System for automatically adjusting feeding speed in meal box production and using method thereof

Abstract

The invention relates to the field of meal box production. The invention discloses a system for automatically adjusting the feeding speed in meal box production and a using method of the system. The using method comprises the steps that S1, initial data of materials are collected; s2, the initial feeding amount of the materials is confirmed; s3, the system is started, the materials are subjected to a heating reaction, and the actual temperature of the reaction furnace is set and controlled; s4, dynamically adjusting the feeding speed; and S5, continuously monitoring and optimizing. The feeding speed can be adjusted in real time according to temperature changes and plastic material characteristics. The matching of material supply and reaction speed is ensured, the unnecessary heating time and equipment idling are reduced, and the energy consumption is reduced. Loss caused by long-time idling or overload operation of equipment is avoided, the service life of the equipment is prolonged, and the maintenance cost is reduced. Different types of plastics have different hot working properties, and the system can be individually set according to the characteristics of specific materials to ensure that each type of plastics can be processed under the optimal condition.

Description

Technical Field

[0001] The present invention relates to the field of lunch box production, and in particular to a system for automatically adjusting a feeding speed in lunch box production and a use method thereof. Background Art

[0002] Different types of plastics have very different thermal processing properties such as melting point, thermal stability, and fluidity. For example, polyethylene (PE) and polycarbonate (PC) have different melting points, with PE having a relatively low melting point and PC having a higher melting point. If the same feed rate is maintained, for plastics with low melting points, fast heating and fast reaction speed in gradient heating, insufficient feed will cause the subsequent reaction to be "out of food", affecting production efficiency and product quality; for plastics with high melting point, temperature gradient comprehensive function and slow reaction speed, material accumulation may occur, affecting the normal operation of the equipment. In the gradient heating process, the temperature continues to rise and the reaction speed is accelerated and strengthened. If the feed rate is fixed, it cannot match the rapid reaction of the plastic at different temperature stages. In the stage where the temperature rises faster, the fixed feed rate will lead to insufficient material supply, so that the reaction cannot be fully carried out, reducing production efficiency; and in the cooling stage, there will be too much feed, causing the material to stay in the equipment for too long, affecting product quality, and even causing equipment failure. Each plastic has its own suitable processing temperature range and reaction conditions. When the feed rate is fixed, for some plastics that can react quickly at lower temperatures, the equipment needs to continue heating to maintain the reaction due to insufficient feed, resulting in ineffective energy consumption; for some plastics that require higher temperatures and longer reactions, a fixed feed rate will cause the material to stay in the equipment for an unreasonable amount of time, and the heating time will be too long, which will also lead to energy waste. If the feed rate cannot match the reaction rate, it will cause excessive energy loss, and the equipment will run idle without enough material for processing. Idling equipment will not only damage the equipment itself, but also consume a lot of energy. This part of energy is not used in the effective production process, resulting in energy waste.

[0003] In the production process of plastic caps, gradient heating technology is sometimes used to process plastics. However, during the gradient processing process, because the temperature increases, the reaction speed is accelerated and strengthened, and the feed rate of the material needs to be accelerated to keep up with the subsequent rapid reaction to prevent energy waste. If each different plastic is kept at the same feed rate for gradient heating, the material feed rate will be consistent and energy will be wasted. Summary of the invention

[0004] In order to solve the deficiencies of the prior art, the present invention discloses a system for automatically adjusting the feeding speed in lunch box production and a method for using the system, which can adjust the feeding speed of materials when the temperature changes according to different material properties and can reduce energy consumption.

[0005] The present invention discloses a system for automatically adjusting the feeding speed in lunch box production and a method for using the system, which comprises: S1: Collect the initial data of the material, monitor and collect the material temperature and material humidity data in the material storage environment in real time through sensors, and collect the material particle size and shape data, the viscosity data after the material and ingredients are mixed, and the material density data; S2: confirm the initial feed amount of the material, and determine the initial feed amount of the material into the reactor according to the initial data of the material; S3: Start the system, heat the material for reaction, and set and control the actual temperature of the reactor; S4: Dynamically adjust the feed rate. As the temperature changes, the actual feed rate is adjusted according to the current actual temperature, initial feed amount, temperature gradient comprehensive function and other factors affecting the feed rate. S5: Continuous monitoring and optimization, real-time monitoring of key parameters such as temperature and feed rate, and timely processing of alarm information when abnormal conditions are found.

[0006] Furthermore, the initial feed amount F of the material is determined based on the initial data of the material. o : ; F base : Base feed amount, a constant value preset based on experience; X o : The value of the oth factor, which includes material temperature, material humidity, material particle size and shape, material viscosity and material density; w o : The weight of the oth factor.

[0007] Furthermore, the actual speed F of the material entering the reactor is actually controlled: ; F0: initial feed rate, the speed at which the material enters the reactor at the beginning of the production process; T c : The actual temperature in the current reactor; T base : Base temperature, the material temperature before heating begins; f(T g ): Comprehensive function of temperature gradient based on all material properties; K p : Comprehensive coefficient, the influence of other factors on feed rate except temperature gradient.

[0008] Furthermore, the temperature gradient comprehensive function based on all material properties is: ; n: the quantity of the material; w i : The weight of material i, which is set according to the type of material; f i (T g ): Comprehensive function of temperature gradient of material i.

