinding media is a granular material that helps with grinding. The grinding media filling rate refers to the proportion of the media to the volume of the grinding chamber), the grinding media size refers to the size of the media particles, and the grinding media hardness refers to the hardness of the media material. The environmental control component is used to control the temperature and pH value of the grinding chamber. Through the environmental control component, the current grinding temperature control timing information and grinding pH value control timing information are received.

[0041] Based on the existing wireless communication technology, a communication connection with the titanium dioxide grinding equipment can be established to connect the material device, the grinding bin, the medium bin, and the environmental control component, and read the corresponding control parameters. Finally, the feeding speed, the grinding speed, the grinding medium filling rate, the grinding medium size, and the grinding medium hardness are added to the grinding machine control parameters and integrated to form the grinding machine control parameters. The grinding temperature control timing information and the grinding pH value control timing information are integrated to form the grinding environment control parameters, which provide a basis for the subsequent particle dispersion analysis and particle color analysis, facilitate the grinding quality analysis, and thus adjust the grinding parameters to improve the grinding quality.

[0042] Further, step 2 of this application includes:

[0043] The humidity and viscosity of titanium dioxide are obtained; according to the grinding machine control parameters, the grinding temperature control timing information, the grinding pH value control timing information, the humidity of titanium dioxide and the viscosity of titanium dioxide, a plurality of particle size detection record information of the same model of titanium dioxide grinding equipment are collected, wherein the particle size detection record information of the same model represents the historical detection data of the particle size of titanium dioxide grinding particles of the same model of titanium dioxide grinding equipment; dispersion calculation is performed on the plurality of particle size detection record information of the same model to obtain a plurality of initial particle dispersion quality coefficients; outlier mean fitting is performed on the plurality of initial particle dispersion quality coefficients to obtain the particle dispersion quality coefficient.

[0044] Furthermore, the present application also includes the following steps:

[0045] According to the several pieces of particle size detection record information of the same model, extract the first piece of particle size detection record information of the same model, wherein the first piece of particle size detection record information of the same model includes multiple sample particle size detection record values; configure the particle size threshold interval; count the proportion of samples whose particle size detection record values ​​of the multiple samples fall into the particle size threshold interval, obtain the first initial particle dispersion quality coefficient, and add it to the several initial particle dispersion quality coefficients.

[0046] Specifically, titanium dioxide humidity refers to the water content in titanium dioxide. Too high or too low humidity will affect the dispersion and grinding effect of particles. Titanium dioxide viscosity is an indicator of the fluidity of titanium dioxide under certain conditions. Changes in viscosity will directly affect the uniformity of grinding and the dispersion of the final particles. Both titanium dioxide humidity and titanium dioxide viscosity can be detected and obtained through existing sensors, such as capacitive humidity sensors and rotational viscometers. Next, combined with the grinding machinery control parameters, grinding temperature control timing information, grinding pH value control timing information, as well as titanium dioxide humidity and titanium dioxide viscosity data, several same-model particle size detection record information of titanium dioxide grinding equipment is collected. The same-model particle size detection record information refers to the titanium dioxide particle size data measured multiple times in history on the same model of titanium dioxide grinding equipment. These records provide the particle size distribution of the grinding equipment under different conditions.

[0047] For example, if the grinding temperature, pH value, humidity and viscosity of each grinding operation are the same in the past 100 grinding operations, the particle size detection data under these conditions are collected and sorted to obtain several particle size detection record information of the same model.

[0048] Furthermore, a dispersion calculation is performed on several records of particle size detection of the same model to obtain several initial particle dispersion quality coefficients. The dispersion calculation is to evaluate the dispersion effect of the particles by analyzing the particle size distribution of titanium dioxide particles in different detection records. For example, the uniformity and distribution range of the particle size in each record are calculated, and these indicators are converted into initial particle dispersion quality coefficients.

[0049] Subsequently, these initial particle dispersion quality coefficients are fitted with the mean after removing outliers, that is, removing outliers or extreme data points, and then averaging the remaining data to obtain a more accurate particle dispersion quality coefficient, ensuring that the final dispersion quality coefficient can accurately reflect the particle dispersion under normal grinding conditions without being affected by abnormal data.

[0050] Mean fitting with outliers is a method for dealing with data outliers. It removes outliers and calculates the average of the remaining data to obtain more accurate results. For example, all initial particle dispersion quality coefficients are preliminarily calculated to obtain their overall mean μ and standard deviation σ. For example, suppose there are 10 initial particle dispersion quality coefficients, which are: 0.78, 0.82, 0.85, 0.90, 0.75, 0.88, 0.92, 0.80, 0.83, 0.95. First, calculate the mean μ and standard deviation σ of these data. According to the calculation results of the mean and standard deviation, set a threshold for determining outliers (usually ±2σ or ±3σ). Outliers refer to values ​​outside this range. For example, if the calculated mean is 0.85 and the standard deviation is 0.05, then the range of ±2σ is [0.75, 0.95]. Values ​​outside this range will be regarded as outliers and removed. After removing the outliers, the remaining data is recalculated to get the final particle dispersion quality coefficient after removing the outliers. This can accurately evaluate the grinding quality of titanium dioxide and accurately determine whether the grinding quality meets the expected standards.

