Automatic control system and control method for sol tank
By introducing a cross-step optimization algorithm module into the sol tank automation control system, the shortcomings of the existing system in the coordinated operation, energy consumption management and intelligent analysis between process steps are solved, and the global linkage and optimization between process steps are achieved, which significantly improves production efficiency and product quality.
Patent Information
- Application Number
- CN202411741951.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-29
- Publication Date
- 2025-02-28
AI Technical Summary
The existing sol tank automation control system has shortcomings in the collaborative operation between process steps, flexibility in step switching, energy consumption management and intelligent analysis, resulting in low production efficiency, unstable product quality and high energy consumption.
The cross-step optimization algorithm module is used to dynamically adjust the parameters of each process step to achieve global linkage and optimization between process steps. This module includes an energy consumption optimization submodule, a step collaboration submodule and a data analysis submodule. It monitors and adjusts the power of heating, cooling, stirring and vacuum in real time, optimizes the step switching conditions and sequence, and optimizes process parameters through data analysis.
It achieves efficient coordination between process steps, shortens production cycles, reduces energy consumption, improves product quality and system intelligence level, and significantly improves production efficiency and product consistency.
Smart Images
Figure CN119536178A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the technical field of industrial automation control, in particular to an automatic control system for a sol tank and a control method thereof, which are suitable for efficient control of temperature control, stirring and vacuuming processes in a sol preparation process. Background Art
[0002] Sol tank is an important core equipment in industrial production, and is widely used in the preparation process of medical glue, industrial coatings, food additives and other products. The main functions of the sol tank include heating, stirring and mixing the glue, and vacuuming to ensure the uniformity and stable quality of the glue. However, in practical applications, the automatic control system of the sol tank in the prior art still has the following deficiencies, which makes it difficult to further optimize production efficiency, product quality and energy consumption: 1. The process steps are independent and lack global optimization: Current automation systems for sol tanks are usually optimized for a single process step (such as heating, stirring or vacuuming), making it difficult to achieve coordinated operation between process steps. For example, the vacuum rate may need to be dynamically adjusted during stirring to reduce bubbles, but existing technologies usually control the two separately, resulting in poor linkage and difficulty in optimizing production efficiency on a global scale.
[0003] 2. The switching of work steps is not flexible enough, which affects efficiency: The switching of process steps (such as from heating to stirring) mostly relies on fixed time settings or human judgment, and fails to make dynamic adjustments based on real-time parameters (such as temperature, adhesive viscosity, etc.). It is easy to switch too early or too late, resulting in a waste of process time and affecting production efficiency.
[0004] 3. High energy consumption and lack of dynamic control capabilities: The traditional sol tank automation system lacks a global optimization strategy for energy consumption, making it difficult to achieve a reasonable allocation of heating, cooling and stirring power. For example, during the temperature control process, the balance between heating power and cooling power cannot be dynamically adjusted, resulting in energy waste. Especially in large-scale continuous production, the energy consumption problem is particularly prominent.
[0005] 4. Lack of intelligent analysis and adaptive adjustment: Existing sol tank systems usually rely on fixed parameters for operation, and it is difficult to adjust process parameters according to different formulations or batch requirements. Due to the lack of historical data accumulation and analysis capabilities, the system cannot optimize parameter settings through trend prediction and regression modeling, and process adjustment still mainly relies on manual experience.
[0006] Although some new sol tank control technologies (such as PLC systems) have achieved automated operation to a certain extent, these technologies still remain at the optimization of a single process step and fail to solve the linkage problem between multiple process steps. At the same time, the existing technology lacks dynamic optimization algorithms across process steps, and fails to use real-time and historical data to achieve global energy consumption optimization and adaptive adjustment.
[0007] Therefore, there is an urgent need for a sol tank automation control system that can achieve linkage regulation and global energy consumption optimization between process steps through cross-step optimization algorithms, and at the same time use data analysis to improve parameter adjustment capabilities, so as to solve the above-mentioned problems in the existing technology and meet the needs of modern industrial production for high efficiency, high quality and low energy consumption. Summary of the invention
[0008] The purpose of the present invention is to provide an automatic control system for a sol tank, which realizes global linkage and parameter optimization of process steps by introducing a cross-step optimization algorithm, overcomes the problems of low efficiency, high energy consumption and quality fluctuation in the prior art, and ensures the high efficiency and consistency of glue solution preparation.