[0009] Furthermore, the comprehensive coefficient K of other factors affecting the feed rate besides the temperature gradient is p : ; m: the number of different impact factors; w j : The weight of the j-th impact factor, reflecting the importance of the j-th impact factor; g j : A function of how the jth influencing factor affects the feed rate.

[0010] Furthermore, the reaction furnace includes an upper heating furnace and a lower heating furnace, and the two heating furnaces are temperature-controlled separately, wherein T c : ; w upper : The weight of the upper heating furnace related to temperature, indicating the upper heating furnace's effect on the current temperature T c The impact of w lowerr : The weight of the lower heating furnace related to temperature, indicating the effect of the lower heating furnace on the current temperature T c The impact of T upper : The actual heating temperature of the upper heating furnace; T lowerr : The actual heating temperature of the lower heating furnace; Among them, w upper and w lowerr : ; k upper : Thermal conductivity of the upper heating furnace; k lower : Thermal conductivity of the lower heating furnace; V upper : The volume of the heating area of ​​the upper heating furnace; V lower : The volume of the heating area of ​​the lower heating furnace; Among them, w upper +w lower =1.

[0011] Furthermore, the system for automatically adjusting the feeding speed in the production of lunch boxes includes: A reaction furnace, used for heating and reacting materials; Data acquisition module, which includes various sensors for real-time monitoring and collecting data in the material storage environment; An initial feed amount calculation module is used to determine the initial feed amount of the material entering the reactor according to the collected initial data of the material; A heating control module includes a plurality of temperature sensors, which are installed at various positions inside and outside the reaction furnace. The heating control module is used to set and control the actual temperature of the reaction furnace and control the heating temperature to heat the material. The heating control module transmits the actual temperature and other temperature-related data to the feed speed adjustment module; The feed rate adjustment module is used to dynamically adjust the actual feed rate of the material according to the current actual temperature, initial feed amount, temperature gradient comprehensive function and other non-temperature factors affecting the feed rate; The monitoring and optimization module is used to monitor the temperature and feed rate in the reactor in real time.

[0012] Further, the reaction furnace is connected to a data acquisition module, an initial feed amount calculation module, a heating control module, a feed speed adjustment module and a monitoring and optimization module; The data acquisition module is connected to the initial feed amount calculation module and the monitoring and optimization module; The initial feed amount calculation module is connected to the feed speed adjustment module; The heating control module is connected to the feed rate adjustment module and the monitoring and optimization module; A feed rate adjustment module connected to the monitoring and optimization module; The monitoring and optimization module is connected to the data acquisition module, the initial feed amount calculation module, the heating control module and the feed speed adjustment module.

[0013] Furthermore, the data acquisition module includes a temperature sensor, a humidity sensor, a particle size and shape sensor, a viscometer and a densitometer.

[0014] Furthermore, the system for automatically adjusting the feeding speed in the production of lunch boxes also includes: User interface and remote monitoring module, which is used to provide an intuitive operation interface, facilitate operators to monitor and control the entire production process, and through the Internet connection, allow managers to monitor the operating status of production equipment in real time at any location; The data analysis and reporting module is used to collect and store data during the production process and regularly generate production reports, including output, quality, energy consumption and equipment status.

[0015] Beneficial effects of the present invention: The present application discloses a system for automatically adjusting the feed speed in the production of lunch boxes and a method for using the system, which can adjust the feed speed in real time according to temperature changes and plastic material characteristics. For plastics with low melting points, fast heating and fast reaction speeds, the feed speed can be automatically accelerated to ensure sufficient material supply and avoid insufficient subsequent reaction materials due to insufficient feeding, thereby improving production efficiency. For plastics with high melting points and slow reaction speeds, the feed speed can be automatically slowed down to prevent excessive accumulation of materials in the equipment and affect the normal operation of the equipment. By real-time monitoring of parameters such as temperature, humidity, viscosity, and dynamically adjusting the feed speed based on these data, it is ensured that each plastic can be processed under its most suitable processing conditions. It helps to maintain the stability and consistency of the product and improve the quality of the final product. During the cooling process, the system can automatically reduce the feed speed to prevent excessive accumulation or solidification of materials during cooling, thereby avoiding affecting the final performance of the product.

[0016] The present application discloses a system for automatically adjusting the feed rate in the production of lunch boxes and a method for using the system. Through intelligent control, it ensures that the material supply matches the reaction rate, reduces unnecessary heating time and equipment idling, and reduces energy consumption. It avoids equipment losses caused by long-term idling or overload operation, extends the service life of the equipment, and reduces maintenance costs. Different types of plastics have different thermal processing properties. The system can be personalized according to the characteristics of the specific material to ensure that each plastic can be processed under optimal conditions. The flexibility of production is enhanced and it is suitable for the processing needs of a variety of plastic materials. Whether it is the heating or cooling stage, the system can quickly respond to temperature changes and adjust the feed rate in time to ensure the continuity and stability of the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of a system for automatically adjusting the feed speed in lunch box production in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the specific implementation modes of the present invention will be clearly and completely described below.

