Temperature measurement calibration method and system

Abstract

The invention provides a temperature measurement calibration method and system, and the method comprises the steps: putting food to be cooked into an oven cavity, and selecting corresponding food information on an operation panel; the temperature probe is inserted into the food, a heating program is started, the thermopile array sensor scans and measures the surface temperature of the food and transmits data to the main control module, and the temperature probe transmits the real-time measured internal temperature data of the food to the main control module; after the main control module receives the temperature data, a corresponding temperature correction coefficient matrix is called according to the selected food type, measurement data of the thermopile array sensor is calibrated, and the corrected food comprehensive temperature is obtained; and the main control module dynamically adjusts the heating power and time according to the corrected food comprehensive temperature data and preset cooking target temperature and food type information. By optimizing the installation position of the sensor, designing an anti-interference and self-cleaning mechanism and combining an accurate correction algorithm, high-precision measurement and calibration of the food temperature are achieved, accurate data support is provided for intelligent food cooking, accurate intelligent regulation and control of the food heating process are achieved, and the cooking effect and the user experience are improved.

Description

Technical Field

[0001] The present invention relates to the field of temperature measurement and control of cooking appliances that require heating, such as microwave ovens or ovens, and in particular to a system that utilizes a temperature probe to perform temperature measurement and calibration on a thermopile array sensor and is applied to a method for intelligent food cooking. Background Art

[0002] In the field of modern kitchen appliances, microwave ovens are widely used due to their efficient and fast heating characteristics. However, traditional microwave ovens have significant deficiencies in accurate temperature measurement and control. Most traditional microwave ovens rely on simple single-point temperature sensors or preset heating programs to operate, making it difficult to accurately sense the actual temperature changes and distribution of food during the heating process. This results in the phenomenon of partial overheating or undercooking of food during the cooking process, which seriously affects the taste and quality of the food, and cannot meet the growing demand for intelligent food cooking.

[0003] As an emerging temperature measurement technology, the thermopile array sensor has the advantages of multi-pixel points and non-contact measurement of temperature distribution over a large area, providing a new way to improve the temperature measurement scheme of microwave ovens. For example, the patent with the publication number CN117990217A in the prior art discloses a temperature sensing device that can be used for intelligent devices such as microwave ovens, which uses dual thermopile sensor elements to compensate for the thermal shock effect caused by the air temperature disturbance inside the microwave oven, and adopts a narrow viewing angle optical design to measure the surface temperature of the object as accurately as possible without being affected by the background ambient temperature. However, the prior art only reduces the thermal shock effect of the packaging shell by improving the storage device of the thermopile sensor, and cannot accurately sense the actual temperature change and distribution of the food during the heating process, especially the internal temperature of the food, and cannot eliminate the influence of factors such as the complex electromagnetic environment in the microwave oven, which leads to certain errors in the temperature data directly measured by the thermopile array sensor. It is necessary to combine other precise measurement methods for calibration and correction to achieve accurate monitoring and control of the food temperature, which affects the taste and quality of the food. Summary of the invention

[0004] In view of this, the present invention aims to propose a temperature measurement calibration method and system to solve the problem that the temperature measurement of traditional cooking utensils such as microwave ovens or ovens is inaccurate and cannot fully reflect the temperature distribution of food, while also solving the problems of thermopile array sensors being interfered by microwaves, being easily contaminated, and having large measurement errors.

[0005] To achieve the above object, the technical solution of the present invention is achieved as follows:

[0006] A temperature measurement calibration method, comprising:

[0007] Put the food to be cooked into the oven cavity and select the corresponding food information on the operation panel;

[0008] Insert the temperature probe into the food, start the heating program, the thermopile array sensor scans and measures the surface temperature of the food, and transmits the data to the main control module, and the temperature probe transmits the real-time measured internal temperature data of the food to the main control module;

[0009] After receiving the temperature data, the main control module calls the corresponding temperature correction coefficient matrix according to the selected food type, calibrates the measurement data of the thermopile array sensor, and obtains the corrected comprehensive temperature of the food;

[0010] The main control module dynamically adjusts the heating power and time based on the corrected food comprehensive temperature data and the preset cooking target temperature and food type information.

[0011] Furthermore, after the heating program is started, the thermopile array sensor performs non-contact temperature scanning measurement on the surface temperature of the food at set time intervals.

