A multi-point constant temperature heating control method and system for graphene layer

Abstract

The present invention discloses a multi-point constant temperature heating control method and system for a graphene layer, and relates to the field of intelligent control technology. The method comprises: determining multiple heating points distributed on the graphene layer; performing real-time temperature monitoring on the multiple heating points, and outputting multiple temperature monitoring data; inputting multiple temperature monitoring data into a constant temperature equilibrium control model, and identifying temperature deviations of each heating point according to the constant temperature equilibrium control model, determining abnormal heating points, and adjacent heating points of the abnormal heating points; obtaining the current real-time heating control parameters of the abnormal heating points and adjacent heating points; performing feedback adjustment according to the real-time heating control parameters, and outputting the adjusted heating control parameters, so as to adjust the heating control parameters to perform temperature coordinated control on the abnormal heating and adjacent heating points. The method solves the technical problems of uneven heating of the graphene layer and inaccurate temperature control in the prior art, and achieves the technical effect of improving the heating uniformity of the graphene layer and realizing multi-point constant temperature precision control.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, specifically to a multi-point constant temperature heating control method and system for graphene layers. Background Technology

[0002] With the rapid development of science and technology, graphene, as an emerging material, has shown great application potential in various fields such as heating, sensing, and energy storage due to its excellent electrical and thermal conductivity and extremely high mechanical strength. Especially in the heating field, graphene layers, due to their ultra-thin, efficient, and uniform heating characteristics, are widely used in intelligent temperature control systems, smart homes, medical equipment, and industrial heating. However, in practical applications, ensuring the uniformity of heating and precise temperature control of the graphene layer has become a key technical challenge restricting its further promotion and application. Traditional heating control methods often use single-point or a few-point temperature monitoring and control, which is difficult to comprehensively reflect the temperature distribution on the graphene layer, leading to problems such as uneven heating and large temperature fluctuations. Furthermore, due to the special properties of graphene materials, its physical characteristics such as heat conduction and heat radiation during the heating process also place higher demands on temperature control. Summary of the Invention

[0003] This application provides a multi-point isothermal heating control method and system for graphene layers, which solves the technical problems of uneven heating and inaccurate temperature control of graphene layers in the prior art.

[0004] In view of the above problems, this application provides a method and system for controlling multi-point isothermal heating of graphene layers.

[0005] The first aspect of this application provides a method for multi-point isothermal heating control of a graphene layer, the method comprising:

[0006] Multiple heating points are distributed on the graphene layer, each heating point having a corresponding heating element, and each heating element including a conductive element. A multi-point temperature monitoring module is set up to monitor the temperature of the multiple heating points in real time and output multiple temperature monitoring data. The multiple temperature monitoring data are input into a constant temperature equilibrium control model, and the model identifies temperature deviations at each heating point to determine abnormal heating points and their neighboring heating points. The current real-time heating control parameters of the abnormal heating points and the neighboring heating points are obtained, including heating power, heating duration, and temperature deviation value. Feedback adjustment is performed based on the real-time heating control parameters, and adjusted heating control parameters are output to perform coordinated temperature control of the abnormal heating points and the neighboring heating points.

[0007] A second aspect of this application provides a multi-point isotropic heating control system for a graphene layer, the system comprising:

