Control method and system for preventing dry boiling of a hob, hob and medium

Abstract

The application discloses a kind of control method, system, cooktop and medium of dry burning of cooktop, the detection method includes: obtaining the cooking temperature data and cooking duration of cooktop;According to cooking temperature data and cooking duration, calculate dry burning confidence, and generate cooking temperature curve;If dry burning confidence reaches set threshold, control start temperature curve similarity matching mechanism, and similarity data is obtained by calculation;According to similarity data, determine whether the cooking scene type of cooktop is dry burning scene or not.The application introduces cooking curve database, adopts temperature curve similarity matching mechanism, effectively distinguishes pot to take away scene and other special cooking scenes, improves the accuracy of dry burning detection.

Description

Technical Field

[0001] This invention relates to the field of stove technology, and in particular to a control method, system, stove and medium for preventing dry burning in stoves. Background Technology

[0002] Most anti-dry-burning algorithms distinguish specific cooking scenarios using temperature curves. However, in some special cooking scenarios, cooking temperature curves similar to those in a dry-burning situation may appear. For example, when the user tosses the pan or removes it from the heat, the stove is in an empty-heating state. A sudden rise in the cooking temperature curve, similar to the temperature curve after water has boiled away, is judged as dry-burning and the stove is turned off, even though the user actually wants to continue cooking. Furthermore, due to factors such as the type of cookware, the temperature change caused by the food during cooking may increase to a certain extent, leading to a misjudgment of dry-burning and the stove being turned off, even though the user does not actually intend to turn off the stove.

[0003] Therefore, existing methods for detecting dry burning in stoves have low accuracy and poor user experience. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the defect of the prior art in some special cooking scenarios that may be misjudged as dry burning, resulting in low accuracy of dry burning detection, and to provide a control method, system, stove and medium for preventing dry burning of stove.

[0005] The present invention solves the above-mentioned technical problems through the following technical solution:

[0006] In a first aspect, the present invention provides a method for controlling the prevention of dry burning in a stove, the method comprising:

[0007] Obtain cooking temperature data and cooking time from the cooktop;

[0008] The confidence level for dry burning is calculated based on the cooking temperature data and the cooking time, and a cooking temperature curve is generated.

[0009] If the confidence level of dry burning reaches a set threshold, the temperature curve similarity matching mechanism is activated to calculate similarity data. The temperature curve similarity matching mechanism is used to characterize the matching of the cooking temperature curve with any cooking curve in the cooking curve database based on duration similarity, temperature similarity, and curve similarity.

[0010] Based on the similarity data, it is determined whether the cooking scenario type of the stove is a dry-burning scenario.

[0011] Preferably, the similarity data includes duration similarity values, temperature similarity values, and curve similarity values. The step of determining whether the cooking scenario type of the stove is a dry-burning scenario based on the similarity data includes:

[0012] The comprehensive similarity value between the cooking temperature curve and any cooking curve in the cooking curve database is calculated based on the duration similarity value, the temperature similarity value, and the curve similarity value.

[0013] The cooking scenario type corresponding to the highest comprehensive similarity value is taken as the target scenario type, and it is determined whether dry burning has occurred based on the target scenario type; the cooking scenario category includes at least one of the following: no pot dry burning scenario, oil burning scenario, pot removed scenario, dry burning scenario, casserole misjudgment scenario, and stir-frying / pan-frying scenario.

[0014] Preferably, the step of obtaining similarity data through the control start-up temperature curve similarity matching mechanism includes:

[0015] Based on the proportion of different cooking times set in the cooking curve database, several time similarity values ​​corresponding to the cooking time are determined;

[0016] The cooking temperature curve and any cooking curve in the cooking curve database are subjected to Jaccard similarity calculation and Yu Xuan similarity calculation respectively, resulting in several temperature similarity values ​​and curve similarity values.

[0017] The similarity data is generated based on the duration similarity value, the temperature similarity value, and the curve similarity value.