[0019] The present invention discloses a system for automatically adjusting the feeding speed in lunch box production and a method for using the system, which comprises: S1: Collect the initial data of the material, monitor and collect the material temperature and material humidity data in the material storage environment in real time through sensors, and collect the material particle size and shape data, the viscosity data after the material and ingredients are mixed, and the material density data; S2: confirm the initial feed amount of the material, and determine the initial feed amount of the material into the reactor according to the initial data of the material; S3: Start the system, heat the material for reaction, and set and control the actual temperature of the reactor; S4: Dynamically adjust the feed rate. As the temperature changes, the actual feed rate is adjusted according to the current actual temperature, initial feed amount, temperature gradient comprehensive function and other factors affecting the feed rate. S5: Continuous monitoring and optimization, real-time monitoring of key parameters such as temperature and feed rate, and timely processing of alarm information when abnormal conditions are found.

[0020] The present application discloses a system for automatically adjusting the feed speed in the production of lunch boxes and a method for using the system, which can adjust the feed speed in real time according to temperature changes and plastic material characteristics. For plastics with low melting points, fast heating and fast reaction speeds, the feed speed can be automatically accelerated to ensure sufficient material supply and avoid insufficient subsequent reaction materials due to insufficient feeding, thereby improving production efficiency. For plastics with high melting points and slow reaction speeds, the feed speed can be automatically slowed down to prevent excessive accumulation of materials in the equipment and affect the normal operation of the equipment. By real-time monitoring of parameters such as temperature, humidity, viscosity, and dynamically adjusting the feed speed based on these data, it is ensured that each plastic can be processed under its most suitable processing conditions. It helps to maintain the stability and consistency of the product and improve the quality of the final product. During the cooling process, the system can automatically reduce the feed speed to prevent excessive accumulation or solidification of materials during cooling, thereby avoiding affecting the final performance of the product.

[0021] The present application discloses a system for automatically adjusting the feed rate in the production of lunch boxes and a method for using the system. Through intelligent control, it ensures that the material supply matches the reaction rate, reduces unnecessary heating time and equipment idling, and reduces energy consumption. It avoids equipment losses caused by long-term idling or overload operation, extends the service life of the equipment, and reduces maintenance costs. Different types of plastics have different thermal processing properties. The system can be personalized according to the characteristics of the specific material to ensure that each plastic can be processed under optimal conditions. The flexibility of production is enhanced and it is suitable for the processing needs of a variety of plastic materials. Whether it is the heating or cooling stage, the system can quickly respond to temperature changes and adjust the feed rate in time to ensure the continuity and stability of the production process.

[0022] As an implementation method, the initial feed amount F of the material is determined based on the initial data of the material. o : ; F base : Base feed amount, a constant value preset based on experience; X o : The value of the oth factor, which includes material temperature, material humidity, material particle size and shape, material viscosity and material density; wo : The weight of the oth factor.

[0023] Where X o Factors in: Material temperature: Temperature will increase material fluidity, thus affecting the feed rate.

[0024] Material humidity: Humidity can change the viscosity of the material and slow down the feed rate.

[0025] Particle size and shape: Particles of different sizes and shapes will affect the flowability and bulk density of the material.

[0026] Viscosity: The viscosity of the material and its ingredients after mixing directly affects the flow properties of the material.

[0027] Density: The density of the material affects the weight of the material per unit volume, which in turn affects the feed rate.

[0028] Weight w o Source and determination method: Experimental data: The fluidity and feed rate of materials under different conditions, such as temperature and humidity, are measured experimentally, and then the weight of each factor is determined based on the experimental results. If it is found that temperature has a particularly large impact on the fluidity of a certain material, a higher weight can be given to the temperature.

[0029] Historical data and experience: Based on historical data from past production runs and operator experience, determine which factors have the greatest impact on feed rate. Certain materials tend to clump in high humidity environments, so humidity will be weighted higher.

[0030] Physical and Chemical Property Analysis: Analyze the physical and chemical properties of the material to assess the specific impact of each factor on the material's behavior. For more viscous materials, the weight of viscosity will be higher; for more dense materials, the weight of density will be higher.

[0031] Machine learning: Using machine learning algorithms, the weights are automatically adjusted based on a large amount of data. Through continuous learning and optimization, the system that automatically adjusts the feeding speed in lunch box production can gradually find the weight combination that best suits the current material characteristics.

[0032] Specific steps to determine weights: Identify key factors: First, identify which factors have a significant impact on feed rate, such as temperature, humidity, particle size and shape, viscosity and density.

[0033] Initial weighting: Based on experience and preliminary experiments, an initial weight is assigned to each factor. If a material is greatly affected by temperature, the temperature weight can be initially set higher.

[0034] Experimental Validation: Test the effectiveness of these weights in a small-scale experiment to see if the actual feed rate matches the expected one.

[0035] Adjust weights: Adjust weights based on experimental results to ensure that the weights accurately reflect the actual impact of each factor on the feed rate.

[0036] Continuous optimization: During the actual production process, continue to collect data and fine-tune the weights based on actual conditions to ensure the stability and efficiency of the system that automatically adjusts the feed rate in lunch box production.

[0037] Example 1: Determine the initial feed amount F0: 1. Determine the reference feed volume F base ; The preset reference feed rate based on experience is: F base =100kg / min.

[0038] 2. Collect initial data of materials; The following initial data were collected: material temperature T=30°C, material humidity H=60%, particle size and shape factor G=0.8, viscosity factor V=0.7, and density factor D=0.9.

