Induction cooker cookware characteristic judgment method

Abstract

The invention discloses a method for judging the characteristics of an induction cooker cookware, which comprises the following steps of: monitoring and managing the states of large induction cooker cookware with different temperatures and pressures and adjusting the change of the load per unit area by utilizing the heat conductivity information of various induction cooker cookware loads and a whale algorithm technology; the method comprises the following steps: acquiring electromagnetic conversion load related information of iron, steel, stainless steel and a mixed material of the induction cooker cookware; the related information of the electromagnetic conversion load of the iron, the steel, the stainless steel and the mixed material comprises different diameters and bottom surface areas of different induction cooker cookware, unit area cooker bottom magnetic conductivity and heat conductivity information of the induction cooker cookware load of the electromagnetic heating adaptability of the unit area cookware; according to the statistical condition of the thermal conductivity information of the cooker load of the induction cooker, the thermal conductivity information of the cooker load of the induction cooker is classified, the use experience of the induction cooker is improved, the heating efficiency and the energy-saving effect are greatly improved, and the method is suitable for complex scenes of different types of cookware.

Description

Technical Field

[0001] The invention relates to the field of monitoring and management of induction cookers, and in particular to a method for determining characteristics of induction cookers. Background Art

[0002] With the increasing application of induction cookers and electromagnetic heating equipment, more and more users are using induction cookers. At present, household induction cookers can heat iron, steel and other pots. Many complete machine manufacturers will be equipped with pots, but users will use induction cookers to heat various pots at home, such as double-bottom pots and honeycomb iron pots. These pots will cause the temperature rise of the IGBT power device of the induction cooker to be too high due to the material and other reasons, thereby increasing the damage rate of the IGBT. At present, there are two mainstream solutions in the market: 1. Detect the IGBT temperature. If the IGBT temperature exceeds a certain range, the power output of the induction cooker will be reduced. The disadvantage of this type of solution is that if the induction cooker uses sufficient power to heat the IGBT, the temperature rise will be very fast. The temperature sensor has no time to detect the overtemperature, which will cause the IGBT to be damaged or the system will automatically shut down the output power. 2. Judge the characteristics of the pot through overvoltage (reverse pressure), that is, the IGBT C pole voltage, and the system resonant frequency. If the pot characteristics are judged to be poor, a lower power will be given. This solution has a high probability of misjudgment and is difficult to achieve batch consistency, affecting the user experience. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a method that utilizes the thermal conductivity information of various induction cooker cookware loads and a whale algorithm technology to realize the monitoring and management of the states of induction cookers with different temperatures and pressures and the adjustment of the load changes per unit area.

[0004] The present invention provides a method for determining the characteristics of an induction cooker, the method comprising:

[0005] Collecting electromagnetic conversion load information of iron, steel, stainless steel and mixed materials of electromagnetic cookers, wherein the electromagnetic conversion load information of iron, steel, stainless steel and mixed materials includes thermal conductivity information of electromagnetic cooker loads of different diameters and bottom areas of different electromagnetic cookers, magnetic permeability of the bottom per unit area of ​​the cooker, and electromagnetic heating adaptability of the cooker per unit area;

[0006] The thermal conductivity information of the induction cooker load includes the contact quality of the induction cooker during operation, the coating state of the cooker surface, the heat flow and output power, the bottom temperature, the bottom heat distribution, the heat capacity and contact thermal resistance of the contents of the cooker;

[0007] The contact quality of the cookware and the coating state of the cookware surface are collected per unit time, and the heat flow and output power, the bottom temperature of the cookware, the heat distribution of the bottom of the cookware, the heat capacity and contact thermal resistance of the contents of the cookware are collected per unit time according to the preset food doneness;

[0008] According to the statistics of the thermal conductivity information of the induction cooker load, the thermal conductivity information of the induction cooker load is classified to obtain the thermal conductivity of the cooker material at different temperatures and pressures within the statistical period, the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, wherein the thermal conductivity of the cooker material at different temperatures and pressures within the statistical period includes the contact quality of the cooker and the coating state of the cooker surface, and the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load include heat flow and output power, pot bottom temperature, pot bottom heat distribution, heat capacity and contact thermal resistance of the contents of the cooker;

[0009] The thermal conductivity of the cookware materials at different temperatures and pressures, the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, and the corresponding different diameters and bottom areas of the induction cooker cookware, and the magnetic permeability of the bottom per unit area are uploaded to the power control adaptive model to establish the thermal conductivity jump management algorithm of the induction cooker cookware load with different food doneness requirements and the thermal conductivity jump management algorithm of the induction cooker cookware load with different materials;

[0010] Among them, the input of the thermal conductivity jump management algorithm of the induction cooker cookware load with different food doneness requirements is the thermal conductivity of the cookware materials with different temperatures and pressures within the statistical period, and the output is the cookware control gear and IGBT temperature of the thermal conductivity jump management algorithm of the induction cooker cookware load with different materials; the input of the thermal conductivity jump management algorithm of the induction cooker cookware load with different materials is the influence of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load and the determined cookware control gear and IGBT temperature, and the output is the permeability of the bottom of the induction cooker cookware per unit area;

[0011] In practical applications, the thermal conductivity of the cookware materials of different temperatures and pressures of the induction cooker is collected per unit time within the statistical period, and input into the thermal conductivity jump management algorithm of the induction cooker load with different food doneness requirements, so as to obtain the pot control gear and IGBT temperature of the thermal conductivity jump management algorithm of the induction cooker load with different materials;

[0012] Given a power value, control the induction cooker to reach the set power value, determine if the power difference range is within the preset range, then record the pot characteristic value of the induction cooker at this power, filter the pot characteristic value and record it in the pot characteristic array PanData[]. Repeat the above operation until all the pot power characteristic values ​​of the set power levels are recorded;

[0013] Compare the pot control gear and IGBT temperature of the thermal conductivity jump management algorithm for induction cooker pots of different materials with the preset pot gear and IGBT temperature error:

[0014] When the control gear of the cookware and the IGBT temperature error are less than the preset cookware gear and IGBT temperature error, there is no need to set the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, and continue to collect and analyze the thermal conductivity of cookware materials at different temperatures and pressures within the statistical period;

[0015] When the control gear of the cookware and the IGBT temperature error are equal to or greater than the preset cookware gear and IGBT temperature error, set the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, and input the influence of the load form, the temperature gradient of the load, the density and thermal conductivity, the cookware control gear, and the IGBT temperature into the thermal conductivity jump management algorithm for different material induction cooker cookware loads to obtain the magnetic permeability per unit area of the bottom of the induction cooker cookware.

