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

Abstract

The invention discloses a multi-point constant-temperature heating control method and system for a graphene layer, and relates to the technical field of intelligent control. The method comprises the following steps: determining a plurality of heating points distributed on a graphene layer; performing real-time temperature monitoring on the plurality of heating points, and outputting a plurality of temperature monitoring data; inputting the plurality of temperature monitoring data into a constant-temperature balance control model, performing temperature deviation identification on each heating point according to the constant-temperature balance control model, and determining an abnormal heating point and a heating point adjacent to the abnormal heating point; acquiring current real-time heating control parameters of the abnormal heating point and the adjacent heating point; and feedback adjustment is carried out according to the real-time heating control parameters, and the adjusted heating control parameters are output, so that temperature cooperative control is carried out on abnormal heating and adjacent heating points through the adjusted heating control parameters. The technical problems of non-uniform heating and inaccurate temperature control of the graphene layer in the prior art are solved, and the technical effects of improving the heating uniformity of the graphene layer and realizing multi-point constant-temperature accurate control are achieved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to a multi-point constant temperature heating control method and system for a graphene layer. Background Art

[0002] With the rapid development of science and technology, graphene, as an emerging material, has shown great application potential in many fields such as heating, sensing, and energy storage due to its excellent electrical and thermal conductivity and extremely high mechanical strength. Especially in the field of heating, graphene layers are widely used in intelligent temperature control systems, smart homes, medical equipment, and industrial heating due to their ultra-thin, efficient, and uniform heating characteristics. However, in practical applications, how to ensure the uniformity of heating of the graphene layer and the precise control of temperature has become a key technical problem that restricts its further promotion and application. Traditional heating control methods often use temperature monitoring and control at a single point or a few points, which makes it difficult to fully reflect the temperature distribution on the graphene layer, resulting in uneven heating, large temperature fluctuations, and other problems. In addition, due to the particularity of graphene materials, its physical properties such as heat conduction and heat radiation during the heating process also put forward higher requirements for temperature control. Summary of the invention

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

[0004] In view of the above problems, the present application provides a multi-point constant temperature heating control method and system for a graphene layer.

[0005] In a first aspect of the present application, a multi-point constant temperature heating control method for a graphene layer is provided, the method comprising: Determine multiple 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; set a multi-point temperature monitoring module, perform real-time temperature monitoring of the multiple heating points according to the multi-point temperature monitoring module, and output multiple temperature monitoring data; input the multiple temperature monitoring data into a constant temperature equilibrium control model, identify temperature deviations of each heating point according to the constant temperature equilibrium control model, determine abnormal heating points, and heating points adjacent to the abnormal heating points; obtain 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; perform feedback adjustment according to the real-time heating control parameters, output the adjusted heating control parameters, and use the adjusted heating control parameters to perform temperature coordinated control of the abnormal heating and the adjacent heating points.

[0006] A second aspect of the present application provides a multi-point constant temperature heating control system for a graphene layer, 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; a temperature monitoring component: provides a multi-point temperature monitoring module, performs real-time temperature monitoring on the plurality of heating points according to the multi-point temperature monitoring module, and outputs a plurality of temperature monitoring data; a temperature deviation identification component: inputs the plurality of temperature monitoring data into a constant temperature equilibrium control model, performs temperature deviation identification on each heating point according to the constant temperature equilibrium control model, determines an abnormal heating point, and a heating point adjacent to the abnormal heating point; a parameter acquisition component: obtains 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; a control component: performs feedback adjustment according to the real-time heating control parameters, outputs an adjusted heating control parameter, and uses the adjusted heating control parameter to perform temperature coordinated control on the abnormal heating and the adjacent heating points.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: First, multiple heating points distributed on the graphene layer are determined, wherein each heating point is provided with a corresponding heating element, and each heating element includes a conducting element. Next, a multi-point temperature monitoring module is set, and multiple heating points are monitored in real time according to the multi-point temperature monitoring module, and multiple temperature monitoring data are output. Then, multiple temperature monitoring data are input into a constant temperature equilibrium control model, and temperature deviations of each heating point are identified according to the constant temperature equilibrium control model, and abnormal heating points and adjacent heating points of the abnormal heating points are determined. Further, the current real-time heating control parameters of the abnormal heating points and adjacent heating points are obtained, including heating power, heating time and temperature deviation value. Finally, feedback adjustment is performed according to the real-time heating control parameters, and the heating control parameters are output to adjust the heating control parameters to coordinate the temperature of abnormal heating and adjacent heating points. The technical problems of uneven heating of the graphene layer and inaccurate temperature control in the prior art are solved, and the technical effects of improving the heating uniformity of the graphene layer and realizing multi-point constant temperature precision control are achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in 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.