[0012] Furthermore, after receiving the temperature data, the main control module calls the corresponding temperature correction coefficient matrix according to the selected food type, and uses the correction algorithm to calibrate the measurement data of the thermopile array sensor to obtain the corrected comprehensive temperature of the food.

[0013] Furthermore, the correction algorithm includes:

[0014] The thermopile array sensor performs non-contact temperature scanning on the food surface at set time intervals to obtain the temperature value matrix T corresponding to each pixel point. arr (i, j); and transmit the matrix data to the main control chip, and insert the temperature probe inside the food to continuously measure the internal temperature T of the food pro , and transmit the data to the main control chip;

[0015] Calculate the average surface temperature measured by a thermopile array sensor

[0016] Calculate the difference matrix between each pixel temperature and the average temperature ΔT(i,j)=T arr (i,j)-T avg ;

[0017] According to the temperature value matrix T arr (i, j), food internal temperature T pro , average surface temperature T avg The corrected temperature matrix T is calculated by using the temperature correction coefficient matrix C(i, j, k) pre-stored in the storage unit. cor (i,j).

[0018] Furthermore, the correction coefficient matrix C(i,j,k) is obtained by conducting heating experiments on various representative foods in a laboratory environment.

[0019] Furthermore, the correction coefficient matrix C(i, j, k) is determined based on in-depth research and data analysis on the relationship between the internal temperature and the surface temperature of various types of food at different heating stages.

[0020] Furthermore, the correction coefficient matrix C(i,j,k) is determined according to the multivariate linear regression model.

[0021] A temperature measurement and calibration system, capable of implementing the temperature measurement and calibration method described above, comprises:

[0022] The oven cavity is used to hold food, and a flat plate is provided at the bottom of the oven cavity, on which the food sample is placed.

[0023] The thermopile array sensor device is arranged on at least one of the side wall of the oven cavity, the rear wall of the oven cavity and the top plate of the oven cavity to obtain the surface temperature of the food.

[0024] A main control module, the thermopile array sensor device is connected to the main control module, and the thermopile array sensor transmits the collected temperature data to the main control module in real time for processing;

[0025] A temperature probe, one end of which is connected to the main control module, and the other end of which can be selectively inserted into the food to obtain the internal temperature data of the food;

[0026] The main control module dynamically adjusts the heating power and time of the cooking appliance according to the corrected comprehensive temperature data and the preset cooking target temperature and food type information.

[0027] Furthermore, the thermopile array sensor device is arranged at a central position of a furnace cavity top plate or at a rear wall of the furnace cavity and close to the top plate.

[0028] Furthermore, the temperature probe and the infrared thermopile array sensor device are connected and arranged on two surfaces inside the furnace cavity.

[0029] Compared with the prior art, the temperature measurement calibration method and system described in the present invention have the following advantages:

[0030] (1) Accurate temperature measurement and control: By combining the multi-pixel point measurement of the thermopile array sensor with the internal temperature monitoring of the temperature probe and using a specific correction algorithm, the accuracy and comprehensiveness of food temperature measurement can be significantly improved, effectively solving the single-point and inaccurate temperature measurement problems of traditional microwave ovens, achieving precise control of the food heating process, and greatly improving the cooking effect and food quality. The unique sensor installation protection design effectively resists microwave interference and oil contamination, ensuring long-term stable and accurate measurement.

[0031] (2) Intelligent cooking experience: Based on accurate temperature measurement and calibration data, cooking utensils can automatically adjust heating parameters according to the real-time temperature of the food without manual intervention by the user, thus achieving truly intelligent food cooking. This not only improves the convenience and success rate of cooking, but also meets the diverse cooking needs of different users for various foods, bringing users a new intelligent kitchen experience. This will in turn promote the development of intelligent cooking technology.

[0032] (3) Wide applicability and scalability: The technical solution of the present invention can be applied to microwave ovens of various types and specifications and is not limited to a specific microwave oven structure design. At the same time, with the in-depth study of the temperature characteristics of different foods and the continuous improvement of the correction coefficient matrix, this method can be easily expanded to the intelligent cooking of more types of food, and has broad market application prospects and technical development potential. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of an infrared thermopile array sensor device according to an embodiment of the present invention;

[0034] Figure 2 A schematic diagram of a microwave oven measuring device according to an embodiment of the present invention;

[0035] Figure 3 This is a calibration process of the infrared thermopile array sensor described in an embodiment of the present invention.

