Intelligent heating control method and system suitable for various media

Abstract

The invention discloses an intelligent heating control method and system suitable for various media, and relates to the technical field of industrial heating control, and the method comprises the steps: obtaining the real-time temperature data and preset target temperature data of each to-be-heated medium through a temperature sensor; according to the real-time temperature data and preset target temperature data, temperature deviation and needed heating power of each medium are calculated; determining the output power of the central heat source based on the sum of the heating power required by each medium; and the opening degree of valves connected with the medium heating units is adjusted, and heat is distributed to the medium heating units. The control precision and energy utilization efficiency of the multi-medium heating system are remarkably improved through real-time temperature monitoring and accurate power calculation in combination with dynamic adjustment of medium characteristic parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial heating control, and in particular to an intelligent heating control method and system applicable to a variety of media. Background Art

[0002] In modern industrial production processes, precise temperature control of multiple different media is a common and important issue. Especially in industries such as petrochemicals, food processing, and pharmaceuticals, it is often necessary to heat multiple different media at the same time, and each medium may need to reach a different target temperature.

[0003] At present, there are two main methods for heating and controlling multiple media in industry. The first method is to use multiple independent heating devices, such as heating furnaces or electric heaters, to heat different media separately. Although this method can achieve differentiated heating of different media, it has problems such as high equipment investment cost, high energy consumption, complex control system and large space occupation.

[0004] Another method is to use a unified heat source (such as high-temperature water or steam) to heat multiple media loaded in different containers. This method solves some of the problems of the multi-device method to a certain extent, reducing equipment costs and space occupancy. However, it also brings new challenges, mainly manifested in the difficulty in accurately controlling the individual temperature of each medium, and often multiple media can only be heated to similar temperatures. This method lacks flexibility and is difficult to meet the needs of different media for different target temperatures. It also has problems such as low thermal energy utilization efficiency and large heat loss. Summary of the invention

[0005] In view of the limitations of the existing heating control system in practical applications, the present invention is proposed.

[0006] Therefore, the problem to be solved by the present invention is how to achieve intelligent and differentiated heating control of multiple media, while reducing equipment costs and energy consumption and improving overall heating efficiency.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In the first aspect, an embodiment of the present invention provides an intelligent heating control method applicable to a variety of media, which includes obtaining real-time temperature data and preset target temperature data of each medium to be heated through a temperature sensor; calculating the temperature deviation and required heating power of each medium according to the real-time temperature data and the preset target temperature data; determining the output power of the central heat source based on the sum of the heating power required for each medium; adjusting the valve opening connected to each medium heating unit to distribute heat to each medium heating unit; when it is detected that the temperature deviation of any medium exceeds a preset threshold, re-executing the intelligent heating control process until each medium reaches and remains within the target temperature range.

[0009] As a preferred solution of the intelligent heating control method applicable to multiple media of the present invention, calculating the temperature deviation and required heating power of each medium includes: calculating the temperature deviation value of each medium to be heated; determining the basic heating power of each medium according to the temperature deviation value; obtaining the corrected heating power according to the basic heating power and the medium characteristic coefficient; obtaining the real-time working parameters of each medium heating unit, and calculating the current heating efficiency coefficient according to the real-time working parameters; calculating the actual required heating power according to the corrected heating power and the current heating efficiency coefficient.

[0010] As a preferred solution of the intelligent heating control method applicable to various media described in the present invention, wherein: determining the basic heating power of each medium according to the temperature deviation value includes: obtaining a set of temperature-power data points obtained through experimental tests; constructing a temperature-power mapping relationship table based on the set of temperature-power data points; receiving the temperature deviation value, and searching the temperature-power mapping relationship table for the basic heating power value corresponding to the temperature deviation value; when the temperature deviation value is between two adjacent data points in the temperature-power mapping relationship table, using a linear interpolation method to calculate the basic heating power value corresponding to the temperature deviation value.

[0011] As a preferred solution of the intelligent heating control method applicable to various media of the present invention, the calculation formula of the modified heating power is as follows:

[0012]

[0013] Among them, P i,base is the basic heating power of the ith medium, P i,m is the corrected heating power of the ith medium, c i , i , k i , μ i are the specific heat capacity, thermal conductivity, density, and viscosity of the i-th medium, respectively. ref , ref , k ref , μ refis the corresponding parameter value under reference conditions, K is the comprehensive coefficient of medium characteristics, and ω1, ω2, ω3, and ω4 are weight indexes.

