Food material unfreezing method and system and intelligent electric appliance
By determining the position and thickness of food ingredients through the temperature distribution within the cavity of the smart appliance and calculating the thawing time, the problem of food ingredients thawing on the surface but not inside in existing technologies is solved, achieving uniform and safe thawing of food ingredients.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-09
- Publication Date
- 2026-04-10
AI Technical Summary
When existing home appliances determine the thawing status by detecting the surface characteristics of food, they are prone to situations where the surface of the food is thawed but the inside is not, resulting in insufficient thawing and poor results.
Based on the temperature distribution within the cavity of the smart appliance, the location and thickness of the food are determined by temperature difference information, and the target thawing time is calculated by combining preset thawing parameters to achieve uniform thawing.
This ensures that ingredients thaw evenly, improves the thawing effect, and guarantees the safety and quality of the ingredients.
Smart Images
Figure CN121817252A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of intelligent electrical appliances, and in particular to a food material thawing method and system and an intelligent electrical appliance. BACKGROUND
[0002] With the improvement of people's living quality, the popularization and application of Internet, big data, artificial intelligence and voice interaction technology, more and more traditional lifestyles are gradually changing, and the use of household appliances has gradually moved towards intelligentization. While bringing more convenience to users, the functions of various household appliances tend to be diversified.
[0003] For existing household appliances with thawing function, they usually determine whether thawing is completed by detecting the temperature, color and texture of the surface of the food material in real time. However, according to the characteristics of the surface of the food material to determine the thawing state, it is easy to cause the situation that the surface of the food material is thawed while the inside is not thawed, and there is a problem of insufficient thawing and poor thawing effect of the food material. SUMMARY
[0004] In order to solve the above technical problems, the present application discloses a food material thawing method, system and intelligent electrical appliance, which determines the food material position information corresponding to the target food material based on the temperature distribution of the cavity, determines the thickness of the target food material based on the food material position information, and then determines the target thawing time based on the thickness of the target food material, thereby improving the thawing effect of the target food material.
[0005] In one aspect, the present application provides a food material thawing method, which is applied to an intelligent electrical appliance, and the method comprises: In response to a food material thawing instruction, the temperature distribution of the cavity of the intelligent electrical appliance and the preset thawing parameters corresponding to the target food material are obtained; the temperature distribution of the cavity comprises a first area temperature distribution and a second area temperature distribution, the first area temperature distribution is the temperature distribution corresponding to the bearing area in the target cavity of the intelligent electrical appliance, and the second area temperature distribution is the temperature distribution corresponding to other areas in the target cavity except the bearing area; Based on the temperature difference information of the first area temperature distribution and the second area temperature distribution, the food material position information corresponding to the target food material is determined; The thickness of the target food material is determined based on the food material position information; The target thawing time corresponding to the target food material is obtained by performing data fusion processing on the target food material thickness and the preset thawing parameters; A thawing execution instruction is generated based on the target thawing time and the preset thawing parameters; the thawing execution instruction is used to instruct the intelligent electrical appliance to thaw the target food material according to the target thawing time and the preset thawing parameters.
[0006] In some embodiments, determining the location information of the target ingredient based on the temperature difference information between the temperature distribution of the first region and the temperature distribution of the second region includes: The target temperature threshold is determined based on the temperature difference information. Based on the target temperature threshold, the target food temperature point corresponding to the target food is determined from the temperature distribution of the second region; the temperature corresponding to the target food temperature point is less than the target temperature threshold. The location information corresponding to the temperature point of the target food ingredient is determined as the location information of the food ingredient.
[0007] In some embodiments, determining the target temperature threshold based on the temperature difference information includes: The absolute value of the difference between the first average temperature corresponding to the temperature distribution in the first region and the second average temperature corresponding to the temperature distribution in the second region is determined as the temperature difference information. A preset temperature coefficient is determined based on the temperature difference information; The preset temperature coefficient, the first average temperature, and the second average temperature are fused to obtain the target temperature threshold.
[0008] In some embodiments, determining the target food thickness based on the food location information includes: The initial thickness sequence corresponding to the target ingredient is determined based on the ingredient position information corresponding to the temperature point of each column of target ingredients; the initial thickness sequence includes the initial ingredient thickness corresponding to the temperature point of each column of target ingredients. The thickness of the target food ingredient is determined based on the initial thickness sequence.
[0009] In some embodiments, determining the target food thickness based on the initial thickness sequence includes: The initial food thickness in the initial thickness sequence is subjected to thickness correction processing to obtain the target thickness sequence; The cross-sectional area of the target food ingredient is determined based on the target thickness sequence; The thickness of the target food ingredient is determined based on the cross-sectional area.
