Rheumatism immune thermotherapy device and method

Abstract

The invention provides a rheumatism immune thermotherapy device and method, and the method comprises the steps: initializing the temperature control priority of each heating module in the rheumatism immune thermotherapy device according to a target temperature, and determining a real-time temperature sequence of all heating modules during preheating; acquiring skin temperature data when a to-be-thermally-treated part of a target user is preheated, and determining stability contributions of all heating modules through the skin temperature data and the real-time temperature sequence; determining a module priority sequence of the rheumatism immune thermal therapy device according to the stability contribution, and determining dynamic thermal field distribution of the rheumatism immune thermal therapy device according to the module priority sequence and the thermal sensitivity of the to-be-thermally-treated part of the target user; and based on the dynamic thermal field distribution, controlling the rheumatism immune thermal therapy device to heat the part to be subjected to thermal therapy of the target user. According to the scheme, the temperature of the heating module in the rheumatism immune thermotherapy device can be automatically adjusted, the constant and comfortable heating temperature is ensured, and therefore the temperature control precision of the rheumatism immune thermotherapy device is improved.

Description

Technical Field

[0001] This application relates to the field of hyperthermia technology. More specifically, this application relates to a rheumatic immune hyperthermia device and method. Background Art

[0002] A rheumatic immune hyperthermia device is a device used to treat rheumatic immune diseases (such as rheumatoid arthritis, systemic lupus erythematosus, etc.). It mainly relieves inflammation, relieves pain, improves blood circulation, and enhances tissue repair by heating a part or the whole body of the human body. Common types of hyperthermia devices include: infrared hyperthermia devices, electric heating pad heaters, hot water baths or hot compresses, far-infrared hyperthermia devices, etc.

[0003] Existing rheumatic immune hyperthermia devices utilize heating control technology to act on a part or the whole body of the human body at a certain temperature through physical means, which can relieve joint pain, swelling, and stiffness. However, the heating control system in traditional rheumatic immune hyperthermia devices is relatively simple, resulting in the risk that the heating module may have unstable temperature or overheat. Especially during long-term use, temperature fluctuations may cause discomfort to users during use and even lead to low-temperature burns. Therefore, how to automatically adjust the temperature of the heating module in a rheumatic immune hyperthermia device to ensure a constant and comfortable heating temperature, thereby improving the temperature control accuracy of the rheumatic immune hyperthermia device has become a difficult problem faced by the industry. Summary of the Invention

[0004] This application provides a rheumatic immune hyperthermia device and method, which can automatically adjust the temperature of the heating module in the rheumatic immune hyperthermia device to ensure a constant and comfortable heating temperature, thereby improving the temperature control accuracy of the rheumatic immune hyperthermia device.

[0005] In a first aspect, this application provides an intelligent heating method based on priority regulation, including: Initializing the temperature control priorities of each heating module in the rheumatic immune hyperthermia device according to the target temperature for hyperthermia of the target user by the rheumatic immune hyperthermia device, and then determining the real-time temperature sequence of all heating modules when the rheumatic immune hyperthermia device preheats the part to be hyperthermia of the target user based on all the temperature control priorities; Collecting the epidermal temperature data when the part to be hyperthermia of the target user is preheated, determining the temperature adjustment factors of each heating module for the part to be hyperthermia of the target user through the epidermal temperature data and the real-time temperature sequence, and then performing fuzzy inference on all the temperature adjustment factors based on the fuzzy logic algorithm to obtain the stability contribution of all heating modules to the overall temperature of the rheumatic immune hyperthermia device; Dynamically regulate the temperature control priorities of each heating module according to the stability contributions to obtain a module priority sequence for temperature control of the rheumatic immune hyperthermia device, and then determine the dynamic thermal field distribution of the rheumatic immune hyperthermia device for the target user according to the module priority sequence and the thermal sensitivity of the target user's hyperthermia site; Control the rheumatic immune hyperthermia device to heat the target user's hyperthermia site based on the dynamic thermal field distribution.

[0006] In some embodiments, initializing the temperature control priorities of each heating module in the rheumatic immune hyperthermia device according to the target temperature for hyperthermia of the target user by the rheumatic immune hyperthermia device specifically includes: Obtain the target temperature for hyperthermia of the target user by the rheumatic immune hyperthermia device; Determine the initial temperature control states of each heating module in the rheumatic immune hyperthermia device; Determine the local temperature deviation of each heating module according to all the initial temperature control states and the target temperature; Determine the temperature control priorities of each heating module when the rheumatic immune hyperthermia device performs temperature control through all the local temperature deviations.

[0007] In some embodiments, determining the real-time temperature sequence of all heating modules when the rheumatic immune hyperthermia device preheats the target user's hyperthermia site based on all the temperature control priorities specifically includes: For each heating module in the rheumatic immune hyperthermia device, determine the initial electric power of the heating module based on the temperature control priority of the heating module; Start the heating module to preheat the target user's hyperthermia site according to the initial electric power to obtain the temperature change data of the heating module, and then obtain the temperature change data of each heating module in the rheumatic immune hyperthermia device; Determine the real-time temperature sequence of all heating modules when the rheumatic immune hyperthermia device preheats the target user's hyperthermia site through all the temperature change data.

[0008] In some embodiments, determining the temperature adjustment factor of each heating module for the target user's hyperthermia site through the epidermal temperature data and the real-time temperature sequence specifically includes: Perform temperature interval frequency domain decomposition on the epidermal temperature data to obtain the relative frequency domain density of the epidermal temperature of the target user's hyperthermia site in each temperature interval; Determine the temperature fluctuation entropy of the target user's hyperthermia site according to all the relative frequency domain densities; Determine the temperature adjustment factor of each heating module in the rheumatic immune hyperthermia device for the target user's hyperthermia site based on the temperature fluctuation entropy and the real-time temperature sequence.