[0018] Secondly, the present invention provides a control system for preventing dry burning of a stove, the control system comprising:

[0019] The acquisition module is used to acquire the cooking temperature data and cooking time of the stove.

[0020] The calculation module is used to calculate the dry-burning confidence level based on the cooking temperature data and the cooking time, and to generate a cooking temperature curve;

[0021] The control module is used to activate the temperature curve similarity matching mechanism and calculate similarity data if the dry burning confidence reaches a set threshold. The temperature curve similarity matching mechanism is used to characterize the matching of the cooking temperature curve with any cooking curve in the cooking curve database based on duration similarity, temperature similarity, and curve similarity.

[0022] The determination module is used to determine whether the cooking scenario type of the stove is a dry-burning scenario based on the similarity data.

[0023] Preferably, the similarity data includes duration similarity values, temperature similarity values, and curve similarity values, and the determination module includes:

[0024] The first calculation unit is used to calculate a comprehensive similarity value between the cooking temperature curve and any cooking curve in the cooking curve database based on the duration similarity value, the temperature similarity value, and the curve similarity value.

[0025] The determination unit is used to take the cooking scene type corresponding to the highest comprehensive similarity value as the target scene type, and to determine whether dry burning has occurred based on the target scene type; the cooking scene category includes at least one of the following: no pot dry burning scene, oil burning scene, pot removed scene, dry burning scene, casserole misjudgment scene, and stir-fry / pan-fry scene.

[0026] Preferably, the control system further includes:

[0027] The collection module is used to collect several cooking curves corresponding to different cooking scenario types and set cooking times;

[0028] A construction module is used to construct a cooking curve database based on the cooking curves; the cooking curve database includes the percentage of different set cooking times for each cooking scenario type.

[0029] Preferably, the control module includes:

[0030] The determining unit is used to determine the proportion of different cooking scenario categories corresponding to the cooking time based on the cooking curve database, and to obtain several time similarity values;

[0031] The second calculation unit is used to perform Jaccard similarity calculation and cosine similarity calculation on the cooking temperature curve and any cooking curve in the cooking curve database respectively, and obtain several temperature similarity values ​​and curve similarity values ​​accordingly.

[0032] The generation unit is used to generate the similarity data based on the length similarity value, the temperature similarity value, and the curve similarity value.

[0033] Thirdly, the present invention provides a cooktop, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, it implements the cooktop anti-dry-burning control method as described in the first aspect.

[0034] Fourthly, the present invention provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the stove anti-dry-burning control method as described in the first aspect.

[0035] The significant advantages of this invention are as follows: it acquires cooking temperature data and cooking time of the stove; it calculates the dry-burn confidence level based on the cooking temperature data and cooking time, and generates a cooking temperature curve; when the dry-burn confidence level reaches a set threshold, it controls the activation of a temperature curve similarity matching mechanism to calculate similarity data; and it determines whether the cooking scenario of the stove is a dry-burn scenario based on the similarity data. This invention introduces a cooking curve database and adopts a temperature curve similarity matching mechanism to effectively distinguish special cooking scenarios such as pot removal scenarios, thereby improving the accuracy of dry-burn detection. Attached Figure Description

[0036] Figure 1 This is a first flowchart of the stove anti-dry burning control method of Embodiment 1 of the present invention.

[0037] Figure 2 This is the second flowchart of the stove anti-dry burning control method of Embodiment 1 of the present invention.

[0038] Figure 3 This is a flowchart of step S14 of the stove anti-dry burning control method in Embodiment 1 of the present invention.

[0039] Figure 4 This is a flowchart of step S13 of the stove anti-dry burning control method in Embodiment 1 of the present invention.

[0040] Figure 5 This is a schematic diagram of the first module of the stove anti-dry burning control system according to Embodiment 2 of the present invention.

[0041] Figure 6 This is a schematic diagram of the second module of the stove anti-dry burning control system according to Embodiment 2 of the present invention.