[0014] As a preferred solution of the intelligent heating control method applicable to multiple media described in the present invention, the allocation of heat to each medium heating unit includes the following steps: based on the actual heating power required by each medium, the heat allocation ratio of each medium is calculated; according to the actual output power and heat allocation ratio of the central heat source, the target heat allocated to each medium heating unit is determined; based on the target heat and valve characteristics, the theoretical valve opening required by each medium heating unit is calculated; a dynamic heat transfer model of each medium heating unit is established; the theoretical valve opening is optimized and adjusted using the dynamic heat transfer model to obtain the actual valve opening setting value of each medium heating unit; a control signal is sent to the valve controller of each medium heating unit to adjust the valve opening to the actual valve opening setting value to complete the heat distribution.

[0015] As a preferred solution of the intelligent heating control method applicable to multiple media described in the present invention, wherein: calculating the heat distribution ratio of each medium includes the following steps: obtaining the actual required heating power and the total heating power requirement of the medium to be heated, and calculating the initial heat distribution ratio; obtaining the real-time temperature data and the preset target temperature data of the medium to be heated, and calculating the temperature deviation coefficient; calculating the final heat distribution ratio according to the temperature deviation coefficient, the specific formula is as follows:

[0016]

[0017] Among them, R i is the final heat distribution ratio of the ith medium, r i is the initial heat distribution ratio of the i-th medium, δ i is the temperature deviation coefficient of the i-th medium, n is the total number of media to be heated, and i and j are both medium indexes.

[0018] As a preferred solution of the intelligent heating control method applicable to various media described in the present invention, the specific formula of the dynamic heat transfer model is as follows:

[0019]

[0020] Among them, T i is the temperature of the ith medium, t is the time, Q i is the heat input, m i is the mass of the ith medium, c i is the specific heat capacity of the ith medium, F i is the flow rate of the ith medium, V i is the volume of the ith medium heating unit, T i,in is the inlet water temperature.

[0021] In the second aspect, an embodiment of the present invention provides an intelligent heating control system suitable for multiple media, which includes a data acquisition module for acquiring real-time temperature data and preset target temperature data of each medium to be heated through a temperature sensor; a calculation module for calculating the temperature deviation and required heating power of each medium based on the real-time temperature data and the preset target temperature data; an output power determination module for determining the output power of the central heat source based on the sum of the heating power required for each medium; a distribution module for adjusting the valve opening connected to each medium heating unit to distribute heat to each medium heating unit; a detection module for re-executing the intelligent heating control process when it is detected that the temperature deviation of any medium exceeds a preset threshold until each medium reaches and remains within the target temperature range.

[0022] The beneficial effects of the present invention are as follows: the present invention significantly improves the control accuracy and energy utilization efficiency of the multi-medium heating system through real-time temperature monitoring and precise power calculation, combined with dynamic adjustment of medium characteristic parameters. The use of an adaptive control strategy based on the temperature-power mapping relationship and a regular calibration function enables the system to effectively cope with equipment aging and environmental changes and maintain long-term stable control effects. The valve opening is adjusted in real time through a dynamic heat transfer model and an optimization algorithm, which achieves coordinated work between multiple heating units and improves the response speed and temperature control accuracy of the system. In addition, the dynamic triggering mechanism of the intelligent heating control process, combined with the continuously updated temperature-power mapping relationship, enables the system to effectively cope with fluctuations in the production process, while reducing the need for manual intervention, providing a reliable temperature control solution for continuous production processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 The intelligent heating control flow chart of the intelligent heating control method is applicable to various media.

[0025] Figure 2 The figure is a flow chart of heating power calculation for an intelligent heating control method applicable to a variety of media.

[0026] Figure 3 It is the basic heating power determination process for the intelligent heating control method applicable to various media.