[0010] In some embodiments, performing thickness correction processing on the initial food thickness in the initial thickness sequence to obtain the target thickness sequence includes: Based on the mean thickness and standard deviation of the thickness corresponding to the initial thickness sequence, abnormal thicknesses are determined from the initial food thickness; The abnormal thickness is replaced with the neighborhood thickness to obtain the target thickness sequence; the neighborhood thickness is determined based on the initial food thickness adjacent to the abnormal thickness in the initial thickness sequence.
[0011] In some embodiments, determining abnormal thicknesses from the initial food thicknesses based on the mean thickness and standard deviation of the initial thickness sequence includes: Potential outlier conditions are determined based on the mean thickness and the standard deviation of thickness. The initial food thickness that satisfies the potential outlier condition in the initial thickness sequence is determined as the potential outlier thickness; If the number of potential outlier thicknesses is less than a preset threshold, the potential outlier thickness is determined as the abnormal thickness.
[0012] In some embodiments, the preset thawing parameters include the food density, thermophysical properties, and thawing temperature corresponding to the target food, and the step of performing data fusion processing on the thickness of the target food and the preset thawing parameters to obtain the target thawing time corresponding to the target food includes: The initial temperature of the target ingredient is determined based on the temperature information corresponding to the temperature point of the target ingredient. The target thawing time is obtained by fusing data of the initial temperature of the food, the thickness of the target food, the density of the food, the thermophysical parameters, and the thawing temperature.
[0013] On the other hand, this application also provides a smart appliance that uses the food defrosting method described above, and the smart appliance is one of a microwave oven, a steam oven, or an air fryer.
[0014] On the other hand, this application also provides a food thawing system, the system including a data acquisition terminal and a controller; The acquisition terminal is used to acquire the cavity temperature distribution of the smart appliance and send the cavity temperature distribution to the controller; The controller is used to execute the food thawing method as described above.
[0015] Implementing the embodiments of this application has the following beneficial effects: The food thawing method disclosed in this application determines the location information of the target food based on temperature differences between different regions within the target cavity of a smart appliance. Based on this location information, the thickness of the target food is determined, and then a target thawing time is determined based on the thickness. The food is then thawed according to this target thawing time. By considering the thickness of the target food when determining the target thawing time, the method ensures uniform thawing, improves the thawing effect, and simultaneously guarantees the safety and quality of the food. Attached Figure Description
[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] Figure 1 A schematic flowchart illustrating a method for thawing food provided in an embodiment of this application; Figure 2 A schematic diagram of a target cavity provided in an embodiment of this application; Figure 3 A flowchart illustrating a method for determining the location information of food ingredients provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a smart appliance provided in an embodiment of this application; Figure 5 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.
[0019] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. Furthermore, the terms "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such information can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in a sequence other than that illustrated or described herein.
[0020] The food defrosting system provided in this application includes a data acquisition end and a controller. The data acquisition end refers to an infrared sensor deployed in the target cavity of a smart appliance, and the controller refers to the controller of the smart appliance. The smart appliance can be one of the kitchen appliances with defrosting functions, such as a microwave oven, a steam oven, or an air fryer.
[0021] The acquisition terminal is used to acquire the cavity temperature distribution of the smart appliance and send the cavity temperature distribution to the controller; The controller is configured to, in response to a food defrosting command, acquire the cavity temperature distribution of the smart appliance and preset defrosting parameters corresponding to the target food; the cavity temperature distribution includes a first region temperature distribution and a second region temperature distribution, the first region temperature distribution being the temperature distribution corresponding to the bearing area in the target cavity of the smart appliance, and the second region temperature distribution being the temperature distribution corresponding to other areas in the target cavity besides the bearing area; based on the temperature difference information between the first region temperature distribution and the second region temperature distribution, determine the food location information corresponding to the target food; determine the thickness of the target food based on the food location information; perform data fusion processing on the thickness of the target food and the preset defrosting parameters to obtain the target defrosting time corresponding to the target food; generate a defrosting execution command based on the target defrosting time and the preset defrosting parameters; the defrosting execution command is used to instruct the smart appliance to defrost the target food according to the target defrosting time and the preset defrosting parameters.