[0009] The technical solution of the automatic control system of the sol tank of the present invention is as follows: the system comprises: A control unit is used to coordinate the execution of each process step and realize fully automated control based on sensor signals and preset process parameters. The control unit includes: Programmable logic controller (PLC), which executes control algorithms and outputs instructions; Human-machine interface (HMI) for operators to monitor and set process parameters; Data storage module, used to record key parameters in the process; Monitoring module, including sensors and alarm systems, is used to monitor temperature, pressure, liquid level and other parameters in real time and ensure the safety of system operation; The execution unit is used to complete the main process operations of the sol process, and the execution unit includes: Temperature control module, which can achieve precise control of glue temperature through heating and cooling; Stirring module, supporting multi-stage stirring and speed adjustment; Vacuum module, used to remove bubbles in the glue; The cross-step optimization algorithm module is used to achieve global optimization by dynamically adjusting the parameters of each process step, including: Energy consumption optimization submodule dynamically allocates power for heating, cooling, stirring and vacuuming; The work step coordination submodule optimizes the switching conditions and sequence between work steps based on real-time data; The data analysis submodule analyzes historical and real-time data to optimize process parameters.
[0010] Preferably, the energy consumption optimization submodule realizes energy consumption minimization based on the following formula: ; in: , and The real-time power for heating, cooling and stirring respectively; Total energy consumption, which means the cumulative value of all energy consumption of the sol tank during the entire process, in joules J or kilowatt-hours KWH; The process start time, such as the heating start time, in seconds; It is the process end time, such as the vacuum completion time, in seconds.
[0011] Preferably, the stirring and vacuuming coordinated optimization submodule adjusts the stirring speed and the vacuuming speed in real time by the following formula: ; in is the remaining bubble volume, and the goal is to reduce this value; is the initial bubble volume; is the vacuum rate, which indicates the amount of gas extracted per unit time; is the stirring speed, which affects the bubble diffusion and dissipation rate.
[0012] Preferably, the multi-node dynamic adjustment submodule dynamically optimizes the work step switching time based on the following formula: ; in It is the work step switching time after dynamic optimization; The initial switching time is calculated based on process experience; is a process license function based on the volume of the glue solution ,temperature and viscosity .
[0013] The operating method for automatic control of a sol tank of the present invention comprises the following steps: 1. Initialize process parameters: Set target temperature , Target vacuum , Target stirring speed and target energy cap ; The system records the initial glue volume and the initial bubble volume .
[0014] 2. Dynamic temperature control process: Start the heating module and increase the heating power Adjust to: = ; in, = - ; When the temperature approaches When the cooling module is started, the cooling power Adjust to: = .
[0015] 3. Co-optimization of stirring and vacuuming: Adjust the stirring speed according to real-time monitoring data and vacuum rate ; The stirring and vacuuming operations are optimized in conjunction, and the remaining bubble volume is dynamically updated using the following formula: ; when Stop the vacuum operation.
[0016] 4. Cross-step optimization: Dynamically adjust the switching time of each process step , based on the following formula: ; in, is the current glue volume, is the real-time temperature, is the viscosity of the glue.
[0017] 5. Energy consumption monitoring and adjustment: Real-time calculation of current total energy consumption , through the following formula: ; like , adjust the stirring speed and heating / cooling power, giving priority to reducing power consumption in non-critical steps.
[0018] 6. Data recording and feedback: Record and analyze key process parameters (such as temperature, vacuum degree, stirring speed, energy consumption) in real time; If an abnormality occurs such as If the set range is exceeded, the system will automatically trigger an alarm and suspend the relevant process.
[0019] The present invention proposes an automatic control system for a sol tank, which achieves the following significant technical effects by introducing a cross-step optimization algorithm module and combining dynamic adjustment and global optimization strategies: First, in terms of production efficiency, the present invention dynamically calculates the process switching time by real-time monitoring of process parameters (such as temperature, vacuum degree, glue viscosity, etc.) , avoiding the delay or early start problems that may be caused by traditional fixed time switching. Efficient coordination between process steps is achieved, reducing unnecessary waiting time in the production line, shortening the overall production cycle by 10%-20%, and significantly increasing the production volume per unit time.