[0016] Analyze the data change trend of the cookware characteristic values of each power gear obtained by testing to distinguish the cookware type. When PanData[0]>PanData[1]>PanData[2]....>PanData[n] and the difference reaches the set value, it is judged that the characteristic of the cookware is a downward trend of the initial power gear; if PanData[0]<PanData[1]<PanData[2]....<PanData[n] and the difference reaches the set value, it is judged that the characteristic of the cookware is an upward trend of the initial power gear. When the value of PanData[n] is less than the preset change value, it is judged that this power interval belongs to a stable trend;

[0017] Analyze the most suitable working power range of the cookware according to the cookware characteristic values of each power gear obtained by testing. According to the monitored array of cookware characteristic values, find the gear with the smallest value and its stable range, and give a suitable power output according to the application requirements.

[0018] Preferably, the steps for establishing the thermal conductivity jump management algorithm for induction cooker cookware loads with different food doneness requirements are as follows:

[0019] According to the relevant information of electromagnetic conversion loads of iron, steel, stainless steel, and mixed materials, sort out the thermal conductivity and the corresponding magnetic permeability per unit area of the bottom of cookware materials with different diameters and bottom areas of induction cooker cookware;

[0020] Process and perform spatio-temporal convolution on the thermal conductivity of cookware materials at different temperatures and pressures within the statistical period to convert the original data into practical features for use by the power control adaptive model;

[0021] Use the power control adaptive model to calculate data according to the prepared attention mechanism, perform model attention mechanism calculation using the selected algorithm, and adjust the parameters of the model;

[0022] After the attention mechanism is calculated, the relevant parameters of the model are extracted as the output of the thermal conductivity jump management algorithm for the induction cooker cooker load with different food doneness requirements.

[0023] Preferably, the steps for establishing the thermal conductivity jump management algorithm for the induction cooker cookware loads of different materials are:

[0024] According to the electromagnetic conversion load information of iron, steel, stainless steel and mixed materials, the influence of the load form of induction cookers, the temperature gradient of the load, the density and thermal conductivity of the load and the corresponding magnetic permeability of the bottom of the pot per unit area are sorted out;

[0025] The whale algorithm is used for training, taking the influence of load shape, load temperature gradient, load density and thermal conductivity as independent variables, and the magnetic permeability of the bottom of the pot per unit area as the optimization target, to model the boundary conditions of the data and calculate the attention mechanism of the model;

[0026] After the attention mechanism is calculated, the thermal conductivity jump management algorithm of the induction cooker pot load of different materials is used to predict the permeability of the pot bottom per unit area of ​​the induction cooker pot;

[0027] The whale algorithm is used to calculate the information related to the electromagnetic conversion load of iron, steel, stainless steel and mixed materials, and the statistical deviation between the magnetic permeability per unit area of ​​the pot bottom and the actual magnetic permeability per unit area of ​​the pot bottom is calculated.

[0028] Preferably, the data collection method for the influence of the load shape, the temperature gradient of the load, the density of the load and the thermal conductivity includes:

[0029] Use the air temperature monitoring device to monitor and collect the heat flow and output power of the induction cooker. Monitor and collect the bottom temperature of the induction cooker based on the power equipment monitoring platform. Monitor and collect the contact thermal resistance of the induction cooker, and analyze the peak value and jump range of the heat flow and output power changes. Use the remote sensing system to monitor and collect the bottom heat distribution signal generated by the induction cooker. Use the registration management system to collect the heat capacity of the contents of the induction cooker around the induction cooker, and count the impact of the heat capacity of different contents of the cooker.

[0030] Preferably, the preset cookware gear position and the preset influencing factors of the IGBT temperature error include power load, IGBT rated voltage, switching frequency, over-temperature protection threshold and on-resistance.

[0031] The present invention proposes a method for determining the characteristics of induction cookers, which has the following advantages:

[0032] 1. Multi-dimensional characteristic analysis: This method comprehensively analyzes the performance of the cookware at different power levels based on multiple characteristic parameters of the cookware (such as load temperature gradient, density, thermal conductivity, and magnetic permeability of the bottom of the cooker per unit area). This multi-dimensional characteristic analysis can more comprehensively and accurately identify the material and thermal performance of the cookware, which helps to optimize the heating effect and energy utilization of the induction cooker.

[0033] 2. Accurate trend judgment: By analyzing the change trend of the characteristic value of the cookware at each power level (such as an upward trend, a downward trend or a stable trend), the thermal performance characteristics of the cookware can be accurately judged. This trend analysis not only improves the accuracy of identifying the type of cookware, but also provides a scientific basis for determining its most suitable working power range.

[0034] 3. Dynamic adaptation to different cookware materials: This method fully considers the electromagnetic conversion characteristics of different cookware materials such as iron, steel, stainless steel and mixed materials, as well as the influence of the cookware shape and bottom structure, so that it can dynamically adapt to various cookware types and improve the compatibility and adaptability of the induction cooker.

[0035] 4. Optimization of thermal conductivity management algorithm: Through the thermal conductivity jump management algorithm and statistical analysis, combined with specific application requirements, the method can predict the thermal performance of the cooker and reduce the problem of overheating or insufficient heating. This intelligent management optimizes the performance of the induction cooker, making it more energy-efficient and efficient.

[0036] 5. Intelligent power adjustment: The method can automatically find the most suitable working power range of the cooker and provide appropriate power output based on the analysis results of the cooker characteristic value array (such as PanData[]). This automatic adjustment function reduces the complexity of manual adjustment while ensuring the best heating effect.

[0037] 6. Improve system reliability: Through IGBT temperature monitoring and difference judgment, ensure that the system will not be affected by overheating and other problems during operation. This real-time monitoring mechanism enhances the reliability and safety of the system.

[0038] 7. Data-driven accurate modeling: This method relies on a large amount of test data and statistical analysis to model the characteristics of the cookware. Combined with boundary conditions and optimization algorithms (such as the whale algorithm), it can achieve accurate prediction and adaptation of the characteristics of the cookware. This data-driven approach has significant advantages in optimizing calculation accuracy and system performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0040] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application may be combined with each other. The present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0041] like Figure 1 As shown, a method for determining the characteristics of an induction cooker of the present invention specifically comprises the following steps:

[0042] S1. Collecting electromagnetic conversion load information of iron, steel, stainless steel and mixed materials of electromagnetic cookers, wherein the electromagnetic conversion load information of iron, steel, stainless steel and mixed materials includes thermal conductivity information of electromagnetic cooker loads of different diameters and bottom areas of different electromagnetic cookers, magnetic permeability of the bottom per unit area of ​​the cooker, and electromagnetic heating adaptability of the cooker per unit area;

[0043] In order to realize the status monitoring and management of large-scale induction cookers with different temperatures and pressures, it is first necessary to collect information related to the electromagnetic conversion load of iron, steel, stainless steel and mixed materials of induction cookers. This data can provide information about the performance of induction cookers during operation, the magnetic permeability of the bottom of the pot per unit area, and the thermal conductivity of the relevant induction cooker load, providing a basis for subsequent status evaluation and adjustment of unit area load changes;

[0044] The thermal conductivity information of the induction cooker cooker load includes:

[0045] Contact quality of cookware and state of cookware surface coating: Collect contact quality and state of cookware surface coating of induction cooker cookware, and analyze the change of contact quality and state of cookware surface coating; the change of contact quality and state of cookware surface coating can reflect the stability of induction cooker cookware. It is necessary to collect the contact quality and state parameters of cookware surface coating of induction cooker cookware per unit time, and record their change.

