CN110488696B - Intelligent dry burning prevention method and system - Google Patents
Intelligent dry burning prevention method and system Download PDFInfo
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- CN110488696B CN110488696B CN201910739744.8A CN201910739744A CN110488696B CN 110488696 B CN110488696 B CN 110488696B CN 201910739744 A CN201910739744 A CN 201910739744A CN 110488696 B CN110488696 B CN 110488696B
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
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Abstract
An intelligent dry burning prevention method comprises the following steps: acquiring a state image of the cooking appliance in the cooking process; identifying the state image to acquire attribute information related to the cooking process, and searching dry burning critical state information matched with the attribute information in a database according to the identified attribute information; acquiring temperature information of a cooking appliance in a cooking process; and judging whether the cooking appliance is dried according to the temperature information and the searched dry-burning critical state information. Because the dry-burning state of the cooking appliance is judged by combining image identification and temperature detection, the state image of the cooking appliance in the cooking process is classified and identified by an artificial intelligence method, and the cooking state is monitored in real time by adopting a corresponding dry-burning critical state point according to an identification result, the accuracy of judging the dry-burning states of different cooking appliances is effectively improved, and the identification error is effectively reduced. And the whole system has low development cost, is convenient to assemble with other household kitchenware and is more convenient and faster to use.
Description
Technical Field
The invention relates to the technical field of kitchenware, in particular to an energy-knowing dry-burning-preventing method and system.
Background
The dry burning prevention technology for the kitchen range is mainly applied to the household cooking environment, the technology can effectively avoid the conditions of rapid rust, oxidation, damage and the like of the cooker caused by dry burning and a series of potential safety hazards of extinguishing a fire source, conduction, gas leakage, fire and the like of liquid contained due to the damage of the cooker, and a safer living environment is created at home.
Under the current household appliance market development condition, the dry burning prevention technology of the kitchen range is in a link of updating iteration. The anti-dry burning technology that appears at present can not make corresponding adjustment according to the culinary art condition in the in-service use scene, also can not make accurate discernment to the different materials and the classification of cooking utensils whether to have the dry burning condition to it, perhaps in order to realize preventing the dry burning effect, uses very complicated logical structure and identification model, has spent a large amount of costs.
Disclosure of Invention
The application provides an intelligent dry-burning prevention method and system, which can judge whether a cooking appliance is in a dry-burning prevention state or not by identifying attribute information related to a cooking process and combining with the currently collected temperature, so that an intelligent dry-burning prevention effect is achieved.
According to a first aspect, an embodiment provides an intelligent dry-burning prevention method, comprising the steps of:
acquiring a state image of the cooking appliance in the cooking process;
identifying the state image to acquire attribute information related to a cooking process, and searching dry-burning critical state information matched with the attribute information in a database according to the identified attribute information, wherein the attribute information related to the cooking process of the cooking appliance and the dry-burning critical state of the cooking appliance related to the attribute information are stored in the database;
acquiring temperature information of a cooking appliance in a cooking process;
and judging whether the cooking appliance is dried according to the temperature information and the searched dry-burning critical state information.
In one embodiment, the attribute information related to the cooking process includes a cooking appliance self attribute, a heat source attribute and a food material attribute, wherein the attribute information related to the cooking appliance stored in the database at least includes the cooking appliance self attribute.
In one embodiment, the attributes of the cooking appliance include, but are not limited to, the material, size, kind and aging degree of the cooking appliance, the attributes of the heat source include, but are not limited to, the kind of heat source and the amount of fire, and the attributes of the food material include, but are not limited to, the kind and size of the food material and the position of the food material in the cooking appliance.
In one embodiment, the identifying the state image and obtaining the attribute information related to the cooking process specifically obtains the attribute of the cooking appliance in the state image, so as to search, in a database, dry-cooking critical state information related to the attribute of the cooking appliance according to the attribute of the cooking appliance, and determine whether the cooking appliance is dry-cooked according to the temperature information and the searched dry-cooking critical state information.