[0051] Among them, the specific steps of performing dispersion calculation on the several pieces of particle size detection record information of the same model to obtain several initial particle dispersion quality coefficients include: extracting any one piece of information from the several pieces of particle size detection record information of the same model collected as the first piece of particle size detection record information of the same model, the first piece of particle size detection record information of the same model including multiple sample particle size detection record values, for example, in one grinding operation, the particle size data of 100 titanium dioxide particles are recorded.

[0052] Next, configure the particle size threshold interval, which is a pre-set range that defines the ideal particle size distribution of titanium dioxide particles. This interval is usually set based on production standards or quality requirements. For example, if the standard requires the particle size of titanium dioxide to be between 0.5 microns and 1.0 microns, then the particle size threshold interval can be set to 0.5-1.0 microns.

[0053] After configuring the threshold interval, count the proportion of particle size detection record values ​​of multiple samples that fall into the particle size threshold interval, that is, evaluate how many proportions of particle sizes in this batch of samples meet the set standards, and use this proportion as the first initial particle dispersion quality coefficient. Assuming that from 100 samples, 85 particles have a particle size within the range of 0.5-1.0 microns, then these particles account for 85%, and the first initial particle dispersion quality coefficient is set to 0.85. Finally, add the first initial particle dispersion quality coefficient to several initial particle dispersion quality coefficients.

[0054] Similarly, the same method is used to perform initial particle dispersion quality coefficient on the second and third particle size detection record information of the same model, respectively, until several particle size detection record information of the same model are traversed to obtain several complete initial particle dispersion quality coefficients, which are used for subsequent statistical analysis and outlier removal mean fitting to obtain the final particle dispersion quality coefficient, ensuring that the evaluation of the dispersion of titanium dioxide particles is accurate and representative, thereby providing reliable data support for optimizing the grinding process.

[0055] Further, step 4 of this application includes:

[0056] The CIE Lab color space record information of several titanium dioxide particles of the same model of the titanium dioxide grinding equipment is collected with the grinding temperature control timing information and the particle dispersion quality coefficient as constraints; the same coordinate color feature statistics are performed on the CIE Lab color space record information of the several titanium dioxide particles of the same model to obtain the first coordinate color feature set, the second coordinate color feature set, and the Nth coordinate color feature set; the first coordinate color feature set, the second coordinate color feature set, and the Nth coordinate color feature set are traversed to perform concentrated feature analysis to obtain the first coordinate concentrated color feature, the second coordinate concentrated color feature, and the Nth coordinate concentrated color feature; the comparison titanium dioxide particle CIE Lab color space is constructed according to the first coordinate concentrated color feature, the second coordinate concentrated color feature, and the Nth coordinate concentrated color feature.

[0057] Specifically, the grinding temperature control timing information and the particle dispersion quality coefficient are used as the constraints for screening data, and the historical titanium dioxide particle CIE Lab color space records corresponding to the grinding temperature control timing information and the particle dispersion quality coefficient are selected to generate several CIE Lab color space record information of titanium dioxide particles of the same model. Next, the same coordinate color feature statistics are performed on the CIE Lab color space record information of several titanium dioxide particles of the same model under the same conditions. It can be understood that the CIE Lab color space is a three-dimensional color space model that describes the color through three parameters: L (brightness), a (red and green axis), and b (yellow and blue axis). The same coordinate color feature statistics refers to the summary and analysis of the color features of multiple samples at the same CIE Lab coordinate position. That is, the three parameters of L (brightness), a (red and green axis) and b (yellow and blue axis) are used as the x-axis, y-axis, and z-axis of the coordinate axis, and the characteristic values ​​of several CIE Lab color space record information of titanium dioxide particles of the same model on the three axes are respectively counted to generate the first coordinate color feature set, the second coordinate color feature set, and until the Nth coordinate color feature set. Wherein, N is the total number of CIE Lab color space recorded information of several titanium dioxide particles of the same type.

[0058] Then, the first coordinate color feature set, the second coordinate color feature set, and the Nth coordinate color feature set are traversed to perform concentrated feature analysis, that is, the mode corresponding to the coordinate point in each coordinate color feature set on L (brightness), a (red-green axis), and b (yellow-blue axis) is analyzed to form a coordinate concentrated color feature, and so on, the first coordinate concentrated color feature, the second coordinate concentrated color feature, and the Nth coordinate concentrated color feature corresponding to the first coordinate color feature set, the second coordinate concentrated color feature, and the Nth coordinate concentrated color feature are obtained. Finally, the first coordinate concentrated color feature, the second coordinate concentrated color feature, and the Nth coordinate concentrated color feature are used to form a comparison of the CIE Lab color space of titanium dioxide particles. Comparison of the CIE Lab color space of titanium dioxide particles is a comprehensive reference model used to evaluate whether the color of titanium dioxide produced by the current grinding machine control parameters and grinding environment control parameters is consistent with the standard color, so as to facilitate the judgment of whether the color quality of the titanium dioxide after grinding meets the expected standard, thereby assisting in adjusting the grinding process and ensuring the grinding quality.

