A raw material conveying control method for a paste production

Abstract

This invention discloses a method for controlling the conveying of raw materials in ointment production, relating to the field of fluid conveying control technology in ointment production. The method includes: collecting physical morphology data of the ointment raw material and analyzing it to obtain the conveying difficulty value and its level; acquiring structural data of the conveying path and analyzing it to obtain the path conveying difficulty value; correlating the two to obtain a comprehensive conveying difficulty value; determining the target pressure range, pressure change rate, and continuous pressurization time based on this value, and implementing conveying according to a staged pressurization strategy; during the conveying process, comparing the actual and target conveying states in real time to determine deviations; when a deviation is detected, dynamically calibrating and adjusting the pressurization parameters to bring the conveying state back to stability. This invention achieves precise quantification and adaptive intelligent control of conveying difficulty through coupled analysis of raw material characteristics and path resistance, solving the problems of easy blockage, instability, and high energy consumption in ointment raw material conveying, and improving conveying efficiency and reliability.

Description

Technical Field

[0001] This invention relates to the field of fluid transport control technology in ointment production, specifically a raw material transport control method for ointment production. Background Technology

[0002] In the production of ointments (such as medicated creams, lotions, ointments, and cosmetic pastes), it is common to transport semi-fluid ointment-like raw materials from storage tanks to subsequent processes such as mixing and filling. These raw materials typically exhibit non-Newtonian fluid properties, and their rheological parameters, such as apparent viscosity and yield stress, are affected by factors such as temperature, shear history, and solids content in the formulation. Furthermore, during transportation, they are prone to problems such as unstable transport, pipeline blockage, excessive energy consumption, or damage to raw material properties due to high flow resistance, shear thinning, or thixotropy.

[0003] Currently, the transportation of ointment raw materials mostly relies on pumping systems with fixed parameters or manual adjustments based on operator experience. Existing methods lack comprehensive analysis of the real-time physical state of the raw materials and the structural resistance of the transportation path, making it impossible to adaptively regulate pressure based on dynamic changes in raw material characteristics and pipeline conditions. This often leads to raw material stagnation when the transportation pressure is insufficient, or raw material phase separation, pipeline wear, and energy waste when the pressure is too high.

[0004] Therefore, there is an urgent need for a method for intelligently assessing the overall difficulty of conveying materials and, based on this, achieving precise, stable, and adaptive pressurization control. Summary of the Invention

[0005] The purpose of this invention is to solve the technical problems in existing ointment raw material transportation methods, such as poor transportation process stability, high energy consumption, low automation, easy blockage, and damage to raw material quality, which are caused by neglecting the coupling effect between the physical form of the raw material and the transportation path. Therefore, this invention proposes a raw material transportation control method for ointment production.

[0006] The objective of this invention can be achieved through the following technical solution: a method for controlling the delivery of raw materials for ointment production, comprising:

[0007] S001: Collect physical morphology data for semi-fluid paste raw materials used in ointment production. The physical morphology data includes the apparent viscosity, yield stress, solid content, particle dispersion state, and rheological properties of the raw materials under the current temperature conditions.

[0008] S002: Based on the collected physical morphology data, the flow behavior of the paste-like raw material under preset conveying conditions is analyzed to obtain the material conveying difficulty value;

[0009] S003: During the transportation of paste-like raw materials, acquire the corresponding transportation path data; based on the transportation path data, analyze the structural factors that generate flow resistance in the transportation path to obtain the path transportation difficulty value;

[0010] S004: Based on the correlation analysis between the raw material transportation difficulty level and the transportation difficulty value of the described path, a comprehensive transportation difficulty value is obtained;

[0011] S005: Based on the comprehensive transportation difficulty value, obtain the target pressure range, pressure change rate and continuous pressurization time parameters for pressurized transportation, and implement pressurized control transportation of paste raw materials according to the staged pressurization strategy;

[0012] S006: During the pressurized controlled conveying process, real-time data on pressure, flow stability, and conveying continuity within the conveying pipeline are acquired. The actual conveying state is compared and analyzed with the target conveying state to determine whether there is a conveying deviation.

[0013] S007: When a conveying deviation is detected, the current pressurized conveying parameters are calibrated and analyzed, and the pressurized conveying parameters are dynamically adjusted according to the calibration analysis results to bring the conveying state back to the target conveying state.