[0039] 3. Determine the weight w o ; According to material characteristics and experimental data, the following weights are set: Temperature w1=0.2: The material is sensitive to temperature, and the increase in temperature will significantly affect the fluidity.

[0040] Humidity w2=-0.1: Increased humidity slows down the feed rate, so the weight is negative.

[0041] Particle size and shape w3=0.15: affects material fluidity and stacking characteristics.

[0042] Viscosity w4=-0.1: Increased viscosity slows down the feed rate, so the weight is negative.

[0043] Density w5=0.05: affects the weight of material per unit volume.

[0044] 4. Calculate the initial feed amount F0; Use the summation formula: ; Substitute the specific values ​​into the formula: F0=100+0.2·30+(-0.1)·60+0.15·0.8+(-0.1)·0.7+0.05·0.9≈100.095kg / min; 5. Results The final calculated initial feed rate F0 is about 100.095 kg / min. F0 reflects the optimal feed rate of the material under the current initial conditions, ensuring the stability and efficiency of the production process.

[0045] As an implementation method, the actual speed F of the material entering the reaction furnace is actually controlled: ; F0: initial feed rate, the speed at which the material enters the reactor at the beginning of the production process; T c : The actual temperature in the current reactor; T base : Base temperature, the material temperature before heating begins; f(T g ): Comprehensive function of temperature gradient based on all material properties; K p : Comprehensive coefficient, the influence of other factors on feed rate except temperature gradient.

[0046] The actual speed F of the material entering the reactor is actually controlled: Initial feed rate F0 is the speed at which the material enters the reactor at the beginning of the production process. It is calculated based on the initial data of the material, such as temperature, humidity, particle size and shape, viscosity, density, etc.

[0047] The actual temperature T in the current reactor c The current temperature in the reactor changes with time, including changes due to temperature increase or decrease.

[0048] Measurement method: Real-time monitoring is performed through the temperature sensor installed in the reactor, and the data is transmitted to the central processor.

[0049] Reference temperature T base , the material temperature before heating begins. The initial temperature of the material before entering the reactor can be directly measured by a temperature sensor.

[0050] f(T g ), a comprehensive function of the temperature gradient based on all material properties, reflecting the effect of temperature changes on material behavior.

[0051] Comprehensive coefficient K p , the influence of other factors on feed rate besides temperature gradient.

[0052] Specific: Initial feed rate F0: the feed rate of the material in the initial state before the heating reaction.

[0053] Calculated based on the initial characteristics of the material such as temperature, humidity, particle size and shape, viscosity and density. Used to provide a benchmark feed rate to ensure that the material has a reasonable starting rate when entering the reactor.

[0054] Temperature gradient comprehensive function f(T g ): The fluidity change of the material affected by the temperature change after the material enters the temperature rise reaction. The temperature gradient comprehensive function based on all material characteristics reflects the impact of temperature change on the fluidity of the material. Dynamically adjust the feed rate to adapt to temperature changes to ensure the optimal fluidity of the material at different temperatures.

[0055] Comprehensive coefficient K p :The comprehensive coefficient of the influence of other factors on the feeding speed in addition to the temperature gradient is determined after the material is heated and reacted. Consider factors other than temperature such as humidity, viscosity changes, density, chemical reaction rate, etc. to ensure that the system for automatically adjusting the feeding speed in lunch box production can fully cope with changes in various non-temperature factors. Ensure that the system for automatically adjusting the feeding speed in lunch box production can flexibly cope with complex production environments and dynamically adjust the feeding speed.

[0056] F0 is the initial state of the material before heating reaction, which determines the initial feed rate.

[0057] f(T g ) reflects the change in fluidity of the material due to temperature changes during the heating process, and helps adjust the feed rate to adapt to temperature changes.

[0058] K p The influence of factors other than temperature on the feeding speed is taken into consideration to ensure that the system for automatically adjusting the feeding speed in lunch box production can be flexibly adjusted in complex environments.

[0059] Example 2: There are the following specific values: Initial feed rate F0=100kg / min: calculated based on the initial data of the material.

[0060] Reference temperature T base =30℃: The temperature of the material before entering the reactor.

[0061] The actual temperature T in the current reactor c Changes over time: Time t1:T c =40℃, time t2:T c =60℃, time t3:T c =80℃.

[0062] Temperature gradient comprehensive function f(T g ): Assume that it is a linear function f(T g)=0.01×T g .

[0063] Comprehensive coefficient K p =0.5: Set based on historical data and experience.

[0064] Calculate the actual feed rate F at different time points: Time t1: T c =40℃: F=100+0.5·(40-30)·0.01·40=100+0.5·10·0.4=102 kg / min.

[0065] Time t2: T c =60℃: F=100+0.5·(60-30)·0.01·60=100+0.5·30·0.6=109kg / min.

[0066] Time t3: T c =80℃: F=100+0.5·(80-30)·0.01·80=100+0.5·50·0.8=120kg / min.

[0067] As the temperature in the reactor increases, the actual feed rate F also gradually increases. This ensures that the material is processed evenly under suitable temperature conditions, improves production efficiency and product quality, and can reduce energy loss and improve energy utilization. By dynamically adjusting the feed rate, the system that automatically adjusts the feed rate in lunch box production can adapt to temperature changes and other factors and maintain optimal operating conditions.