[0009] Figure 1A schematic flow chart of a multi-point constant temperature heating control method for a graphene layer provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a multi-point constant temperature heating control system for a graphene layer provided in an embodiment of the present application.

[0010] Description of the reference numerals: heating point determination component 11 , temperature monitoring component 12 , temperature deviation identification component 13 , parameter acquisition component 14 , control component 15 . DETAILED DESCRIPTION

[0011] The present application solves the technical problems of uneven heating of the graphene layer and inaccurate temperature control in the prior art by providing a multi-point constant temperature heating control method and system for the graphene layer.

[0012] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0013] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. 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 explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0014] Embodiment 1, as Figure 1 As shown, the present application provides a multi-point constant temperature heating control method for a graphene layer, wherein the method comprises: A plurality of heating points distributed on the graphene layer are determined, wherein a corresponding heating element is arranged on each heating point, and each heating element includes a conductive element.

[0015] Multiple heating points are identified and determined on the graphene layer, each heating point is provided with a corresponding heating element, and each heating element is equipped with a conductive element, which is used to control the heating element to maintain a constant temperature state. It not only has high thermal conductivity efficiency, but also can reduce the rate of temperature change, thereby maintaining a constant temperature.

[0016] Furthermore, after determining the 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; identify the position characteristics of the multiple distribution positions, the position characteristics include the distance between the positions and the heating parts of the positions; divide the multiple heating points into regions according to the position characteristics, and output multiple 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 balance control model is used to perform constant temperature balance control on the multiple heating regions.

[0017] 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 regional division. After obtaining the distribution position of each heating point, it is necessary to identify the characteristic information of these positions. The position characteristics include the distance between the positions and the heating part of the position. The distance between the positions refers to the physical distance between the heating points. By measuring the distance between the positions, their distribution density on the graphene layer can be analyzed. The heating part of the position refers to the specific heating area where the heating point is located, that is, the heating part acted by the heating pad. According to the position characteristics, the heating points are divided into regions according to the following rules: when the distance between the heating points is less than the preset distance threshold and belongs to the same heating part, these heating points are classified as one heating area, and then multiple heating areas are obtained, each of which contains heating points that meet the preset distance and heating part conditions, so as to facilitate subsequent temperature coordinated control. After completing the zone division of the heating points, the constant temperature balance control model will perform constant temperature control on each heating area. The constant temperature balance control model will monitor and adjust the temperature in each area in real time to ensure that the heating points in each area are maintained within the set temperature range to prevent overheating or temperature deviation problems.

[0018] Furthermore, the constant temperature balanced control model is used to perform constant temperature balanced control on the multiple heating areas, and the method includes: According to the multiple heating areas, multiple temperature comparison samples are generated; the initialization network is trained respectively with the multiple temperature comparison samples and label information indicating abnormal temperature deviation 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; the multiple local constant temperature balanced control models are integrated and learned 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 multiple updated local constant temperature balanced control models.