[0014] In a preferred embodiment of the present invention, the flow behavior of the paste-like raw material under preset conveying conditions is analyzed, including:

[0015] The physical parameters are dimensionless to obtain standardized parameters, including the standardized apparent viscosity, yield stress, temperature and solid content.

[0016] Based on the standardized parameters, the viscous resistance index, yield resistance index, temperature-corrected resistance index, and solid phase resistance index were constructed respectively.

[0017] The dominant resistance factor is obtained by analyzing the viscous resistance index, yield resistance index, temperature-corrected resistance index, and solid phase resistance index. Based on the dominant resistance factor and each resistance index, the difficulty value of raw material transportation is calculated through comprehensive resistance correction.

[0018] In a preferred embodiment of the present invention, the structural factors that generate flow resistance in the conveying path are analyzed, including:

[0019] The conveying path is divided into several continuous pipe segments describing axial flow behavior and several local structural units describing local resistance effects. The local structural units include elbows, valves and connecting structures.

[0020] For each continuous pipe segment, the geometric constraint ratio is calculated based on its segment length and inner diameter, and the geometric constraint ratio is subjected to square and logarithmic nonlinear processing to obtain the resistance evolution factor of the pipe segment; the resistance evolution factors of all continuous pipe segments are summed to obtain the comprehensive resistance index of the continuous pipe segment.

[0021] For each bend, the curvature coupling resistance factor is calculated based on its bending angle and equivalent radius of curvature; the curvature coupling resistance factors of all bends are summed and then subjected to square root compression to obtain the comprehensive resistance index of the bend.

[0022] For all local structural elements, the local structural abrupt change resistance index is calculated based on the cross-sectional abrupt change coefficient of each element;

[0023] The dominant resistance factor is determined from the comprehensive resistance index of continuous pipe section, comprehensive resistance index of elbow, and resistance index of local structural change.

[0024] Based on the dominant resistance factors, the logarithmic term is used as a multi-source resistance coupling correction function, and the path transportation difficulty value is calculated through product operation.

[0025] As a preferred embodiment of the present invention, a correlation analysis is performed on the raw material transportation difficulty level and the route transportation difficulty value, including:

[0026] Map discrete material transportation difficulty levels to continuous level coefficients;

[0027] The path transportation difficulty value is normalized by interval processing to obtain the path normalized difficulty value;

[0028] The grade coefficient is compared with the path normalization difficulty value to determine whether the current transportation process is path-driven or material-driven.

[0029] Based on the judgment results, either the path-enhanced nonlinear mapping model or the raw material-enhanced exponential mapping model is selected to calculate the overall transportation difficulty value.

[0030] The calculated comprehensive transportation difficulty value is stabilized and corrected to obtain the final comprehensive transportation difficulty value.

[0031] In a preferred embodiment of the present invention, pressurization control and delivery of paste-like raw materials are implemented according to a staged pressurization strategy, including:

[0032] Based on the different numerical ranges of the final comprehensive conveying difficulty value, the corresponding pressurization control mode is matched. The control modes include low-difficulty flexible conveying mode, medium-difficulty stable conveying mode and high-difficulty enhanced conveying mode.

[0033] Based on the final comprehensive transportation difficulty value, the lower and upper pressure limits of the stratified target pressure range are calculated using a function containing logarithmic terms.

[0034] Different pressure change rate functions are set for the initial pressurization stage, the enhanced pressurization stage, and the stable maintenance stage in the pressurization process, and each function uses the final comprehensive transportation difficulty value as a variable.

[0035] Based on the final comprehensive transportation difficulty value and the real-time flow response correction term, the continuous pressurization time is determined by a dynamic continuous pressurization time model.

[0036] In a preferred embodiment of the present invention, a comparative analysis of the actual conveying state and the target conveying state is performed, including:

[0037] Construct an actual transport status vector based on real-time acquired transport status data;

[0038] Construct a target delivery state vector based on the target pressure range, pressure change rate, and continuous pressurization time;

[0039] Next, calculate the conveying deviation vector and the conveying deviation intensity function between the actual conveying state and the target conveying state;

[0040] Time window analysis was performed on the transport deviation intensity function to obtain the deviation evolution index;

[0041] The type of transport deviation is determined based on the transport deviation intensity function and deviation evolution index.