[0008] Heating Point Determination Component: Determines multiple heating points distributed on the graphene layer, wherein each heating point is equipped with a corresponding heating element, and each heating element includes a conductive element; Temperature Monitoring Component: Sets up a multi-point temperature monitoring module to perform real-time temperature monitoring on the multiple heating points and outputs multiple temperature monitoring data; Temperature Deviation Identification Component: Inputs the multiple temperature monitoring data into a constant temperature equilibrium control model, identifies temperature deviations at each heating point based on the constant temperature equilibrium control model, and determines abnormal heating points and their neighboring heating points; Parameter Acquisition Component: Acquires the current real-time heating control parameters of the abnormal heating point and the neighboring heating point, including heating power, heating duration, and temperature deviation value; Control Component: Performs feedback adjustment based on the real-time heating control parameters, outputs adjusted heating control parameters, and uses the adjusted heating control parameters to perform coordinated temperature control on the abnormal heating point and the neighboring heating point.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] First, multiple heating points are distributed on the graphene layer, each equipped with a corresponding heating element, and each heating element includes a conductive element. Next, a multi-point temperature monitoring module is set up to monitor the temperature of multiple heating points in real time and output multiple temperature monitoring data. Then, the multiple temperature monitoring data are input into a constant temperature equilibrium control model. Based on the constant temperature equilibrium control model, temperature deviations at each heating point are identified, determining abnormal heating points and their neighboring heating points. Further, the current real-time heating control parameters for abnormal and neighboring heating points are obtained, including heating power, heating duration, and temperature deviation value. Finally, feedback adjustment is performed based on the real-time heating control parameters, outputting adjusted heating control parameters to coordinate temperature control of abnormal and neighboring heating points. This solves the technical problems of uneven heating and inaccurate temperature control in existing technologies, achieving the technical effects of improving the heating uniformity of the graphene layer and realizing precise multi-point constant temperature control. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 A schematic flowchart of a multi-point isothermal heating control method for a graphene layer provided in an embodiment of this application;

[0013] Figure 2 This is a schematic diagram of a multi-point constant temperature heating control system for a graphene layer provided in an embodiment of this application.

[0014] Explanation of reference numerals in the attached diagram: heating point determination component 11, temperature monitoring component 12, temperature deviation identification component 13, parameter acquisition component 14, control component 15. Detailed Implementation

[0015] This application provides a multi-point isothermal heating control method and system for graphene layers, which solves the technical problems of uneven heating and inaccurate temperature control of graphene layers in the prior art.

[0016] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0017] It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0018] Example 1, as Figure 1 As shown, this application provides a method for controlling multi-point isothermal heating of a graphene layer, wherein the method includes:

[0019] Multiple heating points are distributed on the graphene layer, wherein each heating point is provided with a corresponding heating element, and each heating element includes a conductive element.

[0020] Multiple heating points are identified and defined on the graphene layer. Each heating point is equipped with a corresponding heating element, and each heating element is equipped with a conductive element. The conductive element is used to control the heating element to maintain a constant temperature state. It not only has high thermal conductivity, but also reduces the rate of temperature change, thereby maintaining a constant temperature.

[0021] Furthermore, after determining the multiple heating points distributed on the graphene layer, the method also includes:

[0022] The distribution locations of multiple heating points on the graphene layer are determined and output. The positional characteristics of the multiple distribution locations are identified, including the distance between the locations and the heating part affected by the location. The multiple heating points are divided into regions according to the positional characteristics, and multiple heating regions are output. The heating points in each heating region are heating points that are less than a preset distance away and belong to the same heating part. The constant temperature equalization control model is used to perform constant temperature equalization control on the multiple heating regions.

[0023] After identifying and determining multiple heating points on the graphene layer, it is necessary to further clarify the specific location of each heating point. These locations will be recorded as the basis for subsequent temperature control and region division. After obtaining the distribution location of each heating point, it is necessary to identify the characteristic information of these locations. Location characteristics include the distance between locations and the heating area affected by each location. The distance between locations refers to the physical distance between each heating point; by measuring the distance between locations, their distribution density on the graphene layer can be analyzed. The heating area affected by each location refers to the specific heating region where the heating point is located, that is, the heating area where the heating pad acts. Based on the location characteristics, the heating points are divided into regions according to the following rules: when the distance between heating points is less than a preset distance threshold and they belong to the same heating area, these heating points are grouped into one heating region, resulting in multiple heating regions. Each heating region contains heating points that meet the preset distance and heating area conditions for subsequent coordinated temperature control. After the heating point areas are divided, the constant temperature equalization control model will perform constant temperature control on each heating area. The constant temperature equalization control model will monitor and adjust the temperature in each area in real time to ensure that the heating point in each area is maintained within the set temperature range and to prevent overheating or temperature deviation.