[0022] See Figure 1 , Figure 1 This is a flowchart illustrating a method for thawing food provided in an embodiment of this application. The method is applied to the controller of a smart appliance and includes: S101, in response to the food defrosting command, the cavity temperature distribution of the smart appliance and the preset defrosting parameters corresponding to the target food are obtained; the cavity temperature distribution includes a first region temperature distribution and a second region temperature distribution, the first region temperature distribution is the temperature distribution corresponding to the bearing area in the target cavity of the smart appliance, and the second region temperature distribution is the temperature distribution corresponding to other areas in the target cavity other than the bearing area. In some embodiments, the food defrosting instruction can be generated based on the user's operation of triggering the defrosting function after placing the target food into the smart appliance; the target food is the food to be defrosted; the preset defrosting parameters corresponding to the target food are determined based on the food type of the target food, which can be input or selected by the user, or determined by the sensor deployed in the target cavity of the smart appliance after identifying the target food.
[0023] In some embodiments, an infrared sensor for collecting the temperature distribution within the cavity is disposed on the inner wall of the smart appliance; see also Figure 2 , Figure 2This is a schematic diagram of a target cavity provided in an embodiment of this application. The target cavity of the smart appliance is divided into two parts: a first region and a second region. The first region refers to the bearing region, i.e., the tray region. The bottom 20% of the target cavity is the first region. The second region refers to the other regions in the target cavity besides the first region. The top 80% of the target cavity is the second region. The second region includes the target food. The cavity temperature distribution refers to the cavity temperature distribution at the moment when the controller of the smart appliance receives the food defrosting command.
[0024] S103, based on the temperature difference information between the temperature distribution of the first region and the temperature distribution of the second region, determine the location information of the target ingredient; In some embodiments, a target temperature threshold can be obtained based on the temperature difference information between the temperature distribution of the first region and the temperature distribution of the second region. By comparing the target temperature threshold with the temperature information corresponding to each temperature point in the cavity temperature distribution, the target food temperature point corresponding to the target food can be determined from each temperature point involved in the cavity temperature distribution. Then, the food location information corresponding to the target food can be determined based on the location information corresponding to the target food temperature point.
[0025] S105, determine the thickness of the target ingredient based on the ingredient location information; In some embodiments, for Figure 2 The schematic diagram of the target cavity shown can be used to establish a coordinate system with the lower left corner as the origin, the horizontal direction as the x-axis, and the vertical direction as the y-axis. The position information of the target ingredient is the coordinate information of the temperature point of the target ingredient. Based on the coordinate information of the temperature point of the target ingredient, the cross-sectional area of the target ingredient can be calculated. Based on the cross-sectional area of the target ingredient, the equivalent thickness of the target ingredient can be obtained, that is, the thickness of the target ingredient.
[0026] S107, perform data fusion processing on the thickness of the target food and the preset thawing parameters to obtain the target thawing time corresponding to the target food; In some embodiments, the preset thawing parameters include the food density, thermophysical parameters and thawing temperature of the target food. By performing data fusion processing on the thickness of the target food and the preset thawing parameters of the target food, the target thawing time of the target food can be obtained.
[0027] S109, a thawing execution instruction is generated based on the target thawing time and the preset thawing parameters; the thawing execution instruction is used to instruct the smart appliance to thaw the target food according to the target thawing time and the preset thawing parameters.
[0028] In some embodiments, a thawing execution command is generated based on the target thawing time and thawing temperature corresponding to the target food ingredient, so that the smart appliance thaws the target food ingredient according to the target thawing time and thawing temperature corresponding to the target food ingredient.
[0029] In some embodiments, see Figure 3 , Figure 3 This is a flowchart illustrating a method for determining the location information of a food ingredient according to an embodiment of this application. The step of determining the location information of the target food ingredient based on the temperature difference information between the temperature distribution of the first region and the temperature distribution of the second region includes: S301, Determine the target temperature threshold based on the temperature difference information; In some embodiments, a target temperature threshold can be obtained based on the temperature difference information between the temperature distribution of the first region and the temperature distribution of the second region. The target temperature threshold is used to determine the target food temperature point corresponding to the target food from the temperature points involved in the cavity temperature distribution.
[0030] S303, based on the target temperature threshold, determine the target food temperature point corresponding to the target food from the temperature distribution of the second region; the temperature corresponding to the target food temperature point is less than the target temperature threshold; In some embodiments, the temperature of the target ingredient is low, and the temperature point with a temperature lower than the target temperature threshold among the temperature points involved in the temperature distribution of the second region is determined as the target ingredient temperature point.
[0031] S305, the location information corresponding to the target food temperature point is determined as the food location information.
[0032] In some embodiments, the coordinate information corresponding to the temperature point of the target ingredient is the location information of the ingredient corresponding to the target ingredient.