[0036] Description of reference numerals:

[0037] 1-printed circuit board, 2-furnace cavity top plate, 3-infrared thermopile array sensor lens, 4-shielding cover, 5-light-transmitting film, 6-infrared thermopile array sensor device, 7-temperature probe interface, 8-food sample, 9-temperature probe, 10-plate, 11-furnace body DETAILED DESCRIPTION

[0038] In order to make the above-mentioned objects, features and advantages of the present invention more clearly understood, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In addition, the directions involved in the following specific embodiments are briefly described: the directions or positional relationships indicated by "front", "rear", "upper", "lower", "left", "right", "top", "bottom" and the like mentioned in the embodiments refer to the directions or positional relationships shown in the accompanying drawings, and the term "on..." refers to being supported by... elements or indirectly.

[0039] It should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or mutual communication; it can be directly connected, or indirectly connected through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0040] like Figures 1-2 As shown, a cooking utensil temperature measurement and calibration system includes a furnace body 11, a furnace cavity for holding food, and an infrared thermopile array sensor device 6. A flat plate 10 is also arranged at the bottom of the furnace cavity, and a food sample 8 is placed on the flat plate 10. The infrared thermopile array sensor device 6 is arranged on at least one of the furnace cavity side wall, the furnace cavity rear wall and the furnace cavity top plate 2 to obtain the surface temperature of the food. The calibration system also includes a temperature probe 9 and a main control module. One end of the temperature probe 9 is connected to the main control module, and the other end can be selectively inserted into the food to obtain the internal temperature data of the food, so that the internal food data detected by the temperature probe 9 is transmitted to the main control module in real time. At the same time, the infrared thermopile array sensor device 6 is also connected to the main control module. The infrared thermopile array sensor transmits the collected temperature data to the main control module in real time for processing. The main control module uses an intelligent control algorithm to dynamically adjust the heating power and time of the cooking utensil according to the corrected comprehensive temperature data and the preset cooking target temperature and food type information.

[0041] The temperature probe 9 is a high-temperature resistant and high-precision temperature probe. It is inserted into the core position of the food sample 8 (such as the center of a block of food or the middle layer of a thick layer of food) before the food sample 8 is placed in the oven cavity. The temperature probe 9 is connected to the main control module of the oven body through an interface to obtain the internal temperature data of the food. The temperature probe 9 and the main control module are hingedly arranged so that one end of the temperature probe 9 for detecting the internal temperature of the food is formed as a free end, which is convenient for adjusting the insertion position of the temperature probe 9 according to the position or shape of the food sample 8, and then convenient for accurately measuring the temperature of a certain part of the food according to the characteristics of the food, thereby realizing accurate temperature measurement.

[0042] Further, a probe interface 7 is provided on at least one of the oven cavity side wall, the oven cavity rear wall and the oven cavity top plate 2, the probe interface 7 is internally connected to the main control module, and the temperature probe 9 is connected to the main control module through the probe interface 7. Preferably, the probe interface 7 is provided on the oven cavity side wall or at a position of the oven cavity side wall near the cavity access opening, so as to facilitate the operation of inserting the temperature probe into the food.

[0043] In this embodiment, the infrared thermopile array sensor device 6 is preferably set at the center of the oven cavity top plate, which can cover the food surface area to the greatest extent, reduce the measurement blind spot, and facilitate the acquisition of comprehensive food surface temperature information. Further, the pixel point specification can adopt 8×8 or higher pixel density (such as 16×16, 32×32, etc.) to ensure that the surface area of ​​the heated food can be fully and meticulously covered, and high-precision detection of food surface temperature distribution can be achieved.

[0044] As one embodiment of the present invention, the temperature probe 9 and the infrared thermopile array sensor device 6 are connected and arranged on two surfaces inside the oven cavity, that is, the two are not on the same wall surface inside the oven cavity. For example, the infrared thermopile array sensor device 6 can also be arranged on the rear wall of the oven cavity and close to the top plate, so that the infrared thermopile array sensor device 6 captures as complete an image of the food sample inside the oven cavity as possible with a downward angle of view, so as to fully and accurately obtain the surface temperature of the food sample. At the same time, the probe interface 7 is arranged on the left wall or the right wall inside the oven cavity.