[0024] Furthermore, the constant temperature equalization control model is used to perform constant temperature equalization control on the multiple heating zones, and the method includes:

[0025] Based on the multiple heating regions, multiple temperature comparison samples are generated; the initialization network is trained using the multiple temperature comparison samples and label information indicating abnormal temperature deviations to obtain multiple local isothermal equilibrium control models, wherein the multiple local isothermal equilibrium control models correspond to the multiple heating regions respectively; the multiple local isothermal equilibrium control models are integrated for learning to obtain a global isothermal equilibrium control model; the model parameters of the multiple local isothermal equilibrium control models are updated based on the model parameters of the global isothermal equilibrium control model to obtain updated multiple local isothermal equilibrium control models.

[0026] Specifically, based on real-time temperature data from multiple heating zones, several temperature comparison samples are generated to analyze temperature differences between zones. Each sample includes the current temperature value of the zone and its temperature comparison information with neighboring zones. Using the generated temperature comparison samples and labels indicating abnormal temperature deviations, initial local isothermal equilibrium control models are established for each heating zone. Each local model is trained independently to learn the temperature characteristics and response patterns of abnormal deviations in its corresponding heating zone. The multiple local isothermal equilibrium control models are integrated and trained to form a global isothermal equilibrium control model. This integrated learning optimizes the global temperature equilibrium control strategy by combining the heating characteristics of multiple zones. The optimized parameters of the global isothermal equilibrium control model are used to update the parameters of each local model. The updated local models can simultaneously consider local heating characteristics and global equilibrium requirements, thereby improving the coordination and consistency between heating zones. The updated local isothermal equilibrium control models are combined with the global model to ensure that the temperature control of multiple heating zones can adapt to local needs while meeting the global equilibrium control objective.

[0027] Furthermore, after outputting multiple heating regions, the temperature sensitivity coefficient corresponding to each heating part in the multiple heating regions is recorded, and multiple temperature sensitivity coefficients are output; based on the multiple temperature sensitivity coefficients, conductive elements with different heat conduction performance are configured on the heating element of each region, wherein the indicators for calculating heat conduction performance include conductive element density, heat conduction rate, and heat capacity.

[0028] After dividing the heating zone into multiple areas, the temperature response characteristics of each heating element are monitored, and its temperature sensitivity coefficient is recorded. The temperature sensitivity coefficient reflects the degree of temperature response of the heating element to heat input; the higher the value, the more sensitive it is to changes in heat. Optionally, temperature change data of each heating element under different heating conditions are collected through experiments or simulations. Based on the collected data, statistical analysis is performed on the temperature change data to extract key indicators reflecting sensitivity. The temperature sensitivity coefficient of each heating element is then calculated by an expert team.

[0029] Based on the temperature sensitivity coefficient of each heating zone, conductive components with different thermal conductivity properties are selected. These components can be metal sheets, thermally conductive adhesives, heat pipes, etc. To accurately match the needs of the heating zone, the thermal conductivity performance of the conductive components is calculated, including the component density (mass per unit volume), thermal conductivity rate (the rate at which heat passes through a unit area per unit time), and heat capacity (the material's ability to absorb or release heat). Based on the calculated results of the temperature sensitivity coefficient and thermal conductivity performance of the heating zone, the optimal conductive component is configured on the heating element of each zone. For example, for heating zones with a high temperature sensitivity coefficient, a conductive component with a high thermal conductivity rate and low heat capacity can be selected to quickly respond to temperature changes and reduce energy loss.

[0030] Furthermore, after configuring conductive elements with different thermal conductivity properties on the heating element of each region according to the multiple temperature sensitivity coefficients, the method further includes:

[0031] Record the flexibility requirement of each heating part in the multiple heating regions and output multiple flexibility requirements; based on the multiple flexibility requirements, configure conductive elements with different flexibility indices on the heating element in each region, wherein the indices for calculating the flexibility indices include the hardness and thickness of the conductive elements.

