Intelligent temperature control mixing method and system for veterinary drug oral liquid preparation tank

Abstract

The invention relates to the technical field of intelligent production of veterinary oral liquid, discloses an intelligent temperature control mixing method of a veterinary oral liquid preparation tank and a system thereof, and mainly solves the problems that a traditional liquid preparation tank depends on manpower, the temperature control precision is low, mixing is uneven, thermosensitive components are prone to inactivation and the like. The method comprises the steps of parameter presetting, medium temperature pre-adjustment, component dynamic adding and temperature control mixing, uniformity verification and output cleaning. The system is composed of a central control module, a multi-parameter monitoring module, a high-precision temperature control module, an intelligent stirring drive module, a material management module and a data communication module. According to the invention, the incremental PID algorithm is adopted to accurately control the temperature, and the stirring speed is adaptively adjusted based on the temperature change rate and the real-time viscosity, so that the full-automatic intelligent control of the mixing process is realized. According to the invention, the uniformity of the product and the retention rate of active ingredients can be obviously improved, the energy consumption and the labor cost are reduced, the complete tracing of production data is realized, and the method is suitable for veterinary oral liquid production with strict temperature control requirements.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent production of veterinary oral liquid, and particularly to an intelligent temperature control mixing method and system for a veterinary oral liquid preparation tank. BACKGROUND

[0002] Veterinary oral liquids, such as antibiotic, vitamin, antiparasitic drug, etc. liquid preparations, are indispensable disease prevention and treatment products in modern livestock and poultry breeding industry. The core link of its production is to fully mix various ingredients such as raw materials, stabilizers, flavoring agents, etc. and solvent (usually water) in the preparation tank to form a uniform and stable solution. The preparation tank is a key equipment in the veterinary preparation workshop, and the mixing quality directly determines the effectiveness, safety and batch consistency of the final product.

[0003] During the whole preparation process, temperature control is crucial. Many veterinary raw materials, especially some antibiotics and biological preparations, are heat-sensitive substances, which are extremely sensitive to temperature. The production process requires that the mixed solution must be mixed and maintained within a narrow and precise temperature window (for example, 35℃±1℃). If the temperature is too low, some auxiliary materials may not be fully dissolved and mixed evenly; if the temperature is slightly above the upper limit, the heat-sensitive active ingredients may be degraded, inactivated, or even produce toxic byproducts, resulting in the entire batch of products being scrapped and causing huge economic losses. Therefore, the temperature control mixing process of the preparation tank is the "neck" link in the production of veterinary oral liquids, and its process level directly reflects the technical strength and quality control ability of the production enterprise.

[0004] At present, most domestic and foreign veterinary drug production enterprises, especially small and medium-sized enterprises, still widely use traditional or semi-automatic preparation tank systems. Such systems have exposed many technical problems in the application process, mainly focusing on the following three aspects:

[0005] Firstly, it is highly dependent on human experience, with poor control accuracy and insufficient stability: the temperature regulation of traditional preparation tanks is usually achieved by workers observing the mechanical thermometer readings on the tank body and manually adjusting the opening of the steam valve and cooling water valve. This operation mode completely depends on the experience and responsibility of the workers. The habit differences of different shifts and different operators will lead to inconsistency in process execution. Manual response has a lag, when low-temperature or room-temperature materials are added, the temperature in the tank will change suddenly, and the operator often waits for the temperature to change before adjusting, which cannot compensate for the temperature shock in time, causing system overshoot or adjustment oscillation, so that the temperature deviates from the process requirement range for a long time, which continuously threatens the activity of heat-sensitive components;