[0009] In some embodiments, fuzzy inference is performed on all temperature adjustment factors based on a fuzzy logic algorithm to obtain the specific contributions of all heating modules to the overall temperature stability of the rheumatism and immunity thermotherapy device, which specifically includes: Perform fuzzy level division on all temperature adjustment factors to obtain multiple fuzzy levels; For each heating module, determine the fuzzy membership degrees of the temperature adjustment factors of the heating module at each fuzzy level; Determine the stability contribution degrees of the heating modules according to all the fuzzy membership degrees, and further obtain the stability contribution degrees of each heating module; Based on all the stability contribution degrees, determine the contributions of all heating modules to the overall temperature stability of the rheumatism and immunity thermotherapy device.

[0010] In some embodiments, the temperature control priorities of each heating module are dynamically regulated through the stability contributions to obtain the module priority sequence for temperature control of the rheumatism and immunity thermotherapy device, which specifically includes: Determine the fuzzy priorities of each heating module in the rheumatism and immunity thermotherapy device according to the stability contributions; For each heating module, adjust the temperature control priority of the heating module based on the fuzzy priority of the heating module to obtain the module priority of the heating module, and further obtain the module priority of each heating module; Determine the module priority sequence for temperature control of the rheumatism and immunity thermotherapy device through all the module priorities.

[0011] In some embodiments, according to the module priority sequence and the thermal sensitivity of the target user's thermotherapy site, determine the dynamic thermal field distribution of the rheumatism and immunity thermotherapy device for the target user, which specifically includes: Determine the thermal sensitivity of the target user's thermotherapy site; Determine the dynamic temperature control curve of the rheumatism and immunity thermotherapy device for the target user through the thermal sensitivity; According to the module priority sequence and the distances between each heating module and the target user's thermotherapy site, determine the heating intensity distribution domain when the target user undergoes thermotherapy; Based on the dynamic temperature control curve and the heating intensity distribution domain, determine the dynamic thermal field distribution of the rheumatism and immunity thermotherapy device for the target user.

[0012] In a second aspect, the present application provides a rheumatism and immunity thermotherapy device, including an intelligent heating unit, and the intelligent heating unit includes: An initialization module, configured to initialize the temperature control priorities of each heating module in the rheumatic immune hyperthermia device according to the target temperature for hyperthermia of the target user by the rheumatic immune hyperthermia device, and then determine the real-time temperature sequence of all heating modules when the rheumatic immune hyperthermia device preheats the part to be hyperthermia of the target user based on all the temperature control priorities; A dynamic regulation module, configured to collect the epidermal temperature data when preheating the part to be hyperthermia of the target user, determine the temperature adjustment factors of each heating module for the part to be hyperthermia of the target user through the epidermal temperature data and the real-time temperature sequence, and then perform fuzzy inference on all the temperature adjustment factors based on the fuzzy logic algorithm to obtain the stability contribution of all heating modules to the overall temperature of the rheumatic immune hyperthermia device; The dynamic regulation module is configured to dynamically regulate the temperature control priorities of each heating module through the stability contribution to obtain a module priority sequence for temperature control of the rheumatic immune hyperthermia device, and then determine the dynamic heat field distribution of the rheumatic immune hyperthermia device for hyperthermia of the target user according to the module priority sequence and the thermal sensitivity of the part to be hyperthermia of the target user A heating execution module, configured to control the rheumatic immune hyperthermia device to heat the part to be hyperthermia of the target user based on the dynamic heat field distribution.

[0013] In a third aspect, the present application provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to obtain the code and execute the above-mentioned intelligent heating method based on priority regulation.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned intelligent heating method based on priority regulation is implemented.

[0015] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects: In the rheumatism and immunity heat therapy device and method provided by the present application, first, the temperature control priorities of each heating module in the rheumatism and immunity heat therapy device are initialized according to the target temperature for heat therapy of the target user by the rheumatism and immunity heat therapy device. Then, based on all the temperature control priorities, the real-time temperature sequence of all heating modules when the rheumatism and immunity heat therapy device preheats the part to be heat-treated of the target user is determined; the epidermal temperature data when the part to be heat-treated of the target user is preheated is collected, and the temperature adjustment factors of each heating module for the part to be heat-treated of the target user are determined through the epidermal temperature data and the real-time temperature sequence. Then, based on the fuzzy logic algorithm, fuzzy reasoning is performed on all the temperature adjustment factors to obtain the stability contribution of all heating modules to the overall temperature of the rheumatism and immunity heat therapy device; the temperature control priorities of each heating module are dynamically regulated through the stability contribution to obtain the module priority sequence for temperature control of the rheumatism and immunity heat therapy device. Then, based on the module priority sequence and the heat sensitivity of the part to be heat-treated of the target user, the dynamic heat field distribution of the rheumatism and immunity heat therapy device for heat therapy of the target user is determined; based on the dynamic heat field distribution, the rheumatism and immunity heat therapy device is controlled to heat the part to be heat-treated of the target user.

