Industrial automatic control system

Abstract

The invention discloses an industrial automatic control system, which relates to the technical field of industrial automatic control and comprises an initial uniform mixing module, a real-time parameter monitoring module, a feature extraction and quantification module, an intelligent state evaluation module, a state classification decision module, a stable stage operation module and a dynamic speed regulation response module, the paper pulp raw materials are mixed by the high-shear mixer at the preset shear rate, so that uniform dispersion of fibers, fillers and additives is ensured, and the flowability and consistency of the pulp are improved. The paper pulp mixing quality is collaboratively optimized through the initial mixing module, the real-time monitoring module, the intelligent evaluation module and the dynamic speed regulation module. Bubble generation signals are accurately captured, bubble cores are quickly responded and damaged, and defects are avoided; in the stable stage, the standard shearing rate is maintained, energy consumption and equipment abrasion are reduced, the production efficiency is improved, scrap is reduced, the operation cost is optimized, and the market competitiveness is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial automatic control, and in particular to an industrial automatic control system. Background Art

[0002] Industrial automatic control refers to the automatic adjustment and optimization of the operation of equipment, process flow or the entire system in industrial production through preset control systems and algorithms to achieve stable, efficient and precise production operations. It dynamically controls key variables (such as temperature, pressure, flow, speed, etc.) through control devices to ensure that the production process runs according to the set parameters and goals, thereby improving production efficiency, reducing energy consumption, ensuring product quality, and reducing dependence on human intervention. Industrial automatic control is widely used in manufacturing, energy, chemical and other fields, promoting the development of intelligent production.

[0003] High shear mixers play an important role in the papermaking industry, especially in the process of evenly dispersing short fibers, fillers, pigments or chemical additives into the pulp. It generates strong shear force through high-speed rotating blades or rotors, quickly breaks the agglomeration in the pulp, achieves uniform mixing of fibers and additives, and improves the stability and uniformity of the pulp. This equipment is particularly suitable for the production of high-performance paper (such as high-strength paperboard or coated paper) because it can ensure the precise distribution of coating slurry, fillers and additives, and improve the surface quality, strength and functional properties of the paper. In addition, high shear mixers can significantly shorten mixing time, improve production efficiency, and reduce quality problems caused by uneven distribution of additives.

[0004] The prior art has the following deficiencies: In the prior art, when pulp raw materials are mixed by a high shear mixer, the traditional method usually adopts a standardized shear rate to simplify the equipment operation and maintenance process. However, when bubbles are generated in the slurry during the stirring process and the standardized shear rate is still used for mixing, serious consequences may occur. The excessive presence of bubbles will form tiny pinholes or gaps in the coating slurry, significantly reducing the adhesion and uniformity of the coating, and then causing coating peeling or surface defects. This problem is particularly critical in the production of high-end coated paper (such as coated paper and art paper). It not only destroys the smoothness and consistency of the paper, but also seriously affects subsequent processes such as printing and writing, resulting in customer order cancellations and large-scale product scrapping, and ultimately causing significant damage to the company's reputation and market competitiveness.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The purpose of the present invention is to provide an industrial automatic control system that optimizes pulp mixing quality through initial mixing, real-time monitoring, intelligent evaluation and dynamic speed regulation modules. It can accurately capture bubble generation signals, quickly respond to destroy bubble nuclei, and avoid defects; maintain a standard shear rate in the stable stage, reduce energy consumption and equipment wear, improve production efficiency, reduce scrap, optimize operating costs, and enhance market competitiveness, so as to solve the problems in the above-mentioned background technology.

[0007] In order to achieve the above-mentioned object, the present invention provides the following technical solutions: an industrial automatic control system, including an initial uniform mixing module, a real-time parameter monitoring module, a feature extraction and quantification module, an intelligent state evaluation module, a state classification decision module, a stable stage operation module and a dynamic speed regulation response module: The initial uniform mixing module increases the shear mixer to mix the pulp raw materials through the preset shear rate, ensuring the uniform dispersion of fibers, fillers and additives, and improving the fluidity and consistency of the pulp; Real-time parameter monitoring module, which monitors and records the physical and chemical parameters of pulp raw materials in real time during the mixing process, providing raw data for subsequent analysis and decision-making; The feature extraction and quantification module pre-processes the acquired data information, extracts the key features reflecting the bubble development trend in the pulp raw material from the pre-processed data, and conducts in-depth analysis of the extracted key features under the detection window to quantify the change trend of the pulp raw material; The intelligent status assessment module inputs the analyzed key features into the pre-trained machine learning model, performs intelligent assessment on the quantified features, and predicts the status of pulp raw materials; The state classification decision module divides the state of pulp raw materials into "bubble potential formation stage" and "stable equilibrium stage" according to the evaluation results of the machine model; The stable phase operation module continues to use the preset standardized shear rate for the "stable equilibrium phase" to maintain the stability and consistency of the slurry; The dynamic speed control response module dynamically increases the shear rate in the "potential bubble formation stage", destroys potential bubble nuclei, strengthens the dispersion and fusion of fibers and additives, and thus avoids bubble formation.

[0008] Preferably, key features reflecting the development trend of bubbles in the pulp raw material are extracted from the preprocessed data, and the extracted features include the fluid dynamics disturbance intensity during the pulp mixing process and the intensity of the vortex inside the pulp. Under the detection window, the extracted fluid dynamics disturbance intensity during the pulp mixing process and the intensity of the vortex inside the pulp are analyzed to generate a fluid dynamic disturbance index and an eddy current intensity index, respectively. The changing trend of the pulp raw material is quantified by the fluid dynamic disturbance index and the eddy current intensity index.