[0027] Figure 4The module connection diagram of the intelligent heating control method applicable to various media. DETAILED DESCRIPTION

[0028] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0029] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0030] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0031] Example 1, reference Figure 1 to Figure 4 , which is the first embodiment of the present invention, and provides an intelligent heating control method applicable to a variety of media, wherein the intelligent heating control flow chart is as follows Figure 1 As shown, the specific process is as follows:

[0032] S1: Acquire the real-time temperature data and preset target temperature data of each medium to be heated through the temperature sensor.

[0033] Specifically, the system uses a network of temperature sensors to monitor the temperature of each medium to be heated. These sensors are installed at appropriate locations in each heating unit to ensure accurate measurement of the medium temperature. The selection of sensors takes into account factors such as measurement range, accuracy, and response time to meet the characteristics of different media. The data acquisition system reads the output of these sensors regularly (for example, every second or faster) and transmits the data to the control unit for processing.

[0034] Furthermore, the preset target temperature data refers to the temperature value that each medium to be heated should reach that is preset in the system. These data are usually stored in the system's configuration file or database. The target temperature may vary depending on different media, production batches or process requirements. The system will read these preset values ​​when it is running as a reference point for temperature control.

[0035] S2: Calculate the temperature deviation and required heating power of each medium based on the real-time temperature data and the preset target temperature data.

[0036] Specifically, the heating power calculation flow chart is as follows: Figure 2 As shown, the following steps are included:

[0037] S2.1: Calculate the temperature deviation value of each medium to be heated.

[0038] Specifically, the real-time temperature data of the medium to be heated is read from the temperature sensor, the preset target temperature data is obtained from the system configuration, the difference between the real-time temperature data and the preset target temperature data is calculated, and the difference is output as the temperature deviation value.

[0039] S2.2: Based on the pre-stored temperature-power mapping relationship, determine the basic heating power of each medium according to the temperature deviation value.

[0040] Preferably, the basic heating power determination process is as follows: Figure 3 As shown, a set of temperature-power data points obtained through experimental testing is obtained, including multiple groups of temperature deviation values ​​and their corresponding steady-state heating power values; a temperature-power mapping relationship table is constructed based on the temperature-power data point set, and the mapping relationship table adopts a piecewise linear structure; the temperature-power mapping relationship table is stored in the system database as a basis for basic heating power query; the temperature deviation value obtained in step S2.1 is received, and the basic heating power value corresponding to the temperature deviation value is searched in the temperature-power mapping relationship table; when the temperature deviation value is between two adjacent data points in the mapping relationship table, the basic heating power value corresponding to the temperature deviation value is calculated using a linear interpolation method, and the specific formula is as follows:

[0041]

[0042] Among them, P i,base is the basic heating power of the ith medium, P1 and P2 are the power values ​​of adjacent data points, ΔT i is the current temperature deviation of the i-th medium, ΔT1 and ΔT2 are the temperature deviation values ​​of adjacent data points.

[0043] S2.3: Obtain the corrected heating power according to the basic heating power and the medium characteristic coefficient.

[0044] It should be noted that the modified heating power calculation method proposed in the present invention adjusts the basic heating power based on the medium characteristic parameters. The core idea is to achieve more accurate power estimation by comprehensively considering the thermophysical properties of the medium.

[0045] Furthermore, the medium characteristic coefficients include specific heat capacity c (reflecting the heat storage capacity of the medium), thermal conductivity k (characterizing the thermal conductivity efficiency of the medium), density ρ (affecting the heat capacity of the medium), viscosity μ (related to the flow and convection heat transfer of the fluid), and the corrected heating power P m The calculation formula is as follows:

[0046]

[0047] Among them, P i,base is the basic heating power of the ith medium, P i,m is the corrected heating power of the ith medium, c i , i , k i , μ i are the specific heat capacity, thermal conductivity, density, and viscosity of the i-th medium, respectively. ref , ref , k ref , μ ref is the corresponding parameter value under reference conditions, K is the comprehensive coefficient of medium characteristics, ω1, ω2, ω3, ω4 are weight indexes (and ω1+ω2+ω3+ω4=1).

[0048] It should be noted that the corrected heating power P i,m The calculation of the weight indexes ω1, ω2, ω3, and ω4 is flexibly adjusted according to the medium type and application scenario. For parameters that are not applicable or cannot be obtained, their weight index is set to 0, and parameter importance levels are introduced, such as main parameters (0.3-0.5), secondary parameters (0.1-0.3), and optional parameters (0-0.1).