[0019] Specifically, based on the real-time temperature data of multiple heating areas, multiple temperature comparison samples are generated for analyzing the temperature difference between areas, each sample includes the temperature value of the current area and its temperature comparison information with the adjacent areas; using the generated temperature comparison samples and label information indicating abnormal temperature deviation, initial local constant temperature balance control models are established for multiple heating areas respectively, and each local model learns the temperature characteristics of its corresponding heating area and the response law of abnormal deviation through independent training; multiple local constant temperature balance control models are integrated and learned, and a global constant temperature balance control model is trained by combining the characteristics of all local models. The integrated learning optimizes the global temperature balance control strategy by comprehensively analyzing the heating characteristics of multiple areas; using the optimization parameters of the global constant temperature balance control model, the parameters of each local model are updated, and the updated local model can take into account both local heating characteristics and global balance requirements, thereby improving the coordination and consistency between heating areas; the updated local constant temperature balance control model is combined with the global model to ensure that the temperature control of multiple heating areas can adapt to local needs and meet the global balance control goals.

[0020] Furthermore, after outputting the multiple heating areas, the temperature sensitivity coefficient corresponding to each heating position in the multiple heating areas is recorded, and multiple temperature sensitivity coefficients are output; based on the multiple temperature sensitivity coefficients, conductive elements with different thermal conductivity performances are configured on the heating element of each area, wherein the indicators for calculating the thermal conductivity performance include conductive element density, thermal conduction rate, and heat capacity.

[0021] After the division of multiple heating areas is completed, the temperature response characteristics of each heating part are monitored and its temperature sensitivity coefficient is recorded. The temperature sensitivity coefficient reflects the temperature response degree of the heating part to the heat input. The higher the value, the more sensitive the response to heat changes. Optionally, through experiments or simulations, the temperature change data of each heating part under different heating conditions are collected. Based on the collected data, the temperature change data is statistically analyzed to extract key indicators reflecting sensitivity, and the temperature sensitivity coefficient of each heating part is calculated based on the expert team.

[0022] According to the temperature sensitivity coefficient of each heating area, select conductive parts with different thermal conductivity, which can be metal sheets, thermal conductive glue, heat pipes, etc. In order to accurately match the needs of the heating area, calculate the thermal conductivity of the conductive parts, including the density of the conductive parts (mass per unit volume), the thermal conductivity rate (the rate at which heat passes through a unit area per unit time), and the thermal capacity (the ability of the material to absorb or release heat); according to the temperature sensitivity coefficient of the heating area and the calculation results of the thermal conductivity performance, configure the optimal conductive parts on the heating parts of each area. For example, for a heating area with a higher temperature sensitivity coefficient, you can choose a conductive part with a high thermal conductivity rate and low thermal capacity to quickly respond to temperature changes and reduce energy loss.

[0023] Furthermore, 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: The flexibility requirement of each heating part in the multiple heating areas is recorded, and multiple flexibility requirements are output; according to the multiple flexibility requirements, conductive parts with different flexibility indexes are configured on the heating parts of each area, wherein the indicators for calculating the flexibility index include conductive part hardness and conductive part thickness.

[0024] After completing the configuration of the thermal conductivity performance of the conductive part, monitor the flexibility requirement of each heating part. The flexibility requirement reflects the requirements of the heating part in adapting to deformation, contact area change or pressure distribution uniformity. Optionally, through experiments or simulations, collect the deformation data of each heating part under different external forces, and perform statistical analysis on the deformation data based on the collected data to extract key indicators reflecting the flexibility requirements, and calculate the flexibility requirement of each heating part based on the expert team. According to the flexibility requirement of each heating area, select conductive parts with different flexibility indicators. These conductive parts need to meet certain flexibility requirements while maintaining good thermal conductivity. In order to accurately match the requirements of the heating area, calculate the flexibility indicators of the conductive parts, including the hardness of the conductive parts (the ability of the material to resist deformation) and the thickness of the conductive parts (the physical size of the material); according to the flexibility requirement of the heating area and the calculation results of the flexibility indicators, configure the optimal conductive parts on the heating parts of each area. For example, for heating areas with higher flexibility requirements, conductive parts with lower hardness and appropriate thickness can be selected to maintain good fit and deformation ability.