[0042] In a preferred embodiment of the present invention, calibration analysis of the current pressurized delivery parameters includes:

[0043] After detecting a continuous conveying deviation, the dominant influencing factors of the conveying deviation are identified based on the conveying deviation vector;

[0044] Construct parameter sensitivity functions for the target pressure range, pressure change rate, and duration of pressurization; obtain the set of pressurization parameters to be calibrated;

[0045] Calculate the parameter calibration offset based on the deviation intensity function and the final comprehensive transportation difficulty value;

[0046] An asynchronous, step-by-step dynamic adjustment strategy is adopted to update the parameters, and after adjustment, it is verified whether the delivery state reverts to the target state.

[0047] As a preferred embodiment of the present invention, the dynamic adjustment strategy includes:

[0048] When pressure deviation is determined to be the dominant factor, adjust the lower and upper limits of the target pressure range;

[0049] When the flow stability deviation exceeds the allowable range, the pressure change rate is limited or reduced;

[0050] The adjusted parameter update method is: Θ (k+1) =Θ (k) +ΔΘ (k) , where Θ represents any pressurization control parameter.

[0051] Compared with the prior art, the beneficial effects of the present invention are:

[0052] 1. This invention proposes a method to quantify the flow characteristics of the raw material itself and the structural resistance of the conveying path, and performs a correlation analysis between the two to obtain a comprehensive conveying difficulty value that reflects the complexity of the current conveying task, thus overcoming the limitations of traditional methods that rely on a single empirical parameter for control.

[0053] 2. Based on the comprehensive conveying difficulty value, this invention dynamically determines the optimal target pressure range, pressure change rate and pressurization time. Through a multi-stage pressurization strategy including pre-pressurization, main pressurization and steady-state maintenance, it can apply the most suitable pressure according to the characteristics of different stages such as the start-up, flow and maintenance of raw materials, avoid pressure shock and insufficient pressure, ensure the continuity and stability of conveying, and reduce the risk of pipe blockage and energy consumption.

[0054] 3. During the conveying process, this invention compares the actual state with the target state in real time. By constructing a deviation model, it quickly identifies transient fluctuations and deviations. Once a continuous conveying deviation is detected, it can automatically trace the dominant influencing factors and quantitatively calibrate and dynamically adjust the pressurization parameters to quickly return to the optimal operating state. This improves robustness, adaptability, and long-term operational reliability, reducing reliance on manual intervention. Attached Figure Description

[0055] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0056] Figure 1 This is a flowchart of the method steps of the present invention. Detailed Implementation

[0057] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0058] It should be understood that the terms “comprising” and “including” used in this disclosure and claims indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0059] It should also be understood that the terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the disclosure. As used in this disclosure and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this disclosure and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0060] Please see Figure 1 As shown, a method for controlling the delivery of raw materials for ointment production includes:

[0061] S001: Collect physical morphology data for semi-fluid paste raw materials used in ointment production. The physical morphology data includes the apparent viscosity, yield stress, solid content, particle dispersion state, and rheological properties of the raw materials under the current temperature conditions.

[0062] S002: Based on the collected physical morphology data, the flow behavior of the paste-like raw material under preset transportation conditions is analyzed to obtain the material transportation difficulty value, and the material transportation difficulty value is divided into a preset transportation difficulty level range.

[0063] S003: During the transportation of paste-like raw materials, acquire the corresponding transportation path data. This data includes the total length of the transportation pipeline, the inner diameter of different pipe sections, the number of pipe bends and their bending angles, changes in pipeline slope, and the distribution of valves and connecting structures along the route. Based on the transportation path data, analyze the structural factors that generate flow resistance in the transportation path to obtain the path transportation difficulty value.

[0064] S004: After obtaining the material transportation difficulty level and route transportation difficulty value, a correlation analysis is performed between the two to obtain a comprehensive transportation difficulty value. Based on historical transportation operation data, the comprehensive transportation difficulty value is corrected.

[0065] S005: Based on the comprehensive transportation difficulty value, obtain parameters such as the target pressure range, pressure change rate, and continuous pressurization time for pressurized transportation, and implement pressurized control transportation of paste raw materials according to the staged pressurization strategy, so that the paste raw materials are in a suitable flow state at different transportation stages.

[0066] S006: During the pressurized controlled conveying process, the pressure changes, flow stability, and conveying continuity data in the conveying pipeline are acquired in real time or periodically, and the actual conveying state is compared and analyzed with the target conveying state to determine whether there is a conveying deviation.