[0042] Figure 7 This is a schematic diagram of the electronic device used to implement the control method for preventing dry burning of a stove according to Embodiment 3 of the present invention. Detailed Implementation

[0043] The present invention will be further illustrated by way of embodiments below, but the present invention is not limited to the scope of the embodiments described herein.

[0044] Example 1

[0045] The stove anti-dry-burning control method in this embodiment, such as Figure 1 As shown, the control method includes:

[0046] S11. Obtain the cooking temperature data and cooking time of the stove.

[0047] S12. Calculate the dry burning confidence level based on the cooking temperature data and cooking time, and generate the cooking temperature curve.

[0048] S13. When the confidence level of a certain cooking reaches a set threshold, the temperature curve similarity matching mechanism is activated. The similarity data is calculated based on the cooking temperature curve and cooking time. The temperature curve similarity matching mechanism is used to characterize the matching of cooking temperature curve with any cooking curve in the cooking curve database based on time similarity, temperature similarity and curve similarity.

[0049] S14. Determine whether the cooking scenario type of the stove is a dry-burning scenario based on similarity data.

[0050] For steps S11-S12 above, the cooking temperature and corresponding time of the ingredients during the current cooking process are obtained from the smart cooking stove. This time interval can be 1 second, 5 seconds, 10 seconds, or 20 seconds, depending on the type of ingredients and the performance of the cooking stove. A cooking temperature curve is generated based on the obtained cooking temperature and corresponding time. The cooking temperature data is obtained through a temperature detector on the smart cooking stove, and the cooking time is obtained through a timer on the smart cooking stove. The confidence coefficients for temperature dimension information (param_a) and temperature rise dimension information (param_b) are set as follows: temperature threshold (A), temperature difference threshold (B), temperature data (a), temperature difference data (b), and the maximum temperature of the probe (Max_Temperature). param_a = f((aA) / (Max_Temperature-A)). The calculation formula for the temperature evaluation result f(x) is as follows: f(x) = 0, x < -1, f(x) = 0.5x + 0.5, -1 <x<1,f(x)=1,x> 1. param_b = 1 - param_a. After normalizing the temperature difference data, we get normal_b = (bB) / B. The formula for calculating the confidence level of dry burning is as follows: Score = param_a + param_b * normal_b.

[0051] Regarding steps S13-S14 above, when the dry-burning confidence level exceeds a set threshold, it indicates that the stove may be dry-burning under the current conditions. Since dry-burning judgment is based on both temperature and temperature rise, misjudgments may occur in specific cooking scenarios. Therefore, a temperature curve similarity matching mechanism is activated to match duration similarity, temperature similarity, and curve similarity. This prevents misjudgments caused by the stove being in an empty-burning state after the pot is removed, resulting in a rapid temperature rise and a high dry-burning confidence level. When the cooking temperature curve has a stable period, it indicates that the stove is cooking with water; when the cooking temperature curve does not have a stable period, it indicates that the stove is cooking without water. When the stove is cooking with water, duration similarity, temperature similarity, and curve similarity values ​​are obtained sequentially through duration similarity matching, temperature similarity, and curve similarity matching. A comprehensive similarity value is calculated based on these values, and the comprehensive similarity value is used to determine whether the current cooking scenario is a dry-burning scenario. If the current cooking scenario of the stove is determined to be a true dry-burning scenario, the stove will be controlled to turn off the heat immediately. If the current cooking scenario of the stove is determined to be a false dry-burning scenario, the stove will be controlled not to perform the dry-burning protection operation.

[0052] In this embodiment, by introducing a temperature curve similarity matching mechanism, the accuracy of the stove's anti-dry-burning judgment is improved, completely solving the misjudgment situation in special cooking scenarios such as when the pot is removed, and improving the user's cooking experience.