[0068] As an implementation, a temperature gradient synthesis function based on all material properties: ; n: the quantity of the material; w i : The weight of material i, which is set according to the type of material; f i (T g ): Comprehensive function of temperature gradient of material i.

[0069] f(T g ) is a function that comprehensively considers all material properties and reflects the comprehensive impact of the behavior changes of different materials under different temperature gradients on the feed rate. g ), the system that automatically adjusts the feeding speed in lunch box production can dynamically adjust the feeding speed according to the current temperature gradient, ensuring that the material is processed under appropriate conditions, improving production efficiency and product quality. As the temperature in the reactor changes, f(Tg ) will be updated in real time, allowing the feed rate to adapt to temperature changes and avoid production problems caused by temperature fluctuations.

[0070] f i (T g ) is used to describe the behavior changes of the i-th material under different temperature gradients. It reflects the specific response of the material to temperature changes, such as physical properties such as viscosity, fluidity and density that change under the influence of temperature.

[0071] Material characteristics i (T g ) Specific analysis: 1. Experimentally determine the physical and chemical properties of each material at different temperatures and record their changing patterns. Some materials become less viscous and more fluid at high temperatures, while others clump or harden at low temperatures.

[0072] 2. Based on the historical data of previous production processes, analyze the behavior of materials under different temperature conditions and determine their comprehensive temperature gradient function.

[0073] 3. The empirical formula fitted based on experimental data can be directly used to describe the behavior changes of materials at different temperatures. i (T g ) shows a positive relationship and a linear relationship f i (T g )=k i ×T g , where k i is the proportionality coefficient. Then, computer simulation technology is used to simulate the behavior of the material at different temperatures to obtain its temperature gradient comprehensive function. When the system of this application is actually used, the specific f is obtained by comparing it with the existing material comparison table of the factory. i (T g ) value.

[0074] Material quantity n: refers to the number of different types of materials involved in mixing or processing. There are many kinds of raw materials such as plastic particles, additives, etc. in the production of lunch boxes.

[0075] Material weight w i :Set according to the type of material and its sensitivity to temperature changes. If a material is greatly affected by temperature, its weight w i The weights can be determined through experimental data, historical records or experience.

[0076] Temperature gradient comprehensive function f i (T g): describes the change in properties of the i-th material at different temperatures. Some materials have lower viscosity and better fluidity at high temperatures, while others will clump or harden at low temperatures. It can be an empirical formula, the result of fitting experimental data, or obtained through a simulation model.

[0077] Embodiment 3: There are three different materials involved in mixing: material 1: plastic particles, material 2: additive A, material 3: additive B.

[0078] Determine the weight w i , according to the characteristics of the material, set the following weights: Material 1 (plastic particles): greatly affected by temperature, weight w1=0.5.

[0079] Material 2 (Additive A): Moderately affected by temperature, weight w2=0.3.

[0080] Material 3 (additive B): less affected by temperature, weight w3=0.2.

[0081] Temperature gradient comprehensive function f i (T g ): According to experimental data or experience, the following temperature gradient comprehensive function is obtained: Material 1 (plastic granules): f1(T g )=0.01×T g ; Material 2 (additive A): f2(T g )=0.005×T g ; Material 3 (additive B): f3(T g )=0.002×T g ; Calculate the comprehensive function f(T g ): Current temperature gradient T g =50℃, calculate the comprehensive function f(T g ): f(T g )=w1·f1(T g )+w2·f2(T g )+w3·f3(T g ); The specific calculation is as follows: Material 1 (plastic granules): w1·f1(T g )=0.5·(0.01×50)=0.5·0.5=0.25; Material 2 (additive A): w2·f2(T g)=0.3·(0.005×50)=0.3·0.25=0.075; Material 3 (additive B): w3·f3(T g )=0.2·(0.002×50)=0.2·0.1=0.02; Sum all items: f(T g )=0.25+0.075+0.02=0.345; The final calculated temperature gradient comprehensive function f(T g ) is 0.345. This value reflects the combined effect of all material properties on the feed rate under the current temperature gradient. The system that automatically adjusts the feed rate in lunch box production can dynamically adjust the feed rate according to the characteristics of different materials and their response to temperature changes, ensuring the stability and efficiency of the production process.

[0082] As an embodiment, the comprehensive coefficient K of the influence of other factors on the feed rate other than the temperature gradient is p : ; m: the number of different impact factors; w j : The weight of the j-th impact factor, reflecting the importance of the j-th impact factor; g j : A function of how the jth influencing factor affects the feed rate.

[0083] Comprehensive coefficient K p It is a comprehensive measure of the impact of other factors on the feed rate after the material is heated and reacted, except for the temperature gradient. p， The system that automatically adjusts the feeding speed in lunch box production can monitor and respond to changes in factors other than temperature in real time, dynamically adjust the feeding speed, and ensure the stability and efficiency of production. p The system that automatically adjusts the feeding speed in lunch box production can be accurately controlled in a complex and changeable production environment to avoid production problems caused by changes in a single factor. p The system that allows automatic adjustment of the feed rate in lunch box production is personalized for different materials, ensuring that each material is processed under optimal conditions, improving product quality and production efficiency.