[0067] S007: When a conveying deviation is detected, the current pressurized conveying parameters are calibrated and analyzed, and the pressurized conveying parameters are dynamically adjusted according to the calibration analysis results, so that the conveying state of the paste raw material gradually returns to the target conveying state.

[0068] The analysis of the flow behavior of the paste-like raw material under preset conveying conditions is specifically carried out as follows:

[0069] The physical parameters are dimensionless to obtain the corresponding standardized parameters, including the apparent viscosity μ, yield stress τ0, raw material temperature T, and solid content C of the raw material after standardization.

[0070] Based on each standardized parameter, corresponding flow resistance indices are constructed, including: the viscous resistance index R. μ :R μ =ln(1+μ); Yield resistance index R τ :R τ =1+τ0; Temperature-corrected drag index R T :R T =exp(T-1), where T is the standardized temperature, ranging from 0.5 to 1.5; solid-phase resistance index R C :R C =(1+C) 2 ;

[0071] After calculating each resistance index, the dominant resistance factor in the flow process of the paste-like raw material is obtained, and its determination rule is: R max =max(R μ R τ R T R C ).

[0072] Based on the determination of the dominant resistance factor, a comprehensive resistance correction term is set to make overall corrections to the non-dominant factors, thus obtaining the raw material transportation difficulty value D. m The calculation formula is: D m =R max ·(1+ln(1+R μ +R τ +R T +R C ));

[0073] Based on the difficulty value D of raw material transportation m The numerical value of the material's conveying difficulty is used to categorize the conveying difficulty into a preset range of conveying difficulty levels. The specific categorization rule is as follows: if the material conveying difficulty value D... m When β1 < β1, it is judged as a low conveying difficulty level; if β1 ≤ raw material conveying difficulty value D m When the value is less than β2, it is judged as medium conveying difficulty level; if the raw material conveying difficulty value is D...m When ≥β2, it is judged as a high level of transportation difficulty; where β1 and β2 are the transportation difficulty values ​​D calculated by collecting transportation data of different paste-like raw materials in historical production. m The relationship between β1 and delivery success rate can be determined by cluster analysis (such as K-means) or expert experience, with typical values ​​ranging from β1∈[1.5, 3.0] to β2∈[4.0, 6.0].

[0074] The analysis of structural factors that generate flow resistance in the conveying path is carried out in the following specific process:

[0075] Based on the transportation path data, the transportation path is divided into several continuous pipe segments and several local structural units. Among them, the continuous pipe segments describe the axial flow behavior of the paste-like raw material, and the local structural units are used to describe the local resistance effects caused by elbows, valves, and connecting structures.

[0076] For each continuous pipe segment j, obtain its segment length L. j With inner diameter D j And calculate the geometric constraint ratio G of the pipe section. j :G j =L j / D j ;

[0077] Based on the shear accumulation effect that easily occurs during the long-distance transportation of paste-like raw materials, the geometric constraint ratio of each pipe section is subjected to nonlinear evolution processing to obtain the pipe section resistance evolution factor R{S,j}: R S，j =ln(1+G j 2 );

[0078] By aggregating the resistance evolution factors of all continuous pipe segments, the comprehensive resistance index R of the continuous pipe segment is obtained. S : Where M is the number of continuous pipe segments.

[0079] For each bend k in the conveying path, the bending angle θ is obtained. k and the corresponding equivalent radius of curvature r k And calculate the elbow curvature coupling resistance factor R. E，k : ;

[0080] The curvature coupling resistance factors of all elbows are accumulated and then subjected to square root compression to obtain the comprehensive elbow resistance index R. E : Where N is the number of bends.

[0081] Valves, reducers, and connecting structures in the conveying path are considered as local abrupt change units, and the local structural abrupt change resistance index R is calculated. V The calculation method is as follows: Where Q is the number of local structural units. For the first The cross-sectional change coefficient of each local structural unit is used to characterize the magnitude of change in the flow cross section.

[0082] In obtaining the comprehensive resistance index R of the continuous pipe section S Elbow overall resistance index R E and the resistance index R of local structural abrupt changes V Then, determine the dominant resistance factor R in the current transport path. dom That is: R dom =max(R S R E R V );

[0083] Based on the identification of the dominant resistance factors, the non-dominant resistance factors are comprehensively corrected using a multi-source resistance coupling correction function to obtain the path transport difficulty value D. p The calculation formula is: D p =R dom ·[1+ln(1+R S ·R E +R V )).