[0046] Heat flow and output power: Based on the air temperature monitoring device, the heat flow and output power of the induction cooker are monitored and collected, including the maximum value, average value and variance of the heat flow and output power. The changes in heat flow and output power can reflect the mechanical operation status of the induction cooker and the changes in the load per unit area.

[0047] Pot bottom temperature: Use the power equipment monitoring platform to monitor and collect the changes in the pot bottom temperature of the induction cooker, including the pot bottom temperature inside and outside the equipment. Abnormal changes in the pot bottom temperature can indicate changes in the load per unit area such as overload or poor heat dissipation of the induction cooker;

[0048] Pot bottom heat distribution: Based on the remote sensing system, the pot bottom heat distribution signal generated by the induction cooker pot is monitored and collected, and analyzed. The pot bottom heat distribution signal can provide the internal status information of the induction cooker pot.

[0049] Heat capacity of pot contents: Based on the household registration management system, the heat capacity of pot contents around the induction cooker pots is collected, and the changes in the effects of the heat capacity of different pot contents are counted, and the abnormal changes in the effects of the heat capacity of different pot contents are counted.

[0050] Contact thermal resistance: Monitor and collect the contact thermal resistance of induction cookers, analyze the peak value and jump range of heat flow and output power changes, and the test results of contact thermal resistance can provide information about insulation performance.

[0051] By collecting and recording the thermal conductivity information of these induction cooker cookware loads with different diameters and bottom surface areas, an information database of induction cooker cookware is established for subsequent data analysis, correlation analysis and model attention mechanism calculation; wherein, the contact quality of the cookware and the state of the cookware surface coating are collected per unit time, and the heat flux and output power, pot bottom temperature, pot bottom heat distribution, heat capacity and contact thermal resistance of the pot contents are collected per unit time according to the preset food doneness; by collecting information related to the electromagnetic conversion load of iron, steel, stainless steel and mixed materials of induction cooker cookware, basic data on the performance of induction cooker cookware during operation and the magnetic permeability of the pot bottom per unit area can be provided, which provides an important basis for subsequent state evaluation, unit area load change adjustment and performance optimization.

[0052] By analyzing the information related to the electromagnetic conversion load of iron, steel, stainless steel and mixed materials, the stability, mechanical operation status, insulation performance and potential unit area load change of induction cooker pots can be revealed; in addition to the contact quality of the pot and the jump data of the coating status of the pot surface, through air temperature monitoring devices, power equipment monitoring platforms, bottom heat distribution detection, household registration management system and contact thermal resistance detection and other detection methods, the induction cooker pots are monitored and managed in an all-round way, and the status information of the induction cooker pots is collected from different angles to improve the accuracy of unit area load change detection and adjustment.

[0053] By collecting information related to the electromagnetic conversion load of iron, steel, stainless steel and mixed materials of induction cooker cookware and the thermal conductivity information of the induction cooker cookware load, we can fully understand the performance of induction cooker cookware, the magnetic permeability of the pot bottom per unit area and the thermal conductivity information of the induction cooker cooker load, and provide basic data and basis for subsequent status evaluation, unit area load change adjustment and performance optimization.

[0054] S2. According to the statistics of the thermal conductivity information of the induction cooker load, the thermal conductivity information of the induction cooker load is classified to obtain the thermal conductivity of the cooker materials at different temperatures and pressures within the statistical period, the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, wherein the thermal conductivity of the cooker materials at different temperatures and pressures within the statistical period includes the contact quality of the cooker and the coating state of the cooker surface, and the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load include heat flow and output power, pot bottom temperature, pot bottom heat distribution, heat capacity and contact thermal resistance of the contents of the cooker;

[0055] In this step, it is necessary to classify the thermal conductivity information of the induction cooker load according to the statistics of the thermal conductivity information of the induction cooker load, and divide the thermal conductivity information of the induction cooker load with different diameters and bottom areas into two different information, namely, the thermal conductivity of the cooker material at different temperatures and pressures within the statistical period, the influence of the load shape, the temperature gradient of the load, and the density and thermal conductivity of the load;

[0056] The thermal conductivity of the cookware materials at different temperatures and pressures during the statistical period includes the contact quality of the cookware and the coating state of the cookware surface. These data can be collected by monitoring and collecting the contact quality and coating state parameters of the induction cooker cookware per unit time;

[0057] The influence of load shape, load temperature gradient, load density and thermal conductivity including heat flow and output power, pot bottom temperature, pot bottom heat distribution, heat capacity and contact thermal resistance of the pot contents, which are used to monitor and collect the heat flow and output power, pot bottom temperature, pot bottom heat distribution, heat capacity and contact thermal resistance of the pot contents during the operation of the induction cooker;

[0058] The classification basis of thermal conductivity of cookware materials at different temperatures and pressures, the influence of load form, temperature gradient of load, density of load and thermal conductivity during the statistical period is as follows:

[0059] Different types of unit area load changes correspond to different thermal conductivity information of induction cooker loads. By classifying the contact quality of the cooker and the coating state of the cooker surface separately from other multiple feature data, different types of unit area load changes can be judged and analyzed more specifically. The contact quality of the cooker and the state jump of the coating state of the cooker surface are more likely to be related to the unit area load changes of different temperatures and pressures, while the heat flow and output power, bottom temperature of the pot, sound and other data are more likely to be related to the mechanical or insulation unit area load changes. The contact quality of the cooker and the coating state of the cooker surface are more convenient to collect in the unit time monitoring and management. These data can be used to quickly make a preliminary judgment on the unit area load change;

[0060] The influence of load shape, temperature gradient of load, density and thermal conductivity of load involve more sensor collection and detection equipment, which requires a certain amount of time and cost. Therefore, by presetting a preset pot gear and IGBT temperature error, if the pot control gear and IGBT temperature of the thermal conductivity of the pot material at different temperatures and pressures during the statistical period are less than the preset pot gear and IGBT temperature error, it is possible to avoid frequently setting the influence of load shape, temperature gradient of load, density and thermal conductivity of load, thereby improving the management effect.