In an embodiment, the identifying the state image to obtain the attribute information related to the cooking process specifically obtains the attribute of the cooking appliance and the type of food in the cooking appliance in the state image, so as to search, in a database, the dry-cooking critical state information associated with the attribute of the cooking appliance and the type of food according to the attribute of the cooking appliance and the type of food, and determine whether the cooking appliance is dry-cooked according to the temperature information and the searched dry-cooking critical state information.
In one embodiment, the identifying the state image to obtain the attribute information related to the cooking process specifically obtains the attribute of the cooking appliance and the type and size of the food in the cooking appliance in the state image, and the determining whether the cooking appliance is dry-burned includes:
searching dry-burning critical state information associated with the attributes of the cooking appliance and the food material types in a database according to the attributes of the cooking appliance and the food material types;
dynamically setting dry-cooking critical state information of the current cooking process according to the size of the identified food material and the searched dry-cooking critical state information;
and judging whether the cooking appliance is dried according to the temperature information and the currently set critical state information of the dried cooking.
In one embodiment, the process of acquiring attribute information related to the cooking process by the identification state image further includes acquiring a heat source type so as to look up associated dry-cooking critical state information in a database in combination with the heat source type.
In one embodiment, the identifying the state image and acquiring the attribute information related to the cooking process further comprises acquiring a heat source type and a fire power, and the determining whether the cooking appliance is dry-burned comprises the steps of:
searching related dry burning critical state information in a database by combining with the type of the heat source;
dynamically setting dry-cooking critical state information of the current cooking process by combining the recognized firepower and the searched dry-cooking critical state information;
and judging whether the cooking appliance is dried according to the temperature information and the currently set critical state information of the dried cooking.
In an embodiment, if the acquired attributes of the cooking utensil in the state image are partial attributes, the method further includes a step of filling the non-acquired attributes of the cooking utensil.
In one embodiment, the unexplored attributes of the cooking appliance are populated using mean, nearest neighbor, regression equation estimation, or expectation maximization.
In one embodiment, the method further comprises the step of updating the database.
In one embodiment, the method further comprises the step of starting to prevent dry heating if the cooking appliance is judged to be dry heating.
In one embodiment, the starting of the anti-dry heating comprises starting an alarm or/and automatically turning off a heat source.
According to a second aspect, an embodiment provides an intelligent dry-heating prevention system, comprising:
the image acquisition module is used for acquiring a state image of the cooking appliance in the cooking process;
the temperature acquisition module is used for acquiring temperature information of the cooking appliance in the cooking process;
the processing module is used for executing the following operations to judge whether the cooking appliance is in dry burning or not:
identifying the state image to acquire attribute information related to a cooking process;
searching dry-burning critical state information matched with the attribute information in the database according to the identified attribute information, wherein the attribute information related to the cooking process of the cooking appliance and the dry-burning critical state of the cooking appliance related to the attribute information are stored in the database;
and judging whether the cooking appliance is dried according to the temperature information and the searched dry-burning critical state information.
In one embodiment, the attribute information related to the cooking process includes a cooking appliance self attribute, a heat source attribute and a food material attribute, wherein the attribute information related to the cooking appliance stored in the database at least includes the cooking appliance self attribute.
In one embodiment, the attributes of the cooking appliance include, but are not limited to, the material, size, kind and aging degree of the cooking appliance, the attributes of the heat source include, but are not limited to, the kind of heat source and the amount of fire, and the attributes of the food material include, but are not limited to, the kind and size of the food material and the position of the food material in the cooking appliance.
In one embodiment, the processing module identifies the state image to obtain attribute information related to a cooking process, specifically obtains an attribute of the cooking appliance in the state image, searches dry-cooking critical state information associated with the attribute of the cooking appliance in a database according to the attribute of the cooking appliance, and determines whether the cooking appliance is dry-cooked according to the temperature information and the searched dry-cooking critical state information.
In an embodiment, the processing module identifies the state image to obtain attribute information related to a cooking process, specifically obtains a self-attribute of the cooking appliance and a type of food in the cooking appliance in the state image, searches, in a database, dry-cooking critical state information associated with the self-attribute of the cooking appliance and the type of food according to the self-attribute of the cooking appliance and the type of food, and determines whether the cooking appliance is dry-cooked according to the temperature information and the searched dry-cooking critical state information.