[0059] Furthermore, the present application also includes the following steps:

[0060] When the particle dispersion quality coefficient does not meet the dispersion quality coefficient threshold, or / and the particle color quality coefficient does not meet the color quality coefficient threshold, multi-sample point optimization is performed on the grinding machine control parameters and the grinding environment control parameters to obtain updated grinding machine control parameters and updated grinding environment control parameters; the titanium dioxide grinding equipment is initialized according to the updated grinding machine control parameters and the updated grinding environment control parameters.

[0061] Furthermore, the present application also includes the following steps:

[0062] The grinding machine control parameters and the grinding environment control parameters are randomly adjusted for multiple times to obtain a plurality of grinding machine control parameters and a plurality of grinding environment control parameters, wherein the plurality of grinding machine control parameters and the plurality of grinding environment control parameters correspond to each other one by one; a plurality of particle dispersion quality coefficient evaluation values ​​and a plurality of particle color quality coefficient evaluation values ​​of the plurality of grinding machine control parameters and the plurality of grinding environment control parameters are obtained; a trend optimization analysis is performed based on the plurality of particle dispersion quality coefficient evaluation values ​​and the plurality of particle color quality coefficient evaluation values ​​to obtain the updated grinding machine control parameters and the updated grinding environment control parameters.

[0063] Furthermore, the present application also includes the following steps:

[0064] Calculate a number of first normalized eigenvalues ​​of the plurality of particle dispersion quality coefficient evaluation values; calculate a number of second normalized eigenvalues ​​of the plurality of particle color quality coefficient evaluation values; construct a number of reference coordinates based on the plurality of first normalized eigenvalues ​​and the plurality of second normalized eigenvalues; calculate the normalized eigenvalue of the dispersion quality coefficient threshold value, and calculate the normalized eigenvalue of the color quality coefficient threshold value, and construct reference coordinates; traverse the plurality of reference coordinates, perform distance analysis with the reference coordinates, and obtain a number of evaluation distances; sort the plurality of reference coordinates according to the plurality of evaluation distances, and obtain the first A sorting result; according to the first sorting result, extract a first number of head reference coordinates and a second number of tail reference coordinates; take the solution of the first number of head reference coordinates as the search target, and take the solution of the second number of tail reference coordinates as the search starting point for random search to generate a number of newly added grinding machine control parameters and a number of newly added grinding environment control parameters; when the number of newly added grinding machine control parameters and the number of newly added grinding environment control parameters have solutions that meet the dispersion quality coefficient threshold and the color quality coefficient threshold, output the updated grinding machine control parameters and the updated grinding environment control parameters; otherwise, execute an optimization loop.

[0065] Specifically, when the particle dispersion quality coefficient meets the dispersion quality coefficient threshold, and the particle color quality coefficient meets the color quality coefficient threshold, the titanium dioxide grinding equipment is initialized according to the grinding machine control parameters and the grinding environment control parameters. Conversely, when the particle dispersion quality coefficient does not meet the dispersion quality coefficient threshold, or / and the particle color quality coefficient does not meet the color quality coefficient threshold, it means that the current grinding quality does not meet the expected standards. At this time, it is necessary to perform multi-sample point optimization on the grinding machine control parameters and the grinding environment control parameters to obtain updated grinding machine control parameters and updated grinding environment control parameters.

[0066] Multi-sample point optimization is an iterative process. In layman's terms, the grinding machine control parameters and grinding environment control parameters are randomly adjusted, such as changing the grinding speed, adjusting the medium filling rate, or modifying the control timing information of the temperature and pH value. After each parameter adjustment, a new grinding analysis will be performed, and the particle dispersion quality coefficient and particle color quality coefficient will be updated and calculated using the same method as the particle dispersion quality coefficient and particle color quality coefficient in the previous steps. For example, if the original grinding speed is 1200 rpm, you can try to adjust the speed to 1150 rpm and calculate the updated particle dispersion quality coefficient and particle color quality coefficient. Through multiple adjustments and experiments, a series of updated grinding machine control parameters and grinding environment control parameters will be collected, and the grinding machine control parameters and grinding environment control parameters that can make the dispersion quality coefficient and color quality coefficient reach or exceed the dispersion quality coefficient threshold and color quality coefficient threshold are selected as the updated grinding machine control parameters and the updated grinding environment control parameters.

[0067] Finally, the titanium dioxide grinding equipment is initialized according to the updated grinding machinery control parameters and the updated grinding environment control parameters, that is, the updated grinding machinery control parameters and the updated grinding environment control parameters are loaded into the control system of the titanium dioxide grinding equipment, so that the titanium dioxide grinding equipment operates under the new optimized conditions. For example, if the final optimized grinding speed is 1150 rpm, the grinding temperature is controlled at 55°C, and the pH value is maintained at 8.2, then these parameters will be set as the new standard working conditions. In this way, the grinding process can be dynamically adjusted and optimized to ensure that the particle dispersion and color quality of titanium dioxide meet the expected standards, improve the consistency and stability of the product, and ensure the grinding quality of titanium dioxide.