[0025] A multi-point temperature monitoring module is provided, and real-time temperature monitoring is performed on the multiple heating points according to the multi-point temperature monitoring module to output multiple temperature monitoring data.

[0026] Temperature monitoring sensors are arranged near multiple heating points of the graphene layer, each sensor corresponds to a heating point, and these sensors can collect local temperature data in real time for subsequent temperature analysis and control. According to the distribution location and heating requirements of the heating points, the temperature monitoring sensors are reasonably arranged to ensure that the temperature changes of each heating point can be accurately monitored; all temperature monitoring sensors are connected to the multi-point temperature monitoring module to form a data acquisition network; the multi-point temperature monitoring module collects and monitors the temperature of each heating point in real time; the temperature data of multiple heating points collected in real time are recorded and output to obtain multiple temperature monitoring data.

[0027] The multiple temperature monitoring data are input into a constant temperature balanced control model, and temperature deviation of each heating point is identified according to the constant temperature balanced control model to determine abnormal heating points and heating points adjacent to the abnormal heating points.

[0028] The temperature data of multiple heating points collected by the real-time temperature monitoring module are input into the constant temperature balance control model. The constant temperature balance control model calculates the temperature deviation degree of each heating point according to the preset temperature range and threshold value. The actual temperature can be compared with the expected temperature and the deviation value can be calculated. The model identifies the heating points whose temperature deviation degree exceeds the threshold value, i.e., abnormal heating points, based on the calculated deviation value. The identified abnormal heating points are marked and their related information (such as heating point identification, temperature value, deviation degree, etc.) is recorded. The adjacent heating points of the abnormal heating points are determined according to the layout of the heating system and the distribution of the heating points.

[0029] Furthermore, the abnormal heating point and the adjacent heating points of the abnormal heating point are determined, and the method includes: Determine an abnormal heating point, wherein the abnormal heating point is a heating point whose temperature deviation is greater than a preset deviation; obtain adjacent heating points within a preset radius based on the abnormal heating point; and screen and output adjacent heating points belonging to the same heating area among the adjacent heating points within the preset radius.

[0030] Specifically, a preset deviation is set, which represents an acceptable temperature deviation range. When the temperature deviation of a certain heating point exceeds this preset value, it is regarded as 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. The calculated temperature deviation is compared with the preset deviation. If the temperature deviation of a certain heating point is greater than the preset deviation, it is determined to be an abnormal heating point. In order to determine the adjacent heating points of the abnormal heating point, a preset radius needs to be set, which defines the range of heating points adjacent to the abnormal heating point. According to the position of the abnormal heating point, all heating points within the preset radius are searched, and these heating points are regarded as the adjacent heating points of the abnormal heating point. For all adjacent heating points, according to their area identification information, the heating points belonging to the same heating area as the abnormal heating point are screened out.

[0031] The current real-time heating control parameters of the abnormal heating point and the adjacent heating point are obtained, including heating power, heating time and temperature deviation value.

[0032] Heating power is the real-time power input value provided by the heating element to the current heating point, which is used for temperature regulation; heating duration is the cumulative time from the start of heating to the current moment, which is 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 effect of temperature regulation. According to the determined abnormal heating point and adjacent heating points, real-time heating control parameters are obtained, including heating power, heating duration and temperature deviation.

[0033] 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.

[0034] Conduct an in-depth analysis of the real-time heating control parameters (including heating power, heating time, and temperature deviation) of the abnormal heating point and the adjacent heating points. Based on the analysis results of the real-time heating control parameters, formulate a feedback adjustment strategy, which may include adjusting the heating power, changing the heating time, optimizing the temperature setting value, etc., so that the temperature of the abnormal heating point and the adjacent heating point can be coordinated and controlled to reach the expected temperature range and reduce the temperature deviation. Based on the calculated adjustment heating control parameters, the temperature of the abnormal heating point and its adjacent heating points is coordinated and controlled.