[0033] This application embodiment determines the target temperature threshold based on the temperature difference information between different regions in the target cavity of the smart appliance. Based on the target temperature threshold, the target food temperature point corresponding to the target food is determined. The location information corresponding to the target food temperature point is the food location information corresponding to the target food. Based on the food location information corresponding to the target food, the thickness of the target food can be accurately calculated. Then, based on the thickness of the target food, the target thawing time corresponding to the target food is determined. Since the thickness of the target food is considered when determining the target thawing time, it can be ensured that the target food can thaw evenly, thereby improving the thawing effect of the target food.
[0034] In some embodiments, determining the target temperature threshold based on the temperature difference information includes: The absolute value of the difference between the first average temperature corresponding to the temperature distribution in the first region and the second average temperature corresponding to the temperature distribution in the second region is determined as the temperature difference information. A preset temperature coefficient is determined based on the temperature difference information; The preset temperature coefficient, the first average temperature, and the second average temperature are fused to obtain the target temperature threshold.
[0035] In some embodiments, the cavity temperature distribution is as follows: The first average temperature corresponding to the temperature distribution in the first region , The first region temperature distribution includes the number of temperature points, and the second region temperature distribution corresponds to the second average temperature. , The second region's temperature distribution includes the number of temperature points and information on temperature differences. .
[0036] In some embodiments, if The preset temperature coefficient ,but 5 ,but 6. Target temperature threshold .
[0037] This application embodiment determines the target temperature threshold based on the temperature difference information between different regions in the target cavity of the smart appliance. Based on the target temperature threshold, the target food temperature point corresponding to the target food is determined. The location information corresponding to the target food temperature point is the food location information corresponding to the target food. Based on the food location information corresponding to the target food, the thickness of the target food can be accurately calculated. Then, based on the thickness of the target food, the target thawing time corresponding to the target food is determined. Since the thickness of the target food is considered when determining the target thawing time, it can be ensured that the target food can thaw evenly, thereby improving the thawing effect of the target food.
[0038] In some embodiments, determining the target food thickness based on the food location information includes: The initial thickness sequence corresponding to the target ingredient is determined based on the ingredient position information corresponding to the temperature point of each column of target ingredients; the initial thickness sequence includes the initial ingredient thickness corresponding to the temperature point of each column of target ingredients. The thickness of the target food ingredient is determined based on the initial thickness sequence.
[0039] In some embodiments, the location information of the target ingredient is: Each of the target ingredients Each corresponds to an initial ingredient thickness, which is based on each corresponding Determine the temperature point of each target ingredient, i.e., each Corresponding initial food thickness ,in This is the conversion factor from coordinates to actual dimensions.
[0040] In some embodiments, the initial thickness sequence is formed by the initial food thickness corresponding to each target food temperature point. The thickness of the target ingredient is determined based on the initial thickness sequence.
[0041] This application embodiment determines the location information of the target food based on the temperature difference information between different regions in the target cavity of the smart appliance, determines the thickness of the target food based on the location information of the target food, and then determines the target thawing time based on the thickness of the target food. Since the thickness of the target food is taken into account when determining the target thawing time, it can ensure that the target food can thaw evenly and improve the thawing effect of the target food.
[0042] In some embodiments, determining the target food thickness based on the initial thickness sequence includes: The initial food thickness in the initial thickness sequence is subjected to thickness correction processing to obtain the target thickness sequence; The cross-sectional area of the target food ingredient is determined based on the target thickness sequence; The thickness of the target food ingredient is determined based on the cross-sectional area.
[0043] In some embodiments, abnormal thicknesses in the initial thickness sequence are corrected to obtain a target thickness sequence, and the cross-sectional area of the target food ingredient is calculated based on the target thickness sequence. Target ingredient thickness .
[0044] This application embodiment determines the location information of the target food based on the temperature difference information between different regions in the target cavity of the smart appliance, determines the thickness of the target food based on the location information of the target food, and then determines the target thawing time based on the thickness of the target food. Since the thickness of the target food is taken into account when determining the target thawing time, it can ensure that the target food can thaw evenly and improve the thawing effect of the target food.
[0045] In some embodiments, performing thickness correction processing on the initial food thickness in the initial thickness sequence to obtain the target thickness sequence includes: Based on the mean thickness and standard deviation of the thickness corresponding to the initial thickness sequence, abnormal thicknesses are determined from the initial food thickness; The abnormal thickness is replaced with the neighborhood thickness to obtain the target thickness sequence; the neighborhood thickness is determined based on the initial food thickness adjacent to the abnormal thickness in the initial thickness sequence.