[0068] Among them, the specific steps of performing multi-sample point optimization on the grinding machine control parameters and the grinding environment control parameters to obtain updated grinding machine control parameters and updated grinding environment control parameters are as follows: First, the current grinding machine control parameters and grinding environment control parameters are randomly adjusted multiple times, such as adjusting the grinding speed, medium filling rate, temperature control timing, and pH value control timing. Each adjustment will generate a new set of parameter combinations, thereby obtaining a number of grinding machine control parameters and a number of grinding environment control parameters with corresponding relationships. For example, in one adjustment, the grinding speed is adjusted from 1200 rpm to 1150 rpm, and the maximum temperature of the temperature control timing is reduced from 60°C to 55°C, and the pH value control timing is adjusted. Such an adjustment will produce a new set of grinding machine control parameters and grinding environment control parameters.

[0069] The same method as that for calculating the particle dispersion quality coefficient and the particle color quality coefficient is used to calculate the particle dispersion quality coefficient and the particle color quality coefficient corresponding to the plurality of grinding machine control parameters and the plurality of grinding environment control parameters as a plurality of particle dispersion quality coefficient evaluation values ​​and a plurality of particle color quality coefficient evaluation values. These evaluation values ​​reflect the effect of each group of parameter combinations in actual operation.

[0070] Next, a trend optimization analysis is performed based on several particle dispersion quality coefficient evaluation values ​​and several particle color quality coefficient evaluation values. Trend optimization analysis refers to analyzing several particle dispersion quality coefficient evaluation values ​​and several particle color quality coefficient evaluation values ​​to find out which parameter combinations can optimize both particle dispersion and color quality. By analyzing these trends, the range of parameter adjustment is gradually narrowed, and the optimal grinding machine control parameters and grinding environment control parameters are eventually found. The optimal grinding machine control parameters and grinding environment control parameters can improve the grinding effect of titanium dioxide, so that the particle dispersion and color meet or exceed the expected standards. The optimal grinding machine control parameters and grinding environment control parameters are used as updated grinding machine control parameters and the updated grinding environment control parameters, thereby continuously producing high-quality titanium dioxide, ensuring product consistency and stability, and improving grinding quality.

[0071] Among them, the specific steps of performing trend optimization analysis based on the several particle dispersion quality coefficient evaluation values ​​and the several particle color quality coefficient evaluation values ​​to obtain the updated grinding machine control parameters and the updated grinding environment control parameters include: first, normalizing the several particle dispersion quality coefficient evaluation values ​​to obtain several first normalized eigenvalues, and normalizing the several particle color quality coefficient evaluation values ​​to obtain several second normalized eigenvalues. The normalized eigenvalue is a value obtained after standardization, which is used to convert data of different dimensions to the same scale range (usually between 0 and 1) for comparison and analysis. For example, if the dispersion quality coefficient of a group of evaluation values ​​is between 0.7 and 0.9, these values ​​may be converted to the range of 0.0 to 1.0 after normalization. Normalization is a common technical means used by technicians in this field, such as minimum-maximum normalization, Z score normalization, etc., which will not be expanded here.

[0072] Next, a coordinate system is constructed with the first normalized eigenvalue and the second normalized eigenvalue as the horizontal coordinate and the vertical coordinate respectively, and the first normalized eigenvalues ​​and the second normalized eigenvalues ​​are combined according to the corresponding relationship and fall into the coordinate system to obtain a plurality of reference coordinates. Each reference coordinate represents a combination of a set of corresponding dispersion quality and color quality characteristic values.

[0073] On this basis, the same method is used to calculate the normalized eigenvalues ​​of the dispersion quality coefficient threshold and the color quality coefficient threshold, and a reference coordinate is constructed in the constructed coordinate system, and the reference coordinate is used for comparative analysis with the reference coordinate. Further, the several reference coordinates are traversed, and the distance between each reference coordinate and the reference coordinate is calculated to generate several evaluation distances. The smaller the distance, the closer the dispersion quality and color quality of the group of parameter combinations are to the ideal state. For example, the distance between a certain reference coordinate and the reference coordinate is 0.1, while the distance between another reference coordinate is 0.3, and the former is closer to the ideal grinding effect.

[0074] According to the several evaluation distances, several reference coordinates are sorted from small to large to generate a first sorting result, and a first number of head reference coordinates and a second number of tail reference coordinates are extracted. The head reference coordinates represent the reference coordinates closest to the reference coordinates, while the tail reference coordinates are the reference coordinates farthest away. The solution of the first number of head reference coordinates refers to the grinding machine control parameters and grinding environment control parameters corresponding to the first number of head reference coordinates. Similarly, the solution of the second number of tail reference coordinates is also the grinding machine control parameters and grinding environment control parameters corresponding to the second number of tail reference coordinates. The solution of the first number of head reference coordinates is used as the search target, and the solution of the second number of tail reference coordinates is used as the search starting point to randomly adjust the grinding machine control parameters and grinding environment control parameters. In other words, the grinding machine control parameters and grinding environment control parameters of the second number of tail reference coordinates are adjusted in the direction of the grinding machine control parameters and grinding environment control parameters of the first number of head reference coordinates, so as to generate several newly added grinding machine control parameters and grinding environment control parameters. This process aims to further optimize the parameters so that they are close to or reach the ideal state.