[0053] In one alternative implementation, such as Figure 2 As shown, the control method also includes:

[0054] S101. Collect several cooking curves with set cooking times corresponding to different cooking scenario types.

[0055] S102. Construct a cooking curve database based on the cooking curves; the cooking curve database includes the percentage of different cooking times for each cooking scenario type.

[0056] For steps S101-S102 above, several cooking curves with four set cooking times (less than 5 minutes, 5-15 minutes, 15-60 minutes, and more than 60 minutes) are collected under four scenarios: no pot, no oil, no pot, dry cooking, and misjudgment of a clay pot. These curves are then proportionally divided according to the set cooking time to construct a cooking curve database. For example, in the no pot, no pot scenario, 100% of the cooking curves have a set cooking time of less than 5 minutes; in the clay pot misjudgment scenario, 20% have a set cooking time of less than 5 minutes, 30% have a set cooking time of 5-15 minutes, 40% have a set cooking time of 15-60 minutes, and 10% have a set cooking time of more than 60 minutes.

[0057] In one alternative implementation, such as Figure 3 As shown, the similarity data includes duration similarity values, temperature similarity values, and curve similarity values. Step S14 specifically includes:

[0058] S141. Calculate the comprehensive similarity value between the cooking temperature curve and any cooking curve in the cooking curve database based on the duration similarity value, temperature similarity value, and curve similarity value.

[0059] S142. The cooking scene type corresponding to the highest comprehensive similarity value is taken as the target scene type, and it is determined whether dry burning occurs based on the target scene type; the cooking scene category includes at least one of the following: no pot dry burning scene, oil burning scene, pot removed scene, dry burning scene, casserole misjudgment scene and stir-fry / pan-fry scene.

[0060] For steps S141-S142 above, the comprehensive similarity value S i The specific calculation formula is as follows: S i =T i *(K i +C i From the i comprehensive similarity values, the cooking scenario type corresponding to the highest comprehensive similarity value is selected as the target scenario type. If the target scenario type is any one of the following: no pot for dry cooking, oil heating scenario, pot removed scenario, casserole misjudgment scenario, or stir-fry / pan-fry scenario, then dry burning has not occurred. The cooking scenario types in this embodiment can be supplemented and adjusted according to the types of cooking curves actually collected, without specific restrictions.

[0061] In one alternative implementation, such as Figure 4 As shown, step S13 specifically includes:

[0062] S131. Determine several time similarity values ​​corresponding to different cooking times based on the proportion of different cooking times in the cooking curve database.

[0063] S132. Perform Jaccard similarity calculation and cosine similarity calculation on the cooking temperature curve and any cooking curve in the cooking curve database respectively to obtain several temperature similarity values ​​and curve similarity values.

[0064] S133. Generate similarity data based on duration similarity value, temperature similarity value, and curve similarity value.

[0065] For steps S131-S133 above, obtain the duration similarity value T corresponding to the cooking time in each cooking scenario category from the cooking curve database. iThe temperature similarity and curve similarity between the cooking temperature curve and any cooking curve in the cooking curve database are calculated. If the stove's temperature sensor collects data once per second, and the current cooking time is 50 seconds, then 50 cooking temperature data points are collected. When only 45 cooking temperature data points exist in the cooking curve database, two cooking temperature data points are inserted into the database using interpolation to maintain the same length between the two data points. The temperature similarity value K is calculated using the Jaccard similarity algorithm. i The specific formula for calculating temperature similarity is as follows:

[0066]

[0067] Where A represents the cooking temperature data of the cooking temperature curve, B represents the cooking temperature data of any cooking curve in the cooking curve database, and K... i The value range is [0, 1], K i The larger the value, the higher the temperature similarity between A and B. i represents the i-th cooking temperature data in the cooking curve database.