[0046] In some embodiments, the average thickness corresponding to the initial thickness sequence The standard deviation of the initial thickness sequence Based on the mean and standard deviation of the initial thickness sequence, abnormal thicknesses are determined from the initial food thicknesses. These abnormal thicknesses are then replaced with neighboring thicknesses to obtain the target thickness sequence. The neighboring thickness is determined based on the initial food thicknesses adjacent to the abnormal thicknesses in the initial thickness sequence. Specifically, the neighboring thickness can be the mean of the two initial food thicknesses adjacent to the abnormal thicknesses in the initial thickness sequence. If the abnormal thickness is... Then the neighborhood thickness is .
[0047] This application embodiment removes abnormal thickness by replacing abnormal thickness with neighborhood thickness, ensuring the accuracy of the thickness of the food corresponding to the temperature point of each target food item, and thus ensuring the accuracy of the target food thickness. The target thawing time corresponding to the target food is determined based on the target food thickness. Since the thickness of the target food is considered when determining the target thawing time, it can be ensured that the target food can thaw evenly, thereby improving the thawing effect of the target food.
[0048] In some embodiments, determining abnormal thicknesses from the initial food thicknesses based on the mean thickness and standard deviation of the initial thickness sequence includes: Potential outlier conditions are determined based on the mean thickness and the standard deviation of thickness. The initial food thickness that satisfies the potential outlier condition in the initial thickness sequence is determined as the potential outlier thickness; If the number of potential outlier thicknesses is less than a preset threshold, the potential outlier thickness is determined as the abnormal thickness.
[0049] In some embodiments, the potential outlier condition is based on the mean thickness corresponding to the initial thickness sequence. and thickness standard deviation Determining, for example, potential outlier conditions could be The initial food thickness that meets the potential outlier condition in the initial thickness sequence is determined as the potential outlier thickness. If the number of potential outlier thicknesses is less than a preset threshold... If the number of potential outlier thicknesses is greater than or equal to a preset threshold, then these potential outlier thicknesses are normal thickness variations rather than outliers.
[0050] For example, if the initial thickness sequence is [10,12,11,9,8,13,50,10,12,11] (corresponding to i from 0 to 9), calculate the mean thickness corresponding to the initial thickness sequence. and thickness standard deviation : ≈14.6, ≈12.1; Check if the thickness of each initial ingredient satisfies the potential outlier condition | |>2 For i=6, =50,|50 14.6|=35.4>24.2, so 50 is the potential outlier thickness, and all other points satisfy | |≤2 This is not the potential outlier thickness; the number of potential outliers, N=1, is determined by a preset threshold. =5, then N< Therefore, 50 is an abnormal thickness.
[0051] This application embodiment determines abnormal thicknesses from the initial thickness sequence based on potential outlier conditions, and removes abnormal thicknesses by replacing them with neighboring thicknesses, ensuring the accuracy of the thickness of the target food at each target food temperature point, thereby ensuring the accuracy of the target food thickness. The target thawing time corresponding to the target food is determined based on the target food thickness. Since the thickness of the target food is considered when determining the target thawing time, it can be ensured that the target food can thaw evenly, thus improving the thawing effect of the target food.
[0052] In some embodiments, the preset thawing parameters include the food density, thermophysical properties, and thawing temperature corresponding to the target food, and the step of performing data fusion processing on the thickness of the target food and the preset thawing parameters to obtain the target thawing time corresponding to the target food includes: The initial temperature of the target ingredient is determined based on the temperature information corresponding to the temperature point of the target ingredient. The target thawing time is obtained by fusing data of the initial temperature of the food, the thickness of the target food, the density of the food, the thermophysical parameters, and the thawing temperature.
[0053] In some embodiments, the preset thawing parameters include the food density, thermal properties, and thawing temperature of the target food. The thermal properties include latent heat of phase change, average thermal conductivity, freezing point temperature, and specific heat capacity in the frozen state. The initial temperature of the target food is the average temperature of the target food determined based on the temperature information corresponding to the target food temperature point. The target thawing time... ,in, For food density, For latent heat of phase transition, For the target ingredient thickness, The average thermal conductivity, This is the thawing temperature. Freezing point temperature The specific heat capacity in the frozen state, The initial temperature of the ingredients.
[0054] In some embodiments, the smart appliance thaws the target food according to the target thawing time and thawing temperature, and reminds the user to take out the thawed target food in time after thawing is completed.
[0055] This application embodiment determines the location information of the target ingredient based on the temperature difference information between different regions within the target cavity of the smart appliance. Based on the location information, it determines the thickness of the target ingredient, and then determines the target thawing time based on the thickness. The target ingredient is then thawed according to the target thawing time. By considering the thickness of the target ingredient when determining the target thawing time, it ensures that the ingredient thaws evenly, improving the thawing effect while guaranteeing the safety and quality of the ingredient.