[0020] Secondly, in terms of energy consumption, the present invention introduces an energy consumption optimization submodule to calculate the total energy consumption in real time. , and dynamically adjust the power distribution of heating, cooling, stirring and vacuuming, giving priority to the power requirements of key steps. Energy consumption optimization is based on the real-time status of the entire process flow, rather than single-step optimization, avoiding energy waste in each process stage. The energy consumption per unit batch can be reduced by 15%-30%, especially in large-scale production, the energy saving effect is more obvious.
[0021] In terms of product quality, the present invention can dynamically adjust the stirring speed through the coordinated optimization of stirring and vacuuming. and vacuum rate , minimize the amount of bubbles remaining in the glue The linkage operation ensures the uniformity and quality consistency of the glue liquid, reduces the product failure rate by 5%-10%, and significantly reduces subsequent processing problems caused by fluctuations in glue liquid quality.
[0022] The present invention also significantly improves the intelligence level of the system. The data analysis submodule can record the key parameters in the process in real time, and perform regression analysis and trend prediction in combination with historical data. The system can automatically adjust the process parameters to meet different production needs without frequent manual intervention, support fast switching of multiple varieties of formulas, reduce debugging time by 30%-50%, and improve the flexibility of the production line.
[0023] In terms of system safety, the present invention uses sensors to monitor parameters such as temperature, vacuum and liquid level in real time. When an abnormal parameter (such as over-temperature or over-pressure) is detected, the alarm module automatically issues an alarm and terminates related operations. The dynamic adjustment algorithm actively reallocates power or extends the working step time under abnormal conditions, reducing the risk of equipment damage or product scrapping, reducing the failure rate of equipment operation by more than 20%, and significantly reducing maintenance costs.
[0024] In addition, the utilization value of process data is also significantly improved. The present invention records the process parameters and production status of each batch, and forms a visual data report to facilitate subsequent process optimization and management decision-making. The optimization process driven by historical data enables continuous improvement of the production process, and improves process stability and decision-making efficiency through data-driven closed-loop optimization.
[0025] The automatic control system of the sol tank of the present invention not only improves production efficiency and product quality, but also significantly reduces production costs and energy consumption by dynamically optimizing process steps and managing global energy consumption. At the same time, the intelligence and safety of the system make it suitable for large-scale industrial production and has a wide range of market application value. BRIEF DESCRIPTION OF THE DRAWINGS
[0026] Figure 1 It is a structural block diagram of the present invention.
[0027] Figure 2 It is a step diagram of the operating method of the present invention. DETAILED DESCRIPTION
[0028] Embodiment 1: The technical solution of the automatic control system of the sol tank in this embodiment is as follows: the system comprises: A control unit is used to coordinate the execution of each process step and realize fully automated control based on sensor signals and preset process parameters. The control unit includes: Programmable logic controller (PLC), which executes control algorithms and outputs instructions; Human-machine interface (HMI) for operators to monitor and set process parameters; Data storage module, used to record key parameters in the process; Monitoring module, including sensors and alarm systems, is used to monitor temperature, pressure, liquid level and other parameters in real time and ensure the safety of system operation; The execution unit is used to complete the main process operations of the sol process, and the execution unit includes: Temperature control module, which can achieve precise control of glue temperature through heating and cooling; Stirring module, supporting multi-stage stirring and speed adjustment; Vacuum module, used to remove bubbles in the glue; The cross-step optimization algorithm module is used to achieve global optimization by dynamically adjusting the parameters of each process step, including: Energy consumption optimization submodule dynamically allocates power for heating, cooling, stirring and vacuuming; The work step coordination submodule optimizes the switching conditions and sequence between work steps based on real-time data;
[0029] The data analysis submodule analyzes historical and real-time data to optimize process parameters.
[0030] Embodiment 2: The difference between this embodiment and embodiment 1 is that this embodiment further includes: The energy consumption optimization submodule minimizes energy consumption based on the following formula: ; in: , and The real-time power for heating, cooling and stirring respectively; Total energy consumption, which means the cumulative value of all energy consumption of the sol tank during the entire process, in joules J or kilowatt-hours KWH; The process start time, such as the heating start time, in seconds; It is the process end time, such as the vacuum completion time, in seconds.