[0016] It can be seen that this application controls the heating of the part to be thermally treated of the target user by the rheumatism and immunity thermotherapy device based on the dynamic thermal field distribution. First, determining the real-time temperature sequence can obtain the sequence describing the overall temperature change volatility of all heating modules in the rheumatism and immunity thermotherapy device during the preheating stage. The determination of the real-time temperature sequence helps to reflect the temperature change of the heating module in real time, ensuring that the system can accurately understand the heating effect of each module. Second, determining the stability contribution can obtain the contribution degree of the temperature change of all heating modules in the rheumatism and immunity thermotherapy device to the overall temperature change of all heating modules in the rheumatism and immunity thermotherapy device. The determination of the stability contribution helps to handle the uncertainty in the temperature fluctuation of the rheumatism and immunity thermotherapy device, avoid the error caused by the static model in the traditional temperature control method, and achieve smoother temperature regulation. Then, determining the module priority sequence can obtain the priority order list of each heating module in the rheumatism and immunity thermotherapy device to perform the thermotherapy task. The module with a higher priority is regulated and allocated resources first. The determination of the module priority sequence can ensure that each heating module can orderly allocate power output according to the specific needs of the target user (such as heat sensitivity, part to be thermally treated, etc.) during the thermotherapy process, avoiding overheating or insufficient heating. Finally, determining the dynamic thermal field distribution can obtain the distribution state of the heat generated by heating during the thermotherapy of the target user in time and space. The determination of the dynamic thermal field distribution ensures that parameters such as the heating intensity and heating range during the thermotherapy process can meet the physiological needs of the target user, thereby improving the thermotherapy effect and reducing the risk of side effects, avoiding discomfort when the target user uses it, and even causing low-temperature burns. In summary, based on the above solution, the temperature of the heating module in the rheumatism and immunity thermotherapy device can be automatically adjusted to ensure a constant and comfortable heating temperature, thereby improving the temperature control accuracy of the rheumatism and immunity thermotherapy device. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is an exemplary flowchart of an intelligent heating method based on priority regulation shown in some embodiments of this application; Figure 2 is an exemplary flowchart of determining the stability contribution shown in some embodiments of this application; Figure 3 is a unit structure block diagram of a rheumatism and immunity thermotherapy device shown in some embodiments of this application; Figure 4 is a structural schematic diagram of an intelligent heating unit in a rheumatism and immunity thermotherapy device shown in some embodiments of this application; Figure 5 is an internal structure diagram of a computer device for implementing an intelligent heating method based on priority regulation shown in some embodiments of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] To better understand the technical solution of this application, the technical solution of this application will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0019] Referring Figure 1 , this figure is an exemplary flowchart of an intelligent heating method based on priority regulation shown according to some embodiments of this application. The intelligent heating method 100 based on priority regulation mainly includes the following steps: In step 101, the temperature control priorities of each heating module in the rheumatic immune hyperthermia device are initialized according to the target temperature for thermotherapy of the target user by the rheumatic immune hyperthermia device. Then, based on all the temperature control priorities, the real-time temperature sequence of all heating modules when the rheumatic immune hyperthermia device preheats the part to be thermotherapied of the target user is determined.

[0020] In some embodiments, the initialization of the temperature control priorities of each heating module in the rheumatic immune hyperthermia device according to the target temperature for thermotherapy of the target user by the rheumatic immune hyperthermia device can be implemented by the following steps: Obtain the target temperature for thermotherapy of the target user by the rheumatic immune hyperthermia device; Determine the initial temperature control states of each heating module in the rheumatic immune hyperthermia device; Determine the local temperature deviation of each heating module according to all the initial temperature control states and the target temperature; Determine the temperature control priorities of each heating module when the rheumatic immune hyperthermia device performs temperature control through all the local temperature deviations.

[0021] It should be noted that in this application, the temperature control priority indicates the priority degree of heat distribution of each heating module when the rheumatic immune hyperthermia device performs temperature control. The higher this temperature control priority is, the more the heating module will be preferentially allocated during the heat distribution process when the rheumatic immune hyperthermia device performs temperature control.

[0022] Specifically, obtaining the target temperature for thermotherapy of the target user by the rheumatic immune hyperthermia device can be implemented in the following manner, that is: the target temperature input by the user can be received through the user interface unit (such as: touch screen) in the rheumatic immune hyperthermia device and transmitted to the intelligent heating unit; wherein, the target temperature refers to the temperature that needs to be quickly reached and maintained for a long time when performing thermotherapy on the target user; the user interface unit refers to the collection of hardware and software in the rheumatic immune hyperthermia device for realizing the human-computer interaction function; the intelligent heating unit refers to the functional unit in the rheumatic immune hyperthermia device for realizing temperature control, and can be a collection of hardware and software when specifically implemented.

[0023] In specific implementation, the initial temperature control state of each heating module in the rheumatic immune hyperthermia device can be determined in the following manner: that is, the current temperature collected by the temperature sensor in each heating module of the rheumatic immune hyperthermia device before the start of temperature control can be used as the initial temperature control state of the heating module; wherein, the initial temperature control state refers to the thermal state of the heating module in the rheumatic immune hyperthermia device before the intelligent heating unit starts to execute temperature control; the heating module refers to the core component in the rheumatic immune hyperthermia device used to generate and regulate heat to meet the hyperthermia requirements. Each heating module is equipped with an independent temperature sensor (such as: thermocouple, thermistor or infrared temperature detector, etc.) and a heating element (such as: electric heating film, electric heating wire or PTC heater), and can work independently or achieve precise temperature distribution and dynamic adjustment through collaborative control. And each heating module has a unique number, such as: No. 0, No. 1, No. 2 and No. 3.

[0024] In specific implementation, the local temperature deviation of each heating module when the rheumatic immune hyperthermia device performs temperature control can be determined based on all the initial temperature control states and the target temperature in the following manner: that is, the difference between the initial temperature control state of each heating module and the target temperature can be used as the local temperature deviation of the heating module, and thus the local temperature deviations of each heating module can be obtained; wherein, the local temperature deviation refers to the difference between the current temperature of the heating module in the rheumatic immune hyperthermia device and the target temperature, and this local temperature deviation reflects the temperature adjustment range required for each module and is used to initialize the temperature control priority of each module.

[0025] In specific implementation, the temperature control priority of each heating module when the rheumatic immune hyperthermia device performs temperature control can be determined through all the local temperature deviations in the following manner: that is, the sum of the local temperature deviations of all heating modules can be calculated first as the local temperature difference sum, and then the quotient of the local temperature deviation of each heating module in the rheumatic immune hyperthermia device and the local temperature difference sum can be used as the temperature control priority of the heating module. Thus, the temperature control priorities of each heating module when the rheumatic immune hyperthermia device performs temperature control can be obtained.

[0026] In some embodiments, the real-time temperature sequence of all heating modules when the rheumatic immune hyperthermia device preheats the hyperthermia part of the target user can be determined based on all the temperature control priorities by the following steps: For each heating module in the rheumatic immune hyperthermia device, determine the initial electric power of the heating module based on the temperature control priority of the heating module; Start the heating module to preheat the hyperthermia part of the target user according to the initial electric power, obtain the temperature change data of the heating module, and further obtain the temperature change data of each heating module in the rheumatic immune hyperthermia device; Determine the real-time temperature sequence of all heating modules of the rheumatic immune heat therapy device for the heat therapy part of the target user during preheating through all temperature change data.