[0084] Number of different influencing factors m: The number of different non-temperature factors considered. Based on various factors in the production process that affect the feed rate in addition to temperature. For example, humidity, viscosity changes, density, chemical reaction rate, material phase changes, etc.

[0085] The weight w of the jth influencing factor j :Reflects the j The importance of an influencing factor, that is, the degree of influence of this factor on the feed rate. Weight w j Usually it is set through experimental data, historical records or experience. If a certain factor has a greater impact on the feeding speed, its weight is higher; otherwise, it is lower. The weight can be adjusted dynamically according to the actual production situation to ensure that the system that automatically adjusts the feeding speed in lunch box production can flexibly respond to different production conditions.

[0086] How does the jth influencing factor affect the feed rate function g j : A function that describes how the jth influencing factor specifically affects the feed rate. Function g j It can be an empirical formula based on experimental data fitting, the result of a simulation model, or a mathematical expression derived from the analysis of physical and chemical properties. These functions reflect the changing laws of feed rate under specific conditions such as increased humidity and changes in viscosity.

[0087] Example 4: Effect of humidity on viscosity and bulk density:

[0088] Weight w1: 0.3, humidity has a greater impact on viscosity and bulk density. Function g1(H): g1(H) = 0.01 × H, the change ratio of feed rate for each percentage point increase in humidity. Increased humidity will increase viscosity and slow down feed rate.

[0089] Effect of particle size and shape on flow and packing properties: Weight w2, particle size and shape have a certain influence on fluidity and stacking characteristics. Function g2(G): g2(G)=0.02×G, the change ratio of feed rate for each unit change in particle size and shape. The larger the particle or the irregular the shape, the worse the fluidity and the slower the feed rate.

[0090] The influence of material viscosity on flow properties: Weight w3: 0.25, viscosity has a significant effect on flow properties. Function g3(V): g3(V)=-0.01×V, which indicates the proportion of feed rate reduction for every unit increase in viscosity. Negative values ​​indicate that increased viscosity will slow down feed. The greater the viscosity, the harder it is for the material to flow, and the lower the feed rate.

[0091] The influence of material density on the weight of material per unit volume: Weight w4: 0.15, density has a certain influence on the weight of material per unit volume. Function g4(D): g4(D)=0.005×D, the change ratio of feed speed for each unit increase in density. The greater the density, the greater the weight of material per unit volume, and the slower the feed speed.

[0092] Effect of chemical reaction rate on material properties and feed rate: Weight w5: 0.1, chemical reaction rate has a certain influence on material properties and feed rate. Function g5(R): g5(R)=0.003×R, the change ratio of feed rate for each unit increase in reaction rate. The faster reaction rate will change the material properties, which in turn affects the feed rate.

[0093] The specific values ​​are as follows: Effect of humidity on viscosity and bulk density: weight w1=0.3, function g1(H)=0.01×H, current humidity H=60%.

[0094] Effect of particle size and shape on fluidity and stacking properties: weight w2=0.2, function g2(G)=0.02×G, current particle size and shape factor G=0.8.

[0095] The influence of material viscosity on flow properties: weight w3=0.25, function g3(V)=-0.01×V, current viscosity factor V=0.7.

[0096] The influence of material density on the weight of material per unit volume: weight w4=0.15, function g4(D)=0.005×D, current density factor D=0.9.

[0097] The influence of chemical reaction rate on material properties and feed rate: weight w5=0.1, function g5(R)=0.003×R, current reaction rate R=50%.

[0098] Calculate the comprehensive coefficient K p : K p =w1·g1(H)+w2·g2(G)+w3·g3(V)+w4·g4(D)+w5·g5(R); The specific calculation is as follows: Effect of humidity on viscosity and bulk density: w1·g1(H)=0.18; Effect of particle size and shape on flowability and packing properties: w2·g2(G)=0.0032; The influence of material viscosity on flow properties: w3·g3(V)=-0.00175; The influence of material density on the weight of material per unit volume: w4·g4(D)=0.000675; Effect of chemical reaction rate on material properties and feed rate: w5·g5(R)=0.015; Sum all items: K p=0.18+0.0032-0.00175+0.000675+0.015≈0.197125; The final calculated comprehensive coefficient K p It is about 0.197125. This value reflects the comprehensive influence of other factors on the feeding speed besides the temperature gradient. The system that automatically adjusts the feeding speed in the production of lunch boxes can dynamically adjust the feeding speed according to a variety of non-temperature factors to ensure the stability and efficiency of the production process.

[0099] As an embodiment, the reaction furnace includes an upper heating furnace and a lower heating furnace, and the two heating furnaces are temperature-controlled separately, wherein T c : ; w upper : The weight of the upper heating furnace related to temperature, indicating the upper heating furnace's effect on the current temperature T c The impact of w lowerr : The weight of the lower heating furnace related to temperature, indicating the effect of the lower heating furnace on the current temperature T c The impact of T upper : The actual heating temperature of the upper heating furnace; T lowerr : The actual heating temperature of the lower heating furnace; Among them, w upper and w lowerr : ; k upper : Thermal conductivity of the upper heating furnace; k lower : Thermal conductivity of the lower heating furnace; V upper : The volume of the heating area of ​​the upper heating furnace; V lower : The volume of the heating area of ​​the lower heating furnace; Among them, w upper +w lower =1.