[0006] Secondly, the mixing is uneven, and local overheating and mixing dead angle are prone to occur: the traditional stirring system usually adopts fixed rotating speed or limited rotating speed adjustment. The design of stirring paddle and the setting of rotating speed are usually based on experience rather than scientific calculation. For different volumes and viscosities of liquid medicine, the fixed stirring mode is difficult to achieve uniform mixing of the whole tank. Especially in the tank wall, tank bottom and stirring blind area, fluid static or low speed area is prone to form, and the components are unevenly dispersed. More seriously, the temperature of the area close to the heating coil or tank wall is significantly higher than the main body liquid temperature, and the local overheating (Hot Spots) phenomenon is prominent. These high-temperature "micro-environment" is the "killer" of heat-sensitive components, and the inactivation rate is much higher than the level indicated by the average temperature, resulting in uneven product effective content, and the concentration in some areas may be invalid while the concentration in other areas exceeds the standard;

[0007] Thirdly, the production process is not traceable, and the quality risk is high: the traditional production mode lacks data recording in the whole process. The key process parameters such as temperature and stirring are not recorded electronically, but rely on manual meter reading, which has the risk of misrecording, missing recording or even after-recording. Once the product quality problem (such as content not meeting the standard) occurs, it is difficult to trace which process link deviates, which brings great difficulty to problem troubleshooting and quality improvement. At the same time, due to the lack of data support, process optimization and large-scale production (from small test to pilot test and then to large-scale production) mainly rely on experience, which has long cycle, high cost and high risk.

[0008] In summary, the skilled person in the art urgently needs a technical solution that can completely revolutionize the working mode of the traditional liquid preparation tank. The solution needs an intelligent method and system to solve the above problems. SUMMARY

[0009] The purpose of the present application is to solve the above problems, and an intelligent temperature control mixing method and system for a veterinary oral liquid preparation tank are designed.

[0010] To achieve the above purpose, the technical scheme of the present application is an intelligent temperature control mixing method for a veterinary oral liquid preparation tank, which comprises the following steps:

[0011] S1: parameter presetting and system initialization: input the target production parameters into the system;

[0012] S2: medium pre-warming and initial mixing: pre-warm the solvent and start stirring at the basic rotating speed;

[0013] S3: component addition and dynamic temperature control mixing: add components in sequence, and dynamically adjust the temperature control power and stirring speed in real time to maintain the target temperature;

[0014] S4: uniformity verification and temperature maintenance: verify the mixing uniformity through the sensor;

[0015] S5: output and cleaning: output the liquid medicine and perform automatic cleaning.

[0016] The mathematical model expression of the calculated basic rotation speed R base in S2 is:

[0017] R base = k * ln(V total ) + C

[0018] In the formula, V total is the target total liquid volume, and k and C are empirical constants related to the liquid preparation tank.

[0019] In step S3, the dynamic adjustment of the temperature control power is calculated by using the incremental PID algorithm to calculate the temperature control power adjustment amount ΔP(n). The mathematical model expression for calculating the dynamic adjustment of the temperature control power adjustment amount ΔP(n) is:

[0020] ΔP(n) = K p *[e(n) - e(n-1)] + K i *e(n) + K d *[e(n) - 2e(n-1)

[0021] + e(n-2)]]

[0022] In the formula, ΔP(n) is the power adjustment amount of the heating / cooling unit at the nth sampling (unit: W), e(n), e(n-1), and e(n-2) are the temperature deviations at the nth, (n-1)th, and (n-2)th sampling, respectively, K p is the proportional coefficient, K i is the integral coefficient, and K d is the differential coefficient. The above coefficients can be adaptively adjusted according to the viscosity μ and the liquid volume.

[0023] In step S3, the stirring rotation speed R mixer is calculated by using an adaptive model. The mathematical model expression of the adaptive model is:

[0024]

[0025] In the formula, R mixer is the stirring rotation speed at the current time after dynamic adjustment (unit: RPM), is the absolute value of the temperature change rate at the current time (unit: ℃ / s), which is used to cope with the temperature shock caused by the addition of ingredients, μ current is the viscosity estimated by the system at the last time or the last sampling (unit: cP), μ ref is the expected reference viscosity of the formula (unit: cP), and α and β are weight coefficients, which are determined by machine learning or a large amount of process data optimization.