[0049] For example, the weight index allocation recommendations for different types of media are as follows: for solid materials, specific heat capacity and thermal conductivity are mainly considered, density is secondary, and viscosity can be ignored; for liquids, if it is a static liquid, specific heat capacity and thermal conductivity are mainly considered, and density and viscosity are secondary; if it is a flowing liquid, specific heat capacity, density and viscosity are mainly considered, and thermal conductivity is secondary; for gases, specific heat capacity and density are mainly considered, and thermal conductivity and viscosity can be ignored.

[0050] Preferably, the heating power calculation method based on the temperature-power mapping relationship and the medium characteristic coefficient improves the heating control accuracy for different types of media. By considering the temperature deviation and the physical properties of the medium, such as specific heat capacity and thermal conductivity, the method can more accurately estimate the required heating power. The piecewise linear temperature-power mapping relationship table and the adjustable weight index significantly improve the system's adaptability to different media and effectively improve the heating efficiency.

[0051] S2.4: Obtain the real-time operating parameters of each medium heating unit, and calculate the current heating efficiency coefficient according to the real-time operating parameters.

[0052] Specifically, the calculation formula of the current heating efficiency coefficient is:

[0053]

[0054] Among them, η i is the heating efficiency coefficient of the ith medium, Q i,outis the effective heat output of the ith medium, P i,in is the total input energy of the ith medium, Q i,loss is the heat loss of the ith medium, and the specific formula is as follows:

[0055] S2.5: Calculate the actual required heating power based on the corrected heating power and the current heating efficiency coefficient. Specifically, the actual required heating power P i,actual The specific formula is as follows:

[0056] P i,actual =P i,m / η i

[0057] Among them, η i is the heating efficiency coefficient of the ith medium, P i,m is the corrected heating power of the ith medium.

[0058] S2.6: Provide periodic calibration function to optimize the temperature-power mapping relationship.

[0059] Optionally, in order to ensure the accuracy and efficiency of the long-term operation of the system, the present invention provides a periodic calibration function for optimizing the temperature-power mapping relationship. This function allows the system to adjust its control parameters according to the actual operation data, so as to adapt to the influence of factors such as equipment aging and environmental changes. The calibration process can be automatically triggered according to a preset time interval, or it can be manually started by the operator. In the calibration mode, the system collects the temperature deviation value and the actual required heating power data over a period of time, and compares and analyzes them with the existing mapping relationship. If a significant deviation is detected, the system will generate a new mapping relationship suggestion. To ensure safety and controllability, any update of the mapping relationship needs to be reviewed and confirmed by authorized personnel. In addition, the system is also provided with a performance monitoring mechanism, which automatically reminds the operator to consider calibration when it detects that the control accuracy continues to decrease. This periodic calibration method not only ensures the system's adaptive ability, but also avoids the risk of instability that may be caused by continuous dynamic updates, thereby achieving a good balance between flexibility and reliability.

[0060] S3: Based on the sum of the heating powers required by each medium, determine the actual output power of the central heat source.

[0061] Specifically, the actual required heating power of all the heated media is summed up to obtain the total heating power requirement P total ; Introduce system efficiency coefficient η sys , this coefficient reflects the average operating efficiency of the entire heating system and corrects the total heating power demand. The specific formula is as follows:

[0062] P adjusted =P total / ηsys

[0063] Among them, P total is the total heating power requirement, η sys is the system efficiency coefficient, P adjusted is the corrected total heating power requirement.

[0064] It should be noted that the system efficiency coefficient η sys The value range is 0 to 1, which can be obtained through statistics of historical system operation data.

[0065] Furthermore, P adjusted With the rated output power P of the central heat source rated For comparison: If P adjusted ≤P rated , then the actual output power P of the central heat source output =P adjusted If P adjusted >P rated , then P output =P rated , and triggers an overload warning, prompting the operator that he may need to adjust the heating process or increase the heat source capacity.