[0068] Curve similarity represents the similarity of temperature trends across curves. The curve similarity value C is calculated using the cosine similarity algorithm. i The specific formula for calculating curve similarity is as follows:

[0069]

[0070] Where A represents the cooking temperature data of the cooking temperature curve, B represents the cooking temperature data of any cooking curve in the cooking curve database, and C... i The value range is [-1, 1], C i The larger the value, the higher the similarity between curves A and B. i represents the i-th cooking temperature data in the cooking curve database.

[0071] This embodiment provides a method for controlling the dry-burning prevention of cooktops. When the dry-burning confidence level reaches a set threshold, a temperature curve similarity matching mechanism is activated to calculate similarity data. This method avoids the problem of low accuracy in judging whether a cooktop has dry-burned based solely on the dry-burning confidence level. The method determines whether the cooking scenario of the cooktop is a dry-burning scenario based on the similarity data. By introducing a cooking curve database and using a temperature curve similarity matching mechanism, this method effectively distinguishes special cooking scenarios such as when the pot is removed, improving the accuracy of dry-burning detection, reducing false positives, and enhancing the user experience.

[0072] Example 2

[0073] The stove's anti-dry-burning control system in this embodiment, such as... Figure 5As shown, by way of example and not limitation, the control system includes: an acquisition module 210, a calculation module 220, a control module 230, and a decision module 240.

[0074] The acquisition module 210 is used to acquire the cooking temperature data and cooking time of the stove.

[0075] The calculation module 220 is used to calculate the dry burning confidence level based on cooking temperature data and cooking time, and generate a cooking temperature curve;

[0076] The control module 230 is used to control the activation of the temperature curve similarity matching mechanism when the confidence level of a certain cooking reaches a set threshold, and to calculate the similarity data. The temperature curve similarity matching mechanism is used to characterize the matching of cooking temperature curves with any cooking curve in the cooking curve database based on time similarity, temperature similarity, and curve similarity.

[0077] The determination module 240 is used to determine whether the cooking scenario type of the stove is a dry-burning scenario based on similarity data.

[0078] The acquisition module 210 acquires the cooking temperature and corresponding time of the ingredients during the current cooking process recorded by the smart cooking stove. This time interval can be 1 second, 5 seconds, 10 seconds, or 20 seconds, depending on the type of ingredients and the performance of the cooking stove. The calculation module 220 generates a cooking temperature curve based on the acquired cooking temperature and corresponding time. The cooking temperature data is obtained through a temperature detector on the smart cooking stove, and the cooking time is obtained through a timer on the smart cooking stove. The confidence coefficients for temperature dimension information (param_a) and temperature rise dimension information (param_b) are set as follows: temperature threshold (A), temperature difference threshold (B), temperature data (a), temperature difference data (b), and the maximum temperature of the probe (Max_Temperature). The formula for calculating the temperature evaluation result (f(x)) is as follows: f(x) = 0, x < -1, f(x) = 0.5x + 0.5, -1 <x<1,f(x)=1,x> 1. param_b = 1 - param_a. After normalizing the temperature difference data, we get normal_b = (bB) / B. The formula for calculating the confidence level of dry burning is as follows: Score = param_a + param_b * normal_b.

[0079] When the confidence level for dry burning exceeds a set threshold, it indicates that the stove may be dry burning under the current conditions. Since dry burning is determined based on both temperature and temperature rise, misjudgments may occur in specific cooking scenarios. Therefore, a temperature curve similarity matching mechanism is activated to match duration similarity, temperature similarity, and curve similarity. This prevents misjudgments caused by the stove being in an empty-burning state after the pot is removed, resulting in a rapid temperature rise and a high confidence level for dry burning. When the cooking temperature curve has a stable period, it indicates that the stove is cooking with water; when the cooking temperature curve does not have a stable period, it indicates that the stove is cooking without water. When the stove is cooking with water, the control module 230 sequentially performs duration similarity matching, temperature similarity matching, and curve similarity matching to obtain duration similarity values, temperature similarity values, and curve similarity values. A comprehensive similarity value is calculated based on these values, and the comprehensive similarity value is used to determine whether the current cooking scenario is a dry burning scenario. When the current cooking scenario of the stove is determined to be a true dry burning scenario, the determination module 240 controls the stove to immediately turn off the flame. When the current cooking scenario of the stove is determined to be a false dry burning scenario, the stove is controlled not to perform the dry burning protection operation.