[0026] An intelligent temperature control mixing system, comprising the following modules:

[0027] A central control module, mainly used for running control algorithm, processing data and controlling the working of functional modules;

[0028] A multi-parameter monitoring module, connected with the central control module, used for real-time acquisition of parameters in the tank;

[0029] A high-precision temperature control module, connected with the central control module, used for adjusting the temperature in the tank;

[0030] An intelligent stirring driving module, connected with the central control module, used for driving and adjusting the rotating speed of the stirrer in the tank;

[0031] A material management module, connected with the central control module, used for controlling the addition and output of materials in the tank;

[0032] A data management and communication module, connected with the central control module, used for recording the data output by the central control module and communicating with external systems.

[0033] The multi-parameter monitoring module comprises at least one of temperature sensors, liquid level sensors, viscosity estimation units and PH value / conductivity / NIR sensors.

[0034] The high-precision temperature control module comprises an electric heating unit, a cooling coil and a regulating valve, and can simultaneously perform heating and cooling operations.

[0035] The intelligent stirring driving module comprises a frequency converter and a servo motor, and can realize stepless speed regulation of the stirring rotating speed.

[0036] The central control module is integrated with mathematical models for calculating the basic rotating speed R base , the incremental PID control amount ΔP(n) and the adaptive stirring rotating speed R mixer .

[0037] The system further comprises a human-computer interaction interface, connected with the central control module, used for inputting parameters and displaying the system state.

[0038] Compared with the prior art, the present application has the following beneficial effects:

[0039] 1. The present application can improve product quality and consistency, through precise temperature control and intelligent mixing, to ensure that the activity loss rate of heat-sensitive components is significantly reduced (expected to be controlled below 1%), the product content uniformity (CU value) is greatly improved, the batch difference is extremely small, and the product quality is significantly better than that of products produced by traditional methods;

[0040] 2、The present application effectively improves production efficiency and automation degree, full-process automatic control, reduces the dependence on skilled operators, shortens the production cycle of single batch products, and reduces the waste rate and downtime caused by manual misoperation;

[0041] 3、The present application can reduce the comprehensive production cost, reduce the loss of raw materials due to degradation, reduce energy consumption (avoid excessive heating / cooling), save labor cost, and reduce the comprehensive production cost from multiple aspects;

[0042] 4、The present application realizes digital management and traceability, has full-process data recording and monitoring function, automatically generates electronic batch record, meets the GMP data integrity requirement, is convenient for quality traceability and process analysis, provides the possibility for continuous improvement and optimization, realizes the digitization and traceability of the production process, provides a solid data foundation for quality assurance (QA) and process optimization, improves production efficiency, reduces energy consumption and waste rate, and finally promotes the intelligent, high-quality transformation and upgrading of veterinary drug preparation production;

[0043] 5、The present application can realize precise, automatic and real-time control of temperature, the system can automatically monitor temperature and quickly respond to internal and external disturbances (such as material addition and environmental temperature change), automatically adjust the input of cold and heat source through intelligent algorithm, strictly control temperature fluctuation in the narrow range required by process, and effectively get rid of the dependence on manual operation;

[0044] 6、The present application realizes the intelligentization and self-adaptation of mixing process, the system can dynamically adjust the stirring intensity and mode according to real-time working conditions (such as liquid level, viscosity and temperature change trend), ensure that efficient and uniform mixing effect can be provided at any time, and strongly eliminate local overheating and mixing dead angle, so as to provide the most gentle and uniform mixing environment for heat-sensitive components. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 It is a flow chart of the intelligent temperature control mixing method of the veterinary oral liquid preparation tank according to embodiment 1 of the present application;

[0046] Figure 2 It is an implementation process parameter table of the vitamin compound oral liquid method according to embodiment 2 of the present application;