[0009] Preferably, the specific steps of analyzing the fluid dynamic disturbance intensity during the slurry mixing process under the detection window to generate the fluid dynamic disturbance index are as follows: During the slurry mixing process, the disturbance field model is established by real-time monitoring of the pressure distribution and flow rate changes to describe the dynamic state inside the slurry. The generation formula is as follows: , where is the perturbation field model performance value, are coordinates in three-dimensional space, is the Laplace operator of the pressure field, is the slurry density, is the dynamic viscosity, is the velocity distribution, is the differential symbol; According to the disturbance field model, the local disturbance energy density is further calculated to quantify the energy generated by the dynamic fluctuations in the slurry. The calculation expression is as follows: , where is the local perturbation energy density, is the energy loss coefficient, is the high-order divergence of the slurry velocity field; Comprehensive disturbance field model performance value and the local perturbation energy density , generate a comprehensive fluid dynamic disturbance index, the generation formula is as follows: , where is the fluid dynamic disturbance index, It is the reference pressure value when the slurry is in a stable equilibrium state. is the reference energy density when the slurry is in a stable equilibrium state, is the slurry volume, is a volume element.

[0010] Preferably, the specific steps of analyzing the strength of the eddy current inside the slurry under the detection window to generate the eddy current strength index are as follows: In the slurry mixing process, the vortex field is first obtained through fluid dynamics calculation. The calculation expression is as follows: , where is the vorticity field, which represents the local intensity of the fluid rotational motion, is a vector differential operator, is the velocity field vector, is the curl of the velocity field, is the vector cross product operator; According to the collected vorticity field The local eddy current energy density in the slurry mixing area is further calculated based on the data. The calculation expression is as follows: , where is the local eddy current energy density, is the slurry density, is the dynamic viscosity, is the divergence of the vorticity field; The local eddy energy density is integrated over the entire mixing region and combined with the rotational non-uniformity and spatial weighting to generate the global eddy intensity index. The formula is as follows: , is the eddy current intensity index, is the spatial region, is the curl modulus of the vorticity field, is the spatial weight function.

[0011] Preferably, after analyzing the extracted features, the analyzed fluid dynamic disturbance index and eddy current intensity index are input into a pre-learned machine learning model, and a pulp mixing deviation index is generated through the machine learning model, and the pulp raw material state is intelligently predicted through the pulp mixing deviation index.

[0012] Preferably, the pulp mixing deviation index generated when the pulp raw material state is intelligently predicted by the pre-learned machine learning model is compared and analyzed with a pre-set pulp mixing deviation index reference threshold, and the state of the pulp raw material is divided, and the division steps are as follows: If the pulp mixing deviation index is greater than a preset pulp mixing deviation index reference threshold, the state of the pulp raw material is classified as a "bubble potential formation stage"; If the pulp mixing deviation index is less than or equal to a preset pulp mixing deviation index reference threshold value, the state of the pulp raw material is classified as a "stable equilibrium stage".

[0013] Preferably, for the "potential bubble formation stage", the specific steps of dynamically increasing the shear rate, destroying the potential bubble nuclei, and strengthening the dispersion and fusion of fibers and additives to avoid bubble formation are as follows: When the pulp enters the "potential bubble formation stage", the shear rate is dynamically adjusted to suppress bubble generation. The shear rate adjustment amount is based on the pulp mixing deviation index. The difference between the pulp mixing deviation index reference threshold is calculated using the following expression: , , where is the shear rate adjustment, is the adjustment factor, is the reference threshold value of pulp mixing deviation index, is the preset normalized shear rate, is the dynamically adjusted shear rate; The shear rate is adjusted dynamically , generating strong shear force, thereby destroying the potential bubble nuclei in the slurry. The shear force is determined by the slurry viscosity and shear rate. At the same time, the local pressure change further evaluates the degree of elimination of the bubble nuclei. The calculation expression is as follows: , , where is the shear force, is the dynamic viscosity, is the local pressure change, is the effective area of ​​the slurry mixer; After applying the dynamic shear rate, the adjustment effect is continuously monitored and the adjusted pulp mix deviation index is calculated ,like , indicating that the slurry has returned to a stable state and gradually recovered to the preset standardized shear rate ,like , the dynamic shear rate is maintained until the potential formation trend of bubbles disappears completely. The expression is as follows: Restore the preset rate; Maintain dynamic shear rate.

[0014] In the above technical solution, the technical effects and advantages provided by the present invention are: The present invention uses a complete industrial automatic control system, from initial mixing to dynamic adjustment, and each module works together to effectively optimize the mixing quality of pulp. The initial uniform mixing module ensures that the fibers, fillers and additives of the pulp reach a highly uniform state at the initial stage of mixing, laying a stable foundation for subsequent monitoring and regulation. The real-time monitoring and feature extraction module accurately captures the early signals of bubble generation through fluid dynamic disturbance indicators and eddy current intensity indicators, and the intelligent evaluation module converts these signals into specific pulp mixing deviation indexes to provide data support for dynamic response. When the potential formation stage of bubbles is detected, the dynamic speed regulation response module quickly adjusts the shear rate to effectively destroy the potential bubble nucleus and avoid bubble expansion and formation, thereby solving the problem of pinholes and coating peeling of coated paper caused by bubble generation from the root. This closed-loop control significantly reduces the scrap rate and return rate of finished paper, especially in the production of high-end coated paper, greatly improving product quality and customer satisfaction, while reducing economic losses caused by quality defects.