[0027] It should be noted that in this application, the real-time temperature sequence refers to the sequence that describes the overall temperature volatility of all heating modules in the rheumatic immune heat therapy device during the preheating stage; specifically, when implemented, the initial electric power of the heating module can be determined based on the temperature control priority of the heating module in the following way, that is: first obtain the total power limit of all heating modules in the rheumatic immune heat therapy device, and calculate the sum of the temperature control priorities of all heating modules as the priority sum, and then multiply the ratio of the temperature control priority of the heating module to the priority sum by the total power limit of all heating modules, and the obtained value is used as the initial electric power of the heating module. Among them, the initial electric power refers to the starting power output value of the heating module in the rheumatic immune heat therapy device during the preheating process, and this initial electric power is used to start the heating module to provide necessary heat for the system to achieve temperature rise and rapidly increase the temperature of the part to be heat-treated.

[0028] In addition, it should be noted that in this application, the temperature change data is a set composed of the temperature values fed back by the heating module for the temperature control of the rheumatic immune heat therapy device during the preheating stage. This temperature change data reflects the actual working state of the heating module and can be used to evaluate the heating performance of the heating module; specifically, when implemented, starting from the initial electric power, the heating module is started to preheat the part to be heat-treated of the target user, and the temperature change data of the heating module can be obtained in the following way, that is: first start the heating module, and use the existing pulse width modulation technology to precisely control the heating power of the heating module, and then collect the real-time temperature of the heating module every preset acquisition time interval through the temperature sensor in the heating module, and use the set of all collected temperature values as the temperature change data of the heating module. Among them, the acquisition time interval can be preset according to the actual situation. In this application, the acquisition time interval is preset to five seconds, and in other embodiments, it can also be preset to other times, which is not specifically limited here.

[0029] In specific implementation, the real-time temperature sequence of all heating modules when the rheumatism immune heat therapy device preheats the target user's heat therapy site can be obtained through all temperature change data in the following way: for each heating module, first denoise the temperature change data of the heating module through an existing denoising method (for example: low-pass filter), then use an existing statistical distribution analysis method (for example: histogram estimation analysis method) to divide the denoised temperature change data into multiple feedback temperature intervals, take the ratio of the number of temperature values in each feedback temperature interval to the total number of temperature values in the temperature change data as the frequency domain density of this feedback temperature interval, and then take the product of the frequency domain density and the logarithm of the frequency domain density with base 10 as the frequency domain logarithm product of this feedback temperature interval, thus obtaining the frequency domain logarithm product of each feedback temperature interval. Take the negative value of the sum of all frequency domain logarithm products as the temperature change entropy of the heating module. Through the above method, the temperature change entropy of each heating module can be obtained, and then the sequence formed by arranging the temperature change entropies of all heating modules in ascending order according to the heating module numbers is used as the real-time temperature sequence of all heating modules when the rheumatism immune heat therapy device preheats the target user's heat therapy site. Among them, the number of feedback temperature intervals can be set according to the actual situation. In this application, it is set to 10. In other embodiments, it can also be set to other numbers, which are not specifically limited here.

[0030] In step 102, collect the epidermal temperature data when preheating the target user's heat therapy site, determine the temperature adjustment factors of each heating module for the target user's heat therapy site through the epidermal temperature data and the real-time temperature sequence, and then perform fuzzy inference on all temperature adjustment factors based on the fuzzy logic algorithm to obtain the stability contribution of all heating modules to the overall temperature of the rheumatism immune heat therapy device.

[0031] It should be noted that in this application, the epidermal temperature data refers to the data set composed of the epidermal temperatures on the skin surface of the target user's heat therapy site. In specific implementation, the epidermal temperature data when preheating the target user's heat therapy site can be obtained in the following way: when the rheumatism immune heat therapy device collects the real-time temperature of the heating module every other preset collection time interval, synchronously use an infrared temperature sensor (for example: thermal imaging sensor) to collect the epidermal temperature on the skin surface of the target user's heat therapy site, and take the set of all collected epidermal temperatures as the epidermal temperature data when preheating the target user's heat therapy site.

[0032] In some embodiments, the steps for determining the temperature adjustment factors of each heating module for the target user's heat therapy site through the epidermal temperature data and the real-time temperature sequence can be implemented as follows: Perform temperature interval frequency domain decomposition on the epidermal temperature data to obtain the relative frequency domain density of the epidermal temperature of the target user's heat therapy site in each temperature interval; Determine the temperature fluctuation entropy of the target user's heat therapy site based on all the relative frequency domain densities; Based on the temperature fluctuation entropy and the real-time temperature sequence, determine the temperature adjustment factors of each heating module in the rheumatic immune heat therapy device for the target user's heat therapy site.

[0033] It should be noted that in this application, the temperature adjustment factor is a quantitative index that measures the influence degree of the temperature fluctuation characteristics of the heating module in the rheumatic immune heat therapy device on the temperature change of the target user's heat therapy site, and is an important parameter for evaluating the temperature control performance of the heat therapy device.

[0034] In addition, it should be noted that in this application, the relative frequency domain density refers to the contribution ratio of the changes of different frequency components in the time series to the overall change of the time series. This relative frequency domain density helps to analyze the dominant frequency of temperature change and its influence degree on the overall temperature fluctuation when analyzing the epidermal temperature fluctuation of the target user's heat therapy site; in specific implementation, performing temperature interval frequency domain decomposition on the epidermal temperature data to obtain the relative frequency domain density of the epidermal temperature of the target user's heat therapy site in each temperature interval can be achieved in the following way, that is: an existing statistical distribution analysis method (such as: histogram estimation analysis method) can be used to divide the epidermal temperature data into multiple temperature intervals. For each temperature interval, the ratio of the number of epidermal temperatures in the temperature interval to the total number of epidermal temperatures in the epidermal temperature data can be used as the relative frequency domain density of the epidermal temperature in the temperature interval. Through the above method, the relative frequency domain density of the epidermal temperature of the target user's heat therapy site in each temperature interval can be obtained. Among them, the number of temperature intervals can be set according to the actual situation. In this application, it is set to 10. In other embodiments, it can also be set to other numbers, which are not specifically limited here.