In one embodiment, the processing module identifies the state image to obtain attribute information related to a cooking process, specifically obtains an attribute of the cooking appliance and a type and a size of food in the cooking appliance in the state image, and the processing module performs the following operations to determine whether the cooking appliance is dry-burned:
searching dry-burning critical state information associated with the attributes of the cooking appliance and the food material types in a database according to the attributes of the cooking appliance and the food material types;
dynamically setting dry-cooking critical state information of the current cooking process according to the size of the identified food material and the searched dry-cooking critical state information;
and judging whether the cooking appliance is dried according to the temperature information and the currently set critical state information of the dried cooking.
In one embodiment, the process of acquiring attribute information related to the cooking process by identifying the state image by the processing module further comprises acquiring a heat source type so as to look up associated dry-cooking critical state information in a database by combining the heat source type.
In one embodiment, the process module identifies that the process of acquiring the attribute information related to the cooking process by the state image further comprises acquiring the type of the heat source and the fire power, and the process module performs the following operations to judge whether the cooking appliance is dry-burned or not:
searching related dry burning critical state information in a database by combining with the type of the heat source;
dynamically setting dry-cooking critical state information of the current cooking process by combining the recognized firepower and the searched dry-cooking critical state information;
and judging whether the cooking appliance is dried according to the temperature information and the currently set critical state information of the dried cooking.
In one embodiment, if the processing module identifies that the obtained attributes of the cooking utensil self from the state image are partial attributes, the processing module is further configured to fill in the non-obtained attributes of the cooking utensil self.
In one embodiment, the cooking appliance further comprises an alarm module, and the processing module is used for controlling the alarm module to give an alarm when the cooking appliance is dried.
According to the intelligent dry-heating prevention method of the embodiment, the dry-heating state of the cooking appliance is judged in a mode of combining image recognition and temperature detection, the state image of the cooking appliance in the cooking process is classified and recognized by an artificial intelligence method, the cooking state is monitored in real time by adopting the corresponding dry-heating critical state point according to the recognition result, the accuracy of judging the dry-heating state of different cooking appliances is effectively improved, and the recognition error is effectively reduced. And the whole system has low development cost, is convenient to assemble with other household kitchenware and is more convenient and faster to use.
Drawings
FIG. 1 is a flow chart of an intelligent dry burning prevention method;
fig. 2 is a schematic diagram of an intelligent dry-burning prevention system.
Detailed Description
The present invention will be described in further detail with reference to the following detailed description and accompanying drawings.
The first embodiment is as follows:
the embodiment provides an intelligent dry-burning prevention method, which is applied to controlling the dry burning of a kitchen range, and the specific control flow chart is shown in figure 1, and specifically comprises the following steps.
S1: the method comprises the steps of collecting state images of the cooking appliance in the cooking process.
S2: and identifying the state image to acquire attribute information related to the cooking process, and searching the dry burning critical state information matched with the attribute information in the database according to the identified attribute information.
The database stores attribute information related to the cooking process of the cooking appliance and the dry-burning critical state of the cooking appliance related to the attribute information.
S3: acquiring temperature information of a cooking appliance in a cooking process;
s4: and judging whether the cooking appliance is dried according to the temperature information and the searched dry-burning critical state information.
Because the dry-burning state of the cooking appliance is judged by combining image identification and temperature detection, the state image of the cooking appliance in the cooking process is classified and identified by an artificial intelligence method, and the cooking state is monitored in real time by adopting a corresponding dry-burning critical state point according to an identification result, the accuracy of judging the dry-burning states of different cooking appliances is effectively improved, and the identification error is effectively reduced.
The specific implementation of the above steps is described in detail below.
First, it should be noted that, in the present embodiment, attribute information related to a cooking process is obtained by identifying state images of various cooking appliances in the cooking process, and then dry-burning critical state information corresponding to the attribute information is found in a database, so that a corresponding database is required to be constructed in advance, in which a large amount of experimental data of dry-burning of the cooking appliances are stored, that is, experiments are required to be performed on the cooking processes of various types of cooking appliances to obtain dry-burning critical states of cooking of various types of cooking appliances, and the experimental data is stored in the database in a specified format, for example, in a list form, which is only required to be conveniently searched in the database.