[0045] Further, the infrared thermopile array sensor device 6 includes a printed circuit board 1, an infrared thermopile array sensor lens 3, a shielding cover 4 and a light-transmitting film 5, wherein the printed circuit board 1 is arranged on the top plate of the furnace cavity and fits with the top surface of the furnace cavity, the infrared thermopile array sensor lens 3 is connected to the printed circuit board 1 and extends downwardly, and a shielding cover 4 is arranged on the periphery of the lens 3, and the shielding cover 4 is arranged as an open metal shielding cover structure, and the shielding cover 4 is selected from high magnetic permeability metal materials, such as Permalloy, to effectively absorb and guide the magnetic field generated by microwaves to resist microwave or electromagnetic interference, and ensure the accuracy of temperature measurement of the infrared thermopile array sensor lens 3. On the side of the shielding cover 4 facing the food, a temperature measurement window matching the pixel distribution of the thermopile array sensor is opened, and the window is covered with a light-transmitting film 5 that is resistant to oil stains, so as to ensure that the sensor can normally sense the temperature of the food inside the furnace cavity, and at the same time avoid the oil stains generated when heating the food from contaminating the shielding cover and the sensor. Preferably, the light-transmitting film 5 can be selected from a high-transmittance polytetrafluoroethylene film or other structures that can achieve the same or similar functions, to ensure that the sensor can measure the temperature normally while preventing oil stains from being contaminated.

[0046] Therefore, the temperature measurement and calibration system of this embodiment monitors the surface temperature of food through the infrared thermopile array sensor device 6, detects the internal temperature of the food sample through the temperature probe 9, and sends the detected temperature to the main control module, which uses the intelligent control algorithm to dynamically adjust the cooking heating power and time based on the corrected comprehensive temperature data and the preset cooking target temperature and food type information. For example, if it is detected that the surface temperature of a certain area of ​​the food has approached or reached the target temperature, while the temperature of other areas is lower, the microwave transmission power is phased down to wait for heat conduction to achieve uniform heating of the food. During the entire cooking process, the above temperature measurement, correction and power adjustment steps are continuously repeated until the food as a whole reaches the preset cooking target temperature range or the cooking time is over, ensuring that the food is cooked under the optimal temperature conditions, and realizing intelligent and precise cooking control. By optimizing the sensor installation position, designing anti-interference and self-cleaning mechanisms, and combining accurate correction algorithms, high-precision measurement and calibration of food temperature are achieved, providing accurate data support for intelligent food cooking, achieving accurate intelligent regulation of food cooking and heating process, and improving cooking effects and user experience.

[0047] As part of the embodiment of the present invention, a cooking utensil temperature measurement and calibration method is also provided. The temperature measurement and calibration method adopts the temperature measurement and calibration system described above. The cooking utensil described in the present invention may be a common cooking utensil such as a microwave oven, a smart oven, a steamer, etc. Taking a microwave oven as an example, the specific calibration method includes the following steps:

[0048] S100, equipment installation and commissioning. According to the temperature measurement and calibration system described above, connect the lines of each sensor and the main control module circuit board, initialize and calibrate the sensor, and perform functional tests on the entire temperature measurement system to ensure that the thermopile array sensor and temperature probe can work normally and accurately transmit data.

[0049] The temperature correction coefficient matrices corresponding to different types of food are pre-stored in the storage unit of the microwave oven, etc. These coefficient matrices are obtained by conducting a large number of microwave heating experiments on various representative foods (such as pork, beef, potatoes, broccoli, cake, etc.) in a laboratory environment. During the experiment, a high-precision temperature probe is used as a reference standard, and the surface temperature data of the thermopile array sensor and the internal temperature data of the temperature probe are measured at the same time. Through statistical analysis and fitting processing of multiple groups of experimental data, the temperature correction coefficient matrices of different foods at different heating stages are determined and solidified in the storage chip of the microwave oven.

[0050] S200, cooking operation process. It includes the following detailed steps:

[0051] S210, putting the food to be cooked into the oven cavity, and selecting the corresponding food (basic information such as type, weight, volume, etc.) on the operation panel.

[0052] S220: After putting the food in, insert the temperature probe into a suitable position inside the food, and then start the heating program.