[0032] After configuring the thermal conductivity of the conductive components, the flexibility requirement of each heating element is monitored. The flexibility requirement reflects the heating element's ability to adapt to deformation, changes in contact area, or uniform pressure distribution. Optionally, deformation data of each heating element under different external forces is collected through experiments or simulations. Based on the collected data, statistical analysis is performed to extract key indicators reflecting flexibility requirements. The flexibility requirement of each heating element is then calculated by an expert team. Based on the flexibility requirement of each heating area, conductive components with different flexibility indices are selected. These components must maintain good thermal conductivity while meeting certain flexibility requirements. To accurately match the needs of the heating area, the flexibility indices of the conductive components are calculated, including component hardness (the material's resistance to deformation) and component thickness (the material's physical dimensions). Based on the calculated flexibility requirements and indices for each heating area, the optimal conductive component is configured for each area. For example, for heating areas with high flexibility requirements, conductive components with lower hardness and appropriate thickness can be selected to maintain good fit and deformation resistance.

[0033] A multi-point temperature monitoring module is set up to monitor the temperature of the multiple heating points in real time and output multiple temperature monitoring data.

[0034] Temperature monitoring sensors are deployed near multiple heating points in the graphene layer, with each sensor corresponding to one heating point. These sensors can collect local temperature data in real time for subsequent temperature analysis and control. The temperature monitoring sensors are strategically positioned based on the distribution of the heating points and heating requirements to ensure accurate monitoring of temperature changes at each heating point. All temperature monitoring sensors are connected to a multi-point temperature monitoring module, forming a data acquisition network. The multi-point temperature monitoring module collects and monitors the temperature of each heating point in real time. The real-time temperature data from multiple heating points is recorded and output, resulting in multiple temperature monitoring data sets.

[0035] The multiple temperature monitoring data are input into the constant temperature equalization control model. Based on the constant temperature equalization control model, temperature deviations of each heating point are identified to determine abnormal heating points and the adjacent heating points of the abnormal heating points.

[0036] Temperature data from multiple heating points collected by the real-time temperature monitoring module are input into the constant temperature equilibrium control model. Based on preset temperature ranges and thresholds, the model calculates the temperature deviation of each heating point by comparing the actual temperature with the desired temperature and calculating the deviation value. The model identifies heating points whose temperature deviation exceeds the threshold, i.e., abnormal heating points, based on the calculated deviation value. These abnormal heating points are marked and their relevant information (such as heating point identifier, temperature value, and degree of deviation) is recorded. Based on the layout of the heating system and the distribution of heating points, neighboring heating points are determined.

[0037] Furthermore, the method for determining abnormal heating points and neighboring heating points includes:

[0038] Identify abnormal heating points, wherein the abnormal heating points are heating points whose temperature deviation is greater than a preset deviation; based on the abnormal heating points, obtain neighboring heating points within a preset radius; filter the neighboring heating points within the preset radius that belong to the same heating area and output them.

[0039] Specifically, a preset deviation value is set, representing an acceptable temperature deviation range. When the temperature deviation of a heating point exceeds this preset value, it is considered an abnormal heating point. For each heating point, the deviation between its actual temperature and the expected temperature (or the median of the temperature range) is calculated to obtain the temperature deviation value. The calculated temperature deviation value is compared with the preset deviation value. If the temperature deviation value of a heating point is greater than the preset deviation value, it is determined to be an abnormal heating point. To determine the neighboring heating points of the abnormal heating point, a preset radius is set, which defines the range of heating points adjacent to the abnormal heating point. Based on the location of the abnormal heating point, all heating points within the preset radius are searched, and these heating points are considered neighboring heating points of the abnormal heating point. For all neighboring heating points, heating points belonging to the same heating region as the abnormal heating point are selected based on their region identification information.

[0040] Obtain the current real-time heating control parameters of the abnormal heating point and the adjacent heating point, including heating power, heating duration and temperature deviation value.

[0041] Heating power is the real-time power input value provided by the heating element to the current heating point, used for temperature regulation; heating duration is the cumulative time from the start of heating to the current moment, used to analyze the relationship between temperature change and heating duration; temperature deviation is the difference between the actual temperature of the current heating point and the target temperature, reflecting the effectiveness of temperature control. Based on the identified abnormal heating points and adjacent heating points, real-time heating control parameters are obtained, including heating power, heating duration, and temperature deviation.