[0035] In specific implementation, determining the temperature fluctuation entropy of the target user's heat therapy site based on all the relative frequency domain densities can be achieved in the following way, that is: for each relative frequency domain density, calculate the product of the relative frequency domain density and the logarithm of the relative frequency domain density with base 10, and the obtained product is used as the logarithmic product of the relative frequency domain density. If the relative frequency domain density is zero, the logarithmic product is zero. Thus, the logarithmic product of each relative frequency domain density is obtained, and then the negative value of the sum of all logarithmic products is used as the temperature fluctuation entropy of the target user's heat therapy site; among them, the temperature fluctuation entropy is an index that measures the dynamic change regularity of the epidermal temperature of the target user's heat therapy site in the time dimension, and it helps to analyze the temperature stability and regulation effect during the heat therapy process.

[0036] In specific implementation, determining the temperature adjustment factors of each heating module in the rheumatic immune heat therapy device for the heat therapy part of the target user based on the temperature fluctuation entropy and the real-time temperature sequence can be achieved by the following method, that is: for the temperature change entropy of each temperature change data in the real-time temperature sequence, multiply the sum of the temperature change entropy and the temperature fluctuation entropy by the temperature control priority of the heating module corresponding to the temperature change data, and take the obtained product as the temperature adjustment factor of the heating module. Through the above method, the temperature adjustment factors of each heating module in the rheumatic immune heat therapy device for the heat therapy part of the target user can be obtained.

[0037] In some embodiments, referring to Figure 2 , this figure is an exemplary flowchart for determining the stability contribution shown in some embodiments of the present application. In the present application, fuzzy inference is performed on all the temperature adjustment factors based on the fuzzy logic algorithm, and the stability contribution of all heating modules to the overall temperature of the rheumatic immune heat therapy device can be achieved by the following steps: First, in step 1021, perform fuzzy grade division on all the temperature adjustment factors to obtain multiple fuzzy grades; Secondly, in step 1022, for each heating module, determine the fuzzy membership degree of the temperature adjustment factor of the heating module at each fuzzy grade; Then, in step 1023, determine the stable contribution degree of the heating module according to all the fuzzy membership degrees, and further obtain the stable contribution degree of each heating module; Finally, in step 1024, determine the stability contribution of all heating modules to the overall temperature of the rheumatic immune heat therapy device based on all the stable contribution degrees.

[0038] It should be noted that in the present application, the fuzzy grade represents a quantitative index of the fluctuation range of the temperature adjustment factor to different extents; in specific implementation, performing fuzzy grade division on all the temperature adjustment factors to obtain multiple fuzzy grades can be achieved by the following method, that is: first, use the existing normalization method (for example: min-max normalization) to normalize all the temperature adjustment factors, so that all the temperature adjustment factors are transformed into the range of [0, 1], and then use the existing membership function (for example: triangular membership function) to divide all the temperature adjustment factors into multiple fuzzy grades, thereby obtaining multiple fuzzy grades. For example: the fuzzy grade of the temperature adjustment factor in the range of [0, 0.3, 0.5] can be divided into "small fluctuation", the fuzzy grade of the temperature adjustment factor in the range of [0.3, 0.5, 0.7] can be divided into "medium fluctuation", and the fuzzy grade of the temperature adjustment factor in the range of [0.5, 0.7, 1] can be divided into "large fluctuation".

[0039] In addition, it should be noted that in this application, the fuzzy membership degree is a parameter used to describe the degree of belonging of the temperature adjustment factor in the fuzzy level. When specifically implemented, the fuzzy membership degrees of the temperature adjustment factors of the heating module at each fuzzy level can be determined in the following manner, that is, the fuzzy membership degrees of the temperature adjustment factors of the heating module at each fuzzy level can be calculated according to the formula corresponding to the membership function in the above steps.

[0040] When specifically implemented, the stable contribution degree of the heating module can be determined according to all the fuzzy membership degrees in the following manner, that is, the average value of the fuzzy membership degrees of the heating module at all fuzzy levels can be used as the stable contribution degree of the heating module. Among them, the stable contribution degree represents the contribution degree of the temperature change error of the heating module in the overall temperature change error of all heating modules in the rheumatic immune heat therapy device.

[0041] It should be noted that in this application, the stability contribution refers to the contribution degree of the temperature changes of all heating modules in the rheumatic immune heat therapy device to the overall temperature change of all heating modules in the rheumatic immune heat therapy device. When specifically implemented, the stability contribution of all heating modules to the overall temperature of the rheumatic immune heat therapy device can be determined based on all the stable contribution degrees in the following manner, that is, the sequence formed by arranging the stable contribution degrees of all heating modules in ascending order according to the heating module numbers can be used as the stability contribution of all heating modules to the overall temperature of the rheumatic immune heat therapy device.

[0042] In step 103, the temperature control priorities of each heating module are dynamically regulated through the stability contribution to obtain a module priority sequence for temperature control of the rheumatic immune heat therapy device. Then, based on the module priority sequence and the thermal sensitivity of the target user's heat therapy part, the dynamic heat field distribution of the rheumatic immune heat therapy device for the target user is determined.

[0043] In some embodiments, the dynamic regulation of the temperature control priorities of each heating module through the stability contribution to obtain a module priority sequence for temperature control of the rheumatic immune heat therapy device can be implemented by the following steps: Determine the fuzzy priorities of each heating module in the rheumatic immune heat therapy device according to the stability contribution; For each heating module, adjust the temperature control priority of the heating module based on the fuzzy priority of the heating module to obtain the module priority of the heating module, and then obtain the module priority of each heating module; Determine the module priority sequence for temperature control of the rheumatic immune heat therapy device through all the module priorities.