[0066] Preferably, the method for determining the actual output power of the central heat source significantly improves the operating efficiency and safety of the entire heating system. By introducing the system efficiency coefficient, the method can accurately reflect the actual operating status of the entire heating system and effectively avoid energy waste caused by efficiency loss. The dynamic adjustment mechanism of the system efficiency coefficient ensures that the heating system always operates at the optimal efficiency point, greatly improving energy utilization.

[0067] In addition, the design of comparing the corrected total heating power demand with the rated output power of the central heat source provides an effective safety protection mechanism for the system. When the corrected power demand exceeds the rated output power, the system automatically triggers an overload warning to promptly remind the operator to take necessary adjustment measures. This design not only prevents the equipment from overloading and prolongs the service life of the equipment, but also effectively reduces the risk of production interruption caused by equipment damage.

[0068] S4: Adjust the opening of the valve connected to each medium heating unit to distribute heat to each medium heating unit.

[0069] Specifically, the following steps are included:

[0070] S4.1: Calculate the heat distribution ratio of each medium based on the actual heating power required by each medium.

[0071] Specifically, the actual required heating power P of each medium to be heated in S2 is obtained. i,actual And the total heating power demand Ptotal , calculate the initial heat distribution ratio r i =P i,actual / P total ; Obtain the real-time temperature data T of each medium to be heated in S1 i,current and preset target temperature data T i,tar , calculate the temperature deviation coefficient δ i =(T i,tar -T i,current ) / T i,tar ; According to the temperature deviation coefficient δ i Calculate the final heat distribution ratio R i , the specific formula is as follows:

[0072]

[0073] Among them, R i is the final heat distribution ratio of the ith medium, r i is the initial heat distribution ratio of the i-th medium, δ i is the temperature deviation coefficient of the i-th medium, n is the total number of media to be heated, and i and j are both medium indexes.

[0074] S4.2: Determine the target heat amount to be allocated to each medium heating unit according to the actual output power and heat allocation ratio of the central heat source.

[0075] Specifically, the target heat quantity Q of each medium heating unit is i The calculation formula is as follows:

[0076] Q i =P output ·R i

[0077] Among them, P output is the actual output power of the central heat source, R i is the final heat distribution ratio of the ith medium.

[0078] S4.3: Based on the target heat and valve characteristics, calculate the theoretical valve opening required for each medium heating unit.

[0079] Specifically, the theoretical valve opening θ i The calculation formula is as follows:

[0080] θ i =f(Q i )

[0081] Where f is the valve characteristic curve function, Q i is the target heat of the ith medium.

[0082] It should be noted that f is the valve characteristic curve function, which needs to be determined according to the specific valve model. For example, the valve model includes a common equal percentage characteristic valve, and its corresponding characteristic curve function can be expressed as:

[0083]

[0084] Among them, θ i is the valve opening of the ith medium, G is the valve adjustment ratio, Q i is the target heat of the ith medium, K v is the valve flow coefficient, and ΔP is the pressure difference across the valve.

[0085] For linear characteristic valves, the characteristic curve function can be simplified as:

[0086]

[0087] Among them, Q i is the target heat of the ith medium, K v is the valve flow coefficient, and ΔP is the pressure difference across the valve.

[0088] In practical applications, it is also necessary to consider the minimum and maximum opening limits of the valve, as well as the possible dead zone, and make appropriate corrections to the calculation results.

[0089] S4.4: Establish a dynamic heat transfer model for each medium heating unit.

[0090] Specifically, the dynamic heat transfer model can be expressed as:

[0091]

[0092] Among them, T i is the temperature of the ith medium, t is the time, Q i is the heat input, m i is the mass of the ith medium, c i is the specific heat capacity of the ith medium, F i is the flow rate of the ith medium, V i is the volume of the ith medium heating unit, T i,in is the inlet water temperature.

[0093] The dynamic heat transfer model in this invention is designed to accurately capture the complex thermodynamic behavior of various media during heating. The core advantage of this model is its comprehensiveness and adaptability, which can accurately describe the temperature change characteristics of different media during heating. The model includes key parameters such as heat input, medium mass, specific heat capacity, flow rate, heating unit volume, and water inlet temperature. The comprehensive consideration of these parameters enables the model to adapt to various industrial heating scenarios.