[0061] By dividing the thermal conductivity information of the induction cooker cooker load into two pieces of information, the changes in unit area loads of different types can be judged and analyzed more specifically; by presetting a preset cooker gear and IGBT temperature error, if the cooker control gear and IGBT temperature of the thermal conductivity of cooker materials with different temperatures and pressures during the statistical period are less than the preset cooker gear and IGBT temperature error, the influence of frequent setting of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load can be avoided, thereby improving the management effect; the thermal conductivity information of different types of induction cooker cooker loads can be classified separately, and more accurate judgment and adjustment results can be obtained by comprehensively analyzing the correlation between different feature data.

[0062] S3, uploading the thermal conductivity of the cookware materials at different temperatures and pressures, the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, and the corresponding different diameters and bottom areas of the induction cooker cookware, and the magnetic permeability of the bottom per unit area to the power control adaptive model, and establishing the thermal conductivity jump management algorithm of the induction cooker cookware load with different food doneness requirements and the thermal conductivity jump management algorithm of the induction cooker cookware load with different materials;

[0063] The steps for establishing the thermal conductivity jump management algorithm for induction cooker loads with different food doneness requirements are as follows:

[0064] Based on the collected information about electromagnetic conversion load of induction cookers made of iron, steel, stainless steel and mixed materials, the thermal conductivity of induction cookers with different diameters and bottom areas and the corresponding magnetic permeability per unit area of ​​the bottom of the cooker are sorted out;

[0065] The thermal conductivity of the cookware material at different temperatures and pressures within the statistical period is processed and spatially convolved to convert the raw data into practical features for use in the power control adaptive model;

[0066] According to the problem description, select a power control adaptive model suitable for the scenario, use the selected algorithm to calculate the model attention mechanism, and adjust the model parameters;

[0067] After the attention mechanism is calculated, the relevant parameters of the model are extracted as the output of the thermal conductivity jump management algorithm for the induction cooker cooker load with different food doneness requirements.

[0068] The steps to establish the thermal conductivity jump management algorithm for induction cooker loads of different materials are as follows:

[0069] Based on the collected information on electromagnetic conversion loads of induction cookers made of iron, steel, stainless steel and mixed materials, the influence of load form, temperature gradient of load, density and thermal conductivity of load and corresponding magnetic permeability of the bottom of the pot per unit area of ​​induction cookers are sorted out;

[0070] The whale algorithm is used for training, taking the influence of load shape, load temperature gradient, load density and thermal conductivity as independent variables, and the magnetic permeability of the bottom of the pot per unit area as the optimization target, to model the boundary conditions of the data and calculate the attention mechanism of the model;

[0071] After the attention mechanism is calculated, the thermal conductivity jump management algorithm of the induction cooker pot load of different materials is used to predict the permeability of the bottom of the induction cooker per unit area.

[0072] The thermal conductivity jump management algorithm for induction cooker loads of different materials is trained using the whale algorithm.

[0073] The Whale Optimization Algorithm (WOA) is an intelligent optimization algorithm based on the hunting behavior of humpback whales. It simulates the process of humpback whales hunting through bubble nets and is used to solve optimization problems. The core of the Whale Algorithm includes three main stages: surrounding prey, spiral bubble net attack, and random search for prey. These stages together achieve a balance between global search and local search to find the optimal solution.

[0074] Variable definitions in application scenarios, optimization objectives and input variables of the whale algorithm include:

[0075] Input variables: temperature gradient, density, thermal conductivity and other parameters of the pot load.

[0076] Optimization goal: maximize the magnetic permeability of the pot bottom per unit area.

[0077] Constraints: Based on different cookware materials (such as iron, steel, stainless steel, mixed materials) and boundary conditions (such as electromagnetic conversion efficiency, etc.).

[0078] By modeling these parameters through the whale algorithm, the calculation of the magnetic permeability of the pot bottom per unit area can be optimized and the accuracy of the judgment of the pot characteristics can be improved.

[0079] The specific steps of the whale algorithm are:

[0080] Initialize the population and parameters, initialize a set of random solutions (whale individuals), each solution represents a possible combination of values ​​of the pot-related parameters, including load temperature gradient, density, thermal conductivity, etc. - Define the population size N, the maximum number of iterations T, and the control parameters of the algorithm (such as shrinkage factor and screw factor).

[0081] Calculate the fitness function and calculate the fitness value of each individual whale according to the optimization goal (maximizing the magnetic permeability of the pot bottom per unit area). The fitness function can be defined as:

[0082] f(x) = target permeability value - error - constraint violation cost

[0083] The error is calculated based on the deviation between the actual characteristic value of the cookware and the predicted value.

[0084] Updating individual whale positions The whale algorithm uses two main strategies to update positions:

[0085] Surround the prey (local search), assuming that the current optimal solution is the prey position (optimal solution for the cooker parameters). Update the individual whale positions:

[0086] X(t+1)=X * -A·|C·X * -X(t)|

[0087] Where: X * : The position of the current optimal solution. X(t): The position of the current individual whale. A and C: Coefficient vectors, dynamically changing with iteration. A = 2a.ra, C = 2r, a is a control parameter that decreases linearly from 2 to 0, and r is a random number. Spiral bubble net attack (combination of local and global search), simulating the behavior of humpback whales approaching prey through a spiral path, updating the position:

[0088] X(t+1)=|X * -X(t)|·e bl ·cos(2πl)+X *

[0089] Where: b: spiral shape constant. l: random number, range is [-1, 1]. Random search for prey (global search), when the individual whale is far away from the prey, randomly select a solution within the population as a reference and update the position:

[0090] X(t+1)=X rand -A·|C·X rand -X(t)|

[0091] Among them, X randis a randomly selected solution. Determine the stopping condition. If the maximum number of iterations T is reached, or the fitness value converges to the set threshold, the algorithm stops and outputs the current optimal solution. Otherwise, return to continue iterating.

[0092] In the application scenario in the figure, the whale algorithm is specifically used for the following tasks:

[0093] Optimization goal: Maximize the magnetic permeability of the pot bottom per unit area by adjusting parameters such as the temperature gradient, density and thermal conductivity of the pot load.

[0094] Modeling boundary conditions: Use data from different cookware materials (iron, steel, stainless steel, mixed materials) to establish a boundary condition model to ensure that the optimization results meet the physical property constraints.