[0075] If at least one set of the particle dispersion quality coefficient evaluation values ​​of the several newly added grinding machine control parameters and the several newly added grinding environment control parameters meets the dispersion quality coefficient threshold, and the particle color quality coefficient evaluation value meets the color quality coefficient threshold, this set of newly added grinding machine control parameters and the newly added grinding environment control parameters are used as the updated grinding machine control parameters and the updated grinding environment control parameters respectively. Otherwise, the optimization cycle will continue to be executed, that is, the particle dispersion quality coefficient evaluation values ​​and the particle color quality coefficient evaluation values ​​corresponding to the several newly added grinding machine control parameters and the several newly added grinding environment control parameters are normalized to construct new reference coordinates, and the distance is calculated with the reference coordinates, and then sorted, and the head reference coordinates and the tail reference coordinates are continued to be obtained for parameter optimization, that is, the aforementioned optimization steps are repeated until a parameter combination that meets the requirements is found. Through optimization, it can be ensured that the grinding process of titanium dioxide is carried out under the optimal control parameters, high-quality products that meet quality standards are produced, the grinding quality is improved, and the consistency and stability of the product are ensured.

[0076] In summary, the intelligent grinding control method of titanium dioxide provided in this application has the following technical effects:

[0077] 1. Receive grinding machine control parameters and grinding environment control parameters from titanium dioxide grinding equipment, wherein the grinding environment control parameters include grinding temperature control timing information and grinding pH value control timing information; predict particle dispersibility according to the grinding machine control parameters, the grinding temperature control timing information and the grinding pH value control timing information, and obtain particle dispersion quality coefficient; obtain standard titanium dioxide particle CIE Lab color space; predict particle color according to the grinding temperature control timing information and the particle dispersion quality coefficient, and obtain comparison titanium dioxide particle CIE Lab color space; analyze according to the standard titanium dioxide particle CIE Lab color space and the comparison titanium dioxide particle CIE Lab color space to obtain particle color quality coefficient; when the particle dispersion quality coefficient meets the dispersion quality coefficient threshold, and the particle color quality coefficient meets the color quality coefficient threshold, initialize the titanium dioxide grinding equipment according to the grinding machine control parameters and the grinding environment control parameters, and then conduct trial production, and when the trial production verification is passed, start mass production. By receiving the grinding machine control parameters and the environment control parameters in real time, predict the particle dispersion and calculate the particle dispersion quality coefficient. Then, the color is predicted by combining the dispersion quality coefficient and temperature control information, and compared with the standard color space to obtain the particle color quality coefficient. When both the dispersion and color quality reach the threshold, the grinding equipment is initialized according to these parameters to achieve the technical effect of ensuring the stability of the grinding process and the consistency of product quality.

[0078] 2. When the particle dispersion quality coefficient does not meet the dispersion quality coefficient threshold, or / and the particle color quality coefficient does not meet the color quality coefficient threshold, multi-sample point optimization is performed on the grinding machine control parameters and the grinding environment control parameters to obtain updated grinding machine control parameters and updated grinding environment control parameters; the titanium dioxide grinding equipment is initialized according to the updated grinding machine control parameters and the updated grinding environment control parameters, and the grinding process is dynamically adjusted and optimized to ensure that the particle dispersion and color quality of the titanium dioxide meet the expected standards, thereby improving the consistency and stability of the product and ensuring the technical effect of the grinding quality of the titanium dioxide.

[0079] Embodiment 2: Based on the same invention concept as the titanium dioxide intelligent grinding control method in the above embodiment, this application also provides a titanium dioxide intelligent grinding control device, see the attached Figure 2 The titanium dioxide intelligent grinding control device comprises:

[0080] The parameter receiving module 11 is used to receive grinding machine control parameters and grinding environment control parameters from titanium dioxide grinding equipment, wherein the grinding environment control parameters include grinding temperature control timing information and grinding pH value control timing information.

[0081] The particle dispersibility prediction module 12 is used to predict the particle dispersibility according to the grinding machine control parameters, the grinding temperature control timing information and the grinding pH value control timing information to obtain the particle dispersion quality coefficient.

[0082] The standard color space acquisition module 13 is used to obtain the standard titanium dioxide particle CIE Lab color space.

[0083] The particle color prediction module 14 is used to predict the particle color according to the grinding temperature control timing information and the particle dispersion quality coefficient, and obtain the CIE Lab color space of the titanium dioxide particles.

[0084] The particle color quality analysis module 15 is used to analyze the standard titanium dioxide particle CIE Lab color space and the comparison titanium dioxide particle CIE Lab color space to obtain a particle color quality coefficient.

[0085] The equipment initialization module 16 is used to initialize the titanium dioxide grinding equipment according to the grinding machine control parameters and the grinding environment control parameters when the particle dispersion quality coefficient meets the dispersion quality coefficient threshold and the particle color quality coefficient meets the color quality coefficient threshold, and then conduct trial production. When the trial production verification is passed, mass production begins.