[0100] w upper +w lower =1 is to ensure that the upper heating furnace and the lower heating furnace have a comprehensive temperature T c The sum of their contributions is 100%, that is, their weights are relative proportions, which jointly determine the current temperature of the entire reactor. This ensures that the calculated comprehensive temperature T c It is a weighted average of the temperatures of the two heating zones, not a simple addition or any combination.

[0101] The benefits of using two heating furnaces in segmented heating: Each heating furnace can independently control the temperature to ensure that the materials in different areas are processed under the most suitable temperature conditions. For example, some plastic materials require different temperatures at different stages, and segmented heating can better meet these needs. By setting the different temperatures of the upper and lower heating furnaces, an ideal temperature gradient can be formed, so that the material gradually transitions from the low temperature zone to the high temperature zone, avoiding the impact of sudden temperature changes on the material properties. Segmented heating can heat the material to the required temperature in a short time, reducing the overall heating time, thereby improving production efficiency. For plastics with low melting points, fast heating and fast reaction speeds, the upper heating furnace can provide rapid preheating; while for plastics with high melting points and slow reaction speeds, the lower heating furnace can provide continuous and stable heating to ensure that the reaction is fully carried out. Segmented heating can ensure that the material is heated evenly throughout the reaction process, avoiding local overheating or insufficient heating, thereby improving the quality and consistency of the product. By accurately controlling the temperature of each section, product defects such as bubbles and cracks caused by uneven temperature can be effectively prevented.

[0102] However, because the temperature of each section of the segmented heating is different, including the different conduction coefficients of each section of the furnace and the volume of the heating area, this system sets a comprehensive calculation formula to calculate the comprehensive temperature of the two current reactors, and calculates the actual speed F of the material entering the reactor based on the comprehensive temperature.

[0103] Example 5: There are the following specific values:

[0104] Upper heating furnace: actual heating temperature Tupper = 200 °C, thermal conductivity kupper = 0.5 W / m·K, heating area volume Vupper = 0.8 m 3 .

[0105] Lower heating furnace: actual heating temperature T lower =150℃, thermal conductivity k lower =0.3 W / m·K, heating area volume V lower =1.2 m 3 .

[0106] Calculate weights: w upper =0.5 0.80.5 0.8+0.3 1.2=0.40.4+0.36=0.40.76≈0.526; w lower =0.3·1.20.5·0.8+0.3·1.2=0.360.4+0.36=0.360.76≈0.474.

[0107] Calculate the integrated temperature T c : T c=0.526·200+0.474·150=176.3℃.

[0108] The final calculated comprehensive temperature T c It is 176.3°C. This value reflects the actual temperatures of the upper heating furnace and the lower heating furnace and their respective effects on the comprehensive temperature.

[0109] As an implementation method, a system for automatically adjusting the feed speed in lunch box production includes: a reactor for heating and reacting materials, a data acquisition module, the data acquisition module includes various sensors, and is used to monitor and collect data in the material storage environment in real time, an initial feed amount calculation module, which is used to determine the initial feed amount of materials entering the reactor according to the collected initial data of the materials, a heating control module, the heating control module includes a number of temperature sensors, and the temperature sensors are respectively installed at various positions inside and outside the reactor, the heating control module is used to set and control the actual temperature of the reactor and control the heating temperature to heat the materials, the heating control module transmits the actual temperature and other temperature-related data to a feed speed adjustment module, the feed speed adjustment module is used to dynamically adjust the actual feed speed of the material according to the current actual temperature, initial feed amount, temperature gradient comprehensive function and other non-temperature factors on the feed speed, and a monitoring and optimization module is used to monitor the temperature and feed speed in the reactor in real time.

[0110] As an implementation mode, the reaction furnace is connected to a data acquisition module, an initial feed amount calculation module, a heating control module, a feed speed adjustment module and a monitoring and optimization module. The data acquisition module is connected to the initial feed amount calculation module and the monitoring and optimization module. The initial feed amount calculation module is connected to the feed speed adjustment module. The heating control module is connected to the feed speed adjustment module and the monitoring and optimization module. The feed speed adjustment module is connected to the monitoring and optimization module. The monitoring and optimization module is connected to the data acquisition module, the initial feed amount calculation module, the heating control module and the feed speed adjustment module.

[0111] As an implementation method, the data acquisition module includes a temperature sensor, a humidity sensor, a particle size and shape sensor, a viscometer, and a densitometer.

[0112] As an implementation method, the system for automatically adjusting the feeding speed in lunch box production also includes: a user interface and a remote monitoring module, which is used to provide an intuitive operation interface to facilitate operators to monitor and control the entire production process, and through an Internet connection, allows managers to monitor the operating status of production equipment in real time at any location; a data analysis and reporting module, which is used to collect and store data in the production process and regularly generate production reports, including output, quality, energy consumption and equipment status.

[0113] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all these improvements and changes should fall within the scope of protection of the appended claims of the present invention.