[0044] It should be noted that in this application, the fuzzy priority reflects the importance of the heating module for temperature stability and hyperthermia effect; in specific implementation, to determine the fuzzy priority of each heating module in the rheumatic immune hyperthermia device according to the stability contribution, the following method can be adopted, that is: for each heating module, divide the difference between the stable contribution degree of the heating module in the stability contribution and the minimum value of all stable contribution degrees by the difference between the maximum value and the minimum value of all stable contribution degrees, and use the obtained quotient value as the fuzzy priority of the heating module. Through the above method, the fuzzy priority of each heating module in the rheumatic immune hyperthermia device can be obtained.

[0045] In specific implementation, to adjust the temperature control priority of the heating module based on the fuzzy priority of the heating module and obtain the module priority of the heating module, the following method can be adopted, that is: the average value of the temperature control priority and the fuzzy priority of the heating module can be used as the module priority of the heating module; wherein, the module priority is a parameter for resource allocation and sorting of all heating modules during temperature control in the rheumatic immune hyperthermia device during the hyperthermia process. The larger the module priority, the more likely the heating module will be allocated resources first.

[0046] It should be noted that in this application, the module priority sequence refers to the priority order list of each heating module in the rheumatic immune hyperthermia device to execute the hyperthermia task. The module with a higher priority will be regulated and allocated resources first; in specific implementation, to determine the module priority sequence for temperature control of the rheumatic immune hyperthermia device through all the module priorities, the following method can be adopted, that is: all the module priorities can be arranged in a sequence from largest to smallest, and this sequence can be used as the module priority sequence for temperature control of the rheumatic immune hyperthermia device.

[0047] In some embodiments, to determine the dynamic heat field distribution of the rheumatic immune hyperthermia device for the target user during hyperthermia according to the module priority sequence and the thermal sensitivity of the target user's hyperthermia area to be treated, the following steps can be adopted: Determine the thermal sensitivity of the target user's hyperthermia area to be treated; Determine the dynamic temperature control curve of the rheumatic immune hyperthermia device for the target user during hyperthermia through the thermal sensitivity; Determine the heating intensity distribution domain of the target user during hyperthermia according to the module priority sequence and the distance between each heating module and the target user's hyperthermia area to be treated; Determine the dynamic heat field distribution of the rheumatic immune hyperthermia device for the target user during hyperthermia based on the dynamic temperature control curve and the heating intensity distribution domain.

[0048] It should be noted that in this application, heat sensitivity refers to the tolerance of the skin of the target user's heat therapy area to heat stimulation, which helps to determine the temperature control strategy of the rheumatism and immunology heat therapy device. Specifically, when implemented, the heat sensitivity of the target user's heat therapy area can be determined in the following way, that is: a skin heat stimulation test can be performed on the target user's heat therapy area through an existing skin stimulation test (such as a heat pain threshold test) to obtain the heat sensitivity of the target user's heat therapy area.

[0049] In addition, it should be noted that in this application, the dynamic temperature control curve refers to the temperature control curve that dynamically adjusts the heat therapy temperature of the rheumatism and immunology heat therapy device during the heat therapy process. Determining this dynamic temperature control curve according to the heat sensitivity of the target user can meet the individual needs of the target user and ensure the safety and comfort of the heat therapy process.

[0050] Specifically, when implemented, the dynamic temperature control curve of the rheumatism and immunology heat therapy device for the target user during heat therapy can be determined through the heat sensitivity in the following way, that is: first, the temperature fluctuation entropy of the target user's heat therapy area in the above step can be obtained, and the skin temperature of the target user's heat therapy area can be collected in real time at each moment using a skin temperature sensor (such as an infrared thermal imager) as the base temperature value. Multiply the difference between the heat sensitivity and the base temperature value by the temperature fluctuation entropy, and the sum of the product and the base temperature value is used as the output temperature of the target user during heat therapy at this moment. The time-temperature function curve between the output temperature and the base temperature value at each moment when the target user undergoes heat therapy is used as the dynamic temperature control curve of the rheumatism and immunology heat therapy device for the target user during heat therapy.

[0051] It should be noted that in this application, the heating intensity distribution domain refers to the intensity and distribution range of the heat energy applied to the part to be thermally treated of the target user. Specifically, when implemented, the heating intensity distribution domain during the thermal treatment of the target user can be determined according to the module priority sequence and the distance between each heating module and the part to be thermally treated of the target user by the following method, that is: First, establish a three-dimensional model of the part to be thermally treated of the target user and all heating modules in the rheumatic immune thermal therapy device, and use an existing model key point alignment method (for example: the registration method based on the iterative closest point algorithm) to align the two three-dimensional models to obtain a thermal therapy three-dimensional model, and calculate the distance from each heating module in the thermal therapy three-dimensional model to the part to be thermally treated. Then, obtain the total power limit of all heating modules in the rheumatic immune thermal therapy device, and use the quotient obtained by dividing the total power limit by the total number of heating modules as the rated heating power of the heating module. For each heating module, divide the product of the rated heating power and the module priority of the heating module in the module priority sequence by the square of the distance from the heating module to the part to be thermally treated, and use the obtained quotient value as the heating intensity of the heating module. By the above method, the heating intensity of each heating module can be obtained, and then map the heating intensity of all heating modules to the positions of the corresponding heating modules in the thermal therapy three-dimensional model to obtain the heating intensity distribution domain during the thermal treatment of the target user.

[0052] Preferably, in some embodiments, the three-dimensional model of the part to be thermally treated of the target user and all heating modules in the rheumatic immune thermal therapy device can be established by the following method, that is: First, non-invasive imaging technology (for example: three-dimensional laser scanning) can be used to collect the surface geometric data of the part to be thermally treated of the target user, and then use multi-viewpoint cloud synthesis technology to splice the scanned surface geometric data into a complete three-dimensional point cloud, and use a triangular mesh algorithm (for example: Delaunay triangulation) to construct the three-dimensional point cloud into a three-dimensional model to obtain the three-dimensional model of the part to be thermally treated of the target user; Then, the original design drawing of the thermal therapy device can be directly imported into an existing three-dimensional modeling tool (for example: SolidWorks) to model all heating modules in the rheumatic immune thermal therapy device to obtain the three-dimensional model of all heating modules in the rheumatic immune thermal therapy device. In other embodiments, other methods can also be used to perform three-dimensional modeling on the part to be thermally treated of the target user and each heating module in the rheumatic immune thermal therapy device, which is not specifically limited here.