[0086] Furthermore, the parameter receiving module 11 in the titanium dioxide intelligent grinding control device is also used for:

[0087] The titanium dioxide grinding equipment includes a feeding device, a grinding chamber, a medium chamber, and an environmental control component, wherein the environmental control component is used to control the grinding chamber temperature and the grinding chamber pH value, and the medium chamber and the feeding device are connected to the grinding chamber; the feeding speed is received through the feeding device; the grinding rotation speed is received through the grinding chamber; the grinding medium filling rate, the grinding medium size, and the grinding medium hardness are received through the medium chamber; the grinding temperature control timing information and the grinding pH value control timing information are received through the environmental control component; the feeding speed, the grinding rotation speed, the grinding medium filling rate, the grinding medium size, and the grinding medium hardness are added to the grinding mechanical control parameters; the grinding temperature control timing information and the grinding pH value control timing information are added to the grinding environment control parameters.

[0088] Furthermore, the titanium dioxide intelligent grinding control device further includes a parameter optimization module, which is used to:

[0089] When the particle dispersion quality coefficient does not meet the dispersion quality coefficient threshold, or / and the particle color quality coefficient does not meet the color quality coefficient threshold, multi-sample point optimization is performed on the grinding machine control parameters and the grinding environment control parameters to obtain updated grinding machine control parameters and updated grinding environment control parameters; the titanium dioxide grinding equipment is initialized according to the updated grinding machine control parameters and the updated grinding environment control parameters.

[0090] Furthermore, the particle dispersibility prediction module 12 in the titanium dioxide intelligent grinding control device is also used for:

[0091] The humidity and viscosity of titanium dioxide are obtained; according to the grinding machine control parameters, the grinding temperature control timing information, the grinding pH value control timing information, the humidity of titanium dioxide and the viscosity of titanium dioxide, a plurality of particle size detection record information of the same model of titanium dioxide grinding equipment are collected, wherein the particle size detection record information of the same model represents the historical detection data of the particle size of titanium dioxide grinding particles of the same model of titanium dioxide grinding equipment; dispersion calculation is performed on the plurality of particle size detection record information of the same model to obtain a plurality of initial particle dispersion quality coefficients; outlier mean fitting is performed on the plurality of initial particle dispersion quality coefficients to obtain the particle dispersion quality coefficient.

[0092] Furthermore, the particle dispersibility prediction module 12 in the titanium dioxide intelligent grinding control device is also used for:

[0093] According to the several pieces of particle size detection record information of the same model, extract the first piece of particle size detection record information of the same model, wherein the first piece of particle size detection record information of the same model includes multiple sample particle size detection record values; configure the particle size threshold interval; count the proportion of samples whose particle size detection record values ​​of the multiple samples fall into the particle size threshold interval, obtain the first initial particle dispersion quality coefficient, and add it to the several initial particle dispersion quality coefficients.

[0094] Furthermore, the particle color prediction module 14 in the titanium dioxide intelligent grinding control device is also used for:

[0095] The CIE Lab color space record information of several titanium dioxide particles of the same model of the titanium dioxide grinding equipment is collected with the grinding temperature control timing information and the particle dispersion quality coefficient as constraints; the same coordinate color feature statistics are performed on the CIE Lab color space record information of the several titanium dioxide particles of the same model to obtain the first coordinate color feature set, the second coordinate color feature set, and the Nth coordinate color feature set; the first coordinate color feature set, the second coordinate color feature set, and the Nth coordinate color feature set are traversed to perform concentrated feature analysis to obtain the first coordinate concentrated color feature, the second coordinate concentrated color feature, and the Nth coordinate concentrated color feature; the comparison titanium dioxide particle CIE Lab color space is constructed according to the first coordinate concentrated color feature, the second coordinate concentrated color feature, and the Nth coordinate concentrated color feature.

[0096] Furthermore, the parameter optimization module in the titanium dioxide intelligent grinding control device is also used for:

[0097] The grinding machine control parameters and the grinding environment control parameters are randomly adjusted for multiple times to obtain a plurality of grinding machine control parameters and a plurality of grinding environment control parameters, wherein the plurality of grinding machine control parameters and the plurality of grinding environment control parameters correspond to each other one by one; a plurality of particle dispersion quality coefficient evaluation values ​​and a plurality of particle color quality coefficient evaluation values ​​of the plurality of grinding machine control parameters and the plurality of grinding environment control parameters are obtained; a trend optimization analysis is performed based on the plurality of particle dispersion quality coefficient evaluation values ​​and the plurality of particle color quality coefficient evaluation values ​​to obtain the updated grinding machine control parameters and the updated grinding environment control parameters.

[0098] Furthermore, the parameter optimization module in the titanium dioxide intelligent grinding control device is also used for:

[0099] Calculate a number of first normalized eigenvalues ​​of the plurality of particle dispersion quality coefficient evaluation values; calculate a number of second normalized eigenvalues ​​of the plurality of particle color quality coefficient evaluation values; construct a number of reference coordinates based on the plurality of first normalized eigenvalues ​​and the plurality of second normalized eigenvalues; calculate the normalized eigenvalue of the dispersion quality coefficient threshold value, and calculate the normalized eigenvalue of the color quality coefficient threshold value, and construct reference coordinates; traverse the plurality of reference coordinates, perform distance analysis with the reference coordinates, and obtain a number of evaluation distances; sort the plurality of reference coordinates according to the plurality of evaluation distances, and obtain the first A sorting result; according to the first sorting result, extract a first number of head reference coordinates and a second number of tail reference coordinates; take the solution of the first number of head reference coordinates as the search target, and take the solution of the second number of tail reference coordinates as the search starting point for random search to generate a number of newly added grinding machine control parameters and a number of newly added grinding environment control parameters; when the number of newly added grinding machine control parameters and the number of newly added grinding environment control parameters have solutions that meet the dispersion quality coefficient threshold and the color quality coefficient threshold, output the updated grinding machine control parameters and the updated grinding environment control parameters; otherwise, execute an optimization loop.