In this example, the attribute information related to the cooking process includes a cooking appliance self attribute, a heat source attribute, and a food material attribute, where the attribute information related to the cooking appliance stored in the database at least includes the cooking appliance self attribute, and in other embodiments, the database may also store the cooking appliance self attribute and the heat source attribute, and may also store the cooking appliance self attribute, the heat source attribute, and the food material attribute.
The cooking appliance self attribute includes but is not limited to the material, size, kind and aging degree of the cooking appliance, the heat source attribute includes but is not limited to the heat source kind and fire power, and the food material attribute includes but is not limited to the kind and size of the food material and the position of the food material in the cooking appliance.
Different heat sources and different types of food materials have influences on the threshold value of dry burning, such as different firepower, different boiling points of water and oil, and the like. In order to obtain more sampling standards, different heat sources and different food materials are required to be adopted as many as possible to perform dry-burning experiments on different types of cooking appliances, so that a large number of experiments are required to perform the dry-burning experiments on the cooking appliances according to the attributes, and corresponding experimental data are stored in a database. Specifically, during the experiment, cooking utensils (such as a steamer, a wok, a soup pot and the like) are placed on different heat sources (such as a gas stove, an induction cooker and the like); putting different food materials (water, oil, vegetables, meat, etc.) into a cooking utensil; heating the cooking utensil (different firepower); and recording the temperature and the change of the cooking utensil in real time in the heating process, and recording the time node of the experiment dry burning and the corresponding dry burning temperature.
The procedure of the experiment was as follows:
step 1: calibrating the self attribute, the food material attribute and the heat source attribute of the cooking appliance respectively;
specifically, attribute information including various cooking appliances used daily, including but not limited to material, size, type, shape and aging degree, is collected or collected and calibrated.
For example, the cooking utensil can be a steamer, a wok, a frying pan, a soup pot, a braising pot and the like, and the cooking utensil can be a stainless steel pot, an iron pot, a ceramic pot, a glass pot, a marmite and the like.
Step 2: and measuring the dry-burning critical temperature of the cooking appliance in the cooking process according to the calibrated attributes, and forming a list of the attributes calibrated in the experiment and the corresponding dry-burning critical temperature and storing the list in a database.
It should be noted that the above only provides the basic concept of the experimental process, and those skilled in the art can correspondingly adjust the parameters required in the experiment of the cooking process of the cooking appliance according to the actual application, for example, only calibrate the attributes of the cooking appliance itself, as long as the table formed according to the calibrated attributes and the critical temperature of dry-cooking in the corresponding experiment can be stored in the database for the subsequent intelligent dry-cooking prevention application.
In step S1, since it is necessary to acquire the state image of the cooking appliance during the cooking process and to acquire the attribute information related to the cooking process by recognizing the state image in an artificial intelligence manner, it is important to acquire the panoramic image as much as possible, that is, to acquire the image capturing device without any occlusion in the imaging range, in the manner of mounting the image capturing device in step S1.
In step S2, the identification status image is used to acquire the attribute information related to the cooking process, and since the above description describes the type and corresponding attribute components of the attribute information related to the cooking process, step S2 specifically needs to identify which attribute information has a direct influence on the determination of whether the cooking appliance is dry-burned in step S4.
The following recognition results and corresponding dry burning prevention judgment modes are provided below.
The first mode is as follows: identifying the state image and acquiring the attribute information related to the cooking process specifically acquires the attribute of the cooking appliance in the state image, that is, only the attribute of the cooking appliance is identified in this way.
The corresponding dry burning prevention judgment mode is as follows: and searching dry-burning critical state information associated with the attributes of the cooking appliance in the database according to the attributes of the cooking appliance, and judging whether the cooking appliance is dry-burned or not according to the temperature information and the searched dry-burning critical state information.
In the above experiment, for example, a temperature mean value of the cooking appliance in a preset time under the dry-burning condition is collected, and the temperature mean value is set as a dry-burning critical threshold value under each attribute category in the current experiment; for example, when the cooking appliance is in a dry-burning state, the temperature change rate of the cooking appliance from the temperature of entering the dry-burning state to the dry-burning condition for the preset time is set as the dry-burning critical threshold value of each attribute type in the current experiment.