[0042] Feedback adjustment is performed based on the real-time heating control parameters, and adjusted heating control parameters are output. The adjusted heating control parameters are used to perform temperature coordinated control on the abnormal heating and the adjacent heating points.

[0043] A thorough analysis is conducted on the real-time heating control parameters (including heating power, heating duration, and temperature deviation) of the abnormal heating point and its neighboring heating points. Based on the analysis results, a feedback adjustment strategy is formulated, which may include adjusting the heating power, changing the heating duration, and optimizing the temperature setpoint. This enables coordinated temperature control of the abnormal heating point and its neighboring heating points to achieve the expected temperature range and reduce temperature deviation. Based on the calculated adjustment heating control parameters, coordinated temperature control is implemented for the abnormal heating point and its neighboring heating points.

[0044] Furthermore, the method of adjusting the heating control parameters based on feedback, and outputting the adjusted heating control parameters, includes:

[0045] The temperature deviation of the abnormal heating point and the temperature deviation of the adjacent heating point are obtained; the temperature deviation weight of each heating point is determined based on the temperature deviation of the abnormal heating point and the temperature deviation of the adjacent heating point; the collaborative weight of each heating point is calculated based on the temperature deviation weight of each heating point; the real-time heating control parameters are adjusted according to the collaborative weight, and the adjusted heating control parameters are output.

[0046] Specifically, the temperature deviation of abnormal heating points and adjacent heating points is obtained; based on the temperature deviation of each heating point, a temperature deviation weight is assigned. This weight is calculated by comparing the temperature deviation of each heating point with the total deviation of all heating points. For example, the temperature deviation of a certain heating point can be divided by the sum of the temperature deviations of all heating points to obtain the temperature deviation weight of that heating point; according to the temperature deviation, the collaborative weights w1 and w2 of abnormal heating points and adjacent heating points are calculated. Optionally, the collaborative weight w1 of the abnormal heating point is equal to the absolute value of the temperature deviation of the abnormal heating point divided by the absolute value of the temperature deviation of the abnormal heating point plus the absolute value of the temperature deviation of the adjacent heating point. The collaborative weight w2 of the adjacent heating point can be obtained by subtracting the collaborative weight w1 of the abnormal heating point from 1; based on the collaborative weights, the real-time heating control parameters are adjusted according to feedback, the heating power of the heating points is adjusted, and the adjusted heating control parameters of each heating point are output.

[0047] Furthermore, the methods include:

[0048] Obtain heating control parameter samples; test each heating point according to the heating control parameter samples; based on the multi-point temperature monitoring module, obtain heating element-temperature test dataset and conductive element-temperature test dataset; perform conductive element loss rate analysis according to the heating element-temperature test dataset and conductive element-temperature test dataset, and output the conductive loss rate; use the conductive loss rate to update and adjust the real-time heating control parameters.

[0049] Specifically, heating control parameter samples are obtained from historical data, including different heating power and heating duration values. Based on the obtained heating control parameter samples, temperature tests are performed on the heating element at each heating point. By adjusting different heating power and heating duration, the temperature response of each heating point is measured. A multi-point temperature monitoring module is used to collect temperature data of the heating element under different control parameters, generating a heating element-temperature test dataset. Temperature tests are also performed on the conductive element to measure the temperature response characteristics of heat conduction. A multi-point temperature monitoring module is used to collect temperature data of the conductive element under different control parameters, generating a conductive element-temperature test dataset. Based on the heating element-temperature test data... This dataset, containing both heat transfer components and temperature test data, analyzes heat loss during heat transfer. It calculates the heat loss rate, reflecting the degree of heat loss during heat transfer. The heat loss rate can be calculated by comparing the initial temperature of the heat transfer component with the temperature response of the heating element, yielding the percentage of heat loss for each component. The heat loss rate is used as a feedback factor to adjust real-time heating control parameters. Based on the heat loss rate, parameters such as heating power and heating time of the heating element are updated to generate new heating control parameters to compensate for insufficient temperature caused by heat transfer losses. The updated and adjusted heating control parameters are then output for further optimization of temperature control at the heating point, achieving temperature equilibrium.