[0053] It should be noted that in this application, the dynamic thermal field distribution refers to the distribution state of the heat generated during hyperthermia treatment of the target user in terms of time and space. This dynamic thermal field distribution helps to ensure that parameters such as the heating intensity and heating temperature range during the hyperthermia treatment can meet the physiological needs of the target user, thereby improving the hyperthermia treatment effect and reducing the risk of side effects, avoiding discomfort for the target user during use, and even preventing low-temperature burns. Specifically, when implemented, based on the dynamic temperature control curve and the heating intensity distribution domain, the dynamic thermal field distribution of the rheumatism and immunity hyperthermia device for the target user can be achieved in the following manner: the dynamic temperature control curve can be used as the distribution state of the heat generated during heating when the target user undergoes hyperthermia treatment in terms of time, the heating intensity distribution domain can be used as the distribution state of the heat generated during heating when the target user undergoes hyperthermia treatment in terms of space, and the set of the dynamic temperature control curve and the heating intensity distribution domain can be used as the dynamic thermal field distribution of the rheumatism and immunity hyperthermia device for the target user.

[0054] In step 104, based on the dynamic thermal field distribution, control the rheumatism and immunity hyperthermia device to heat the part to be hyperthermia-treated of the target user.

[0055] Specifically, when implemented, the temperature change trend during the hyperthermia treatment can be adjusted according to the dynamic temperature control curve in the dynamic thermal field distribution, and the power output of each heating module during the hyperthermia treatment can be determined in combination with the heating intensity distribution domain. For example: when the hyperthermia temperature value of the part to be hyperthermia-treated at a certain moment is lower than the output temperature at the same moment in the dynamic temperature control curve, obtain the heating intensity distribution domain in the dynamic thermal field distribution at this moment, and automatically increase the power output of each heating module according to the heating intensity ratio of all heating modules in the heating intensity distribution domain; when the hyperthermia temperature value of the part to be hyperthermia-treated at a certain moment is higher than the output temperature at the same moment in the dynamic temperature control curve, obtain the heating intensity distribution domain in the dynamic thermal field distribution at this moment, and automatically reduce the power output of each heating module according to the heating intensity ratio of all heating modules in the heating intensity distribution domain.

[0056] In addition, on the other hand of this application, in some embodiments, this application provides a rheumatism and immunity hyperthermia device. Refer to Figure 4 , this figure is a schematic structural diagram of the intelligent heating unit in the rheumatism and immunity hyperthermia device according to some embodiments of this application. The intelligent heating unit 400 includes: an initialization module 401, a dynamic regulation module 402, and a heating execution module 403, which are described as follows: Initialization module 401. In this application, the initialization module 401 is mainly used to initialize the temperature control priorities of each heating module in the rheumatism and immunity hyperthermia device according to the target temperature for hyperthermia treatment of the target user by the rheumatism and immunity hyperthermia device, and then determine the real-time temperature sequence of all heating modules when the rheumatism and immunity hyperthermia device preheats the part to be hyperthermia-treated of the target user based on all the temperature control priorities. The dynamic regulation module 402. In this application, the dynamic regulation module 402 is used to collect the epidermal temperature data of the target user's part to be preheated during preheating, determine the temperature adjustment factors of each heating module for the target user's part to be thermally treated through the epidermal temperature data and the real-time temperature sequence, and then perform fuzzy inference on all the temperature adjustment factors based on the fuzzy logic algorithm to obtain the stability contribution of all heating modules to the overall temperature of the rheumatic immune thermotherapy device. It should be noted that in this application, the dynamic regulation module 402 is also used to dynamically regulate the temperature control priorities of each heating module through the stability contribution to obtain the module priority sequence for temperature control of the rheumatic immune thermotherapy device, and then determine the dynamic thermal field distribution of the rheumatic immune thermotherapy device for thermally treating the target user according to the module priority sequence and the thermal sensitivity of the target user's part to be thermally treated. The heating execution module 403. In this application, the heating execution module 403 is mainly used to control the rheumatic immune thermotherapy device to heat the target user's part to be thermally treated based on the dynamic thermal field distribution.

[0057] Each module of the intelligent heating unit in the above-mentioned rheumatic immune thermotherapy device can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processor of the computer device in hardware form or be independent of it, or be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0058] In addition, in one embodiment, this application provides a computer device, which can be a server, and its internal structure diagram can be as Figure 5 shown. The computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data of the intelligent heating method based on priority regulation. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it realizes an intelligent heating method based on priority regulation.

[0059] Those skilled in the art can understand that Figure 5 the structure shown in

[0060] In one embodiment, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the steps in the above embodiment of the intelligent heating method based on priority regulation are implemented.

[0061] In one embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above embodiment of the intelligent heating method based on priority regulation are implemented.

[0062] In one embodiment, a computer program product or a computer program is provided. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the steps in the above embodiment of the intelligent heating method based on priority regulation.

[0063] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above embodiments of the methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0064] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0065] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. An intelligent heating method based on priority regulation, which is used to control a rheumatic immune hyperthermia device to perform hyperthermia on a target user, and is characterized in that, The method includes the following steps: Initialize the temperature control priorities of each heating module in the rheumatism immune hyperthermia device according to the target temperature for hyperthermia of the target user by the rheumatism immune hyperthermia device, and then determine the real-time temperature sequence of all heating modules when the rheumatism immune hyperthermia device preheats the part to be hyperthermia of the target user based on all the temperature control priorities; Collect the epidermal temperature data when the part to be hyperthermia of the target user is preheated, determine the temperature adjustment factors of each heating module for the part to be hyperthermia of the target user through the epidermal temperature data and the real-time temperature sequence, and then perform fuzzy inference on all the temperature adjustment factors based on the fuzzy logic algorithm to obtain the stability contribution of all heating modules to the overall temperature of the rheumatism immune hyperthermia device; Dynamically regulate the temperature control priorities of each heating module through the stability contribution to obtain the module priority sequence for temperature control of the rheumatism immune hyperthermia device, and then determine the dynamic heat field distribution of the rheumatism immune hyperthermia device for hyperthermia of the target user according to the module priority sequence and the thermal sensitivity of the part to be hyperthermia of the target user; Control the rheumatism immune hyperthermia device to heat the part to be hyperthermia of the target user based on the dynamic heat field distribution.