And if the dry-cooking critical threshold is the temperature, judging whether the currently acquired temperature is greater than or equal to the found dry-cooking critical threshold, and if so, performing dry-cooking on the cooking appliance.
The second way is: identifying the state image and acquiring the attribute information related to the cooking process specifically acquires the attribute of the cooking appliance and the type of the food in the cooking appliance in the state image, compared with the first mode, the mode of identifying the type of the food in addition to identifying the attribute of the cooking appliance is also adopted.
The corresponding dry burning prevention judgment mode is as follows: searching dry-burning critical state information associated with the attributes of the cooking appliance and the types of the food materials in a database according to the attributes of the cooking appliance and the types of the food materials, and judging whether the cooking appliance is dry-burned or not according to the temperature information and the searched dry-burning critical state information; the first method can be referred to as a specific determination method.
The third mode is that: identifying the state image and acquiring attribute information related to the cooking process specifically acquire the attribute of the cooking appliance and the type and size of food in the cooking appliance in the state image, and the mode needs to identify the attribute of the cooking appliance and the type and size of the food in the cooking appliance.
The corresponding dry burning prevention judgment mode is as follows:
searching dry-burning critical state information associated with the attributes of the cooking appliance and the food material types in a database according to the attributes of the cooking appliance and the food material types;
dynamically setting dry-cooking critical state information of the current cooking process according to the size of the identified food material and the searched dry-cooking critical state information;
and judging whether the cooking appliance is dried according to the temperature information and the currently set critical state information of the dried cooking.
The third method dynamically adjusts the dry-cooking critical state information in combination with the size of the food material, for example, if the volume of the food material calibrated during the experiment is smaller than the volume of the currently cooked food material, the dry-cooking critical threshold value needs to be dynamically adjusted according to the volume of the currently cooked food material, and for example, the adjusted dry-cooking critical threshold value is larger than the dry-cooking critical threshold value recorded during the experiment.
The fourth mode is: the process of acquiring attribute information related to the cooking process by identifying the state image further comprises acquiring heat source types, wherein the heat source types comprise gas types and electric types, and different types of heat sources can influence the critical point of dry burning of the cooking appliance.
The fifth mode is as follows: the process of acquiring attribute information related to the cooking process by identifying the state image further comprises the step of acquiring the type and the fire power magnitude of the heat source, the method can be used in combination with any one of the above methods, and the purpose of the method is to identify the type and the fire power magnitude of the heat source on the basis of acquiring the corresponding attribute in any one of the above methods.
The corresponding dry burning prevention judgment mode is as follows:
on the basis of acquiring corresponding attributes, searching related dry burning critical state information in a database by combining with the type of a heat source;
dynamically setting the dry-cooking critical state information of the current cooking process by combining the recognized firepower and the searched dry-cooking critical state information;
and judging whether the cooking appliance is dried according to the temperature information and the currently set critical state information of the dried cooking.
In practical applications, whether the cooking appliance is dry-burned or not may be determined according to any one of the manners, or any two of the manners, any three of the manners, or any combination of the other manners may be used to obtain corresponding attributes, and determine whether the cooking appliance is dry-burned or not.
Additionally, in some scenarios, certain attributes may be difficult to identify. If the material of the cooking appliance cannot be identified, the attribute needs to be completely supplemented to match the corresponding anti-dry heating threshold, so in this example, if the cooking appliance self attribute in the acquired state image is a partial attribute, the method further includes a step of filling the non-acquired cooking appliance self attribute, for example, filling the non-acquired cooking appliance self attribute by using an average value, nearest neighbor, regression equation estimation or expected value maximization manner.
In order to enrich and improve the experimental data stored in the database, the method further comprises the step of updating the database, such as periodically supplementing the database with new data of the experimental cooking appliance dry-burning. In other embodiments, the data of the dry cooking generated in the actual cooking process can be uploaded to a corresponding database based on the internet.