[0084] The correlation analysis between the two is specifically as follows:

[0085] Based on the obtained material transportation difficulty level, the discrete transportation difficulty level is mapped to the corresponding level coefficient K. m This is to enable correlation analysis with the path transportation difficulty value. The mapping relationship is: if the raw material transportation difficulty level is low, K... m =1; If the difficulty level of raw material transportation is medium, K m =2; if the raw material transportation difficulty level is high, K m =3.

[0086] Based on the obtained path transportation difficulty value D p The path normalization difficulty value D is obtained by performing interval normalization on the path. * p The calculation formula is as follows: , where D p，max and D p，min分别 D is generally obtained through simulation calculations or actual calibration of all conveying paths within the factory area. p，max Take the value for the simplest straight pipe path (approximately 0.5 to 1.0), Dp，min Take the value for the most complex multi-bend path (approximately 5.0 to 8.0).

[0087] In obtaining the grade coefficient K m Path normalization difficulty value D * p Then, the dominant mechanism of the current transportation process is determined, specifically: if If so, it is determined to be path-driven transportation; if If the condition is met, it is determined to be a raw material-dominated transportation method. Here, γ is a preset mechanism judgment threshold used to balance the influence weights of raw material factors and path factors during the transportation process.

[0088] For path-dominated overall difficulty calculation: When the transportation process is determined to be path-dominated, a path-enhanced nonlinear mapping model is used to calculate the overall transportation difficulty value D. c The calculation formula is: D c =D p ·(1+ln(1+K m ·D * p This calculation method is used to amplify the impact of raw material grade differences on transportation difficulty under complex path conditions.

[0089] Calculation of overall transportation difficulty for raw material-dominated processes: When the transportation process is determined to be raw material-dominated, the overall transportation difficulty value D is calculated using a raw material-enhanced index mapping model. c The calculation formula is: D c =K m ·exp(D * p This calculation process reflects the sensitivity of highly complex raw materials to transportation difficulties when path conditions change.

[0090] The calculated overall transportation difficulty value D c After stabilization correction, the final comprehensive transportation difficulty value D is obtained. f The calculation formula is: D f =D c ·(1+ln(1+∣D c -D c，ref ∣));wherein, D c，ref This is a reference comprehensive transportation difficulty value determined based on historical stable operating conditions;

[0091] The process of pressurizing and controlling the delivery of the paste-like raw material according to the staged pressurization strategy is as follows:

[0092] Based on the final comprehensive transportation difficulty value D f The delivery tasks are divided into different difficulty ranges, and corresponding pressurization control modes are matched for each difficulty range:

[0093] If the final comprehensive transportation difficulty value D f When α1 < α1, enter the low-difficulty flexible conveying mode; if α1 ≤ final comprehensive conveying difficulty value D f When the value is less than α2, the system enters a medium-difficulty stable transport mode; if the final comprehensive transport difficulty value is D... f When the value is ≥α2, the system enters a high-difficulty enhanced conveying mode. Here, α1 and α2 are difficulty thresholds set based on equipment capacity and historical operating data.

[0094] After determining the transportation mode, based on the final comprehensive transportation difficulty value D f Constructing hierarchical target pressure ranges [P] min P max The calculation method is as follows: P min =P0·(1+ln(1+D f )) P max =P min ·(1+1+D f ); where P0 is the reference pressure.

[0095] Different pressure change rate functions are set for different pressurization stages:

[0096] The start-up pressurization phase is: V p1 =V0·ln(1+D f The enhanced pressurization phase is as follows: The stable maintenance phase is as follows: Where V0 is the rate of change of the reference pressure.

[0097] To analyze the actual migration behavior of the paste-like raw material in the pipeline, a dynamic continuous pressurization time model T is used. c Its calculation method is as follows: T c =T0·(1+ln(1+D f ))·(1+ΔR); where: T0 is the baseline continuous pressurization time, and ΔR is the real-time flow response correction term, which is used to reflect the degree of transient fluctuation detected by the pressure sensor or flow sensor.