[0035] Furthermore, feedback adjustment is performed according to the real-time heating control parameter, and the heating control parameter is output and adjusted. The method includes: Obtain the temperature deviation of the abnormal heating point and the temperature deviation of the adjacent heating point; determine the 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; calculate the collaborative weight of each heating point with the temperature deviation weight of each heating point; perform feedback adjustment on the real-time heating control parameter according to the collaborative weight, and output the adjusted heating control parameter.

[0036] Specifically, the temperature deviations of the abnormal heating point and the adjacent heating point are obtained; based on the temperature deviations of each heating point, a temperature deviation weight is assigned, and the weight of each heating point is calculated by comparing the temperature deviations of each heating point with the total deviations 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 the heating point; based on the temperature deviations, the collaborative weights w1 and w2 of the abnormal heating point and the adjacent heating point 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, and 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; feedback adjustment is performed on the real-time heating control parameters based on the collaborative weights, the heating power of the heating point is adjusted, and the adjusted heating control parameters of each heating point are output.

[0037] Further, the method comprises: Acquire a heating control parameter sample; test each heating point according to the heating control parameter sample, and acquire a heating component-temperature test data set and a conductive component-temperature test data set based on the multi-point temperature monitoring module; perform conductive component loss rate analysis according to the heating component-temperature test data set and the conductive component-temperature test data set, and output a conductive loss rate; feedback update and adjust the real-time heating control parameters based on the conductive loss rate, and update and adjust the heating control parameters.

[0038] Specifically, a heating control parameter sample is obtained from historical data, including different parameter values ​​such as heating power and heating time; based on the obtained heating control parameter sample, a temperature test is performed on the heating element of each heating point, and the temperature response of each heating point is measured by adjusting different heating powers and heating times. A multi-point temperature monitoring module is used to collect the temperature data of the heating element under different control parameters to generate a heating element-temperature test data set; a conductive element is used to perform a temperature test to measure the temperature response characteristics of the heating conduction. A multi-point temperature monitoring module is used to collect the temperature data of the conductive element under different control parameters to generate a conductive element-temperature test data set; based on the heating element-temperature test data The conduction loss rate can be calculated by the difference between the initial temperature of the conduction component and the temperature response of the heating component to obtain the heat loss percentage of each conduction component; the conduction loss rate is used as a feedback factor to adjust the real-time heating control parameters; according to the conduction loss rate, the parameters such as the heating power and heating time of the heating component are updated to generate new heating control parameters to compensate for the insufficient temperature caused by conduction loss; the updated and adjusted heating control parameters are output to further optimize the temperature control of the heating point and achieve temperature balance.

[0039] In summary, the embodiments of the present application have at least the following technical effects: First, multiple heating points distributed on the graphene layer are determined, wherein each heating point is provided with a corresponding heating element, and each heating element includes a conducting element. Next, a multi-point temperature monitoring module is set, and multiple heating points are monitored in real time according to the multi-point temperature monitoring module, and multiple temperature monitoring data are output. Then, multiple temperature monitoring data are input into a constant temperature equilibrium control model, and temperature deviations of each heating point are identified according to the constant temperature equilibrium control model, and abnormal heating points and adjacent heating points of the abnormal heating points are determined. Further, the current real-time heating control parameters of the abnormal heating points and adjacent heating points are obtained, including heating power, heating time and temperature deviation value. Finally, feedback adjustment is performed according to the real-time heating control parameters, and the heating control parameters are output to adjust the heating control parameters to coordinate the temperature of abnormal heating and adjacent heating points. The technical problems of uneven heating of the graphene layer and inaccurate temperature control in the prior art are solved, and the technical effects of improving the heating uniformity of the graphene layer and realizing multi-point constant temperature precision control are achieved.