[0050] In summary, the embodiments of this application have at least the following technical effects:

[0051] First, multiple heating points are distributed on the graphene layer, each equipped with a corresponding heating element, and each heating element includes a conductive element. Next, a multi-point temperature monitoring module is set up to monitor the temperature of multiple heating points in real time and output multiple temperature monitoring data. Then, the multiple temperature monitoring data are input into a constant temperature equilibrium control model. Based on the constant temperature equilibrium control model, temperature deviations at each heating point are identified, determining abnormal heating points and their neighboring heating points. Further, the current real-time heating control parameters for abnormal and neighboring heating points are obtained, including heating power, heating duration, and temperature deviation value. Finally, feedback adjustment is performed based on the real-time heating control parameters, outputting adjusted heating control parameters to coordinate temperature control of abnormal and neighboring heating points. This solves the technical problems of uneven heating and inaccurate temperature control in existing technologies, achieving the technical effects of improving the heating uniformity of the graphene layer and realizing precise multi-point constant temperature control.

[0052] Example 2, based on the same inventive concept as the multi-point isotropic heating control method for a graphene layer in the foregoing examples, such as... Figure 2 As shown, this application provides a multi-point isotropic heating control system for graphene layers, wherein the system includes:

[0053] Heating point determination component 11: determines multiple heating points distributed on the graphene layer, wherein each heating point is equipped with a corresponding heating element, and each heating element includes a conductive element; Temperature monitoring component 12: sets up a multi-point temperature monitoring module, performs real-time temperature monitoring on the multiple heating points according to the multi-point temperature monitoring module, and outputs multiple temperature monitoring data; Temperature deviation identification component 13: inputs the multiple temperature monitoring data into the constant temperature equilibrium control model, performs temperature deviation identification on each heating point according to the constant temperature equilibrium control model, determines abnormal heating points, and the adjacent heating points of the abnormal heating points; Parameter acquisition component 14: acquires the current real-time heating control parameters of the abnormal heating points and the adjacent heating points, including heating power, heating time, and temperature deviation value; Control component 15: performs feedback adjustment according to the real-time heating control parameters, outputs adjusted heating control parameters, and uses the adjusted heating control parameters to perform temperature coordinated control on the abnormal heating points and the adjacent heating points.

[0054] Furthermore, the control component 15 is used to perform the following methods:

[0055] Obtain heating control parameter samples; test each heating point according to the heating control parameter samples; based on the multi-point temperature monitoring module, obtain heating element-temperature test dataset and conductive element-temperature test dataset; perform conductive element loss rate analysis according to the heating element-temperature test dataset and conductive element-temperature test dataset, and output the conductive loss rate; use the conductive loss rate to update and adjust the real-time heating control parameters.

[0056] Furthermore, the heating point determination component 11 is used to perform the following method:

[0057] The distribution locations of multiple heating points on the graphene layer are determined and output. The positional characteristics of the multiple distribution locations are identified, including the distance between the locations and the heating part affected by the location. The multiple heating points are divided into regions according to the positional characteristics, and multiple heating regions are output. The heating points in each heating region are heating points that are less than a preset distance away and belong to the same heating part. The constant temperature equalization control model is used to perform constant temperature equalization control on the multiple heating regions.

[0058] Furthermore, the heating point determination component 11 is used to perform the following method:

[0059] Based on the multiple heating regions, multiple temperature comparison samples are generated; the initialization network is trained using the multiple temperature comparison samples and label information indicating abnormal temperature deviations to obtain multiple local isothermal equilibrium control models, wherein the multiple local isothermal equilibrium control models correspond to the multiple heating regions respectively; the multiple local isothermal equilibrium control models are integrated for learning to obtain a global isothermal equilibrium control model; the model parameters of the multiple local isothermal equilibrium control models are updated based on the model parameters of the global isothermal equilibrium control model to obtain updated multiple local isothermal equilibrium control models.