[0047] Figure 3 It is a data comparison table of the implementation effect of the vitamin compound oral liquid method according to embodiment 2 of the present application;

[0048] Figure 4 It is a system block diagram of the intelligent temperature control mixing system according to embodiment 3 of the present application;

[0049] Figure 5is a data comparison table of the implementation effect of the intelligent temperature control mixing system according to embodiment 4 of the present application. DETAILED DESCRIPTION

[0050] The embodiments of the present application are specifically described below in combination with the drawings,

[0051] Embodiment 1;

[0052] An intelligent temperature control mixing method of a veterinary oral liquid preparation tank, as shown in the accompanying drawings, comprises the following steps: Figure 1

[0053] S1: parameter presetting and system initialization;

[0054] The main function is that the user inputs the production formula parameters of the present preparation through the man-machine interface, including the target total liquid volume V total , the adding order and timing T_add_i of each heat-sensitive component, the core target temperature T target , the allowed temperature fluctuation range ΔT, and the expected viscosity μ of the mixture, etc.; the system completes self-checking and initialization of each execution unit according to these parameters;

[0055] S2: medium pre-temperature adjustment and initial mixing;

[0056] The main function is that the system controls the feeding valve to inject the main solvent (such as water), and starts the heating / cooling unit to pre-adjust the temperature of the solvent according to T target . When the temperature of the solvent enters the range of [T target - ΔT, T target + ΔT], the stirring motor is started to a basic rotating speed R total calculated based on the total liquid volume V base for preliminary mixing to create a stable environment for adding temperature-sensitive components; wherein the mathematical model expression for calculating the basic rotating speed R base is:

[0057] R base = k * ln(V total ) + C

[0058] In the formula, R base is the basic rotating speed of the stirring mechanism in the tank (unit: RPM), V total is the target total liquid volume, and k and C are empirical constants related to the preparation tank, which are obtained by fitting a large amount of experimental data and are related to the geometric size of the preparation tank and the type of stirring paddle;

[0059] S3: component adding and dynamic temperature control mixing (this step is the core step of the method);

[0060] ​Its main function is to add each component, especially the heat-sensitive component, at a specific time point according to a preset order T_add_i, and during the adding process, the system monitors the temperature T of the mixed solution in real time current , and adjusts the power P of the heating / cooling unit using a dynamic control algorithm heater / P cooler and the rotating speed R of the stirring motor mixer , so as to ensure that T current is always stable within the range of T target ±ΔT, while achieving the best combination of fluid shear force and convection, so that the components are quickly and uniformly dispersed, and local overheating or mixing dead angles are avoided; wherein the mathematical model expression for calculating the dynamic adjustment temperature control power adjustment amount ΔP(n) is:

[0061] ΔP(n)=K p *[e(n)-e(n-1)]+K i *e(n)+K d *[e(n)-2e(n-1)

[0062] +e(n-2)]]

[0063] Wherein, ΔP(n) is the power adjustment amount of the heating / cooling unit at the nth sampling (unit: W), e(n), e(n-1) and e(n-2) are the temperature deviations at the nth, (n-1)th and (n-2)th sampling, respectively, K p is the proportional coefficient, K i is the integral coefficient, and K d is the differential coefficient, and the above coefficients can be adaptively adjusted according to the viscosity μ and the liquid volume;

[0064] The mathematical model expression of the adaptive model is:

[0065]

[0066] Wherein, R mixer is the stirring rotating speed at the current time after dynamic adjustment (unit: RPM), is the absolute value of the temperature change rate at the current time (unit: ℃ / s), which is used to cope with the temperature impact caused by adding components, μ current is the viscosity (unit: cP) estimated by the system at the last time or the last time used according to the power and rotating speed, μ ref is the expected reference viscosity (unit: cP) of the formula, and α and β are both weight coefficients, which are determined by machine learning or a large amount of process data optimization;

[0067] It should be noted that the independent variables of the adaptive stirring model include:

[0068] The temperature change rate (calculated in real time from temperature sensor data), μ current The viscosity estimated at the last time or the last sampling time (calculated from the motor power P motor and the rotational speed estimated at the last time or the last sampling time), μ ref The preset reference viscosity (user input or formula preset); and the dependent variable of the adaptive stirring model is R mixer , which is the target stirring speed of the system output;

[0069] S4: uniformity verification and temperature maintenance;

[0070] The main role is to maintain the target temperature T target and constant speed stirring for a period of time t hold after all ingredients are added, and then detect the uniformity of the mixed solution through multi-dimensional sensing units such as online pH meter, conductivity meter or near infrared (NIR) sensor. When the indicators are stable and the standard deviation is below the threshold, the system determines that the mixing is complete. If it is still not up to standard after a long time, the stirring parameters are adjusted and the mixing time is extended.

[0071] S5: output and cleaning;

[0072] The main role is to control the discharge valve to deliver the liquid medicine to the next process after the mixing is completed, and then automatically start the CIP (clean in place) program to clean the liquid preparation tank and pipeline according to the preset cleaning temperature, flow and time, and prepare for the next production.

[0073] The steps for establishing the above mathematical model are as follows:

[0074] 1. Mechanism analysis: First, based on the principles of fluid mechanics and heat transfer, it is determined that there is a theoretically positive correlation between the key factors affecting mixing efficiency (temperature change, viscosity) and stirring speed;

[0075] 2. Data collection: On the experimental liquid preparation tank, a large number of experiments under different conditions (different liquid volume, different viscosity materials, different addition rate) are carried out, and |dT / dt|, μ current , and the "optimal speed" manually set by experienced operators to maintain uniform mixing and temperature stability are recorded;

[0076] 3. Parameter identification: The large amount of data collected is fitted using multivariate linear regression or machine learning algorithms (such as gradient descent method), so as to determine the weight coefficients α and β in the model and k, C in the basic model;

[0077] 4. Model verification and optimization: The established model is applied to new experiments, and the consistency of the model output speed and the actual optimal speed is compared. According to the error, the model parameters are further adjusted until the prediction accuracy meets the engineering application requirements.

[0078] It should be noted that the point of the present application is to integrate incremental PID control, multi-parameter based adaptive mixing model and online quality monitoring into one, to build a closed-loop intelligent control system, which is not a simple superposition of multiple functions, and has non-obviousness; In addition, the real-time viscosity estimation, temperature change rate and dynamic coupling control of stirring intensity are specifically applied to the preparation of veterinary oral liquid, and there is no same record in domestic and foreign public literature and patents.

[0079] Example 2;

[0080] An intelligent temperature control mixing method for vitamin compound oral liquid production, the production task is to prepare 1000L vitamin A, D, E compound oral liquid, wherein vitamin E is a heat-sensitive component, and the process requires that the mixing temperature be strictly controlled at 40℃±0.5℃; The specific steps of the method are as follows:

[0081] S1: Parameter pre-setting and system initialization:

[0082] The operator inputs the formula parameters through the human-machine interface (HMI):

[0083] V total = 1000L,

[0084] T target = 40℃,

[0085] ΔT = 0.5℃;

[0086] Addition sequence: first inject 800L purified water, then add auxiliary materials (stabilizers, flavorings) in turn, and finally slowly add vitamin E oil concentrate (200L);

[0087] μ ref = 25cP (expected final viscosity), system initialization, complete self-check.

[0088] S2: Medium pre-warming and initial mixing:

[0089] The system controls the feed valve to inject 800L purified water;

[0090] The high-precision temperature control module is started, and the water temperature is heated from room temperature (25℃) to the interval of 39.5℃-40.5℃;

[0091] The system calls the mathematical model to calculate the basic speed: R base =k*ln(1000)+C;

[0092] According to the empirical constant of this model tank (k = 15, C = 50), R base ≈ 15 * 6.9 + 50 = 153.5 RPM; the system sets the stirring speed to 155 RPM for initial mixing.