[0031] Preferably, the stirring and vacuuming coordinated optimization submodule adjusts the stirring speed and the vacuuming speed in real time by the following formula: ; in is the remaining bubble volume, and the goal is to reduce this value; is the initial bubble volume; is the vacuum rate, which indicates the amount of gas extracted per unit time; is the stirring speed, which affects the bubble diffusion and dissipation rate.
[0032] Preferably, the multi-node dynamic adjustment submodule dynamically optimizes the work step switching time based on the following formula: ; in It is the work step switching time after dynamic optimization; The initial switching time is calculated based on process experience; is a process license function based on the volume of the glue solution ,temperature and viscosity .
[0033] Embodiment 3: This embodiment is an operation method for automatic control of a sol tank, comprising the following steps: 1. Initialize process parameters: Set target temperature , Target vacuum , Target stirring speed and target energy cap ; The system records the initial glue volume and the initial bubble volume ; 2. Dynamic temperature control process: Start the heating module and increase the heating power Adjust to: = ; in, = - ; When the temperature approaches When the cooling module is started, the cooling power Adjust to: = ; 3. Co-optimization of stirring and vacuuming: Adjust the stirring speed according to real-time monitoring data and vacuum rate ; The stirring and vacuuming operations are optimized in conjunction, and the remaining bubble volume is dynamically updated using the following formula: ; when When the vacuum pumping operation stops; 4. Cross-step optimization: Dynamically adjust the switching time of each process step , based on the following formula: ; in, is the current glue volume, is the real-time temperature, is the viscosity of the glue.
[0034] 5. Energy consumption monitoring and adjustment: Real-time calculation of current total energy consumption , through the following formula: ; like , adjust the stirring speed and heating / cooling power, giving priority to reducing power consumption in non-critical steps.
[0035] 6. Data recording and feedback: Record and analyze key process parameters (such as temperature, vacuum degree, stirring speed, energy consumption) in real time; If an abnormality occurs such as If the set range is exceeded, the system will automatically trigger an alarm and suspend the relevant process.
[0036] The details are as follows: 1. Parameter initialization: The operator inputs the target process parameters through the human-machine interface (HMI), and the system automatically records the initial state: 1.1 Set the target temperature: = 95°C.
[0037] 1.2. Set the target vacuum degree: = 0.08MPa.
[0038] 1.3. Set the target stirring speed: = 300 rpm (mixing phase).
[0039] 1.4. Record the initial glue volume: = 10 L.
[0040] 1.5. Energy consumption limit: Set the total energy consumption threshold to = 5 kWh.
[0041] 2. Dynamic temperature control process: The system starts the temperature control module and dynamically adjusts the heating and cooling power through the PID control algorithm: 2.1. Heating stage: Real-time temperature Initially 30°C; Heating power The initial setting is 2kW. Increase and gradually decrease; Temperature control formula: ; in, = 2000 J, = 0.85.
[0042] when When the temperature reaches 95°C, stop heating.
[0043] 2.2. Cooling control: If the temperature rises to 98°C due to friction stir, start the cooling module; Cooling power = 1.5 kW, control Return to 95°C.
[0044] 3. Optimization of mixing and vacuuming linkage: The system dynamically adjusts the stirring speed through a linkage algorithm and vacuum rate :
[0045] 3.1. Mixing process: During the mixing phase, the stirring speed is = 200 rpm increased to 300 rpm, duration 5 min; During the exhaust phase, the stirring speed was reduced to 150 rpm and lasted for 10 min.
[0046] 3.2. Vacuuming process: The vacuum rate is initially set to , gradually increasing to ;
[0047] Linkage optimization formula: ; The goal is to reduce the amount of bubbles remaining Reduced to 0.1 L.
[0048] 4. Work step switching optimization: Dynamically adjust the work step switching time through the work step coordination submodule: 4.1. The initial estimated step switching time is = 15min; 4.2. Based on real-time data = 95°C, = 0.2L and viscosity = 300cP, recalculate the switching time: ; in: 0.1 0.05 .02 ; The result is = 14min.
[0049] 4.3. Switch to the exhaust phase.
[0050] 5. Energy consumption monitoring and adjustment: The system calculates total energy consumption in real time : ; The current energy consumption is 4.8kWh, close to the threshold ; The system reduces the stirring power To avoid over-limit.