[0015] The present invention improves the automation level and operation efficiency of the production process and reduces the need for manual intervention through real-time parameter monitoring and intelligent response. When the slurry state is normal, the stable stage operation module maintains a standardized shear rate to avoid unnecessary speed regulation operations and increased energy consumption, while reducing the mechanical load of the equipment, which helps to extend the life of the equipment. In the potential bubble formation stage, the dynamic speed regulation response module adjusts the shear rate according to actual needs, which not only achieves a rapid response to abnormal conditions, but also prevents energy waste and excessive wear that may be caused by traditional fixed-rate operations. This precise and efficient control method not only improves production efficiency, but also optimizes energy utilization and equipment maintenance costs, saving a lot of operating expenses for enterprises, enhancing market competitiveness, and ensuring the long-term stable operation of the production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0017] Figure 1 The figure is a module schematic diagram of an industrial automatic control system of the present invention. DETAILED DESCRIPTION

[0018] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0019] The present invention provides Figure 1 An industrial automatic control system shown includes an initial uniform mixing module, a real-time parameter monitoring module, a feature extraction and quantification module, an intelligent state evaluation module, a state classification decision module, a stable phase operation module and a dynamic speed regulation response module: The initial uniform mixing module increases the shear mixer to mix the pulp raw materials through the preset shear rate, ensuring the uniform dispersion of fibers, fillers and additives, and improving the fluidity and consistency of the pulp; The preset shear rate refers to a fixed shear rate within a certain range that is set in advance during the operation of the high shear mixer, based on the characteristics of the pulp raw materials (such as viscosity, fiber length, filler content and type of additives) and the target process requirements (such as mixing uniformity and fluidity). The shear rate is essentially the velocity gradient generated when the linear velocity of the mixer's stirring blades or rotor contacts the slurry, usually expressed in seconds. By setting the appropriate shear rate, it can be ensured that the slurry is subjected to sufficient shear force during the mixing process, quickly breaking up fiber agglomerates and evenly dispersing fillers and additives, while avoiding fiber breakage caused by excessively high shear rates or uneven mixing caused by too low shear rates. The preset shear rate not only optimizes the mixing efficiency, but also provides a benchmark reference for subsequent monitoring and dynamic adjustment.

[0020] Real-time parameter monitoring module, which monitors and records the physical and chemical parameters of pulp raw materials in real time during the mixing process, providing raw data for subsequent analysis and decision-making; During the mixing process, the state of the pulp raw material may change due to factors such as temperature, viscosity, and fluidity. By installing various sensors (such as viscometers, densitometers, flow meters, temperature sensors, etc.), the high shear mixer can obtain data on these key parameters in real time. These data reflect the immediate state of the pulp raw material during the mixing process and are the basis for subsequent feature extraction and machine learning model evaluation. Real-time data collection ensures comprehensive monitoring of the mixing process and can detect potential problems in a timely manner.

[0021] The feature extraction and quantification module pre-processes the acquired data information, extracts the key features reflecting the bubble development trend in the pulp raw material from the pre-processed data, and conducts in-depth analysis of the extracted key features under the detection window to quantify the change trend of the pulp raw material; The original collected data often contains noise, missing values ​​or outliers, which are unnecessary information that may interfere with subsequent analysis. The preprocessing steps include data cleaning, interpolation of missing values, noise filtering, standardization or normalization to improve the quality and consistency of the data. For example, filtering algorithms are used to remove random noise in sensor signals, or missing data points are filled by interpolation methods. The preprocessed data is cleaner and more reliable, and can accurately reflect the true state of the pulp raw materials.

[0022] The key features reflecting the development trend of bubbles in the pulp raw materials are extracted from the preprocessed data. The extracted features include the fluid dynamics disturbance intensity during the pulp mixing process and the intensity of the vortex inside the pulp. Under the detection window, the extracted fluid dynamics disturbance intensity and the intensity of the vortex inside the pulp during the pulp mixing process are analyzed to generate the fluid dynamic disturbance index and the vortex intensity index respectively. The change trend of the pulp raw materials is quantified by the fluid dynamic disturbance index and the vortex intensity index.

[0023] The significant increase in the intensity of fluid dynamic disturbance during the slurry mixing process usually indicates that bubbles are about to appear in the pulp raw material during the shear mixing process. This is because the increase in the intensity of fluid dynamic disturbance reflects that the stability of the flow inside the slurry is destroyed, and the local area may enter an unstable state due to the fluctuation of shear rate or the change of pressure gradient. In this case, low-pressure areas or enhanced turbulence may form in the slurry, and these conditions are the prerequisites for the generation of bubble nuclei. During mixing, the pressure fluctuation of the fluid will cause the precipitation of dissolved gas in the slurry, further promoting the generation of microbubbles. In addition, the increase in fluid disturbance intensity is often accompanied by uneven local flow velocity and dynamic changes in viscosity, which will aggravate the flow discontinuity of the slurry and provide more favorable conditions for the growth of bubbles. Therefore, when the intensity of fluid dynamic disturbance increases significantly, it can serve as an important early signal of the potential formation of bubbles in the slurry, and it is necessary to immediately suppress the further generation and expansion of bubbles by dynamically adjusting the mixing parameters (such as shear rate) or optimizing the operating conditions.