[0093] S3: Ingredient addition and dynamic temperature control mixing:

[0094] Addition of excipients: the material management module opens the excipient addition valve in sequence. The process is stable in temperature control, and the system only needs to be fine-tuned;

[0095] Addition of vitamin E (core step): when the addition of vitamin E concentrate at 25°C begins, the temperature sensor in the tank detects a sharp drop in temperature (T current from 40.1°C to 39.2°C in 30 seconds);

[0096] Temperature control response: the incremental PID model in the central control module immediately calculates that the heating power needs to be increased significantly (ΔP(n)); the high-precision temperature control module's electric heating tube quickly increases power under PID control, compensates for heat loss, and pulls the temperature back to 40.0°C within 90 seconds, and then enters the fine stabilization phase;

[0097] Stirring response: at the same time, the adaptive stirring model calculates a new stirring speed R current = 155 + 10 * |dT / dt| + 5 * (22 / 25) based on the monitored temperature change rate |dT / dt| and the estimated viscosity μ mixer . When the temperature change is the fastest, |dT / dt| reaches 0.03°C / s, and at this time the stirring speed automatically increases to about 155 + 10 * 0.03 + 5 * 0.88 = 155 + 0.3 + 4.4 = 159.7 RPM. The increase in stirring speed enhances convection and shear force, accelerates the mixing of low-temperature vitamin E and hot water, eliminates local low-temperature areas, and makes the temperature recover more quickly and evenly;

[0098] S4: Homogeneity verification and holding:

[0099] After all the ingredients are added, the system maintains stirring at 40°C and 158 RPM for 15 minutes;

[0100] The online near-infrared (NIR) sensor continuously scans and shows that the standard deviation (SD) of the characteristic absorption peak intensity of vitamin E rapidly decreases from the initial 15% within 10 minutes and stabilizes below 2% (preset threshold). The system determines that the mixing is uniform and qualified;

[0101] S5: Output and cleaning:

[0102] The qualified liquid medicine is delivered to the filling line by the discharge pump;

[0103] The system automatically starts the CIP program, and circulates cleaning with 85°C hot water for 20 minutes, standby.

[0104] The parameters in the specific implementation process of this embodiment are as shown in the table Figure 2 The implementation effect of this embodiment is as shown in the table Figure 3 The other parts are the same as in Embodiment 1.

[0105] Embodiment 3;

[0106] An intelligent temperature control mixing system, as shown in the figure, includes the following functional modules: Figure 4

[0107] The central control module, as the brain of the whole system, is responsible for running the control algorithm, processing all data, coordinating the work of each module, and providing a human-computer interaction interface; contains a mathematical model: integrates all the above mathematical models (PID control, stirring model), and performs real-time calculation and decision-making;

[0108] The multi-parameter monitoring module contains temperature sensors, liquid level sensors, viscosity estimation units, pH / conductivity / NIR sensors, etc., and is mainly responsible for real-time acquisition of physical and chemical parameters in the liquid preparation tank, and transmits the data to the central control module;

[0109] The high-precision temperature control module contains heating units (such as electric heating pipes), cooling units (such as coil pipes passing cooling medium), and regulating valves, which receive the instruction ΔP(n) from the central control module, accurately output heat or cold, and realize fast and smooth adjustment of the temperature in the tank;

[0110] The intelligent stirring drive module contains a frequency converter and a stirring motor, which receives the speed instruction R mixer , stepless adjustment of the speed and torque of the stirring paddle to adapt to the needs of different mixing stages;

[0111] The material management module controls the feeding valve and the discharging valve, accurately controls the addition of various materials (solvents, raw materials, excipients) and the output of the final product according to the preset order and time length;

[0112] The data management and communication module records all the data (temperature, speed, power, time, etc.) input or output by the central control module during the whole production process, forms an electronic batch record, and can interact with the MES (manufacturing execution system) of the factory to realize information management.