[0100] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The intelligent grinding control method and specific examples of titanium dioxide in the first embodiment are also applicable to the intelligent grinding control device of titanium dioxide in the present embodiment. Through the detailed description of the intelligent grinding control method of titanium dioxide, those skilled in the art can clearly know the intelligent grinding control device of titanium dioxide in the present embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0101] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0102] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A titanium dioxide intelligent grinding control method, characterized in that: Applicable to the intelligent grinding control device of titanium dioxide, the intelligent grinding control device of titanium dioxide is connected to the titanium dioxide grinding equipment in communication, including: Receiving grinding machine control parameters and grinding environment control parameters from titanium dioxide grinding equipment, wherein the grinding environment control parameters include grinding temperature control timing information and grinding pH value control timing information; Predicting particle dispersion according to the grinding machine control parameters, the grinding temperature control timing information and the grinding pH value control timing information to obtain a particle dispersion quality coefficient; Obtain the CIE Lab color space of standard titanium dioxide particles; Predicting the color of particles according to the grinding temperature control timing information and the particle dispersion quality coefficient to obtain a CIE Lab color space for comparing titanium dioxide particles; Analyze the standard titanium dioxide particle CIE Lab color space and the comparison titanium dioxide particle CIE Lab color space to obtain a particle color quality coefficient; When the particle dispersion quality coefficient meets the dispersion quality coefficient threshold, and the particle color quality coefficient meets the color quality coefficient threshold, the titanium dioxide grinding equipment is initialized according to the grinding machine control parameters and the grinding environment control parameters, and then trial production is carried out. When the trial production verification is passed, mass production is started; The particle color is predicted according to the grinding temperature control timing information and the particle dispersion quality coefficient to obtain a CIE Lab color space for comparing titanium dioxide particles, including: Collecting CIE Lab color space recording information of a plurality of titanium dioxide particles of the same model of titanium dioxide grinding equipment with the grinding temperature control timing information and the particle dispersion quality coefficient as constraint conditions; Performing same-coordinate color feature statistics on the CIE Lab color space record information of the same type of titanium dioxide particles to obtain a first coordinate color feature set, a second coordinate color feature set, and up to an Nth coordinate color feature set; Traversing the first coordinate color feature set, the second coordinate color feature set, and up to the Nth coordinate color feature set to perform concentrated feature analysis, and obtaining color features in the first coordinate set, color features in the second coordinate set, and up to the Nth coordinate set; The CIE Lab color space for comparing titanium dioxide particles is constructed according to the color features in the first coordinate set, the color features in the second coordinate set, and so on to the color features in the Nth coordinate set.

2. The intelligent grinding control method of titanium dioxide according to claim 1, characterized in that: Receive grinding machine control parameters and grinding environment control parameters from titanium dioxide grinding equipment, including: The titanium dioxide grinding equipment comprises a feeding device, a grinding chamber, a medium chamber, and an environmental control component, wherein the environmental control component is used to control the grinding chamber temperature and the grinding chamber pH value, and the medium chamber and the feeding device are in communication with the grinding chamber; receiving a feeding speed through the feeding device; receiving a grinding speed through the grinding chamber; receiving the filling rate of the grinding medium, the size of the grinding medium, and the hardness of the grinding medium through the medium bin; Receiving the grinding temperature control timing information and the grinding pH value control timing information through the environmental control component; Adding the feed rate, the grinding speed, the grinding medium filling rate, the grinding medium size, and the grinding medium hardness into the grinding machine control parameters; The grinding temperature control timing information and the grinding pH value control timing information are added into the grinding environment control parameters.

3. The intelligent grinding control method of titanium dioxide according to claim 1, characterized in that: Also includes: When the particle dispersion quality coefficient does not satisfy the dispersion quality coefficient threshold, or / and the particle color quality coefficient does not satisfy the color quality coefficient threshold, performing multi-sample point optimization on the grinding machine control parameters and the grinding environment control parameters to obtain updated grinding machine control parameters and updated grinding environment control parameters; The titanium dioxide grinding equipment is initialized according to the updated grinding machine control parameters and the updated grinding environment control parameters.

4. The intelligent grinding control method of titanium dioxide according to claim 1, characterized in that: The particle dispersion quality coefficient is obtained by predicting the particle dispersion according to the grinding machine control parameters, the grinding temperature control timing information and the grinding pH value control timing information, including: Obtain titanium dioxide moisture and titanium dioxide viscosity; According to the grinding machine control parameters, the grinding temperature control timing information, the grinding pH value control timing information, the titanium dioxide humidity and the titanium dioxide viscosity, a plurality of same-model particle size detection record information of the titanium dioxide grinding equipment is collected, wherein the same-model particle size detection record information represents the historical particle size detection data of the titanium dioxide grinding particles of the same-model titanium dioxide grinding equipment; Performing dispersion calculation on the plurality of pieces of particle size detection record information of the same model to obtain a plurality of initial particle dispersion quality coefficients; The plurality of initial particle dispersion quality coefficients are subjected to mean fitting after removing outliers to obtain the particle dispersion quality coefficient.