[0095] Predicting cookware characteristics: The permeability value calculated after optimization by the whale algorithm is compared with the actual permeability value of the cookware to evaluate the prediction accuracy.

[0096] The advantage of the Whale Algorithm in this scenario lies in its balance between global search and local search, which can efficiently solve the problem of optimizing the characteristics of pots. Through multiple rounds of iterations, the Whale Algorithm can accurately find the optimal combination of pot characteristic parameters, improve the accuracy of the induction cooker pot identification method, and provide a reliable basis for subsequent optimization design.

[0097] Establish a corresponding relationship between the magnetic permeability per unit area of ​​the pot bottom and the actual magnetic permeability per unit area of ​​the pot bottom; specifically, by performing attention mechanism calculation and model training on the electromagnetic conversion load related information of iron, steel, stainless steel and mixed materials, the corresponding relationship between the magnetic permeability per unit area of ​​the pot bottom and the actual magnetic permeability per unit area of ​​the pot bottom is obtained, and by performing power control adaptive models such as classification and regression on the electromagnetic conversion load related information of iron, steel, stainless steel and mixed materials, the statistical deviation between the magnetic permeability per unit area of ​​the pot bottom and the actual magnetic permeability per unit area of ​​the pot bottom is calculated;

[0098] Among them, the input of the thermal conductivity jump management algorithm of the induction cooker cookware load with different food doneness requirements is the thermal conductivity of the cookware materials with different temperatures and pressures within the statistical period, and the output is the cookware control gear and IGBT temperature of the thermal conductivity jump management algorithm of the induction cooker cookware load with different materials; the input of the thermal conductivity jump management algorithm of the induction cooker cookware load with different materials is the influence of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load and the determined cookware control gear and IGBT temperature, and the output is the permeability of the bottom of the induction cooker cookware per unit area;

[0099] This step can obtain complete input information by sorting and processing the thermal conductivity and unit area permeability of the pot bottom of the induction cooker with different diameters and bottom areas, so that the thermal conductivity jump management algorithm of the induction cooker load can more accurately judge the state of the device and the unit area permeability of the pot bottom; use the prepared attention mechanism calculation data to perform model attention mechanism calculation on the selected power control adaptive model, and adjust the model parameters, so as to improve the accuracy and performance of the model by continuously optimizing the model parameters and algorithm selection; by outputting the pot control gear and IGBT temperature, the importance of each feature to the judgment of the unit area permeability of the pot bottom can be solved, so as to better understand the relationship between the thermal conductivity jump of the induction cooker load and the unit area permeability of the pot bottom;

[0100] In summary, the thermal conductivity jump management algorithm for induction cooker pot load can more accurately evaluate the status of induction cooker pots and the magnetic permeability of the pot bottom per unit area, providing effective decision support and guidance for eliminating unit area load changes for braking personnel.

[0101] S4. Collect the thermal conductivity of the cookware materials of different temperatures and pressures during the statistical period of the induction cooker per unit time, and input it into the thermal conductivity jump management algorithm of the induction cooker load with different food doneness requirements, so as to obtain the cookware control gear and IGBT temperature of the thermal conductivity jump management algorithm of the induction cooker load with different materials;

[0102] In this step, data is preprocessed before input, including data desensitization, sorting, and normalization, to ensure the quality and consistency of data input into the model;

[0103] The thermal conductivity of the cookware materials with different temperatures and pressures collected within the statistical period per unit time is used as input and passed to the thermal conductivity jump management algorithm of the induction cooker cookware load with different food doneness requirements for spatiotemporal convolution and state evaluation, and the cookware control gear and IGBT temperature are provided for the subsequent thermal conductivity jump management algorithm of the induction cooker cookware load with different materials; the cookware control gear and IGBT temperature reflect the current state and performance status of the induction cooker cookware, and the operation status of the induction cooker cookware can be preliminarily judged and evaluated through the cookware control gear and IGBT temperature;

[0104] In this step, through preprocessing steps such as data desensitization, sorting and normalization, the quality and consistency of the data input into the model can be ensured, outliers, noise and inconsistent sampling rates in the data can be eliminated, and the accuracy and reliability of the monitoring algorithm can be improved;

[0105] The pot control gear position and IGBT temperature obtained by the thermal conductivity jump management algorithm of the induction cooker pot load with different food doneness requirements can reflect the current state and performance of the induction cooker pot. These pot control gear position and IGBT temperature can be used for the preliminary judgment and evaluation of the induction cooker pot, providing important input for the subsequent thermal conductivity jump management algorithm of the induction cooker pot load with different materials;

[0106] By continuously monitoring, managing and evaluating the status of induction cookers and pots, potential changes in load per unit area or abnormal conditions can be discovered in a timely manner, so that maintenance measures can be taken in advance to avoid the impact of changes in load per unit area of ​​the equipment on the supply of different temperatures and pressures. By analyzing and evaluating the status of induction cookers and pots per unit time, the operating strategy of electrical equipment can be optimized, and the operating efficiency and energy utilization efficiency of induction cookers and pots can be improved.

[0107] S5. Given a power value, control the induction cooker to reach the set power value, determine that the power difference range is within the preset range, then record the pot characteristic value of the induction cooker at the power, filter the pot characteristic value and record it in the pot characteristic array PanData[]. Repeat the above operation until all the pot power characteristic values ​​of the set power levels are recorded;

[0108] In the design of the induction cooker control system, accurately adjusting the power and recording the characteristic data of the pot in real time are important links to ensure the heating effect and improve the user experience. The present invention will explain in detail how to control the induction cooker to reach the set power value, determine whether the power difference is within the preset range, record the pot characteristic values, and filter these characteristic values ​​to finally generate the pot characteristic data array PanData[]. This process involves multiple steps and technical points to ensure the accuracy and stability of the system.

[0109] The working principle of the induction cooker is based on changing the frequency of the electromagnetic field to adjust the heating power of the pot, and the heating control is usually achieved by adjusting the power output. After a set power value is given, the induction cooker needs to adjust its output power to ensure that the actual power value of the induction cooker is as close to the target power as possible. In order to ensure the accuracy of the heating process, the system needs to monitor and determine the difference between the actual power of the induction cooker and the set power. If the difference between the actual power and the set power exceeds the preset range (usually called the "power error range"), the power of the induction cooker needs to be readjusted until it reaches the target power range. The setting of the power error range is determined according to the response speed and control accuracy of the induction cooker, and usually a certain amount of fault tolerance is left to avoid excessive and frequent adjustments. By continuously adjusting the power output, the system can stably maintain the target power during the heating process of the pot, thereby ensuring the consistency of the heating effect.