[0098] In this embodiment, the pressurized delivery process is further subdivided into the following stages and sub-stages, including:

[0099] Pre-pressurization stage: P in the range below the stratified target pressure min At this time, the pressure is slowly increased at the pressure level to wet the pipe wall and establish an initial flow channel;

[0100] Main pressurization phase: according to V p1 and V p2 Gradually increase pressure to the target pressure range P in the stratified pressure range maxOvercoming major flow resistance;

[0101] Steady-state maintenance sub-stage: within the target pressure range [P] min P max [Internal periodic fine-tuning of pressure, maintained for a time period T] c ;

[0102] Adaptive adjustment sub-stage: If pressure fluctuations are detected to exceed a preset threshold, the pressure change rate function is dynamically switched;

[0103] Pressure reduction and descent phase: After the delivery is completed, according to V p3 Gradually reduce the pressure to avoid backflow of residual material or negative pressure in the pipeline.

[0104] The switching between stages and sub-stages is performed according to the following criteria: |P real -P target |≤δ; where P real To monitor pressure in real time, P target The target pressure for the stage is δ, and the allowable deviation threshold is δ. If the above conditions are not met, the pressure change rate will be automatically adjusted or the duration of the current stage will be extended, forming a closed-loop pressurization control.

[0105] The comparison and analysis between the actual delivery status and the target delivery status includes:

[0106] During the transportation process, pressure sensors, flow sensors, and operation status acquisition modules installed in the transportation pipeline are used to acquire transportation status data in real time or periodically, including: real-time pressure change data P(t); flow stability characterization data S(t); and transportation continuity characterization data C(t).

[0107] Based on the above data, construct the actual delivery state vector X(t): X(t) = [P(t), S(t), C(t)]

[0108] Based on the obtained target pressure range, pressure change rate, and continuous pressurization time, a target delivery state vector X0(t) is constructed, which has the form: X0(t) = [P0(t), S0(t), C0(t)].

[0109] Where: P0(t) is the target pressure curve; S0(t) is the target flow stability index under the corresponding difficulty range; C0(t) is the target transport continuity index.

[0110] The difference between the actual transport state and the target transport state is quantitatively characterized by the transport deviation vector ΔX(t), which is calculated as follows: ΔX(t) = X(t) - X0(t);

[0111] Furthermore, the transport deviation intensity function E(t) is constructed: ; Among them: ΔP(t)=P(t)-P0(t); ΔS(t)=S(t)-S0(t); ΔC(t)=C(t)-C0(t).

[0112] Next, distinguishing between instantaneous fluctuations and structural deviations, a time window analysis is performed on the transport deviation intensity function E(t), and the deviation evolution index E is calculated within the time window [t−Δt, t]. d (t): ;

[0113] Based on the transport deviation intensity function E(t) and deviation evolution index E d (t), to determine the type of transport deviation:

[0114] When the conveying deviation intensity function E(t)≤θ1 and the deviation evolution index E d When (t)≤θ2, it is determined to be a normal fluctuation state; when the transmission deviation intensity function E(t)>θ1 and the deviation evolution index E d When (t)≤θ2, it is determined to be a transient transport deviation; when the transport deviation intensity function E(t)>θ1 and the deviation evolution index E d When (t) > θ2, it is determined to be a continuous conveying deviation. Here, θ1 and θ2 are preset deviation judgment threshold roots, which are set according to stability requirements, with typical values ​​of θ1=0.3 and θ2=0.05.

[0115] When a transient delivery deviation is identified, the deviation event is recorded and the current pressurization strategy is maintained; when a continuous delivery deviation is identified, a delivery deviation identification signal is generated.

[0116] Based on the delivery deviation identification signal, after obtaining the delivery deviation, the current pressurized delivery parameters are calibrated and analyzed: specifically:

[0117] After detecting a continuous conveying deviation, based on the conveying deviation vector ΔX(t)=[ΔP(t), ΔS(t), ΔC(t)];

[0118] The dominant factors of transport deviation are identified, specifically by calculating the relative contribution of each deviation component:

[0119] , , When a certain contribution exceeds a preset dominant threshold λl, the corresponding parameter is determined to be the dominant influencing factor of the current delivery deviation. The dominant threshold λl is set to 0.5, indicating that when the contribution of a certain deviation component exceeds 50%, it is determined to be the dominant factor.

[0120] For three types of pressurization parameters—target pressure range, rate of pressure change, and duration of pressurization—parameter sensitivity functions are constructed:

[0121] Taking the rate of pressure change as an example, its sensitivity function is defined as: ;

[0122] Similarly, the sensitivity Ψ of the target pressure range is obtained. P (t) and the sensitivity of sustained pressure time Ψ T (t).