2. The method according to claim 1, wherein Initializing the temperature control priorities of each heating module in the rheumatism immune hyperthermia device according to the target temperature for hyperthermia of the target user by the rheumatism immune hyperthermia device specifically includes: Obtain the target temperature for hyperthermia of the target user by the rheumatism immune hyperthermia device; Determine the initial temperature control states of each heating module in the rheumatism immune hyperthermia device; Determine the local temperature deviation of each heating module according to all the initial temperature control states and the target temperature; Determine the temperature control priorities of each heating module when the rheumatism immune hyperthermia device performs temperature control through all the local temperature deviations.

3. The method according to claim 1, characterized in that Determining the real-time temperature sequence of all heating modules when the rheumatism immune hyperthermia device preheats the part to be hyperthermia of the target user based on all the temperature control priorities specifically includes: For each heating module in the rheumatism immune hyperthermia device, determine the initial electric power of the heating module based on the temperature control priority of the heating module; Start the heating module to preheat the part to be hyperthermia of the target user according to the initial electric power to obtain the temperature change data of the heating module, and then obtain the temperature change data of each heating module in the rheumatism immune hyperthermia device; Determine the real-time temperature sequence of all heating modules when the rheumatism immune hyperthermia device preheats the part to be hyperthermia of the target user through all the temperature change data.

4. The method according to claim 1, wherein Determining the temperature adjustment factors of each heating module for the part to be hyperthermia of the target user through the epidermal temperature data and the real-time temperature sequence specifically includes: Perform temperature interval frequency domain decomposition on the epidermal temperature data to obtain the relative frequency domain density of the epidermal temperature of the part to be hyperthermia of the target user in each temperature interval; Determine the temperature fluctuation entropy of the part to be hyperthermia of the target user according to all the relative frequency domain densities; Determine the temperature adjustment factors of each heating module in the rheumatism immune hyperthermia device for the part to be hyperthermia of the target user based on the temperature fluctuation entropy and the real-time temperature sequence.

5. The method according to claim 1, wherein Fuzzy inference is performed on all temperature adjustment factors based on the fuzzy logic algorithm, and the specific contributions of all heating modules to the overall temperature stability of the rheumatic immune hyperthermia device include: Perform fuzzy level division on all temperature adjustment factors to obtain multiple fuzzy levels; For each heating module, determine the fuzzy membership degree of the temperature adjustment factor of the heating module at each fuzzy level; Determine the stability contribution degree of the heating module according to all the fuzzy membership degrees, and then obtain the stability contribution degree of each heating module; Based on all the stability contribution degrees, determine the contributions of all heating modules to the overall temperature stability of the rheumatic immune hyperthermia device.

6. The method according to claim 1, wherein Dynamically regulate the temperature control priorities of each heating module through the stability contribution to obtain the module priority sequence for temperature control of the rheumatic immune hyperthermia device, which specifically includes: Determine the fuzzy priorities of each heating module in the rheumatic immune hyperthermia device according to the stability contribution; For each heating module, adjust the temperature control priority of the heating module based on the fuzzy priority of the heating module to obtain the module priority of the heating module, and then obtain the module priority of each heating module; Determine the module priority sequence for temperature control of the rheumatic immune hyperthermia device through all the module priorities.

7. The method according to claim 1, characterized in that Determine the dynamic thermal field distribution of the rheumatic immune hyperthermia device for the target user during hyperthermia according to the module priority sequence and the thermal sensitivity of the target user's hyperthermia area, which specifically includes: Determine the thermal sensitivity of the target user's hyperthermia area; Determine the dynamic temperature control curve of the rheumatic immune hyperthermia device for the target user during hyperthermia through the thermal sensitivity; Determine the heating intensity distribution range of the target user during hyperthermia according to the module priority sequence and the distance between each heating module and the target user's hyperthermia area; Based on the dynamic temperature control curve and the heating intensity distribution range, determine the dynamic thermal field distribution of the rheumatic immune hyperthermia device for the target user during hyperthermia.

8. A rheumatism immune heat therapy device, characterized in that, It includes an intelligent heating unit, and the intelligent heating unit includes: An initialization module for initializing the temperature control priorities of each heating module in the rheumatic immune hyperthermia device according to the target temperature for hyperthermia of the target user by the rheumatic immune hyperthermia device, and then determining the real-time temperature sequence of all heating modules when preheating the target user's hyperthermia area based on all the temperature control priorities; A dynamic regulation module for collecting the epidermal temperature data during preheating of the target user's hyperthermia area, determining the temperature adjustment factors of each heating module for the target user's hyperthermia area through the epidermal temperature data and the real-time temperature sequence, and then performing fuzzy inference on all the temperature adjustment factors based on the fuzzy logic algorithm to obtain the contributions of all heating modules to the overall temperature stability of the rheumatic immune hyperthermia device; The dynamic regulation module is used to dynamically regulate the temperature control priorities of each heating module through the stability contribution to obtain the module priority sequence for temperature control of the rheumatic immune hyperthermia device, and then determine the dynamic thermal field distribution of the rheumatic immune hyperthermia device for the target user during hyperthermia according to the module priority sequence and the thermal sensitivity of the target user's hyperthermia area A heating execution module, configured to control a rheumatic immune hyperthermia device to heat a part to be hyperthermia of a target user based on the dynamic thermal field distribution.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the intelligent heating method based on priority regulation according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, the steps of the intelligent heating method based on priority regulation according to any one of claims 1 to 7 are implemented.

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