[0056] This application provides a method for defrosting food, applied to a smart appliance. The method includes: responding to a food defrosting command, acquiring the cavity temperature distribution of the smart appliance and preset defrosting parameters corresponding to the target food; the cavity temperature distribution includes a first region temperature distribution and a second region temperature distribution, the first region temperature distribution being the temperature distribution corresponding to a carrying area in the target cavity of the smart appliance, and the second region temperature distribution being the temperature distribution corresponding to other areas in the target cavity besides the carrying area; determining the food location information corresponding to the target food based on the temperature difference information between the first region temperature distribution and the second region temperature distribution; determining the thickness of the target food based on the food location information; performing data fusion processing on the target food thickness and the preset defrosting parameters to obtain a target defrosting time corresponding to the target food; generating a defrosting execution command based on the target defrosting time and the preset defrosting parameters; the defrosting execution command instructing the smart appliance to defrost the target food according to the target defrosting time and the preset defrosting parameters. This application embodiment determines the location information of the target ingredient based on the temperature difference information between different regions within the target cavity of the smart appliance. Based on the location information, it determines the thickness of the target ingredient, and then determines the target thawing time based on the thickness. The target ingredient is then thawed according to the target thawing time. By considering the thickness of the target ingredient when determining the target thawing time, it ensures that the ingredient thaws evenly, improving the thawing effect while guaranteeing the safety and quality of the ingredient.
[0057] This application also provides a smart appliance, see [link to relevant documentation]. Figure 4 , Figure 4 This is a schematic diagram of the structure of a smart appliance provided in an embodiment of this application. The smart appliance includes: The data acquisition module 410 is used to acquire the cavity temperature distribution of the smart appliance and the preset thawing parameters corresponding to the target food in response to the food thawing command; the cavity temperature distribution includes a first region temperature distribution and a second region temperature distribution, the first region temperature distribution is the temperature distribution corresponding to the bearing area in the target cavity of the smart appliance, and the second region temperature distribution is the temperature distribution corresponding to other areas in the target cavity other than the bearing area. The ingredient location information determination module 420 is used to determine the ingredient location information corresponding to the target ingredient based on the temperature difference information between the temperature distribution of the first region and the temperature distribution of the second region. The target ingredient thickness determination module 430 is used to determine the thickness of the target ingredient based on the ingredient location information. The target thawing time determination module 440 is used to perform data fusion processing on the thickness of the target food and the preset thawing parameters to obtain the target thawing time corresponding to the target food. The defrosting execution instruction generation module 450 is used to generate a defrosting execution instruction based on the target defrosting time and the preset defrosting parameters; the defrosting execution instruction is used to instruct the smart appliance to defrost the target food according to the target defrosting time and the preset defrosting parameters.
[0058] In some embodiments, the food ingredient location information determination module 420 includes: A target temperature threshold determination unit is used to determine a target temperature threshold based on the temperature difference information. The target ingredient temperature point determination unit is used to determine the target ingredient temperature point corresponding to the target ingredient from the temperature distribution of the second region based on the target temperature threshold; the temperature corresponding to the target ingredient temperature point is less than the target temperature threshold. The ingredient location information determination unit is used to determine the location information corresponding to the temperature point of the target ingredient as the ingredient location information.
[0059] In some embodiments, the target temperature threshold determination unit includes: The temperature difference information determination subunit is used to determine the absolute value of the difference between the first average temperature corresponding to the temperature distribution of the first region and the second average temperature corresponding to the temperature distribution of the second region as the temperature difference information. A preset temperature coefficient determination subunit is used to determine a preset temperature coefficient based on the temperature difference information. The target temperature threshold determination subunit is used to perform data fusion processing on the preset temperature coefficient, the first average temperature and the second average temperature to obtain the target temperature threshold.
[0060] In some embodiments, the target food thickness determination module 430 includes: An initial thickness sequence determination unit is used to determine the initial thickness sequence corresponding to the target food based on the food position information corresponding to the temperature points of each column of target food; the initial thickness sequence includes the initial food thickness corresponding to the temperature points of each column of target food. The target ingredient thickness determination unit is used to determine the thickness of the target ingredient based on the initial thickness sequence.
[0061] In some embodiments, the target food thickness determination unit includes: A thickness correction subunit is used to perform thickness correction processing on the initial food thickness in the initial thickness sequence to obtain a target thickness sequence; A cross-sectional area determination subunit is used to determine the cross-sectional area of the target food ingredient based on the target thickness sequence; The target ingredient thickness determination subunit is used to determine the thickness of the target ingredient based on the cross-sectional area.