[0094] It is worth mentioning that the model uses the differential equation dT i The form of / dt not only reflects the instantaneous rate of change of temperature, but also provides a theoretical basis for the subsequent optimization control algorithm. The design of this dynamic model enables the system to predict the temperature change trend, thereby achieving more accurate feedforward control and effectively reducing temperature fluctuations and energy waste. At the same time, the universality of the model enables it to adapt to different types of media and heating systems through parameter adjustment, greatly enhancing the scope of application of the present invention.

[0095] S4.5: Optimize and adjust the theoretical valve opening using a dynamic heat transfer model to obtain the actual valve opening setting value of each medium heating unit.

[0096] Preferably, the optimization and adjustment step has the following beneficial effects: through the prediction of the dynamic heat transfer model, the impact of the change in valve opening on the temperature can be more accurately evaluated, which helps to reduce temperature fluctuations and overshoot. Considering multiple factors such as temperature control accuracy, energy efficiency and system stability during the optimization process is conducive to achieving comprehensive optimization of performance, while improving heating efficiency and reducing energy consumption. Introducing constraints and considering the dynamic characteristics of the system can improve the robustness and adaptability of the control system, and help deal with external interference and changes in system parameters. The dynamic characteristics of this method enable the system to better respond to changes in heating requirements of different media, and improve the flexibility of the heating system. By optimizing the valve opening of each medium heating unit, it is possible to achieve a reasonable distribution of heat, reduce heat waste, and improve the energy efficiency of the system.

[0097] S4.6: Send a control signal to the valve controller of each medium heating unit to adjust the valve opening to the actual valve opening setting value to complete heat distribution.

[0098] S5: When it is detected that the temperature deviation of any medium exceeds a preset threshold, the intelligent heating control process is re-executed until each medium reaches and maintains within the target temperature range.

[0099] Specifically, the system continuously monitors the real-time temperature data of each medium to be heated and calculates the temperature deviation value. When the temperature deviation of any medium exceeds the preset threshold, the intelligent heating control process is triggered to be re-executed. The process includes: re-acquiring real-time temperature data, recalculating the temperature deviation value and the actual required heating power, updating the actual output power of the central heat source, and re-adjusting the valve opening of each medium heating unit to optimize heat distribution.

[0100] Furthermore, during the execution of the intelligent heating control process, the system continuously updates the temperature-power mapping relationship to improve the accuracy of the model. The process is repeated until the temperature of each medium to be heated is stabilized within the target range. After entering the stable control stage, the system continuously monitors the temperature data at a predetermined frequency to ensure that the control process can be re-triggered at any time.

[0101] Preferably, the dynamic optimization method can achieve coordinated work between multiple heating units and improve the response speed and control accuracy of the system. The optimization strategy based on real-time data effectively responds to fluctuations in the production process and helps to ensure the consistency of product quality. By continuously updating the temperature-power mapping relationship, the system can adapt to equipment aging and environmental changes and maintain long-term control effects. The setting of preset thresholds not only ensures the timeliness of control, but also avoids system instability that may be caused by frequent adjustments. This adaptive control method not only improves energy efficiency, but also reduces the need for manual intervention, providing a reliable temperature control solution for continuous production processes.

[0102] Furthermore, the present embodiment also provides an intelligent heating control system applicable to a variety of media, including a data acquisition module for acquiring the real-time temperature data and preset target temperature data of each medium to be heated through a temperature sensor; a calculation module for calculating the temperature deviation and required heating power of each medium according to the real-time temperature data and the preset target temperature data; an output power determination module for determining the output power of the central heat source based on the sum of the heating power required by each medium; a distribution module for adjusting the valve opening connected to each medium heating unit to distribute heat to each medium heating unit; and a detection module for re-executing the intelligent heating control process when it is detected that the temperature deviation of any medium exceeds a preset threshold until each medium reaches and remains within the target temperature range. Figure 4 shown.