[0024] The specific steps for analyzing the fluid dynamic disturbance intensity during slurry mixing under the detection window to generate the fluid dynamic disturbance index are as follows: During the slurry mixing process, the disturbance field model is established by real-time monitoring of the pressure distribution and flow rate changes to describe the dynamic state inside the slurry. The generation formula is as follows: , where is the disturbance field model performance value, are coordinates in three-dimensional space, is the Laplace operator of the pressure field, is the slurry density, reflecting the physical properties of the slurry, is the dynamic viscosity, which is used to measure the viscosity of slurry flow. is the velocity distribution, describing the motion state of the slurry, is the differential symbol, indicating the velocity distribution About a certain coordinate ( or ) Through this step, the coupling relationship between the velocity gradient and the pressure field in the slurry can be analyzed, and the disturbance field model can be calculated. This model quantitatively describes the local pressure changes and provides a basis for subsequent disturbance energy calculations.

[0025] The Laplace operator of pressure field is an important mathematical tool to describe the trend of pressure distribution in space, which is defined as the pressure field in three spatial directions. The sum of the second-order partial derivatives of is given by . It reflects the characteristics of pressure diffusion or aggregation in all directions. The Laplace operator is used to analyze the degree and trend of change of local pressure of slurry during mixing. If the Laplace value is large, it usually means that there is significant local inhomogeneity in the pressure field, which may lead to enhanced fluid dynamics disturbances and even the formation of low-pressure areas, providing conditions for the generation of bubbles.

[0026] By calculating the Laplace operator, the overall dynamic characteristics of the pressure field can be quantified, providing an accurate basis for slurry state evaluation and mixing optimization.

[0027] According to the disturbance field model, the local disturbance energy density is further calculated to quantify the energy generated by the dynamic fluctuations in the slurry. The calculation expression is as follows: , where is the local perturbation energy density, is the energy loss coefficient, which is used to quantify the energy lost inside the slurry due to turbulent dissipation, is the high-order divergence of the slurry velocity field.

[0028] The high-order divergence of the slurry velocity field refers to the Laplace operator of the velocity field Divergence , which describes a more complex variation pattern of the velocity field in space. Specifically, the high-order divergence measures how the curvature distribution and non-uniformity of the velocity are further transmitted and diffused in space. It is a quantitative indicator for a deeper analysis of the spatial variation of the velocity field, reflecting the degree of diffusion of local turbulence or fluid disturbances in different regions. The high-order divergence can reveal the complex dynamic behavior in the slurry velocity field, especially during the shear mixing process, when nonlinear turbulence or local flow instability occurs inside the slurry, the high-order divergence value will increase significantly, indicating a significant disturbance in the fluid state. By monitoring this parameter, it can be determined whether there is excessive shear force or uneven flow inside the slurry, which are usually closely related to the formation of bubble nuclei. Therefore, high-order divergence is of great significance in evaluating the fluid dynamics characteristics of slurry, predicting the risk of bubble generation, and optimizing mixer operating parameters.

[0029] Through this step, the disturbance energy density at different positions of the slurry can be accurately calculated. The values ​​indicate strong local dynamic fluctuations, which may lead to bubble generation.

[0030] Comprehensive disturbance field model performance value and the local perturbation energy density , generate a comprehensive fluid dynamic disturbance index, the generation formula is as follows: , where is the fluid dynamic disturbance index, It is the reference pressure value when the slurry is in a stable equilibrium state. is the reference energy density when the slurry is in a stable equilibrium state, is the slurry volume, is a volume element.

[0031] Through the above steps, the dynamic changes of pressure field and energy density are comprehensively considered to generate Indicator. Larger The value indicates that the internal flow stability of the slurry is reduced and the dynamic disturbance is enhanced, suggesting the possibility of bubble generation; the smaller The value indicates that the slurry is stable and can maintain the current shear rate for mixing. This indicator provides a scientific basis for real-time monitoring and adjustment of bubble generation.

[0032] The larger the performance value of the fluid dynamic disturbance index generated after analyzing the fluid dynamic disturbance intensity during the slurry mixing process under the detection window, the greater the flow stability of the pulp raw material has been destroyed, and there may be excessive shear rate or abnormal pressure distribution in the local area, which makes it easy for dissolved gas to precipitate and form bubble nuclei. The increase in this performance value is a typical signal that bubbles are about to appear in the slurry. When the performance value of the fluid dynamic disturbance index is small, the fluid state of the reaction slurry tends to be stable, the shear action is uniform and there is no significant abnormality, indicating that the pulp raw material is in a stable and balanced state during the mixing process.

[0033] The abnormal increase in the intensity of the vortex inside the slurry usually indicates that bubbles are about to appear during the shear mixing process of the pulp raw material. This is because the abnormal increase in the vortex intensity will cause the instability of the local fluid dynamics of the slurry, thus providing favorable conditions for the generation of bubbles. When the vortex intensity increases, the shear stress and rotational motion in the slurry intensify, resulting in a significant decrease in the pressure in the local area, and the low-pressure environment is the key physical condition for the formation of bubble nuclei. In addition, strong vortices may lead to uneven distribution of the slurry, especially when the fibers, fillers or additives are not fully dispersed. This unevenness will form a local high-viscosity area, further amplifying the fluid disturbance and increasing the probability of bubble generation. At the same time, the rotational motion inside the slurry may also involve air or expand the volume of existing tiny bubbles, causing the bubbles to gradually develop into obvious quality defects. Therefore, the abnormal increase in vortex intensity is a key early signal, indicating that the slurry is approaching the critical conditions for bubble generation, and timely intervention is required by dynamically adjusting the shear rate or other process parameters to avoid bubbles from affecting the mixing effect and the quality of the final product.