[0123] By comparing Ψ P (t), Ψ V (t) and Ψ T The value of (t) is used to obtain the set of pressurization parameters that should be calibrated first.

[0124] After determining the parameters to be calibrated, based on the deviation intensity function E(t) and the final comprehensive transportation difficulty value D... f Calculate the parameter calibration offset.

[0125] Taking the upper limit pressure of the target pressure range as an example, its calibration offset ΔP max The calculation method is as follows: ; where sgn(·) represents the sign function, used to distinguish the adjustment direction between insufficient pressure and excessive pressure.

[0126] In this embodiment, an asynchronous, step-by-step dynamic adjustment strategy is adopted for different pressurization parameters:

[0127] Pressure range adjustment: Adjust P only when pressure deviation is the dominant factor. min and P max ;

[0128] Pressure change rate adjustment: When the pressure deviation component satisfies ϕ P ≥λ P And |ΔP(t)|≥δ P When the pressure deviation is determined to be the dominant factor in the current delivery deviation, the target pressure lower limit P is set. min and target pressure upper limit P max Perform calibration and adjustment; where λ P As the dominant judgment threshold, δ P Pressure deviation amplitude threshold

[0129] Continuous pressurization time adjustment: When the flow stability deviation component satisfies |ΔS(t)|≥δ S And the corresponding deviation evolution index satisfies E d (t)≥θ S When the flow stability deviation exceeds the allowable fluctuation range, the pressure change rate V is adjusted accordingly. p Implement restrictions or downgrades; where δ S θ is the threshold for flow stability deviation. SThe threshold for determining the sustained stability deviation.

[0130] The adjusted parameter update method is: Θ (k+1) =Θ (k) +ΔΘ (k) Where Θ represents any pressurization control parameter.

[0131] After completing one dynamic parameter adjustment, the actual conveying status data is reacquired, and a new conveying deviation intensity function E′(t) is calculated.

[0132] If E′(t)≤μ·E(t), where μ<1 is the regression convergence coefficient, then the regression trend from the delivery state to the target delivery state is determined to be valid, and the current pressurization parameters are retained; if the above conditions are not met, then the next round of calibration analysis is triggered, and the above steps are repeated.

[0133] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for controlling the conveying of raw materials in ointment production, characterized in that, include: S001: Collect physical morphology data for semi-fluid paste raw materials used in ointment production. The physical morphology data includes the apparent viscosity, yield stress, solid content, particle dispersion state, and rheological properties of the raw materials under the current temperature conditions. S002: Based on the collected physical morphology data, the flow behavior of the paste-like raw material under preset conveying conditions is analyzed to obtain the material conveying difficulty value; S003: During the transportation of paste-like raw materials, acquire the corresponding transportation path data; Based on transportation route data, the structural factors that generate flow resistance in the transportation route are analyzed to obtain the route transportation difficulty value. S004: Based on the correlation analysis between the raw material transportation difficulty level and the transportation difficulty value of the described path, a comprehensive transportation difficulty value is obtained; S005: Based on the comprehensive transportation difficulty value, obtain the target pressure range, pressure change rate and continuous pressurization time parameters for pressurized transportation, and implement pressurized control transportation of paste raw materials according to the staged pressurization strategy; S006: During the pressurized controlled conveying process, real-time data on pressure, flow stability, and conveying continuity within the conveying pipeline are acquired. The actual conveying state is compared and analyzed with the target conveying state to determine whether there is a conveying deviation. S007: When a conveying deviation is detected, the current pressurized conveying parameters are calibrated and analyzed, and the pressurized conveying parameters are dynamically adjusted according to the calibration analysis results to bring the conveying state back to the target conveying state.

2. The method for controlling the conveying of raw materials for ointment production according to claim 1, characterized in that, The flow behavior of paste-like raw materials under preset conveying conditions was analyzed, including: The physical parameters are dimensionless to obtain standardized parameters, including the standardized apparent viscosity, yield stress, temperature and solid content. Based on the standardized parameters, the viscous resistance index, yield resistance index, temperature-corrected resistance index, and solid phase resistance index were constructed respectively. The dominant resistance factor is obtained by analyzing the viscosity resistance index, yield resistance index, temperature-corrected resistance index, and solid phase resistance index. Based on the dominant resistance factor and each resistance index, the difficulty value of raw material transportation is calculated through comprehensive resistance correction.