[0113] ​It should be noted that the central control module is the core of the whole system, and is bidirectionally connected with all other modules. It receives real-time data from the multi-parameter monitoring module, and after operation by the built-in model, sends control instructions to the high-precision temperature control module and the intelligent stirring driving module, and simultaneously instructs the material management module to complete the adding and outputting operations. In this process, the data management and communication module records the data flow and control flow throughout the process.

[0114] In the specific working process of the system, the operator selects or inputs the formula on the HMI interface (human-machine interaction interface) of the central control module, starts production, the material management module opens the solvent feeding valve, injects a certain amount of solvent, the multi-parameter monitoring module monitors the liquid level and temperature in real time, the central control module starts the high-precision temperature control module to heat the solvent to T target nearby, and then starts the intelligent stirring driving module to the basic rotating speed R base . When reaching the preset time point, the central control module instructs the material management module to open the corresponding raw material valve to add ingredients. During the adding process, the multi-parameter monitoring module detects that the temperature T current fluctuates due to the addition of new ingredients, the central control module immediately calculates the required ΔP(n) by using the PID model, and sends it to the high-precision temperature control module for power adjustment; at the same time, according to the adaptive stirring model, a new R mixer is calculated and sent to the intelligent stirring driving module.

[0115] The above process is repeated until all ingredients are added, the system enters the heat preservation and mixing stage, and the uniformity is verified by the multi-dimensional sensor. After the mixing reaches the standard, the central control module instructs the material management module to open the discharge valve to output the liquid medicine, and finally, the system automatically executes the CIP program, and the data management and communication module generates and stores the complete report of this production.

[0116] Example 4;

[0117] An intelligent temperature control mixing system, the system comprising the following modules:

[0118] Central control module: an industrial-grade PLC (such as Siemens S7-1500 series) is used, and a program in which the incremental PID algorithm and the adaptive stirring model are run is built in;

[0119] Multi-parameter monitoring module:

[0120] Temperature: Pt100 platinum resistance thermometer (accuracy ±0.1℃) is used, which is inserted into different positions in the tank;

[0121] Liquid level: radar liquid level meter is used;

[0122] Viscosity estimation unit: the PLC reads the real-time power of the motor in the intelligent stirring driving module and the rotating speed at the last time or the last time, and calculates the viscosity according to the model μcurrent ∝P motor / (R mixer(t-1) ) 3 real-time estimation is performed;

[0123] Uniformity verification: An online NIR spectrometer (e.g. Merck Mira DS) is used with the probe inserted into the tank to monitor the main component concentration in real time;

[0124] High-precision temperature control module:

[0125] Heating: A stainless steel electric heating tube with a rated power of 36 kW is used, and the PID power control is performed by a solid-state relay (SSR) through PLC;

[0126] Cooling: The tank body jacket is circulated with cooling water, and the flow is controlled by an electric regulating valve, which also receives the PID control signal from the PLC;

[0127] Intelligent stirring drive module: A frequency converter (e.g. ABB ACS880) - three-phase asynchronous motor system is used. The frequency converter receives the 4-20 mA analog signal sent by the PLC, and the motor speed is accurately adjusted in the range of 0-200 RPM;

[0128] Material management module: All feeding and discharging valves are pneumatic diaphragm valves, which are driven by PLC-controlled electromagnetic valves to open and close;

[0129] Data management and communication module: The PLC is connected to an industrial touch screen (HMI) for local operation and display, and is connected to the factory MES system through an Ethernet port to upload all process data (temperature, speed, power, etc. recorded every second).

[0130] The specific working process of this embodiment is: the operator clicks on the "vitamin oral liquid" formula on the HMI and starts; the system automatically performs all the steps in Embodiment 1 or Embodiment 2. The PLC continuously receives data from the temperature sensor, performs PID calculation several times per second, and outputs the corresponding control signal to the heating tube / cooling water valve; at the same time, it dynamically calculates the optimal R current based on the real-time calculation of |dT / dt| and the estimated μ mixe and sends it to the frequency converter; during the entire process, all sensor readings, control instructions, valve opening and closing states, and alarm information are recorded in the PLC's memory card and MES database, forming an unalterable electronic batch record.