[0080] In this embodiment, by introducing a temperature curve similarity matching mechanism, the accuracy of the stove's anti-dry-burning judgment is improved, completely solving the misjudgment situation in special cooking scenarios such as when the pot is removed, and improving the user's cooking experience.

[0081] In one alternative implementation, such as Figure 6 As shown, the control system also includes:

[0082] The collection module 201 is used to collect several cooking curves with set cooking times corresponding to different cooking scenario types.

[0083] Module 202 is used to build a cooking curve database based on the cooking curves; the cooking curve database includes the percentage of different cooking times for each cooking scenario type.

[0084] The collection module 201 collects several cooking curves for four set cooking times: less than 5 minutes, 5-15 minutes, 15-60 minutes, and more than 60 minutes, under four scenarios: no pot, cooking with oil, pot removed, dry cooking, and misjudgment of a clay pot. The construction module 202 then constructs a cooking curve database by proportionally dividing the cooking curves according to the set cooking time. For example, in the no-pot, empty-cooking scenario, 100% of the cooking curves have a set cooking time of less than 5 minutes; in the clay pot misjudgment scenario, 20% have a set cooking time of less than 5 minutes, 30% have a set cooking time of 5-15 minutes, 40% have a set cooking time of 15-60 minutes, and 10% have a set cooking time of more than 60 minutes.

[0085] In one alternative implementation, such as Figure 6 As shown, the similarity data includes duration similarity values, temperature similarity values, and curve similarity values. The determination module 240 includes:

[0086] The first calculation unit 241 calculates the comprehensive similarity value between the cooking temperature curve and any cooking curve in the cooking curve database based on the duration similarity value, temperature similarity value, and curve similarity value.

[0087] The determination unit 242 takes the cooking scene type corresponding to the highest comprehensive similarity value as the target scene type, and determines whether dry burning has occurred based on the target scene type; the cooking scene category includes at least one of the following: no pot dry burning scene, oil burning scene, pot removed scene, dry burning scene, casserole misjudgment scene, and stir-fry / pan-fry scene.

[0088] Overall similarity value S i The specific calculation formula is as follows: S i =T i *(K i +C i The first calculation unit 241 selects the cooking scenario type corresponding to the highest comprehensive similarity value from the i comprehensive similarity values ​​as the target scenario type. If the target scenario type is any one of the following: no pot cooking scenario, oil cooking scenario, pot removed scenario, casserole misjudgment scenario, stir-frying / pan-frying scenario, the determination unit 242 determines that dry burning has not occurred. The cooking scenario type in this embodiment can be supplemented and adjusted according to the type of cooking curve actually collected, without specific restrictions.

[0089] In one alternative implementation, such as Figure 4 As shown, step S13 specifically includes:

[0090] S131. Determine several time similarity values ​​corresponding to different cooking times based on the proportion of different cooking times in the cooking curve database.

[0091] S132. Perform Jaccard similarity calculation and cosine similarity calculation on the cooking temperature curve and any cooking curve in the cooking curve database respectively to obtain several temperature similarity values ​​and curve similarity values.

[0092] S133. Generate similarity data based on duration similarity value, temperature similarity value, and curve similarity value.