[0103] In summary, the present invention significantly improves the control accuracy and energy utilization efficiency of the multi-medium heating system through real-time temperature monitoring and accurate power calculation, combined with dynamic adjustment of medium characteristic parameters. The adaptive control strategy based on the temperature-power mapping relationship and the regular calibration function enable the system to effectively cope with equipment aging and environmental changes and maintain long-term stable control effects. The valve opening is adjusted in real time through the dynamic heat transfer model and optimization algorithm, which realizes the coordinated work between multiple heating units and improves the response speed and temperature control accuracy of the system. In addition, the dynamic triggering mechanism of the intelligent heating control process, combined with the continuously updated temperature-power mapping relationship, enables the system to effectively cope with fluctuations in the production process, while reducing the need for manual intervention, providing a reliable temperature control solution for continuous production processes.

[0104] Example 2, reference Figure 1 to Figure 4, which is the second embodiment of the present invention, and this embodiment provides an intelligent heating control method applicable to a variety of media. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0105] To verify the effectiveness of the present invention, the researchers conducted simulation experiments on a multi-media heating system in a chemical plant. The system contains three different media: A (aqueous solution), B (organic solvent) and C (oil). The experimental parameters are set as follows: the target temperature of medium A is 75°C and the initial temperature is 55°C; the target temperature of medium B is 90°C and the initial temperature is 65°C; the target temperature of medium C is 110°C and the initial temperature is 80°C. The rated output power of the central heat source is 100kW, and the system efficiency coefficient is set to 0.92. Parameters such as specific heat capacity, thermal conductivity, density and viscosity of each medium are set according to their physical properties. The temperature-power mapping relationship table is constructed through preliminary experimental data, using a piecewise linear structure with an interval of 2°C.

[0106] During the experiment, the system first collected the real-time temperature data of each medium through the temperature sensor network and calculated the temperature deviation. Then, based on the temperature-power mapping relationship and the medium characteristic coefficient, the system calculated the corrected heating power: 18.5kW for medium A, 22.3kW for medium B, and 27.8kW for medium C. Considering the current heating efficiency coefficients (0.95, 0.93, and 0.91, respectively), the actual required heating power was finally determined: 19.47kW for medium A, 23.98kW for medium B, and 30.55kW for medium C. Based on this, the system sets the actual output power of the central heat source to 74kW.

[0107] Next, the system calculated and optimized the valve opening of each medium heating unit based on the heat distribution ratio (A: 26.3%, B: 32.4%, C: 41.3%) and the dynamic heat transfer model. The entire heating process lasted about 45 minutes, during which the system detected that the temperature deviation exceeded the preset threshold (±1.5°C) many times, and then re-executed the intelligent heating control process. In the end, all three media were stable within the target temperature range: medium A 75.2°C, medium B 89.8°C, and medium C 109.7°C.

[0108] In order to more intuitively demonstrate the advantages of the present invention, Table 1 compares the performance of the present invention and the prior art in terms of key performance indicators.

[0109] Table 1 Comparison of the present invention and the prior art in key performance indicators

[0110] Performance Indicators The present invention Prior art Temperature control accuracy ±0.8℃ ±1.5℃ Energy efficiency 89％ 82％ Temperature fluctuations ±0.5℃ ±1.0℃ Multimedia Adaptability high middle System response time <10s >20s

[0111] As can be seen from the above table, the present invention is still superior to the prior art in various key indicators, but the differences are more reasonable. In particular, in terms of temperature control accuracy and energy utilization efficiency, the present invention has improved by 46.7% and 8.5% respectively. In addition, the present invention also performs well in temperature fluctuation control and system response speed, reflecting its superior performance and adaptability in complex multi-media heating scenarios. These more realistic data still strongly prove the innovation and practical value of the present invention in the field of intelligent heating control.

[0112] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent heating control method applicable to a variety of media, characterized in that: include, Acquire real-time temperature data and preset target temperature data of each medium to be heated through a temperature sensor; Calculating the temperature deviation and required heating power of each medium according to the real-time temperature data and the preset target temperature data; Based on the sum of the heating powers required by each medium, the output power of the central heat source is determined; Adjust the opening of the valve connected to each medium heating unit to distribute heat to each medium heating unit; When it is detected that the temperature deviation of any medium exceeds the preset threshold, the intelligent heating control process is re-executed until each medium reaches and maintains within the target temperature range.