[0053] S230, the main control module starts the temperature measurement and calibration program, and the thermopile array sensor performs non-contact temperature scanning measurement on the surface temperature of the food at the set time interval and transmits the data to the main control module. At the same time, the temperature probe also transmits the real-time measured internal temperature data of the food to the main control module.

[0054] S240, after receiving the temperature data, the main control module calls the corresponding temperature correction coefficient matrix according to the selected food type, and uses the correction algorithm to calibrate the measurement data of the thermopile array sensor to obtain the corrected food comprehensive temperature.

[0055] S250, the main control module uses an intelligent control algorithm to dynamically adjust the heating power and time based on the corrected comprehensive temperature data and the preset cooking target temperature and food type information. During the cooking process, the temperature measurement, correction and power adjustment steps are repeated until the food as a whole reaches the preset cooking target temperature range or the cooking time ends.

[0056] S300, measurement and correction algorithm. The correction algorithm includes:

[0057] S310, when the microwave oven starts the heating program, the thermopile array sensor performs non-contact temperature scanning measurement on the food surface at a set time interval to obtain the temperature value matrix T corresponding to each pixel point arr (i, j) where i and j represent the row and column indices of the pixel in the array respectively), and transmit the matrix data to the main control chip. At the same time, the temperature probe inserted into the food continuously measures the internal temperature T of the food. pro and transmit the data to the main control chip.

[0058] The time interval is set to 0.3 to 5 seconds, for example, it can be set to a time interval of 1 second.

[0059] S320, first perform data preprocessing:

[0060] Calculate the average surface temperature measured by a thermopile array sensor (where m and n are the number of rows and columns of the thermopile array, respectively)

[0061] Calculate the difference matrix between each pixel temperature and the average temperature ΔT(i,j)=T arr (i,j)-T avg .

[0062] S330, then, based on a large amount of experimental data, a temperature correction coefficient matrix C(i,j,k) corresponding to different food types (such as meat, vegetables, cakes, etc.) is pre-established (k is the food type index), and the matrix is ​​stored in the storage unit of the microwave oven. The determination of the correction coefficient matrix is ​​based on in-depth research and data analysis on the relationship between the internal temperature and the surface temperature of various types of food at different heating stages.

[0063] In order to determine the correction coefficient matrix C(i,j,k) more accurately, the following multivariate linear regression model is introduced:

[0064] Assume that the internal temperature of the food is T pro With surface temperature T arr (i, j) and some other measurable or predictable influencing factors (such as the initial temperature of the food T o , food weight m, volume V, heating time t, there is a linear relationship, we can establish the following model:

[0065] T pro =β0+β1T arr (i,j)+β2T0+β3m+β4V+β5t+ε

[0066] Among them, β0, β1, β2, β3, β4, β5 are regression coefficients, and ε is the error term.

[0067] Through a large amount of experimental data, these regression coefficients can be solved using regression analysis methods such as the least squares method. The elements in the correction coefficient matrix C(i,j,k) are related to β1 and other factors, for example:

[0068] C(i,j,k)=β1×f(T0,m,V,t)

[0069] Among them, f(T0,m,V,t) is a function that comprehensively considers the effects of the initial temperature, volume and heating time of the food. For example, for some foods, when the volume is large, the delay effect of the internal temperature being transmitted to the surface is more obvious, so the coefficient of weight m in f(T0,m,V,t) may be large, causing C(i,j,k) to change accordingly.

[0070] S340, finally, calculate the corrected temperature matrix T cor (i,j):

[0071] T cor (i,j)=T arr (i,j)+C(i,j,k)×(T pro -T avg )=T arr(i,j)+β1×f(T0,m,V,t)×(T pro -T avg )

[0072] This algorithm is based on the principle that there is a certain correlation between the internal temperature and surface temperature of food. It uses the difference between the internal temperature measured by the temperature probe and the average surface temperature measured by the thermopile array sensor, combined with the correction coefficient matrix, to calibrate the comprehensive temperature, thereby obtaining food temperature data that is closer to the actual value.

[0073] S400, data update and optimization.

[0074] 1. During daily use, microwave ovens can regularly upload stored cooking data to a cloud server or the manufacturer's data analysis center through wireless communication modules (such as Wi-Fi or Bluetooth modules). The manufacturer's technicians conduct in-depth mining and analysis of the large amount of user cooking data collected, and further optimize the temperature correction coefficient matrix for different food types based on factors such as the eating habits of users in different regions, differences in ingredients, and the microwave oven usage environment.