In other embodiments, when no attribute information is identified, the cooking process for the cooking appliance may be considered completely unknown at this time. The method also comprises the steps of recommending a plurality of dry burning thresholds to the user, wherein the thresholds comprise a default threshold; the user decides which threshold to adopt, and when the user has no decision, a default threshold is adopted; attributes such as the type and material of the cooking appliance may be recommended to the user, or the user may input corresponding attribute information.
Whether the cooking utensil generates dry combustion can be accurately judged by the mode, and correspondingly, if the cooking utensil generates dry combustion, the method further comprises the step of starting dry combustion prevention, for example, the step of starting dry combustion prevention can be starting alarm, can also be automatically closing a heat source, and can also be the combination of the two.
According to the intelligent dry-heating prevention method provided by the embodiment, the dry-heating state of the cooking appliance is judged by combining image identification and temperature detection, the state images of the cooking appliance in the cooking process are classified and identified by using an artificial intelligence method, and the cooking state is monitored in real time by adopting the corresponding dry-heating critical state point according to the identification result, so that the accuracy of judging the dry-heating state of different cooking appliances is effectively improved, and the identification error is effectively reduced.
Example two:
based on the first embodiment, the present example provides an intelligent dry-burning prevention system, whose schematic diagram is shown in fig. 2, and includes an image acquisition module, a temperature acquisition module, and a processing module.
The image acquisition module is used for gathering cooking utensil at the state image of culinary art in-process, and the image acquisition module includes camera and light filling subassembly, and camera and light filling subassembly correspond and install on smoke extractor or integrated kitchen or other positions, and the mounted position of camera is in order to observe cooking utensil as the standard, and the resolution ratio is in order to clearly shoot the image in kind as the standard.
The temperature acquisition module is used for acquireing cooking utensil temperature information at the culinary art in-process, and the temperature acquisition module can adopt but not limited to multiple spot or single-point infrared temperature sensor, and the temperature acquisition module can be installed on smoke extractor or integrated kitchen, and in addition, the temperature acquisition module also can adopt other temperature sensor that have physical structure to install in other positions, the mounted position of temperature acquisition module is with can acquireing the temperature that places the cooking utensil on the kitchen as the standard.
The processing module is used for executing the following operations to judge whether the cooking utensil is dry-burned or not:
identifying the state image to acquire attribute information related to the cooking process;
searching dry-burning critical state information matched with the attribute information in the database according to the identified attribute information, wherein the attribute information related to the cooking process of the cooking appliance and the dry-burning critical state of the cooking appliance related to the attribute information are stored in the database;
and judging whether the cooking appliance is dried according to the temperature information and the searched dry-burning critical state information.
The attribute information related to the cooking process comprises the attributes of the cooking appliance, the heat source attribute and the food material attribute, wherein the attribute information related to the cooking appliance stored in the database at least comprises the attributes of the cooking appliance; specifically, the attributes of the cooking appliance include, but are not limited to, the material, size, kind and aging degree of the cooking appliance, the attributes of the heat source include, but are not limited to, the kind of the heat source and the amount of fire, and the attributes of the food material include, but are not limited to, the kind and size of the food material and the position of the food material in the cooking appliance.
The processing module is a core processor of the intelligent anti-dry heating system, the processing module is provided with an identification model, and relevant attribute information in the cooking process of the cooking appliance is identified through the identification model.
In order to improve the accuracy of the convolutional neural network model, in the experimental stage, the convolutional neural network model is trained by collecting a large amount of different attribute information, and the convolutional neural network model is trained specifically according to different attributes.
In another embodiment, in the recognition process, the current attribute information may be determined by integrating the recognition results of the plurality of state images.
In other embodiments, the convolutional neural network model can also be trained specifically for a specific use scene, so that the recognition effect of the household cooking appliance of the user is enhanced, and in addition, under the condition of an external network, the convolutional neural network model can be updated in real time, so that the recognition effect of the dry-burning state is continuously optimized.
In combination with the training of the convolutional neural network model, in an embodiment, the processing module identifies the state image based on the trained convolutional neural network model to acquire attribute information related to the cooking process, specifically to acquire the attribute of the cooking appliance in the state image, to search the dry-cooking critical state information related to the attribute of the cooking appliance in the database according to the attribute of the cooking appliance, and to judge whether the cooking appliance is dry-cooked according to the temperature information and the searched dry-cooking critical state information.