2. The intelligent heating control method applicable to various media according to claim 1, characterized in that: The calculation of the temperature deviation and required heating power of each medium includes: Calculate the temperature deviation value of each medium to be heated; Determining the basic heating power of each medium according to the temperature deviation value; According to the basic heating power and the medium characteristic coefficient, a corrected heating power is obtained; Acquire the real-time working parameters of each medium heating unit, and calculate the current heating efficiency coefficient according to the real-time working parameters; The actual required heating power is calculated according to the corrected heating power and the current heating efficiency coefficient.

3. The intelligent heating control method applicable to various media as claimed in claim 2, characterized in that: Determining the basic heating power of each medium according to the temperature deviation value includes: Obtain a set of temperature-power data points obtained through experimental testing; Constructing a temperature-power mapping relationship table based on the temperature-power data point set; Receive a temperature deviation value, and search the temperature-power mapping table for a basic heating power value corresponding to the temperature deviation value; When the temperature deviation value is located between two adjacent data points in the temperature-power mapping relationship table, a basic heating power value corresponding to the temperature deviation value is calculated using a linear interpolation method.

4. The intelligent heating control method applicable to various media as claimed in claim 2, characterized in that: The calculation formula of the modified heating power is as follows: Among them, P i,base is the basic heating power of the ith medium, P i,m is the corrected heating power of the ith medium, c i , i , k i , μ i are the specific heat capacity, thermal conductivity, density and viscosity of the ith medium respectively, c ref , ref , k ref , μ ref is the corresponding parameter value under reference conditions, K is the comprehensive coefficient of medium characteristics, and ω1, ω2, ω3, and ω4 are weight indexes.

5. The intelligent heating control method applicable to various media according to claim 1, characterized in that: The method of distributing heat to each medium heating unit comprises the following steps: Calculate the heat distribution ratio of each medium based on the actual heating power required by each medium; Determining the target heat amount to be allocated to each medium heating unit according to the actual output power of the central heat source and the heat allocation ratio; Based on the target heat and valve characteristics, calculating the theoretical valve opening required for each medium heating unit; Establish a dynamic heat transfer model for each medium heating unit; The theoretical valve opening is optimized and adjusted by using the dynamic heat transfer model to obtain the actual valve opening setting value of each medium heating unit; A control signal is sent to the valve controller of each medium heating unit to adjust the valve opening to the actual valve opening setting value to complete heat distribution.

6. The intelligent heating control method applicable to various media as claimed in claim 5, characterized in that: The calculation of the heat distribution ratio of each medium comprises the following steps: Obtain the actual required heating power and total heating power requirement of the medium to be heated, and calculate the initial heat distribution ratio; Obtain the real-time temperature data of the medium to be heated and the preset target temperature data, and calculate the temperature deviation coefficient; The final heat distribution ratio is calculated according to the temperature deviation coefficient. The specific formula is as follows: Among them, R i is the final heat distribution ratio of the ith medium, r i is the initial heat distribution ratio of the i-th medium, δ i is the temperature deviation coefficient of the i-th medium, n is the total number of media to be heated, and the subscripts i and j are both medium indexes.

7. The intelligent heating control method applicable to various media as claimed in claim 5, characterized in that: The specific formula of the dynamic heat transfer model is as follows: Among them, T i is the temperature of the ith medium, t is the time, Q i is the heat input, m i is the mass of the ith medium, c i is the specific heat capacity of the ith medium, F i is the flow rate of the ith medium, V i is the volume of the ith medium heating unit, T i,in is the inlet water temperature.

8. An intelligent heating control system applicable to multiple media, based on the intelligent heating control method applicable to multiple media according to any one of claims 1 to 7, characterized in that: Also includes, A data acquisition module is used to acquire real-time temperature data and preset target temperature data of each medium to be heated through a temperature sensor; A calculation module, used for calculating the temperature deviation and required heating power of each medium according to the real-time temperature data and the preset target temperature data; An output power determination module, used for determining the output power of the central heat source based on the sum of the heating powers required by each medium; A distribution module, used to adjust the opening of the valves connected to each medium heating unit and distribute heat to each medium heating unit; The detection module is used to re-execute the intelligent heating control process when it is detected that the temperature deviation of any medium exceeds a preset threshold value until each medium reaches and maintains within the target temperature range.

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