[0034] The specific steps for analyzing the strength of the eddy current inside the slurry under the detection window to generate the eddy current strength index are as follows: In the slurry mixing process, the vortex field is first obtained through fluid dynamics calculation. The calculation expression is as follows: , where is the vorticity field, which represents the local intensity of the fluid rotational motion, is a vector differential operator, is the velocity field vector, which indicates the flow velocity of the fluid at each point in space. is the curl of the velocity field, which is the result of the gradient operation of the velocity field and is used to calculate the rotation effect of the fluid in the local area. is the vector cross product operator; The purpose of this step is to quantify the intensity and distribution of the slurry's rotational motion during the mixing process, and to provide basic data for analyzing the eddy current characteristics inside the slurry. This step is the prerequisite for generating the eddy current intensity index, which helps capture the rotation characteristics during the slurry mixing process.

[0035] According to the collected vorticity field The local eddy current energy density in the slurry mixing area is further calculated based on the data. The calculation expression is as follows: , where is the local eddy current energy density, is the slurry density, reflecting the physical properties of the slurry, is the dynamic viscosity, which is used to measure the viscosity of slurry flow. It is the divergence of the vorticity field, reflecting the diffusion or convergence tendency of the vortex; The purpose of this step is to quantify the local energy level of the vortex, combine the vorticity intensity with the slurry properties, and thus evaluate the disturbance intensity and dynamic impact inside the slurry.

[0036] The local eddy energy density is integrated over the entire mixing region and combined with the rotational non-uniformity and spatial weighting to generate the global eddy intensity index. The formula is as follows: , is the eddy current intensity index, is the spatial region used to analyze the spatial range of eddy current intensity, is the curl modulus of the vorticity field, reflecting the non-uniformity of the rotation distribution in the eddy field. is the vector cross product operator, is the spatial weight function, based on the location The defined weight function is used to assign different importance to different points in the monitoring area.

[0037] This step integrates the local energy distribution, rotational non-uniformity, and regional importance to generate a global indicator of vortex strength, indicating whether the slurry is at a high risk of bubble generation.

[0038] The larger the eddy current intensity index value generated after analyzing the intensity of the eddy current inside the slurry under the detection window, the more it usually indicates that bubbles are about to appear in the pulp raw material during the shear mixing process. Conversely, it indicates that the pulp raw material is in a stable and balanced state during the shear mixing process. This is because the eddy current intensity index reflects the intensity of the rotational motion inside the slurry and the degree of fluid dynamic disturbance. When the index value is large, it means that the shear stress and rotational force field inside the slurry are significantly enhanced, which may cause a local pressure drop or unstable flow, creating favorable conditions for the formation of bubble nuclei. At the same time, strong eddies may also cause air entrainment or the expansion of tiny bubbles, further increasing the risk of bubble generation. On the contrary, when the eddy current intensity index value is small and stable, it means that the flow state of the slurry is uniform, there is no obvious disturbance, the fluid is in a stable state, and bubbles are not easy to appear.

[0039] The intelligent status assessment module inputs the analyzed key features into the pre-trained machine learning model, performs intelligent assessment on the quantified features, and predicts the status of pulp raw materials; After analyzing the extracted features, the analyzed fluid dynamic disturbance index and eddy current intensity index are input into the pre-learned machine learning model, and the pulp mixing deviation index is generated by the machine learning model. The pulp raw material state is intelligently predicted by the pulp mixing deviation index.

[0040] A pre-learned machine learning model refers to an intelligent algorithm model that has a certain predictive ability and can be applied to the actual production environment through training on a large amount of historical data. Before this model is actually used, it needs to be trained offline in combination with key parameters in the pulp mixing process (such as fluid dynamic disturbance index and vortex intensity index) and their impact on the final mixing effect. During the training process, the model will learn the nonlinear relationship between the characteristic parameters and the pulp state (such as the "stable equilibrium stage" and the "potential bubble formation stage"), and extract potential patterns that can reflect the trend of mixing deviation. For example, by inputting fluid dynamic disturbance and vortex intensity data at different stages, the model will gradually adjust the internal weights to optimize the classification of pulp state and the prediction of deviation index. Ultimately, the trained model can generate the pulp mixing deviation index from the input features with high accuracy, providing a basis for predicting the state of pulp raw materials.

[0041] The advantage of this pre-learned model lies in its strong generalization and real-time prediction capabilities. On the one hand, the model can summarize rules from complex historical data, so that it can work effectively in new data scenarios. On the other hand, it can quickly generate a pulp mixing deviation index by inputting online data in real time (such as current disturbance indicators and eddy current intensity), reflecting whether the current state is close to abnormality or deviates from the expected mixing effect. This intelligent prediction can significantly improve production efficiency and avoid the uncertainty and delayed response of manual judgment. At the same time, through continuous online feedback, the model can also be retrained regularly to adapt to new working conditions or changes in equipment parameters, thereby ensuring the accuracy and adaptability of its predictions. This makes the pre-learned machine learning model a core tool for intelligent monitoring and adjustment in the pulp mixing process.

[0042] The machine learning model is not limited here and can realize the fluid dynamic disturbance index and eddy current intensity index Comprehensive analysis to generate a pulp blend deviation index The machine learning model can be used. In order to realize the technical solution of the present invention, the present invention provides a specific implementation method; Pulp Mixing Deviation Index The generation formula is as follows: , where , The fluid dynamic disturbance index and eddy current intensity index The preset scaling factor of , Both are greater than 0.