[0110] When the power of the induction cooker reaches the set value and the error range is within the preset range, the system will record the characteristic values ​​of the pot at this power. These characteristic values ​​usually include parameters such as the temperature, thermal efficiency, and heating uniformity of the pot. The measurement of the characteristic values ​​of the pot usually relies on temperature sensors or other related sensor devices. In order to obtain accurate and stable pot characteristic data, the system will record the characteristic values ​​of the pot multiple times over a period of time. During the recording process, since the pot temperature is affected by various factors such as heat conduction and environmental changes, there may be certain fluctuations or noise in the measured values. Therefore, the system needs to filter these characteristic values ​​to remove irrelevant noise and retain the true trend or characteristics. Common filtering algorithms include moving average filtering, median filtering, and Kalman filtering. The purpose of filtering is to reduce random errors in the data so that the final recorded pot characteristic values ​​are more stable and reliable. This process is crucial for the performance evaluation and heating effect analysis of the pot, and can help developers optimize the control strategy of the induction cooker.

[0111] The pan characteristic values ​​after filtering will be stored in the PanData[] array. This array records the pan characteristic data at each power level, which is convenient for subsequent data analysis and system tuning. During the whole process, the induction cooker needs to operate according to multiple set power levels and record and process the pan characteristic values ​​at each level. Therefore, the system needs to repeatedly adjust the power, record the characteristic values, and filter the data according to the number of power levels and the amount of characteristic data at each level. Finally, the PanData[] array will contain the pan characteristic data at all power levels, which can provide a scientific basis for the performance optimization, heating efficiency analysis, and user experience improvement of the induction cooker.

[0112] Based on the set power value, the induction cooker control system can effectively ensure the stability and accuracy of the pot heating process through precise power regulation, characteristic value recording and filtering processing. This process not only improves the efficiency of the induction cooker, but also provides valuable data support for the performance analysis and improvement of the pot. By continuously optimizing the power regulation strategy and characteristic value processing method, the induction cooker can achieve more intelligent and refined control to meet the needs of different users and improve the user experience.

[0113] S6. Compare the pot control gear and IGBT temperature of the thermal conductivity jump management algorithm of the induction cooker pot load of different materials with the preset pot gear and IGBT temperature error: when the pot control gear and IGBT temperature error are less than the preset pot gear and IGBT temperature error, there is no need to set the influence of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load, and continue to collect and analyze the thermal conductivity of the pot materials of different temperatures and pressures within the statistical period;

[0114] S7. When the cookware control gear and the IGBT temperature error are equal to or greater than the preset cookware gear and IGBT temperature error, the effects of the load form, the temperature gradient of the load, the density and thermal conductivity of the load are set, and the effects of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, the cookware control gear, and the IGBT temperature are input into the thermal conductivity jump management algorithm for induction cookware with different materials to obtain the magnetic permeability per unit area of the bottom of the induction cookware.

[0115] When the cookware control gear and the IGBT temperature error are less than the preset cookware gear and IGBT temperature error, there is no need to set the effects of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, and the acquisition and analysis of the thermal conductivity of cookware materials at different temperatures and pressures within the statistical period are continued;

[0116] When the cookware control gear and the IGBT temperature error are equal to or greater than the preset cookware gear and IGBT temperature error, the effects of the load form, the temperature gradient of the load, the density and thermal conductivity of the load are set, and the effects of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, the cookware control gear, and the IGBT temperature are input into the thermal conductivity jump management algorithm for induction cookware with different materials to obtain the magnetic permeability per unit area of the bottom of the induction cookware.

[0117] S8. Analyze the data change trend of the cookware characteristic values of each power gear obtained by testing to distinguish the cookware type. When PanData[0]>PanData[1]>PanData[2]....>PanData[n] and the difference reaches the set value, it is judged that the characteristic of the cookware is a downward trend in the initial power gear; if PanData[0]<PanData[1]<PanData[2]....<PanData[n] and the difference reaches the set value, it is judged that the characteristic of the cookware is an upward trend in the initial power gear. When the value of PanData[n] is less than the preset change value, it is judged that this power interval belongs to a stable trend;

[0118] S9. Analyze the most suitable working power range of the cookware based on the cookware characteristic values of each power gear obtained by testing. According to the monitored array of cookware characteristic values, find the gear with the smallest value and its stable range, and give a suitable power output according to the application requirements.

[0119] In the analysis of the characteristics of cookware for induction cookers, understanding the performance change trend of cookware at different power levels is crucial for determining its optimal operating power range. Specifically, based on the changes in the characteristic values (such as temperature, thermal efficiency, etc.) of the cookware at each power level, the performance trend of the cookware can be analyzed, thereby identifying the type of cookware and determining the most suitable operating power range. This article will explain in detail how to distinguish the type of cookware by analyzing the change trend of the characteristic values of the cookware and determine the optimal power output range.

[0120] By analyzing the change trend of the characteristic values of the cookware at each power level, the heating characteristics of the cookware can be judged. If the characteristic values of the cookware (such as temperature or thermal efficiency) show a decreasing trend at each power level (i.e., PanData[0]>PanData[1]>PanData[2]...>PanData[n], and the difference between each level reaches the set change value), it can be judged that the cookware has the characteristic of "downward trend in the initial power level". At this time, the thermal efficiency or temperature of the cookware gradually decreases at higher power levels, which may be due to the excessive heat capacity or poor heat conduction performance of the cookware, resulting in its inability to effectively absorb more heat or reduce the heating efficiency at high power. On the contrary, if the characteristic values of the cookware show an increasing trend (i.e., PanData[0]<PanData[1]<PanData[2]...<PanData[n], and the difference reaches the set change value), it can be judged as an "upward trend in the initial power level". This situation usually indicates that the cookware has a lower absorption efficiency for lower power, but as the power increases, the heating effect of the cookware gradually improves, which may be because the thermal conductivity of the cookware material is stronger and can better utilize the energy of the induction cooker. In these two trends, the set value of the difference plays a crucial role, which helps to accurately identify the change of the trend and avoid misjudging the characteristics of the cookware due to minor fluctuations. In addition, if the change of the characteristic values of the cookware in a certain power range tends to be stable (i.e., the change value of PanData[n] is less than the preset change value), it can be judged that this range belongs to the "stable trend", meaning that the performance of the cookware at this power level tends to be stable and no obvious changes occur.