[0131] The implementation effect of this embodiment is shown in Figure 5 , which is the same as Embodiment 3.

[0132] The above technical solution only reflects the preferred technical solution of the present application, and some changes made by the skilled in the art to some parts thereof also reflect the principle of the present application and are within the protection scope of the present application.

Claims

1. An intelligent temperature control mixing method for a veterinary oral liquid preparation tank, characterized in that, The method comprises the following steps: S1: parameter presetting and system initialization: input target production parameters into the system; S2: medium pre-warming and initial mixing: pre-warm the solvent and start stirring at a basic rotation speed; S3: ingredient adding and dynamic temperature control mixing: add ingredients in sequence, and dynamically adjust the temperature control power and stirring speed in real time to maintain the target temperature; S4: uniformity verification and temperature maintenance: verify the mixing uniformity through a sensor; S5: output and cleaning: output the liquid medicine and perform automatic cleaning.

2. The method of claim 1, wherein, The mathematical model expression for calculating the basic rotation speed in S2 is: R base = k * ln(V total ) + C where R base is the base rotation speed, V total is the target total liquid volume, and k and C are empirical constants associated with the reagent tank.

3. The method of claim 1, wherein, The mathematical model expression for calculating the adjustment amount of the temperature control power in S3 is: ΔP(n) = K p *[e(n) - e(n-1)] + K i *e(n) + K d *[e(n) - 2e(n-1) + e(n-2)]] Wherein, ΔP(n) is the power adjustment amount of the heating / cooling unit at the n-th sampling (unit: W), e(n), e(n-1) and e(n-2) are the temperature deviations at the n-th, n-1-th and n-2-th sampling respectively, K p is a proportional coefficient, K i is an integral coefficient, K d is a differential coefficient, and the above coefficients can be adaptively adjusted according to the viscosity μ and the liquid amount.

4. The method of claim 1, wherein, The stirring speed in S3 is calculated through an adaptive model, and the mathematical model expression of the adaptive model is: In the formula, R mixer is the stirring speed at the current time after dynamic adjustment, is the absolute value of the temperature change rate at the current time, μ current is the viscosity at the previous time estimated by the system according to the power and the rotating speed, μ ref is the expected reference viscosity of the formula, and α and β are weight coefficients.

5. An intelligent temperature control hybrid system characterized by, The system can implement the method of any one of claims 1-4 on a veterinary oral liquid preparation tank, and the system comprises the following modules: a central control module; a multi-parameter monitoring module connected with the central control module, used for collecting parameters in the tank in real time; a high-precision temperature control module connected with the central control module, used for adjusting the temperature in the tank; an intelligent stirring driving module connected with the central control module, used for driving and adjusting the rotation speed of the stirrer in the tank; a material management module connected with the central control module, used for controlling the addition and output of materials in the tank; a data management and communication module connected with the central control module, used for recording the data output by the central control module and communicating with external systems.

6. The system of claim 5, wherein, The multi-parameter monitoring module comprises at least one of a temperature sensor, a liquid level sensor, a viscosity estimation unit, and a PH value / conductivity / NIR sensor.

7. The system of claim 5, wherein, The high-precision temperature control module comprises an electric heating unit, a cooling coil, and a regulating valve.

8. The system of claim 5, wherein, The intelligent stirring driving module comprises a frequency converter and a servo motor.

9. The system of claim 5, wherein, The central control module is integrated with mathematical models for calculating the basic rotation speed, the adjustment amount of the temperature control power, and the adaptive stirring speed.

10. The system of claim 5, wherein, The system further comprises a human-computer interaction interface connected with the central control module.

Images