[0043] It can be seen from the pulp mixing deviation index that the greater the performance value of the fluid dynamic disturbance index generated after analyzing the fluid dynamic disturbance intensity in the pulp mixing process under the detection window, the greater the performance value of the eddy current intensity index generated after analyzing the intensity of the vortex inside the pulp under the detection window, then the greater the performance value of the pulp mixing deviation index generated when the pulp raw material state is intelligently predicted by the pre-learned machine learning model, indicating that the probability of bubbles appearing in the pulp raw material is greater, and vice versa, the probability of bubbles appearing in the pulp raw material is smaller.

[0044] Preset scale factor , It is used to adjust the weights of different indicators in the comprehensive calculation to reflect the influence of each indicator in generating the pulp mixing deviation index. Specifically, these proportionality coefficients determine the hydrodynamic disturbance index and eddy current intensity index The selection of preset proportionality coefficients is usually based on experimental data, process requirements or specific production conditions, with the aim of ensuring that the pulp mixing deviation index It is more sensitive to changes in key parameters, thereby improving the accuracy of predicting the pulp mixing state.

[0045] when When it is large, the fluid dynamic disturbance index Pulp Mixing Deviation Index The influence of is more significant, which is suitable for process scenarios that are sensitive to fluid dynamic disturbances; When it is larger, the eddy current intensity index It plays a leading role in the formula and is suitable for situations where the eddy current intensity needs to be monitored. Therefore, the reasonable selection and setting of these proportional coefficients can balance the influence of different parameters and ensure that the pulp mixing deviation index is Better meet actual production needs and optimize the monitoring and adjustment of the pulp mixing process.

[0046] The state classification decision module divides the state of pulp raw materials into "bubble potential formation stage" and "stable equilibrium stage" according to the evaluation results of the machine model; The pulp mixing deviation index generated when the pulp raw material state is intelligently predicted by the pre-learned machine learning model is compared and analyzed with the pre-set pulp mixing deviation index reference threshold, and the state of the pulp raw material is divided. The division steps are as follows: If the pulp mixing deviation index is greater than a preset pulp mixing deviation index reference threshold, the state of the pulp raw material is classified as a "bubble potential formation stage"; If the pulp mixing deviation index is less than or equal to a preset pulp mixing deviation index reference threshold value, the state of the pulp raw material is classified as a "stable equilibrium stage".

[0047] The "potential bubble formation stage" refers to the stage in the pulp mixing process when the fluid dynamics and mixing state of the slurry begin to show abnormal changes, which may lead to the generation and expansion of bubbles. At this stage, the key indicators of the slurry (such as fluid dynamic disturbance intensity and eddy strength) may fluctuate significantly, reflecting the existence of low-pressure areas, uneven shear force or unstable viscosity in local areas of the slurry. The "stable equilibrium stage" refers to the pulp mixing process in a dynamic equilibrium state, and the fluid dynamics and physical parameters of the slurry remain stable without significant abnormal fluctuations. This stage shows that the fibers, fillers and additives of the slurry are evenly distributed, the mixing effect is good, and the key indicators (such as fluid dynamic disturbance intensity and eddy strength) are within the normal range.

[0048] The stable phase operation module continues to use the preset standardized shear rate for the "stable equilibrium phase" to maintain the stability and consistency of the slurry; In the "stable equilibrium stage", the main purpose of continuing to use the preset standardized shear rate is to maintain the fluidity, consistency and stability of the mixing state of the slurry. At this time, the fibers, fillers and additives of the slurry have been evenly distributed, and the dynamic changes of the system are small. The use of standardized shear rate can avoid introducing additional disturbances, prevent the occurrence of fiber agglomeration or filler sedimentation in the slurry, and reduce energy consumption and mechanical wear of equipment. In addition, this speed ensures that the slurry has good processing performance in subsequent processing links (such as coating or pressing), reduces quality fluctuations caused by unnecessary rate adjustments, and maintains the efficiency and reliability of the entire production process.

[0049] The dynamic speed control response module dynamically increases the shear rate in the "potential bubble formation stage", destroys potential bubble nuclei, and strengthens the dispersion and fusion of fibers and additives, thereby avoiding bubble formation; In view of the "potential bubble formation stage", the specific steps of dynamically increasing the shear rate, destroying the potential bubble nuclei, and strengthening the dispersion and fusion of fibers and additives to avoid bubble formation are as follows: When the pulp enters the "potential bubble formation stage", the shear rate is dynamically adjusted to suppress bubble generation. The shear rate adjustment amount is based on the pulp mixing deviation index. The difference between the pulp mixing deviation index reference threshold is calculated. The adjusted shear rate is the superposition of the preset standardized shear rate and the adjustment amount. The calculation expression is as follows: , , where is the shear rate adjustment, is the adjustment factor used to adjust the shear rate to the pulp mixing deviation index The response amplitude, is the reference threshold value of pulp mixing deviation index, is the preset normalized shear rate, is the dynamically adjusted shear rate; By calculating the dynamic adjustment , ensuring that the shear rate can respond promptly to abnormal changes in the slurry state and suppress the trend of bubble generation.

[0050] The shear rate is adjusted dynamically , generating strong shear force, thereby destroying the potential bubble nuclei in the slurry. The shear force is determined by the slurry viscosity and shear rate. At the same time, the local pressure change further evaluates the degree of elimination of the bubble nuclei. The calculation expression is as follows: , , where It is shear force. Shear force is a key indicator for destroying bubble nuclei and promoting the full mixing of fibers, fillers and additives. Larger shear force can break the local low-pressure area, thereby inhibiting the generation and expansion of bubbles. is the dynamic viscosity, which is used to measure the viscosity of slurry flow. It is the local pressure change, indicating the pressure adjustment amplitude of the slurry under the action of shear force. is the effective area of ​​the slurry mixer; The enhanced shear forces generated by increasing the shear rate can disrupt local low-pressure areas, inhibit the formation of bubble nuclei, and optimize the dispersion of fibers and additives.