[0062] In some embodiments, the thickness correction subunit includes: An abnormal thickness determination component is used to determine abnormal thickness from the initial food thickness based on the mean thickness and standard deviation of the thickness corresponding to the initial thickness sequence. A target thickness sequence determination component is used to replace the abnormal thickness with a neighboring thickness to obtain the target thickness sequence; the neighboring thickness is determined based on the initial food thickness adjacent to the abnormal thickness in the initial thickness sequence.
[0063] In some embodiments, the abnormal thickness determination component includes: A potential outlier condition determination sub-component is used to determine potential outlier conditions based on the mean thickness and the standard deviation of thickness. A potential outlier thickness determination sub-component is used to determine the initial food thickness that satisfies the potential outlier condition in the initial thickness sequence as the potential outlier thickness. An abnormal thickness determination sub-component is used to determine the potential outlier thickness as the abnormal thickness when the number of potential outlier thicknesses is less than a preset number threshold.
[0064] In some embodiments, the preset thawing parameters include the food density, thermophysical properties, and thawing temperature corresponding to the target food ingredient, and the target thawing time determination module 440 includes: The ingredient initial temperature determination unit is used to determine the initial temperature of the target ingredient based on the temperature information corresponding to the target ingredient temperature point. The target thawing time determination unit is used to perform data fusion processing on the initial temperature of the food, the thickness of the target food, the density of the food, the thermophysical parameters, and the thawing temperature to obtain the target thawing time.
[0065] The apparatus provided in the above embodiments can execute the method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the above embodiments can be found in a food thawing method provided in any embodiment of this application.
[0066] This embodiment also provides a computer-readable storage medium storing computer-executable instructions, which are loaded by a processor and executed by the above-described food thawing method of this embodiment.
[0067] This embodiment also provides an electronic device, which includes a processor and a memory, wherein the memory stores a computer program adapted to be loaded by the processor and executed by the above-described food thawing method of this embodiment.
[0068] The electronic device may be a computer terminal, a mobile terminal, or a server, and may also participate in constituting the apparatus or system provided in the embodiments of this application. For example... Figure 5 As shown, the electronic device 5 may include one or more (shown as 502a, 502b, ..., 502n in the figure) processors 502 (processors 502 may include, but are not limited to, microprocessors MCUs or programmable logic devices FPLDs), a memory 504 for storing information, and a transmission device 506 for communication functions. In addition, it may also include input / output interfaces (I / O interfaces) and network interfaces. Those skilled in the art will understand that... Figure 5 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, electronic device 5 may also include... Figure 5 The more or fewer components shown, or having the same Figure 5 The different configurations shown.
[0069] It should be noted that the aforementioned one or more processors 502 and / or other information processing circuits are generally referred to herein as "information processing circuits". These information processing circuits may be wholly or partially embodied in software, hardware, firmware, or any other combination thereof. Furthermore, the information processing circuits may be a single, independent processing module, or may be wholly or partially integrated into any other element in the electronic device 5.
[0070] The memory 504 can be used to store software programs and modules of application software, such as the program instruction / information storage device corresponding to the method described in the embodiments of this application. The processor 502 executes various functional applications and information processing by running the software programs and modules stored in the memory 504, thereby realizing the above-mentioned food defrosting method. The memory 504 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 504 may further include memory remotely located relative to the processor 502, and these remote memories can be connected to the electronic device 5 via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
[0071] The transmission device 506 is used to receive or send information via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the electronic device 5. In one example, the transmission device 506 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 506 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.
[0072] This specification provides the operational steps of the methods described in the embodiments or flowcharts, but more or fewer operational steps may be included based on conventional or non-inventive labor. The steps and order listed in the embodiments are merely one possible execution order among many steps and do not represent the only execution order. In actual system or interrupt product execution, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment).
[0073] The structure shown in this embodiment is only a partial structure related to the solution of this application and does not constitute a limitation on the device to which the solution of this application is applied. Specific devices may include more or fewer components than shown, or combinations of certain components, or arrangements of different components. It should be understood that the methods, apparatuses, etc., disclosed in this embodiment can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or unit modules through some interfaces.
[0074] Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.
[0075] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this specification can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0076] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.