[0051] 6. Data recording and feedback: 6.1. Systematically record key parameters of production batches, including: Temperature change curve; Bubble residual volume changes; Total energy consumption ; Step switching time .
[0052] 6.2. Automatically generate data reports and store historical data in the database to provide reference for the next batch of optimization.
[0053] Through the above-mentioned operation method, the present invention achieves: 1. Efficiency improvement: production time is reduced by 10%-15%, and batch completion time is 20 minutes; 2. Energy consumption optimization: total energy consumption is reduced by 20%, and each batch consumes 4.8 kWh; 3. Product quality improvement: residual bubbles are reduced to 0.1 L, and quality fluctuation is reduced by 5%.
Claims
1. A sol tank automatic control system, characterized in that: The system includes: A control unit is used to coordinate the execution of each process step and realize fully automated control based on sensor signals and preset process parameters. The control unit includes: Programmable logic controller (PLC), which executes control algorithms and outputs instructions; Human-machine interface (HMI) for operators to monitor and set process parameters; Monitoring module, including sensors and alarm systems, is used to monitor temperature, pressure, liquid level and other parameters in real time and ensure the safety of system operation; The execution unit is used to complete the main process operations of the sol process, and the execution unit includes: Temperature control module, which can achieve precise control of glue temperature through heating and cooling; Stirring module, supporting multi-stage stirring and speed adjustment; Vacuum module, used to remove bubbles in the glue; The cross-step optimization algorithm module is used to achieve global optimization by dynamically adjusting the parameters of each process step, including: Energy consumption optimization submodule dynamically allocates power for heating, cooling, stirring and vacuuming; The work step coordination submodule optimizes the switching conditions and sequence between work steps based on real-time data; The data analysis submodule analyzes historical and real-time data to optimize process parameters.
2. The automatic control system for the sol tank according to claim 1, characterized in that: in, The energy consumption optimization submodule minimizes energy consumption based on the following formula: ； in: , and Real-time power for heating, cooling and stirring respectively; Total energy consumption, which means the cumulative value of all energy consumption of the sol tank during the entire process, in joules J or kilowatt-hours KWH; The process start time, such as the heating start time, in seconds; It is the process end time, such as the vacuum completion time, in seconds.
3. The automatic control system for the sol tank according to claim 1, characterized in that: in, The stirring and vacuuming coordinated optimization submodule adjusts the stirring speed and vacuuming speed in real time through the following formula: ； in is the remaining bubble volume, the goal is to reduce this value; is the initial bubble volume; is the vacuum rate, which indicates the amount of gas extracted per unit time; is the stirring speed, which affects the bubble diffusion and dissipation rate.
4. The automatic control system for the sol tank according to claim 1, characterized in that: in, The multi-node dynamic adjustment submodule dynamically optimizes the work step switching time based on the following formula: ； in It is the work step switching time after dynamic optimization; The initial switching time is calculated based on process experience; is a process license function based on the volume of the glue solution ,temperature and viscosity .
5. A control method for the automatic control system of a sol tank according to any one of claims 1 to 4, characterized in that: The following steps are involved: A. Initialize process parameters: Set target temperature , Target vacuum , Target stirring speed and target energy cap ; The system records the initial glue volume and the initial bubble volume ; B. Dynamic temperature control process: Start the heating module and increase the heating power Adjust to: = ； in, = - ; When the temperature approaches When the cooling module is started, the cooling power Adjust to: = ； C. Co-optimization of stirring and vacuuming: Adjust the stirring speed according to real-time monitoring data and vacuum rate ; The stirring and vacuuming operations are optimized in conjunction, and the remaining bubble volume is dynamically updated using the following formula: ； when When the vacuum pumping operation stops; D. Cross-step optimization: Dynamically adjust the switching time of each process step , based on the following formula: ； in, is the current glue volume, is the real-time temperature, is the viscosity of the glue; E. Energy consumption monitoring and adjustment: Real-time calculation of current total energy consumption , through the following formula: ； like , adjust the stirring speed and heating / cooling power, giving priority to reducing power consumption in non-critical steps; F. Data Recording and Feedback: Record and analyze key process parameters in real time; If an abnormality occurs, the system will automatically trigger an alarm and suspend the relevant process.