5. The intelligent grinding control method of titanium dioxide according to claim 4, characterized in that: The dispersion calculation is performed on the plurality of same-model particle size detection record information to obtain a plurality of initial particle dispersion quality coefficients, including: Extracting a first piece of particle size detection record information of the same model according to the plurality of pieces of particle size detection record information of the same model, wherein the first piece of particle size detection record information of the same model includes a plurality of sample particle size detection record values; Configure particle size threshold interval; The proportion of samples whose particle size detection record values ​​of the plurality of samples fall within the particle size threshold interval is counted to obtain a first initial particle dispersion quality coefficient, which is added to the plurality of initial particle dispersion quality coefficients.

6. The intelligent grinding control method of titanium dioxide according to claim 3, characterized in that: When the particle dispersion quality coefficient does not meet the dispersion quality coefficient threshold, or / and the particle color quality coefficient does not meet the color quality coefficient threshold, multi-sample point optimization is performed on the grinding machine control parameter and the grinding environment control parameter to obtain updated grinding machine control parameters and updated grinding environment control parameters, including: The grinding machine control parameters and the grinding environment control parameters are randomly adjusted for multiple times to obtain a plurality of grinding machine control parameters and a plurality of grinding environment control parameters, wherein the plurality of grinding machine control parameters and the plurality of grinding environment control parameters correspond to each other one by one; Obtaining a number of particle dispersion quality coefficient evaluation values ​​and a number of particle color quality coefficient evaluation values ​​of the number of grinding machine control parameters and the number of grinding environment control parameters; The updated grinding machine control parameters and the updated grinding environment control parameters are obtained by performing trend optimization analysis based on the plurality of particle dispersion quality coefficient evaluation values ​​and the plurality of particle color quality coefficient evaluation values.

7. The intelligent grinding control method of titanium dioxide according to claim 6, characterized in that: The method further comprises: performing trend optimization analysis according to the plurality of particle dispersion quality coefficient evaluation values ​​and the plurality of particle color quality coefficient evaluation values ​​to obtain the updated grinding machine control parameters and the updated grinding environment control parameters, including: Calculating a plurality of first normalized eigenvalues ​​of the plurality of particle dispersion quality coefficient evaluation values; Calculating a plurality of second normalized characteristic values ​​of the plurality of particle color quality coefficient evaluation values; Constructing a plurality of reference coordinates according to the plurality of first normalized eigenvalues ​​and the plurality of second normalized eigenvalues; Calculating the normalized characteristic value of the dispersion quality coefficient threshold and calculating the normalized characteristic value of the color quality coefficient threshold to construct a reference coordinate; Traversing the plurality of reference coordinates, performing distance analysis with the reference coordinates, and obtaining a plurality of evaluation distances; Sorting the plurality of reference coordinates according to the plurality of evaluation distances to obtain a first sorting result; Extracting a first number of head reference coordinates and a second number of tail reference coordinates according to the first sorting result; Taking the solutions of the first number of head reference coordinates as the search target and taking the solutions of the second number of tail reference coordinates as the search starting point, a random search is performed to generate a number of newly added grinding machine control parameters and a number of newly added grinding environment control parameters; When the plurality of newly added grinding machine control parameters and the plurality of newly added grinding environment control parameters have solutions that satisfy the dispersion quality coefficient threshold and the color quality coefficient threshold, outputting the updated grinding machine control parameters and the updated grinding environment control parameters; Otherwise, perform an optimization loop.

8. An intelligent grinding control device for titanium dioxide, characterized in that: The steps for implementing the intelligent grinding control method of titanium dioxide according to any one of claims 1 to 7 include: A parameter receiving module, used for receiving grinding machine control parameters and grinding environment control parameters from titanium dioxide grinding equipment, wherein the grinding environment control parameters include grinding temperature control timing information and grinding pH value control timing information; A particle dispersibility prediction module, used to predict the particle dispersibility according to the grinding machine control parameters, the grinding temperature control timing information and the grinding pH value control timing information, and obtain a particle dispersion quality coefficient; Standard color space acquisition module, used to obtain the CIE Lab color space of standard titanium dioxide particles; A particle color prediction module is used to predict the particle color according to the grinding temperature control timing information and the particle dispersion quality coefficient, and obtain a CIE Lab color space for comparing titanium dioxide particles; A particle color quality analysis module, used to analyze the standard titanium dioxide particle CIE Lab color space and the comparison titanium dioxide particle CIE Lab color space to obtain a particle color quality coefficient; The equipment initialization module is used to initialize the titanium dioxide grinding equipment according to the grinding machine control parameters and the grinding environment control parameters when the particle dispersion quality coefficient meets the dispersion quality coefficient threshold and the particle color quality coefficient meets the color quality coefficient threshold, and then conduct trial production. When the trial production verification is passed, mass production will begin.

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