[0121] The array of pot characteristic values ​​obtained by the test can be further analyzed to find the most suitable working power range of the pot. The changing trend of the pot characteristic value at different power levels provides us with key information about the performance of the pot. Generally, the most suitable working power range of the pot means that the pot has the best heating efficiency or temperature control effect within this power range. In this process, we first need to find the gear with the smallest value and its stable range. The gear with the smallest value usually refers to the gear with the smallest change in the pot characteristic value and the most stable heating efficiency among all power levels. For example, if the temperature of the pot changes very little at a certain power level, it means that the heating efficiency of the pot at this level is very stable, which is usually the best working range of the pot. After determining the gear with the smallest value, we can further analyze the stable range around this gear, that is, the heating characteristic of the pot in this power range changes very little, showing a stable heating effect. Through these data analysis, we can find the best working power range of the pot, which provides an important reference for the power output of the induction cooker.

[0122] Based on the array of monitored pot characteristic values ​​and the most suitable working power range obtained, application requirements can help us determine a suitable power output. The core of this process is to combine the performance characteristics of the pot with the user's application needs. For example, for scenes that require rapid heating, a higher power gear may be selected to ensure that the pot quickly reaches the required temperature; for scenes that require long-term stable heating, a lower power gear may be selected to ensure that the pot maintains a constant temperature for a longer period of time. Through accurate analysis of the pot characteristic values ​​and reasonable selection of the power range, the heating effect and user experience of the induction cooker can be maximized. At the same time, by optimizing the power output, energy waste can be reduced, heating efficiency can be improved, and the needs of different users can be further met.

[0123] By analyzing the changing trend of the characteristic values ​​of the cookware at different power levels, we can not only distinguish the type of cookware, but also determine its most suitable working power range. In combination with actual application needs, reasonable adjustment of power output can not only improve the heating efficiency of the induction cooker, but also provide users with a more refined heating experience. This analysis process involves multiple technical links such as data monitoring, trend identification, and filtering processing, and ultimately realizes intelligent and precise heating control.

[0124] The preset cookware gear position and IGBT temperature error refer to a fixed value or range used to determine whether it is necessary to set the influence of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load. The preset cookware gear position and IGBT temperature error are preset based on the following factors: power load, IGBT rated voltage, switching frequency and over-temperature protection threshold, and on-resistance.

[0125] Furthermore, the preset pot gear position and IGBT temperature error is a dynamic process, which needs to be adjusted and optimized according to actual conditions. By constantly observing and analyzing the system operating status, unit area load change data and maintenance records, it is necessary to continuously optimize the preset pot gear position and IGBT temperature error to improve the accuracy and reliability of status monitoring management.

[0126] When the pot control gear and IGBT temperature error are less than the preset pot gear and IGBT temperature error, the evaluation results of different food doneness requirements of the induction cooker indicate that it is in a normal state. In this case, there is no need to set the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, and the collection and analysis of the thermal conductivity of the initial force cooker material can be continued to help monitor and collect the basic operating status of the induction cooker;

[0127] If the pot control gear and IGBT temperature are equal to or greater than the preset pot gear and IGBT temperature error, it indicates that the evaluation results of different food doneness requirements of the induction cooker indicate that there is a potential load change or abnormality per unit area. In this case, it is necessary to set the influence of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load, and input them together with the pot control gear and IGBT temperature of different food doneness requirements into the thermal conductivity jump management algorithm of the induction cooker load of different materials to obtain the magnetic permeability of the pot bottom per unit area of ​​the induction cooker;

[0128] The thermal conductivity jump management algorithm for induction cooker pots of different materials will comprehensively consider the thermal conductivity of the pot materials at different temperatures and pressures during the statistical period, the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, the preset pot control gear, and the IGBT temperature, and use the whale algorithm and other algorithms to calculate and analyze the attention mechanism, so as to determine the magnetic permeability per unit area of ​​the pot bottom of the induction cooker;

[0129] By comparing the pot control gear, IGBT temperature with the preset pot gear and IGBT temperature error, it is possible to quickly determine whether the induction cooker is in a normal state, thereby deciding whether it is necessary to set the influence of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load. If the pot control gear and IGBT temperature are less than the preset pot gear and IGBT temperature error, additional data collection and analysis can be avoided, saving time and resources.

[0130] When the pot control gear and IGBT temperature are equal to or greater than the preset pot gear and IGBT temperature error, the influence of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load are set, and they are input together with the pot control gear and IGBT temperature into the thermal conductivity jump management algorithm of the induction cooker pot load of different materials, which can provide accurate judgment of the magnetic permeability per unit area of ​​the pot bottom. By comprehensively considering multiple data information and preset parameters, and using algorithms such as the whale algorithm for attention mechanism calculation and analysis, the magnetic permeability per unit area of ​​the induction cooker pot can be accurately determined;

[0131] The determination of the preset pot gear position and IGBT temperature error is based on multiple factors. By comprehensively considering these factors, the preset pot gear position and IGBT temperature error suitable for specific induction cooker pots are formulated to improve the accuracy and reliability of status monitoring management; by observing and analyzing the system operating status, unit area load change data and maintenance records, the preset pot gear position and IGBT temperature error can be continuously optimized to adapt to the actual operating conditions of induction cooker pots and improve the accuracy and reliability of the monitoring algorithm.

[0132] This application uses multi-dimensional parameter analysis and intelligent algorithms to achieve full-process automation of pot feature identification and power optimization, with the advantages of high precision, wide adaptability and reliability. It not only improves the user experience of the induction cooker, but also greatly improves the heating efficiency and energy saving effect, and is suitable for complex scenarios with different types of pots.