Claims
1. A method for thawing food ingredients, characterized in that, The method is applied to smart appliances, and the method includes: In response to a food defrosting command, the temperature distribution of the cavity of the smart appliance and the preset defrosting parameters corresponding to the target food are obtained; the temperature distribution of the cavity includes a first region temperature distribution and a second region temperature distribution, the first region temperature distribution is the temperature distribution corresponding to the bearing area in the target cavity of the smart appliance, and the second region temperature distribution is the temperature distribution corresponding to other areas in the target cavity other than the bearing area. Based on the temperature difference information between the temperature distribution in the first region and the temperature distribution in the second region, the location information of the target ingredient is determined. The thickness of the target ingredient is determined based on the ingredient location information; The target thawing time corresponding to the target food is obtained by performing data fusion processing on the thickness of the target food and the preset thawing parameters. A thawing execution instruction is generated based on the target thawing time and the preset thawing parameters; the thawing execution instruction is used to instruct the smart appliance to thaw the target food according to the target thawing time and the preset thawing parameters.
2. The method for thawing food ingredients according to claim 1, characterized in that, The step of determining the location information of the target ingredient based on the temperature difference information between the temperature distribution in the first region and the temperature distribution in the second region includes: The target temperature threshold is determined based on the temperature difference information. Based on the target temperature threshold, the target food temperature point corresponding to the target food is determined from the temperature distribution of the second region; the temperature corresponding to the target food temperature point is less than the target temperature threshold. The location information corresponding to the temperature point of the target food ingredient is determined as the location information of the food ingredient.
3. The method for thawing food according to claim 2, characterized in that, Determining the target temperature threshold based on the temperature difference information includes: The absolute value of the difference between the first average temperature corresponding to the temperature distribution in the first region and the second average temperature corresponding to the temperature distribution in the second region is determined as the temperature difference information. A preset temperature coefficient is determined based on the temperature difference information; The preset temperature coefficient, the first average temperature, and the second average temperature are fused to obtain the target temperature threshold.
4. The method for thawing food according to claim 2, characterized in that, Determining the thickness of the target ingredient based on the ingredient location information includes: The initial thickness sequence corresponding to the target ingredient is determined based on the ingredient position information corresponding to the temperature point of each column of target ingredients; the initial thickness sequence includes the initial ingredient thickness corresponding to the temperature point of each column of target ingredients. The thickness of the target food ingredient is determined based on the initial thickness sequence.
5. The method for thawing food according to claim 4, characterized in that, Determining the thickness of the target food ingredient based on the initial thickness sequence includes: The initial food thickness in the initial thickness sequence is subjected to thickness correction processing to obtain the target thickness sequence; The cross-sectional area of the target food ingredient is determined based on the target thickness sequence; The thickness of the target food ingredient is determined based on the cross-sectional area.
6. The method for thawing food according to claim 5, characterized in that, The step of performing thickness correction processing on the initial food thickness in the initial thickness sequence to obtain the target thickness sequence includes: Based on the mean thickness and standard deviation of the thickness corresponding to the initial thickness sequence, abnormal thicknesses are determined from the initial food thickness; The abnormal thickness is replaced with the neighborhood thickness to obtain the target thickness sequence; the neighborhood thickness is determined based on the initial food thickness adjacent to the abnormal thickness in the initial thickness sequence.
7. The method for thawing food according to claim 6, characterized in that, The step of determining abnormal thicknesses from the initial food thicknesses based on the mean thickness and standard deviation of the initial thickness sequence includes: Potential outlier conditions are determined based on the mean thickness and the standard deviation of thickness. The initial food thickness that satisfies the potential outlier condition in the initial thickness sequence is determined as the potential outlier thickness; If the number of potential outlier thicknesses is less than a preset threshold, the potential outlier thickness is determined as the abnormal thickness.
8. The method for thawing food according to claim 2, characterized in that, The preset thawing parameters include the food density, thermophysical properties, and thawing temperature corresponding to the target food. The step of data fusion processing of the target food thickness and the preset thawing parameters to obtain the target thawing time for the target food includes: The initial temperature of the target ingredient is determined based on the temperature information corresponding to the temperature point of the target ingredient. The target thawing time is obtained by fusing data of the initial temperature of the food, the thickness of the target food, the density of the food, the thermophysical parameters, and the thawing temperature.
9. A smart appliance, characterized in that, The smart appliance uses the food defrosting method described in any one of claims 1-8, and the smart appliance is one of a microwave oven, a steam oven, and an air fryer.
10. A food defrosting system, characterized in that, The system includes a data acquisition terminal and a controller; The acquisition terminal is used to acquire the cavity temperature distribution of the smart appliance and send the cavity temperature distribution to the controller; The controller is used to perform the food thawing method as described in any one of claims 1-8.