Claims

1. A method for automatically adjusting the feeding speed in lunch box production, characterized in that: include: S1: Collect the initial data of the material, monitor and collect the material temperature and material humidity data in the material storage environment in real time through sensors, and collect the material particle size and shape data, the viscosity data after the material and ingredients are mixed, and the material density data; S2: confirm the initial feed amount of the material, and determine the initial feed amount of the material into the reactor according to the initial data of the material; S3: Start the system, heat the material for reaction, and set and control the actual temperature of the reactor; S4: Dynamically adjust the feed rate. As the temperature changes, the actual feed rate is adjusted according to the current actual temperature, initial feed amount, temperature gradient comprehensive function and other factors affecting the feed rate. S5: Continuous monitoring and optimization, real-time monitoring of key parameters such as temperature and feed rate, and timely processing of alarm information when abnormal conditions are found.

2. A method for automatically adjusting the feeding speed in lunch box production according to claim 1, characterized in that: Confirm the initial feed amount F of the material according to the initial data of the material o : ； F base : Base feed amount, a constant value preset based on experience; X o : The value of the oth factor, which includes material temperature, material humidity, material particle size and shape, material viscosity and material density; w o : The weight of the oth factor.

3. A method for automatically adjusting the feeding speed in lunch box production according to claim 2, characterized in that: The actual speed F of the material entering the reactor is actually controlled: ； F0: initial feed rate, the speed at which the material enters the reactor at the beginning of the production process; T c : The actual temperature in the current reactor; T base : Base temperature, the material temperature before heating begins; f(T g ): Comprehensive function of temperature gradient based on all material properties; K p : Comprehensive coefficient, the influence of other factors on feed rate except temperature gradient.

4. A method for automatically adjusting the feeding speed in lunch box production according to claim 3, characterized in that: A comprehensive function of the temperature gradient based on all material properties: ； n: the quantity of the material; w i : The weight of material i, which is set according to the type of material; f i (T g ): Comprehensive function of temperature gradient of material i.

5. A method for automatically adjusting the feeding speed in lunch box production according to claim 3, characterized in that: The comprehensive coefficient K of other factors affecting the feed rate except the temperature gradient p : ； m: the number of different impact factors; w j : The weight of the j-th impact factor, reflecting the importance of the j-th impact factor; g j : A function of how the jth influencing factor affects the feed rate.

6. A method for automatically adjusting the feeding speed in lunch box production according to claim 3, characterized in that: The reaction furnace includes an upper heating furnace and a lower heating furnace. The two heating furnaces are temperature controlled separately. c : ； w upper : The weight of the upper heating furnace related to temperature, indicating the upper heating furnace's effect on the current temperature T c The impact of w lowerr : The weight of the lower heating furnace related to temperature, indicating the effect of the lower heating furnace on the current temperature T c The impact of T upper : The actual heating temperature of the upper heating furnace; T lowerr : The actual heating temperature of the lower heating furnace; Among them, w upper and w lowerr : ； k upper : Thermal conductivity of the upper heating furnace; k lower : Thermal conductivity of the lower heating furnace; V upper : The volume of the heating area of ​​the upper heating furnace; V lower : The volume of the heating area of ​​the lower heating furnace; Among them, w upper +w lower =1.

7. A system for automatically adjusting the feeding speed in the production of lunch boxes, characterized in that: include: A reaction furnace, used for heating and reacting materials; Data acquisition module, which includes various sensors for real-time monitoring and collecting data in the material storage environment; An initial feed amount calculation module is used to determine the initial feed amount of the material entering the reactor according to the collected initial data of the material; A heating control module includes a plurality of temperature sensors, which are installed at various positions inside and outside the reaction furnace. The heating control module is used to set and control the actual temperature of the reaction furnace and control the heating temperature to heat the material. The heating control module transmits the actual temperature and other temperature-related data to the feed speed adjustment module; The feed rate adjustment module is used to dynamically adjust the actual feed rate of the material according to the current actual temperature, initial feed amount, temperature gradient comprehensive function and other non-temperature factors affecting the feed rate; The monitoring and optimization module is used to monitor the temperature and feed rate in the reactor in real time.

8. A system for automatically adjusting the feeding speed in the production of lunch boxes according to claim 7, characterized in that: The reaction furnace is connected to a data acquisition module, an initial feed amount calculation module, a heating control module, a feed speed adjustment module and a monitoring and optimization module; The data acquisition module is connected to the initial feed amount calculation module and the monitoring and optimization module; The initial feed amount calculation module is connected to the feed speed adjustment module; The heating control module is connected to the feed rate adjustment module and the monitoring and optimization module; A feed rate adjustment module connected to the monitoring and optimization module; The monitoring and optimization module is connected to the data acquisition module, the initial feed amount calculation module, the heating control module and the feed speed adjustment module.

9. A system for automatically adjusting the feeding speed in the production of lunch boxes according to claim 8, characterized in that: The data acquisition module includes temperature sensor, humidity sensor, particle size and shape sensor, viscometer and density meter.

10. A system for automatically adjusting the feeding speed in the production of lunch boxes according to claim 7, characterized in that: The system for automatically adjusting the feeding speed in the production of lunch boxes also includes: User interface and remote monitoring module, which is used to provide an intuitive operation interface, facilitate operators to monitor and control the entire production process, and through the Internet connection, allow managers to monitor the operating status of production equipment in real time at any location; The data analysis and reporting module is used to collect and store data during the production process and regularly generate production reports, including output, quality, energy consumption and equipment status.

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