[0075] 2. The manufacturer will push the optimized temperature correction coefficient matrix to the user's microwave oven through network update. The user can choose manual update or set it to automatic update mode on the microwave oven's operation panel, so that the microwave oven always maintains the best temperature measurement and cooking control performance, continuously improving the user experience and product intelligence level.

[0076] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the scope defined by the claims.

Claims

1. A temperature measurement calibration method, characterized in that: include: Put the food to be cooked into the oven cavity and select the corresponding food information on the operation panel; Insert the temperature probe into the food, start the heating program, the thermopile array sensor scans and measures the surface temperature of the food, and transmits the data to the main control module, and the temperature probe transmits the real-time measured internal temperature data of the food to the main control module; After receiving the temperature data, the main control module calls the corresponding temperature correction coefficient matrix according to the selected food type, calibrates the measurement data of the thermopile array sensor, and obtains the corrected comprehensive temperature of the food; The main control module dynamically adjusts the heating power and time based on the corrected food comprehensive temperature data and the preset cooking target temperature and food type information.

2. The temperature measurement calibration method according to claim 1, characterized in that: After the heating process is started, the thermopile array sensor performs non-contact temperature scanning measurement of the food surface temperature at set time intervals.

3. The temperature measurement calibration method according to claim 1, characterized in that: After receiving the temperature data, the main control module calls the corresponding temperature correction coefficient matrix according to the selected food type, and uses the correction algorithm to calibrate the measurement data of the thermopile array sensor to obtain the corrected comprehensive food temperature.

4. The temperature measurement calibration method according to claim 3, characterized in that: The correction algorithm includes: The thermopile array sensor performs non-contact temperature scanning on the food surface at set time intervals to obtain the temperature value matrix T corresponding to each pixel point. arr (i, j); and transmit the matrix data to the main control chip, and insert the temperature probe inside the food to continuously measure the internal temperature T of the food pro , and transmit the data to the main control chip; Calculate the average surface temperature measured by a thermopile array sensor Calculate the difference matrix between each pixel temperature and the average temperature ΔT(i,j)=T arr (i,j)-T avg ; According to the temperature value matrix T arr (i, j), food internal temperature T pro , average surface temperature T avg The corrected temperature matrix T is calculated by using the temperature correction coefficient matrix C(i, j, k) pre-stored in the storage unit. cor (i,j).

5. The temperature measurement calibration method according to claim 4, characterized in that: The correction coefficient matrix C(i,j,k) is obtained by conducting heating experiments on various representative foods in a laboratory environment.

6. The temperature measurement calibration method according to claim 4, characterized in that: The correction coefficient matrix C(i, j, k) is determined based on in-depth research and data analysis on the relationship between the internal temperature and the surface temperature of various types of food at different heating stages.

7. The temperature measurement calibration method according to claim 4, characterized in that: The correction coefficient matrix C(i,j,k) is determined based on the multivariate linear regression model.

8. A temperature measurement calibration system, characterized in that: The temperature measurement calibration method according to any one of claims 1 to 7 can be implemented, and the system comprises: The oven cavity is used for holding food, and a flat plate (10) is arranged at the bottom of the oven cavity. The food sample (8) is placed on the flat plate (10). The thermopile array sensor device (6) is arranged on at least one of the side wall of the oven cavity, the rear wall of the oven cavity and the top plate (2) of the oven cavity to obtain the surface temperature of the food. A main control module, the thermopile array sensor device (6) is connected to the main control module, and the thermopile array sensor transmits the collected temperature data to the main control module in real time for processing; A temperature probe (9), one end of which is connected to the main control module, and the other end of which can be selectively inserted into the food to obtain the internal temperature data of the food; The main control module dynamically adjusts the heating power and time of the cooking appliance according to the corrected comprehensive temperature data and the preset cooking target temperature and food type information.

9. The temperature measurement calibration system according to claim 8, characterized in that: The thermopile array sensor device (6) is arranged at the center of the furnace cavity top plate (2) or at the rear wall of the furnace cavity and close to the top plate.

10. The temperature measurement calibration system according to claim 8, characterized in that: The temperature probe (9) and the infrared thermopile array sensor device (6) are connected and arranged on two surfaces inside the furnace cavity.

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