[0133] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various equivalent changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for determining the characteristics of an induction cooker, characterized in that: The method comprises: S1. Collecting electromagnetic conversion load information of iron, steel, stainless steel and mixed materials of electromagnetic cookers, wherein the electromagnetic conversion load information of iron, steel, stainless steel and mixed materials includes thermal conductivity information of electromagnetic cooker loads of different diameters and bottom areas of different electromagnetic cookers, magnetic permeability of the bottom per unit area of ​​the cooker, and electromagnetic heating adaptability of the cooker per unit area; S2. According to the statistics of the thermal conductivity information of the induction cooker load, the thermal conductivity information of the induction cooker load is classified to obtain the thermal conductivity of the cooker materials at different temperatures and pressures within the statistical period, the influence of the load form, the temperature gradient of the load, and the density and thermal conductivity of the load; S3, uploading the thermal conductivity of the cookware materials at different temperatures and pressures, the influence of the load form, the temperature gradient of the load, the density and thermal conductivity of the load, and the corresponding different diameters and bottom areas of the induction cooker cookware, and the magnetic permeability of the bottom per unit area to the power control adaptive model, and establishing the thermal conductivity jump management algorithm of the induction cooker cookware load with different food doneness requirements and the thermal conductivity jump management algorithm of the induction cooker cookware load with different materials; S4. Collect the thermal conductivity of the cookware materials of different temperatures and pressures during the statistical period of the induction cooker per unit time, and input it into the thermal conductivity jump management algorithm of the induction cooker load with different food doneness requirements, so as to obtain the cookware control gear and IGBT temperature of the thermal conductivity jump management algorithm of the induction cooker load with different materials; S5. Given a power value, control the induction cooker to reach the set power value, determine that the power difference range is within the preset range, then record the pot characteristic value of the induction cooker at the power, filter the pot characteristic value and record it in the pot characteristic array PanData[]. Repeat the above operation until all the pot power characteristic values ​​of the set power levels are recorded; S6. Compare the pot control gear and IGBT temperature of the thermal conductivity jump management algorithm of the induction cooker pot load of different materials with the preset pot gear and IGBT temperature error: when the pot control gear and IGBT temperature error are less than the preset pot gear and IGBT temperature error, there is no need to set the influence of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load, and continue to collect and analyze the thermal conductivity of the pot materials of different temperatures and pressures within the statistical period; S7. When the pot control gear and IGBT temperature error are equal to or greater than the preset pot gear and IGBT temperature error, the influence of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load are set, and the influence of the load shape, the temperature gradient of the load, the density and thermal conductivity of the load, the pot control gear and the IGBT temperature are input into the thermal conductivity jump management algorithm of the induction cooker pot load of different materials to obtain the permeability of the pot bottom per unit area of ​​the induction cooker pot; S8. Analyze the data change trend of the cookware characteristic values of each power level obtained from the test to distinguish the cookware type. When PanData[0] > PanData[1] > PanData[2].... > PanData[n] and the difference reaches the set value, it is determined that the characteristic of this cookware is a downward trend in the initial power level; if PanData[0] < PanData[1] < PanData[2].... < PanData[n] and the difference reaches the set value, it is determined that the characteristic of this cookware is an upward trend in the initial power level. When the value of PanData[n] is less than the preset change value, it is determined that this power interval belongs to a stable trend. S9. Analyze the most suitable working power range of the cookware based on the cookware characteristic values of each power level obtained from the test. According to the monitored cookware characteristic value array, find the gear with the smallest value and its stable range, and give a suitable power output according to the application requirements.

2. The method for determining the characteristics of an induction cooker according to claim 1, wherein: The thermal conductivity information of the induction cooker cookware load includes the contact quality of the cookware during the operation of the induction cooker, the state of the cookware surface coating, heat flux and output power, bottom temperature of the cookware, bottom heat distribution, heat capacity of the cookware contents, and contact thermal resistance; the contact quality of the cookware and the state of the cookware surface coating are collected per unit time, and the heat flux and output power, bottom temperature of the cookware, bottom heat distribution, heat capacity of the cookware contents, and contact thermal resistance are collected per unit time according to the preset food doneness.

3. The method for determining the characteristics of an induction cooker according to claim 1, wherein: The thermal conductivity of cookware materials at different temperatures and pressures within the statistical period includes the contact quality of the cookware and the state of the cookware surface coating. The influence of the load form, temperature gradient of the load, density of the load, and thermal conductivity include heat flux and output power, bottom temperature of the cookware, bottom heat distribution, heat capacity of the cookware contents, and contact thermal resistance.

4. The method for determining the characteristics of an induction cooker according to claim 1, wherein: The input of the thermal conductivity jump management algorithm for different material induction cooker cookware loads is the influence of the load form, temperature gradient of the load, density of the load, and thermal conductivity, and the determined cookware control gear and IGBT temperature, and the output is the magnetic permeability per unit area of the bottom of the induction cooker cookware.

5. The method for determining the characteristics of an induction cooker according to claim 1, wherein: The running steps of the thermal conductivity jump management algorithm for induction cooker cookware loads with different food doneness requirements include: According to the relevant information of electromagnetic conversion loads of iron, steel, stainless steel, and mixed materials, sort out the thermal conductivity of cookware materials with different diameters and bottom areas of induction cooker cookware and the corresponding magnetic permeability per unit area of the bottom; process and perform spatio-temporal convolution on the thermal conductivity of cookware materials at different temperatures and pressures within the statistical period to convert the original data into practical features for use by the power control adaptive model. Using the power control adaptive model, calculate the data according to the prepared attention mechanism, perform model attention mechanism calculation using the selected algorithm, and adjust the parameters of the model; after the attention mechanism calculation is completed, extract the relevant parameters of the model as the output of the thermal conductivity jump management algorithm for induction cooker cookware loads with different food doneness requirements.

6. The method for determining the characteristics of an induction cooker according to claim 1, wherein: The running steps of the thermal conductivity jump management algorithm for different material induction cooker cookware loads include: According to the electromagnetic conversion load information of iron, steel, stainless steel and mixed materials, the influence of the load form of induction cookers, the temperature gradient of the load, the density and thermal conductivity of the load and the corresponding magnetic permeability of the bottom of the pot per unit area are sorted out; The whale algorithm is used for training, taking the influence of load shape, load temperature gradient, load density and thermal conductivity as independent variables, and the magnetic permeability of the bottom of the pot per unit area as the optimization target, to model the boundary conditions of the data and calculate the attention mechanism of the model; After the attention mechanism is calculated, the thermal conductivity jump management algorithm of the induction cooker pot load of different materials is used to predict the magnetic permeability of the pot bottom per unit area of ​​the induction cooker pot. The whale algorithm is used to calculate the information related to the electromagnetic conversion load of iron, steel, stainless steel and mixed materials, and the statistical deviation between the magnetic permeability of the pot bottom per unit area and the actual magnetic permeability of the pot bottom per unit area is calculated.

7. The method for determining the characteristics of an induction cooker according to claim 1, wherein: The method for collecting data on the influence of the load shape, the temperature gradient of the load, and the density and thermal conductivity of the load includes: using an air temperature monitoring device to monitor and collect the heat flow and output power of the induction cooker; monitoring and collecting the bottom temperature of the induction cooker based on an electric power equipment monitoring platform; monitoring and collecting the contact thermal resistance of the induction cooker, and analyzing the peak value and jump interval of the heat flow and output power changes; using a remote sensing system to monitor and collect the bottom heat distribution signal generated by the induction cooker; using a registration management system to collect the heat capacity of the pot contents around the induction cooker, and counting the influence of the heat capacity of different pot contents.

8. The method for determining the characteristics of an induction cooker according to claim 1, wherein: The preset influencing factors of the preset cookware gear position and IGBT temperature error include power load, IGBT rated voltage, switching frequency, over-temperature protection threshold and on-resistance.

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