[0060] Furthermore, the heating point determination component 11 is used to perform the following method:

[0061] After outputting multiple heating zones, the temperature sensitivity coefficient corresponding to each heating part in the multiple heating zones is recorded, and multiple temperature sensitivity coefficients are output. Based on the multiple temperature sensitivity coefficients, conductive elements with different heat conduction performance are configured on the heating element of each zone. The indicators for calculating heat conduction performance include conductive element density, heat conduction rate, and heat capacity.

[0062] Furthermore, the heating point determination component 11 is used to perform the following method:

[0063] Record the flexibility requirement of each heating part in the multiple heating regions and output multiple flexibility requirements; based on the multiple flexibility requirements, configure conductive elements with different flexibility indices on the heating element in each region, wherein the indices for calculating the flexibility indices include the hardness and thickness of the conductive elements.

[0064] Furthermore, the temperature deviation recognition component 13 is used to perform the following method:

[0065] Identify abnormal heating points, wherein the abnormal heating points are heating points whose temperature deviation is greater than a preset deviation; based on the abnormal heating points, obtain neighboring heating points within a preset radius; filter the neighboring heating points within the preset radius that belong to the same heating area and output them.

[0066] Furthermore, the control component 15 is used to perform the following methods:

[0067] The temperature deviation of the abnormal heating point and the temperature deviation of the adjacent heating point are obtained; the temperature deviation weight of each heating point is determined based on the temperature deviation of the abnormal heating point and the temperature deviation of the adjacent heating point; the collaborative weight of each heating point is calculated based on the temperature deviation weight of each heating point; the real-time heating control parameters are adjusted according to the collaborative weight, and the adjusted heating control parameters are output.

[0068] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0069] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0070] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A multi-point constant temperature heating control method for a graphene layer, characterized in that: The method comprises: Determine a plurality of heating points distributed on the graphene layer, wherein each heating point is provided with a corresponding heating element, and each heating element includes a conductive element; Setting a multi-point temperature monitoring module, performing real-time temperature monitoring on the multiple heating points according to the multi-point temperature monitoring module, and outputting multiple temperature monitoring data; Inputting the plurality of temperature monitoring data into a constant temperature balanced control model, identifying temperature deviations of various heating points according to the constant temperature balanced control model, and determining abnormal heating points and heating points adjacent to the abnormal heating points; Acquire current real-time heating control parameters of the abnormal heating point and the adjacent heating point, including heating power, heating time and temperature deviation value; Feedback adjustment is performed according to the real-time heating control parameter, and the adjusted heating control parameter is output, and the temperature of the abnormal heating and the adjacent heating point is coordinated controlled by the adjusted heating control parameter.

2. A multi-point constant temperature heating control method for a graphene layer as claimed in claim 1, characterized in that: The method comprises: Obtaining heating control parameter samples; Testing each heating point according to the heating control parameter sample, and acquiring a heating element-temperature test data set and a conductive element-temperature test data set based on the multi-point temperature monitoring module; Performing a conductive component loss rate analysis based on the heating component-temperature test data set and the conductive component-temperature test data set, and outputting a conductive component loss rate; The real-time heating control parameter is feedback-updated and adjusted based on the conduction loss rate, so as to update and adjust the heating control parameter.

3. A multi-point constant temperature heating control method for a graphene layer as claimed in claim 1, characterized in that: After determining a plurality of heating points distributed on the graphene layer, the method further comprises: Determine the distribution positions of multiple heating points on the graphene layer, and output the multiple distribution positions; Identifying positional features of the plurality of distributed positions, the positional features including distances between the positions and heating locations acted upon by the positions; Divide the plurality of heating points into regions according to the position features, and output a plurality of heating regions, wherein the heating points in each heating region are heating points that are less than a preset distance and belong to the same heating part; The constant temperature balanced control model is used to perform constant temperature balanced control on the multiple heating areas.