[0093] For steps S131-S133 above, obtain the duration similarity value T corresponding to the cooking time in each cooking scenario category from the cooking curve database. i The temperature similarity and curve similarity between the cooking temperature curve and any cooking curve in the cooking curve database are calculated. If the stove's temperature sensor collects data once per second, and the current cooking time is 50 seconds, then 50 cooking temperature data points are collected. When only 45 cooking temperature data points exist in the cooking curve database, two cooking temperature data points are inserted into the database using interpolation to maintain the same length between the two data points. The temperature similarity value K is calculated using the Jaccard similarity algorithm. i The specific formula for calculating temperature similarity is as follows:

[0094]

[0095] Where A represents the cooking temperature data of the cooking temperature curve, B represents the cooking temperature data of any cooking curve in the cooking curve database, and K... i The value range is [0, 1], K i The larger the value, the higher the temperature similarity between A and B. i represents the i-th cooking temperature data in the cooking curve database.

[0096] Curve similarity represents the similarity of temperature trends across curves. The curve similarity value C is calculated using the cosine similarity algorithm. i The specific formula for calculating curve similarity is as follows:

[0097]

[0098] Where A represents the cooking temperature data of the cooking temperature curve, B represents the cooking temperature data of any cooking curve in the cooking curve database, and C... i The value range is [-1, 1], C i The larger the value, the higher the similarity between curves A and B. i represents the i-th cooking temperature data in the cooking curve database.

[0099] This embodiment provides a control system for preventing dry burning of a cooktop. When the dry burning confidence level reaches a set threshold, the control module activates a temperature curve similarity matching mechanism to calculate similarity data. This method avoids the problem of low accuracy in judging whether the cooktop has dry-burned based solely on the dry burning confidence level. The similarity data is used to determine whether the cooking scenario of the cooktop is a dry-burning scenario. This method introduces a cooking curve database and uses a temperature curve similarity matching mechanism to effectively distinguish special cooking scenarios such as when the pot is removed, improving the accuracy of dry burning detection, reducing false positives, and enhancing the user experience.

[0100] Example 3

[0101] Figure 7 This is a schematic diagram of the structure of an electronic device provided in this embodiment. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the stove anti-dry-burning control method of Embodiment 1. Figure 7 The electronic device 90 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0102] like Figure 7 As shown, the electronic device 90 can be manifested as a general-purpose computing device, such as a server device. The components of the electronic device 90 may include, but are not limited to: at least one processor 91, at least one memory 92, and a bus 93 connecting different system components (including memory 92 and processor 91).

[0103] Bus 93 includes a data bus, an address bus, and a control bus.

[0104] The memory 92 may include volatile memory, such as random access memory (RAM) 921 and / or cache memory 922, and may further include read-only memory (ROM) 923.

[0105] The memory 92 may also include a program / utility 925 having a set (at least one) of program modules 924, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0106] The processor 91 executes various functional applications and data processing by running computer programs stored in the memory 92, such as the stove anti-dry burning control method of Embodiment 1 of the present invention.

[0107] Electronic device 90 can also communicate with one or more external devices 94 (e.g., keyboard, pointing device, etc.). This communication can be performed via input / output (I / O) interface 95. Furthermore, the model-generating device 90 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 96. Figure 7 As shown, network adapter 96 communicates with other modules of the model-generated device 90 via bus 93. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the model-generated device 90, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0108] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0109] Example 4

[0110] This embodiment provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps in the stove anti-dry-burning control method of Embodiment 1.

[0111] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0112] In a possible implementation, the present invention can also be implemented as a program product comprising program code, which, when the program product is run on a terminal device, causes the terminal device to execute the steps in the control method for preventing dry burning of the stove according to Embodiment 1.