In another embodiment, the processing module identifies a state image based on a trained convolutional neural network model to acquire attribute information related to a cooking process, specifically to acquire the attributes of the cooking appliance and the types of food materials in the cooking appliance in the state image, so as to search dry-cooking critical state information related to the attributes of the cooking appliance and the types of the food materials in a database according to the attributes of the cooking appliance and the types of the food materials, and judge whether the cooking appliance is dry-cooked according to the temperature information and the searched dry-cooking critical state information.
In another embodiment, the processing module identifies a state image based on a trained convolutional neural network model to obtain attribute information related to a cooking process, specifically to obtain attributes of a cooking appliance and types and sizes of food materials in the cooking appliance in the state image, and the processing module executes the following operations to determine whether the cooking appliance is dry-burned:
searching dry-burning critical state information associated with the attributes of the cooking appliance and the food material types in a database according to the attributes of the cooking appliance and the food material types;
dynamically setting dry-cooking critical state information of the current cooking process according to the size of the identified food material and the searched dry-cooking critical state information;
and judging whether the cooking appliance is dried according to the temperature information and the currently set critical state information of the dried cooking.
In another embodiment, the process of acquiring attribute information related to the cooking process by the processing module based on the trained convolutional neural network model identification state image further comprises acquiring a heat source type so as to search and associate the dry-burning critical state information in the database by combining the heat source type.
In another embodiment, the process of acquiring attribute information related to a cooking process by the processing module based on the trained convolutional neural network model identification state image further comprises acquiring the type of a heat source and the size of fire, and the processing module executes the following operations to judge whether the cooking appliance is dry-burned:
searching related dry burning critical state information in a database by combining with the type of the heat source;
dynamically setting dry-cooking critical state information of the current cooking process by combining the recognized firepower and the searched dry-cooking critical state information;
and judging whether the cooking appliance is dried according to the temperature information and the currently set critical state information of the dried cooking.
According to the embodiments, the convolutional neural network model can be trained specifically according to specific applications, so as to achieve corresponding recognition results.
If the processing module identifies that the attribute of the cooking appliance obtained from the state image is a partial attribute, the processing module is further configured to fill the attribute of the cooking appliance which is not obtained, and a specific filling manner may refer to the first embodiment.
The cooking appliance also comprises an alarm module, wherein the alarm module is used for controlling the alarm module to give an alarm when the cooking appliance is dried, for example, the alarm module can give an audible and visual alarm, and the processing module can control the heat source to be closed while giving an alarm.
The intelligent anti-dry heating system of the embodiment can also comprise various networking modes such as WIFI, Bluetooth, 2G/3G/4G/5G and the like, so that various data and parameters generated in the cooking process of the cooking appliance can be uploaded to the cloud server through the network, the identification model is updated from the cloud, the use data of a user is updated, and the identification precision is improved.
The intelligent dry-burning prevention system of the embodiment can also comprise a loudspeaker, a microphone, a touch screen and the like, is used for carrying out voice interaction and intelligent control on a consumer, and gives an alarm through the loudspeaker when a dry-burning state occurs.
The present invention has been described in terms of specific examples, which are provided to aid understanding of the invention and are not intended to be limiting. For a person skilled in the art to which the invention pertains, several simple deductions, modifications or substitutions may be made according to the idea of the invention.