[0051] After applying the dynamic shear rate, the adjustment effect is continuously monitored and the adjusted pulp mix deviation index is calculated ,like , indicating that the slurry has returned to a stable state and gradually recovered to the preset standardized shear rate ,like , the dynamic shear rate is maintained until the potential formation trend of bubbles disappears completely. The expression is as follows: Restore the preset rate; Maintain dynamic shear rate.

[0052] Through this closed-loop monitoring and control mechanism, the slurry is ensured to be efficient and uniform during the shear mixing process, and the generation and development of bubbles are completely avoided. This not only improves the mixing quality, but also reduces energy consumption and material loss, ensuring the stability and reliability of the entire process.

[0053] In view of the "potential bubble formation stage", the role of dynamically increasing the shear rate is to effectively destroy the immature bubble nuclei in the slurry by enhancing the shear force, inhibit the further generation and expansion of bubbles, and optimize the mixing uniformity inside the slurry to ensure the full dispersion and fusion of fibers, fillers and additives. When the critical conditions for bubble generation gradually form due to local uneven flow, pressure reduction or viscosity fluctuations in the slurry, a single fixed shear rate is often difficult to cope with these dynamic changes and cannot prevent the formation and aggregation of bubbles. Dynamically increasing the shear rate monitors the changes in the slurry state in real time. For example, when the pulp mixing deviation index (PMDI) exceeds the reference threshold, the system is triggered to adjust the shear rate, enhance the local shear force in the slurry, quickly break the bubble nucleus structure, and eliminate the local uneven material distribution caused by insufficient mixing.

[0054] The key to this adjustment is to improve the overall flow properties of the slurry and reduce the local low-pressure area by increasing the shear rate, thereby fundamentally destroying the physical conditions for bubble generation. At the same time, the enhanced shear rate can also make the additives and fibers inside the slurry more evenly dispersed, avoiding further aggravation of the bubble problem due to uneven distribution. In addition, the adjustment of the dynamic shear rate can also quickly respond to the dynamic changes of the slurry, ensure the stable operation of the mixing system, and reduce the quality defects of the finished product caused by bubble problems. Ultimately, this measure not only improves production efficiency and slurry quality, but also significantly reduces scrap and energy loss caused by bubble formation.

[0055] The present invention uses a complete industrial automatic control system, from initial mixing to dynamic adjustment, and each module works together to effectively optimize the mixing quality of pulp. The initial uniform mixing module ensures that the fibers, fillers and additives of the pulp reach a highly uniform state at the initial stage of mixing, laying a stable foundation for subsequent monitoring and regulation. The real-time monitoring and feature extraction module accurately captures the early signals of bubble generation through fluid dynamic disturbance indicators and eddy current intensity indicators, and the intelligent evaluation module converts these signals into specific pulp mixing deviation indexes to provide data support for dynamic response. When the potential formation stage of bubbles is detected, the dynamic speed regulation response module quickly adjusts the shear rate to effectively destroy the potential bubble nucleus and avoid bubble expansion and formation, thereby solving the problem of pinholes and coating peeling of coated paper caused by bubble generation from the root. This closed-loop control significantly reduces the scrap rate and return rate of finished paper, especially in the production of high-end coated paper, greatly improving product quality and customer satisfaction, while reducing economic losses caused by quality defects.

[0056] The present invention improves the automation level and operation efficiency of the production process and reduces the need for manual intervention through real-time parameter monitoring and intelligent response. When the slurry state is normal, the stable stage operation module maintains a standardized shear rate to avoid unnecessary speed regulation operations and increased energy consumption, while reducing the mechanical load of the equipment, which helps to extend the life of the equipment. In the potential bubble formation stage, the dynamic speed regulation response module adjusts the shear rate according to actual needs, which not only achieves a rapid response to abnormal conditions, but also prevents energy waste and excessive wear that may be caused by traditional fixed-rate operations. This precise and efficient control method not only improves production efficiency, but also optimizes energy utilization and equipment maintenance costs, saving a lot of operating expenses for enterprises, enhancing market competitiveness, and ensuring the long-term stable operation of the production line.

[0057] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0058] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0059] It should be noted that, in this article, if there are first and second, etc., relational terms are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0060] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0061] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0062] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0063] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0064] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0065] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

[0066] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. An industrial automatic control system, characterized in that: It includes initial uniform mixing module, real-time parameter monitoring module, feature extraction and quantification module, intelligent state evaluation module, state classification decision module, stable stage operation module and dynamic speed regulation response module: The initial uniform mixing module increases the shear mixer to mix the pulp raw materials through the preset shear rate, ensuring the uniform dispersion of fibers, fillers and additives, and improving the fluidity and consistency of the pulp; Real-time parameter monitoring module, which monitors and records the physical and chemical parameters of pulp raw materials in real time during the mixing process, providing raw data for subsequent analysis and decision-making; The feature extraction and quantification module pre-processes the acquired data information, extracts the key features reflecting the bubble development trend in the pulp raw material from the pre-processed data, and conducts in-depth analysis of the extracted key features under the detection window to quantify the change trend of the pulp raw material; The intelligent status assessment module inputs the analyzed key features into the pre-trained machine learning model, performs intelligent assessment on the quantified features, and predicts the status of pulp raw materials; The state classification decision module divides the state of pulp raw materials into "bubble potential formation stage" and "stable equilibrium stage" according to the evaluation results of the machine model; The stable phase operation module continues to use the preset standardized shear rate for the "stable equilibrium phase" to maintain the stability and consistency of the slurry; The dynamic speed response module dynamically increases the shear rate in the "potential bubble formation stage", destroys potential bubble nuclei, strengthens the dispersion and fusion of fibers and additives, and thus avoids bubble formation.