[0113] The program code for executing the present invention can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0114] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A method for controlling dry burning in a stove, characterized in that, The control method includes: Obtain cooking temperature data and cooking time from the cooktop; The confidence level for dry burning is calculated based on the cooking temperature data and the cooking time, and a cooking temperature curve is generated. If the confidence level of dry burning reaches a set threshold, the temperature curve similarity matching mechanism is activated to calculate similarity data. The temperature curve similarity matching mechanism is used to characterize the matching of the cooking temperature curve with any cooking curve in the cooking curve database based on duration similarity, temperature similarity, and curve similarity. Based on the similarity data, determine whether the cooking scenario type of the stove is a dry-burning scenario; The control method further includes: Collect several cooking curves with set cooking times corresponding to different cooking scenario types; A cooking curve database is constructed based on the cooking curves; the cooking curve database includes the percentage values ​​of different set cooking times under each of the cooking scenario types; The control start-up temperature curve similarity matching mechanism calculates similarity data through the following steps: Based on the proportion of different cooking times set in the cooking curve database, several time similarity values ​​corresponding to the cooking time are determined; The cooking temperature curve and any cooking curve in the cooking curve database are subjected to Jaccard similarity calculation and cosine similarity calculation respectively, resulting in several temperature similarity values ​​and curve similarity values. The similarity data is generated based on the duration similarity value, the temperature similarity value, and the curve similarity value.

2. The method for controlling dry burning of a stove as described in claim 1, characterized in that, The similarity data includes duration similarity values, temperature similarity values, and curve similarity values. The step of determining whether the cooking scenario type of the stove is a dry-burning scenario based on the similarity data includes: The comprehensive similarity value between the cooking temperature curve and any cooking curve in the cooking curve database is calculated based on the duration similarity value, the temperature similarity value, and the curve similarity value. The cooking scenario type corresponding to the highest comprehensive similarity value is taken as the target scenario type, and it is determined whether dry burning has occurred based on the target scenario type; the cooking scenario type includes at least one of the following: no pot dry burning scenario, oil burning scenario, pot removed scenario, dry burning scenario, casserole misjudgment scenario, and stir-fry / pan-fry scenario.

3. A control system for preventing dry burning in a stove, characterized in that, The control system includes: The acquisition module is used to acquire the cooking temperature data and cooking time of the stove. The calculation module is used to calculate the dry-burning confidence level based on the cooking temperature data and the cooking time, and to generate a cooking temperature curve; The control module is used to activate the temperature curve similarity matching mechanism and calculate similarity data if the dry burning confidence reaches a set threshold. The temperature curve similarity matching mechanism is used to characterize the matching of the cooking temperature curve with any cooking curve in the cooking curve database based on duration similarity, temperature similarity, and curve similarity. The determination module is used to determine whether the cooking scenario type of the stove is a dry-burning scenario based on the similarity data; The control system further includes: The collection module is used to collect several cooking curves corresponding to different cooking scenario types and set cooking times; The construction module is used to construct a cooking curve database based on the cooking curves; the cooking curve database includes the percentage of different set cooking times for each cooking scenario type; The control module includes: The determining unit is used to determine the proportion of different cooking scenario types corresponding to the cooking time based on the cooking curve database, and to obtain several time similarity values. The second calculation unit is used to perform Jaccard similarity calculation and cosine similarity calculation on the cooking temperature curve and any cooking curve in the cooking curve database respectively, and obtain several temperature similarity values ​​and curve similarity values ​​accordingly. The generation unit is used to generate the similarity data based on the length similarity value, the temperature similarity value, and the curve similarity value.

4. The control system for preventing dry burning of a stove as described in claim 3, characterized in that, The similarity data includes duration similarity values, temperature similarity values, and curve similarity values. The determination module includes: The first calculation unit is used to calculate a comprehensive similarity value between the cooking temperature curve and any cooking curve in the cooking curve database based on the duration similarity value, the temperature similarity value, and the curve similarity value. The determination unit is used to take the cooking scene type corresponding to the highest comprehensive similarity value as the target scene type, and to determine whether dry burning has occurred based on the target scene type; the cooking scene type includes at least one of the following: no pot dry burning scene, oil burning scene, pot removed scene, dry burning scene, casserole misjudgment scene, and stir-fry / pan-fry scene.

5. A stove, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the anti-dry-burning control method for the stove as described in claim 1 or 2.

6. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, it implements the stove anti-dry-burning control method as described in claim 1 or 2.

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