Claims (9)
1. An intelligent dry burning prevention method is characterized by comprising the following steps:
acquiring a state image of the cooking appliance in the cooking process;
identifying the state image to acquire attribute information related to a cooking process, and searching dry-burning critical state information matched with the attribute information in a database according to the identified attribute information, wherein the attribute information related to the cooking process of the cooking appliance and the dry-burning critical state of the cooking appliance related to the attribute information are stored in the database; specifically, the attribute information related to the cooking process includes a cooking appliance self attribute, a heat source attribute and a food material attribute, wherein the cooking appliance self attribute includes a material, a size, a kind and an aging degree of the cooking appliance, the heat source attribute includes a heat source kind and a fire power, and the food material attribute includes a food material kind, a size and a position of the food material in the cooking appliance; specifically, the method comprises the following steps:
the method comprises the following steps: acquiring the attribute of the cooking appliance and the type and size of food materials in the cooking appliance in the state image;
searching dry-burning critical state information associated with the attributes and the food material types of the cooking appliances in a database according to the attributes and the food material types of the cooking appliances;
dynamically setting dry-cooking critical state information of the current cooking process according to the size of the identified food material and the searched dry-cooking critical state information;
further comprising the steps of: obtaining the type and the firepower of a heat source;
searching related dry burning critical state information in a database by combining with the type of the heat source;
dynamically setting the dry-cooking critical state information of the current cooking process by combining the recognized firepower and the searched dry-cooking critical state information;
acquiring temperature information of a cooking appliance in a cooking process;
and judging whether the cooking appliance is dried according to the temperature information and the currently set critical state information of the dried cooking.
2. The intelligent dry-heating prevention method according to claim 1, further comprising the step of filling the non-acquired attributes of the cooking appliance if the acquired attributes of the cooking appliance in the status image are partial attributes.
3. The intelligent dry-fire prevention method of claim 2, wherein the unexpected attributes of the cooking appliance are filled in using a mean, nearest neighbor, regression equation estimation or expectation maximization.
4. The intelligent dry-fire prevention method of claim 1, further comprising the step of updating the database.
5. The intelligent dry-heating prevention method according to claim 1, further comprising the step of starting dry-heating prevention if the cooking appliance is judged to be dry-heated.
6. The intelligent dry-heating prevention method according to claim 5, wherein the starting of dry-heating prevention comprises starting an alarm or/and automatically turning off a heat source.
7. The utility model provides an intelligence prevents dry combustion method system which characterized in that includes:
the image acquisition module is used for acquiring a state image of the cooking appliance in the cooking process;
the temperature acquisition module is used for acquiring temperature information of the cooking appliance in the cooking process;
the processing module is used for executing the following operations to judge whether the cooking utensil is dry-burned or not:
identifying the state image to acquire attribute information related to a cooking process, specifically, the attribute information related to the cooking process comprises attributes of a cooking appliance, a heat source attribute and a food material attribute, wherein the attributes of the cooking appliance comprise the material, the size, the category and the aging degree of the cooking appliance, the heat source attribute comprises the heat source category and the firepower, and the food material attribute comprises the category and the size of a food material and the position of the food material in the cooking appliance;
searching dry-burning critical state information matched with the attribute information in a database according to the identified attribute information, wherein the attribute information related to the cooking process of the cooking appliance and the dry-burning critical state of the cooking appliance related to the attribute information are stored in the database; specifically, the method comprises the following steps:
the method comprises the following steps: acquiring the attribute of the cooking appliance and the type and size of food materials in the cooking appliance in the state image;
searching dry-burning critical state information associated with the attributes and the food material types of the cooking appliances in a database according to the attributes and the food material types of the cooking appliances;
dynamically setting dry-cooking critical state information of the current cooking process according to the size of the identified food material and the searched dry-cooking critical state information;
further comprising the steps of: obtaining the type and the firepower of a heat source;
searching related dry burning critical state information in a database by combining with the type of the heat source;
dynamically setting the dry-cooking critical state information of the current cooking process by combining the recognized firepower and the searched dry-cooking critical state information;
and judging whether the cooking appliance is dried according to the temperature information and the currently set critical state information of the dried cooking.
8. The intelligent anti-dry heating system according to claim 7, wherein if the processing module identifies that the obtained cooking utensil self attribute of the status image is a partial attribute, the processing module is further configured to fill the non-obtained cooking utensil self attribute.
9. The intelligent dry-heating prevention system of claim 7, further comprising an alarm module, wherein the alarm module is used for controlling the alarm module to give an alarm when the cooking appliance is dry-heated.
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| CN112902237B (en) * | 2021-01-26 | 2022-03-08 | 宁波方太厨具有限公司 | Protection device of cooker camera, control method of protection device and cooker system |
| CN114115041A (en) * | 2021-11-26 | 2022-03-01 | 杭州老板电器股份有限公司 | Method, system, device and medium for preventing dry pot from being burnt during cooking |
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