3. The method for controlling the conveying of raw materials for ointment production according to claim 1, characterized in that, The structural factors that generate flow resistance in the transport path are analyzed, including: The conveying path is divided into several continuous pipe segments describing axial flow behavior and several local structural units describing local resistance effects. The local structural units include elbows, valves and connecting structures. For each continuous pipe segment, the geometric constraint ratio is calculated based on its segment length and inner diameter, and the geometric constraint ratio is subjected to square and logarithmic nonlinear processing to obtain the resistance evolution factor of the pipe segment; the resistance evolution factors of all continuous pipe segments are summed to obtain the comprehensive resistance index of the continuous pipe segment. For each bend, the curvature coupling resistance factor is calculated based on its bending angle and equivalent radius of curvature; the curvature coupling resistance factors of all bends are summed and then subjected to square root compression to obtain the comprehensive resistance index of the bend. For all local structural elements, the local structural abrupt change resistance index is calculated based on the cross-sectional abrupt change coefficient of each element; The dominant resistance factor is determined from the comprehensive resistance index of continuous pipe section, comprehensive resistance index of elbow, and resistance index of local structural change. Based on the dominant resistance factors, the logarithmic term is used as a multi-source resistance coupling correction function, and the path transportation difficulty value is calculated through product operation.

4. The method for controlling the conveying of raw materials for ointment production according to claim 1, characterized in that, A correlation analysis was conducted between the difficulty level of raw material transportation and the difficulty value of the transportation route, including: Map discrete material transportation difficulty levels to continuous level coefficients; The path transportation difficulty value is normalized by interval processing to obtain the path normalized difficulty value; The grade coefficient is compared with the path normalization difficulty value to determine whether the current transportation process is path-driven or material-driven. Based on the judgment results, either the path-enhanced nonlinear mapping model or the raw material-enhanced exponential mapping model is selected to calculate the overall transportation difficulty value. The calculated comprehensive transportation difficulty value is stabilized and corrected to obtain the final comprehensive transportation difficulty value.

5. The method for controlling the conveying of raw materials for ointment production according to claim 4, characterized in that, The paste-like raw materials are pressurized and transported according to a phased pressurization strategy, including: Based on the different numerical ranges of the final comprehensive conveying difficulty value, the corresponding pressurization control mode is matched. The control modes include low-difficulty flexible conveying mode, medium-difficulty stable conveying mode and high-difficulty enhanced conveying mode. Based on the final comprehensive transportation difficulty value, the lower and upper pressure limits of the stratified target pressure range are calculated using a function containing logarithmic terms. Different pressure change rate functions are set for the initial pressurization stage, the enhanced pressurization stage, and the stable maintenance stage in the pressurization process, and each function uses the final comprehensive transportation difficulty value as a variable. Based on the final comprehensive transportation difficulty value and the real-time flow response correction term, the continuous pressurization time is determined by a dynamic continuous pressurization time model.

6. The method for controlling the conveying of raw materials for ointment production according to claim 5, characterized in that, The actual conveying status is compared and analyzed with the target conveying status, including: Construct an actual transport status vector based on real-time acquired transport status data; Construct a target delivery state vector based on the target pressure range, pressure change rate, and continuous pressurization time; Next, calculate the conveying deviation vector and the conveying deviation intensity function between the actual conveying state and the target conveying state; Time window analysis was performed on the transport deviation intensity function to obtain the deviation evolution index; The type of transport deviation is determined based on the transport deviation intensity function and deviation evolution index.

7. The method for controlling the conveying of raw materials for ointment production according to claim 6, characterized in that, The current pressurized delivery parameters are calibrated and analyzed, including: After detecting a continuous conveying deviation, the dominant influencing factors of the conveying deviation are identified based on the conveying deviation vector; Construct parameter sensitivity functions for the target pressure range, pressure change rate, and duration of pressurization; obtain the set of pressurization parameters to be calibrated; Calculate the parameter calibration offset based on the deviation intensity function and the final comprehensive transportation difficulty value; An asynchronous, step-by-step dynamic adjustment strategy is adopted to update the parameters, and after adjustment, it is verified whether the delivery state reverts to the target state.

8. The method for controlling the conveying of raw materials for ointment production according to claim 7, characterized in that, Dynamic adjustment strategies include: When pressure deviation is determined to be the dominant factor, adjust the lower and upper limits of the target pressure range; When the flow stability deviation exceeds the allowable range, the rate of pressure change is limited or reduced.

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