[0040] Embodiment 2, based on the same inventive concept as the multi-point constant temperature heating control method of a graphene layer in the above embodiment, Figure 2 As shown, the present application provides a multi-point constant temperature heating control system for a graphene layer, wherein the system comprises: A heating point determination component 11: 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 conducting element; a temperature monitoring component 12: provides a multi-point temperature monitoring module, performs real-time temperature monitoring on the plurality of heating points according to the multi-point temperature monitoring module, and outputs a plurality of temperature monitoring data; a temperature deviation identification component 13: inputs the plurality of temperature monitoring data into a constant temperature equilibrium control model, performs temperature deviation identification on each heating point according to the constant temperature equilibrium control model, determines an abnormal heating point, and a heating point adjacent to the abnormal heating point; a parameter acquisition component 14: acquires 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; a control component 15: performs feedback adjustment according to the real-time heating control parameters, outputs an adjusted heating control parameter, and uses the adjusted heating control parameter to perform temperature coordinated control on the abnormal heating and the adjacent heating point.

[0041] Furthermore, the control component 15 is used to execute the following method: Acquire a heating control parameter sample; test each heating point according to the heating control parameter sample, and acquire a heating component-temperature test data set and a conductive component-temperature test data set based on the multi-point temperature monitoring module; perform conductive component loss rate analysis according to the heating component-temperature test data set and the conductive component-temperature test data set, and output a conductive loss rate; feedback update and adjust the real-time heating control parameters based on the conductive loss rate, and update and adjust the heating control parameters.

[0042] Furthermore, the heating point determination component 11 is used to perform the following method: Determine the distribution positions of multiple heating points on the graphene layer and output the multiple distribution positions; identify the position characteristics of the multiple distribution positions, the position characteristics include the distance between the positions and the heating parts of the positions; divide the multiple heating points into regions according to the position characteristics, and output multiple 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 balance control model is used to perform constant temperature balance control on the multiple heating regions.

[0043] Furthermore, the heating point determination component 11 is used to perform the following method: According to the multiple heating areas, multiple temperature comparison samples are generated; the initialization network is trained respectively with the multiple temperature comparison samples and label information indicating abnormal temperature deviation 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; the multiple local constant temperature balanced control models are integrated and learned 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 multiple updated local constant temperature balanced control models.

[0044] Furthermore, the heating point determination component 11 is used to perform the following method: After outputting the multiple heating areas, the temperature sensitivity coefficient corresponding to each heating position in the multiple heating areas is recorded, and the multiple temperature sensitivity coefficients are output; according to the multiple temperature sensitivity coefficients, conductive elements with different thermal conductivity performances are configured on the heating element of each area, wherein the indicators for calculating the thermal conductivity performance include conductive element density, thermal conduction rate, and heat capacity.

[0045] Furthermore, the heating point determination component 11 is used to perform the following method: The flexibility requirement of each heating part in the multiple heating areas is recorded, and multiple flexibility requirements are output; according to the multiple flexibility requirements, conductive parts with different flexibility indexes are configured on the heating parts of each area, wherein the indicators for calculating the flexibility index include conductive part hardness and conductive part thickness.

[0046] Furthermore, the temperature deviation identification component 13 is used to perform the following method: Determine an abnormal heating point, wherein the abnormal heating point is a heating point whose temperature deviation is greater than a preset deviation; obtain adjacent heating points within a preset radius based on the abnormal heating point; and screen and output adjacent heating points belonging to the same heating area among the adjacent heating points within the preset radius.

[0047] Furthermore, the control component 15 is used to execute the following method: Obtain the temperature deviation of the abnormal heating point and the temperature deviation of the adjacent heating point; determine the 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; calculate the collaborative weight of each heating point with the temperature deviation weight of each heating point; perform feedback adjustment on the real-time heating control parameter according to the collaborative weight, and output the adjusted heating control parameter.

[0048] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0049] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0050] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

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 3, characterized in that: 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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