2. An industrial automatic control system according to claim 1, characterized in that: The key features reflecting the development trend of bubbles in the pulp raw materials are extracted from the preprocessed data. The extracted features include the fluid dynamics disturbance intensity during the pulp mixing process and the intensity of the vortex inside the pulp. Under the detection window, the extracted fluid dynamics disturbance intensity and the intensity of the vortex inside the pulp during the pulp mixing process are analyzed to generate the fluid dynamic disturbance index and the vortex intensity index respectively. The change trend of the pulp raw material is quantified by the fluid dynamic disturbance index and the vortex intensity index.

3. An industrial automatic control system according to claim 2, characterized in that: The specific steps for analyzing the fluid dynamic disturbance intensity during slurry mixing under the detection window to generate the fluid dynamic disturbance index are as follows: During the slurry mixing process, the disturbance field model is established by real-time monitoring of the pressure distribution and flow rate changes to describe the dynamic state inside the slurry. The generation formula is as follows: , where is the disturbance field model performance value, are coordinates in three-dimensional space, is the Laplace operator of the pressure field, is the slurry density, is the dynamic viscosity, is the velocity distribution, is the differential symbol; According to the disturbance field model, the local disturbance energy density is further calculated to quantify the energy generated by the dynamic fluctuations in the slurry. The calculation expression is as follows: , where is the local perturbation energy density, is the energy loss coefficient, is the high-order divergence of the slurry velocity field; Comprehensive disturbance field model performance value and the local perturbation energy density , generate a comprehensive fluid dynamic disturbance index, the generation formula is as follows: , where is the fluid dynamic disturbance index, It is the reference pressure value when the slurry is in a stable equilibrium state. is the reference energy density when the slurry is in a stable equilibrium state, is the slurry volume, It is a volume element.

4. An industrial automatic control system according to claim 2, characterized in that: The specific steps for analyzing the strength of the eddy current inside the slurry under the detection window to generate the eddy current strength index are as follows: In the slurry mixing process, the vortex field is first obtained through fluid dynamics calculation. The calculation expression is as follows: , where is the vorticity field, which represents the local intensity of the fluid rotational motion, is a vector differential operator, is the velocity field vector, is the curl of the velocity field, is the vector cross product operator; According to the collected vorticity field The local eddy current energy density in the slurry mixing area is further calculated based on the data. The calculation expression is as follows: , where is the local eddy current energy density, is the slurry density, is the dynamic viscosity, is the divergence of the vorticity field; The local eddy energy density is integrated over the entire mixing region and combined with the rotational non-uniformity and spatial weighting to generate the global eddy intensity index. The formula is as follows: , is the eddy current intensity index, is the spatial region, is the curl modulus of the vorticity field, is the spatial weight function.

5. An industrial automatic control system according to claim 2, characterized in that: After analyzing the extracted features, the analyzed fluid dynamic disturbance index and eddy current intensity index are input into the pre-learned machine learning model, and the pulp mixing deviation index is generated by the machine learning model. The pulp raw material state is intelligently predicted by the pulp mixing deviation index.

6. An industrial automatic control system according to claim 5, characterized in that: The pulp mixing deviation index generated when the pulp raw material state is intelligently predicted by the pre-learned machine learning model is compared and analyzed with the pre-set pulp mixing deviation index reference threshold, and the state of the pulp raw material is divided. The division steps are as follows: If the pulp mixing deviation index is greater than a preset pulp mixing deviation index reference threshold, the state of the pulp raw material is classified as a "bubble potential formation stage"; If the pulp mixing deviation index is less than or equal to a preset pulp mixing deviation index reference threshold value, the state of the pulp raw material is classified as a "stable equilibrium stage".

7. An industrial automatic control system according to claim 6, characterized in that: In view of the "potential bubble formation stage", the specific steps of dynamically increasing the shear rate, destroying the potential bubble nuclei, and strengthening the dispersion and fusion of fibers and additives to avoid bubble formation are as follows: When the pulp enters the "potential bubble formation stage", the shear rate is dynamically adjusted to suppress bubble generation. The shear rate adjustment amount is based on the pulp mixing deviation index. The difference between the pulp mixing deviation index and the reference threshold is calculated as follows: , , where is the shear rate adjustment, is the adjustment factor, is the reference threshold value of pulp mixing deviation index, is the preset normalized shear rate, is the dynamically adjusted shear rate; The shear rate is adjusted dynamically , generating strong shear force, thereby destroying the potential bubble nuclei in the slurry. The shear force is determined by the slurry viscosity and shear rate. At the same time, the local pressure change further evaluates the degree of elimination of the bubble nuclei. The calculation expression is as follows: , , where is the shear force, is the dynamic viscosity, is the local pressure change, is the effective area of ​​the slurry mixer; After applying the dynamic shear rate, the adjustment effect is continuously monitored and the adjusted pulp mix deviation index is calculated ,like , indicating that the slurry has returned to a stable state and gradually recovered to the preset standardized shear rate ,like , the dynamic shear rate is maintained until the potential formation trend of bubbles disappears completely. The expression is as follows: Restore the preset rate; Maintain dynamic shear rate.

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