4. A multi-point constant temperature heating control method for a graphene layer as claimed in claim 3, characterized in that: The constant temperature balance control model is used to perform constant temperature balance control on the multiple heating areas, and the method includes: generating a plurality of temperature comparison samples according to the plurality of heating areas; The initialization network is trained respectively with the multiple temperature comparison samples and the label information indicating the temperature deviation abnormality to obtain multiple local constant temperature balanced control models, wherein the multiple local constant temperature balanced control models correspond to the multiple heating areas respectively; Performing integrated learning on the multiple local constant temperature balanced control models to obtain a global constant temperature balanced control model; The model parameters of the multiple local constant temperature balanced control models are updated according to the model parameters of the global constant temperature balanced control model to obtain the updated multiple local constant temperature balanced control models.

5. A multi-point constant temperature heating control method for a graphene layer as claimed in claim 1, characterized in that: Each heating element includes a conductive element, including: After outputting the multiple heating areas, recording the temperature sensitivity coefficient corresponding to each heating position in the multiple heating areas, and outputting the multiple temperature sensitivity coefficients; According to the multiple temperature sensitivity coefficients, conductive elements with different heat conduction performances are configured on the heating element of each region, wherein the indexes for calculating the heat conduction performance include conductive element density, heat conduction rate and heat capacity.

6. A multi-point constant temperature heating control method for a graphene layer as claimed in claim 5, characterized in that: After configuring a conductive element with different heat conduction performance on the heating element of each region according to the multiple temperature sensitivity coefficients, the method further includes: Recording the flexibility requirement of each heating position in the plurality of heating areas, and outputting a plurality of flexibility requirements; According to the multiple flexibility requirements, conductive members with different flexibility indexes are configured on the heating member of each area, wherein the indexes for calculating the flexibility index include the hardness of the conductive member and the thickness of the conductive member.

7. A multi-point constant temperature heating control method for a graphene layer as claimed in claim 3, characterized in that: Determining an abnormal heating point and a heating point adjacent to the abnormal heating point, the method comprising: Determining an abnormal heating point, wherein the abnormal heating point is a heating point whose temperature deviation is greater than a preset deviation; According to the abnormal heating point, obtaining adjacent heating points within a preset radius; Among the adjacent heating points within the preset radius, adjacent heating points belonging to the same heating area are screened and outputted.

8. A multi-point constant temperature heating control method for a graphene layer as claimed in claim 1, characterized in that: Feedback adjustment is performed according to the real-time heating control parameter, and the heating control parameter is output and adjusted, and the method includes: Acquiring the temperature deviation of the abnormal heating point and the temperature deviation of the adjacent heating point; Determining a temperature deviation weight of each heating point according to the temperature deviation of the abnormal heating point and the temperature deviation of the adjacent heating point; Calculating the synergy weight of each heating point based on the temperature deviation weight of each heating point; Feedback adjustment is performed on the real-time heating control parameter according to the collaborative weight, and the adjusted heating control parameter is output.

9. A multi-point constant temperature heating control system for a graphene layer, characterized in that: A method for controlling multi-point constant temperature heating of a graphene layer according to any one of claims 1 to 8, the system comprising: A heating point determination component: determines a plurality of heating points distributed on the graphene layer, wherein each heating point is provided with a corresponding heating element, and each heating element includes a conductive element; Temperature monitoring component: a multi-point temperature monitoring module is provided, and the temperature of the multiple heating points is monitored in real time according to the multi-point temperature monitoring module, and multiple temperature monitoring data are output; Temperature deviation identification component: input the plurality of temperature monitoring data into the constant temperature balance control model, identify the temperature deviation of each heating point according to the constant temperature balance control model, determine the abnormal heating point, and the heating points adjacent to the abnormal heating point; Parameter acquisition component: acquiring the current real-time heating control parameters of the abnormal heating point and the adjacent heating point, including heating power, heating time and temperature deviation value; Control component: Perform feedback adjustment according to the real-time heating control parameter, output the adjusted heating control parameter, and use the adjusted heating control parameter to perform temperature coordinated control on the abnormal heating and the adjacent heating point.

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