CN112107231B - Processing method and device and storage device - Google Patents
Processing method and device and storage device Download PDFInfo
- Publication number
- CN112107231B CN112107231B CN201910542288.8A CN201910542288A CN112107231B CN 112107231 B CN112107231 B CN 112107231B CN 201910542288 A CN201910542288 A CN 201910542288A CN 112107231 B CN112107231 B CN 112107231B
- Authority
- CN
- China
- Prior art keywords
- processing
- mixture
- information
- recording
- water level
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47J—KITCHEN EQUIPMENT; COFFEE MILLS; SPICE MILLS; APPARATUS FOR MAKING BEVERAGES
- A47J36/00—Parts, details or accessories of cooking-vessels
- A47J36/32—Time-controlled igniting mechanisms or alarm devices
-
- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47J—KITCHEN EQUIPMENT; COFFEE MILLS; SPICE MILLS; APPARATUS FOR MAKING BEVERAGES
- A47J43/00—Implements for preparing or holding food, not provided for in other groups of this subclass
- A47J43/04—Machines for domestic use not covered elsewhere, e.g. for grinding, mixing, stirring, kneading, emulsifying, whipping or beating foodstuffs, e.g. power-driven
- A47J43/07—Parts or details, e.g. mixing tools, whipping tools
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D23/00—Control of temperature
- G05D23/19—Control of temperature characterised by the use of electric means
- G05D23/20—Control of temperature characterised by the use of electric means with sensing elements having variation of electric or magnetic properties with change of temperature
Landscapes
- Engineering & Computer Science (AREA)
- Food Science & Technology (AREA)
- Mechanical Engineering (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- General Preparation And Processing Of Foods (AREA)
- Cookers (AREA)
- Commercial Cooking Devices (AREA)
Abstract
The invention relates to the field of food material processing methods, in particular to a processing method, a processing device and a storage device, wherein the processing method comprises the following steps: pre-self-learning a mixture formed by mixing water and food materials in proportion to generate a self-learned processing model; and calculating the boiling time information of the mixture acquired in real time by adopting the processing model to obtain water level information and processing information corresponding to the mixture, and performing corresponding processing on the mixture according to the processing information. The processing model is generated through self-learning of the mixture, then when the device is used every time, water level information and processing information can be obtained according to boiling time through the processing model, then the mixture is processed according to the processing information, and the intelligent degree is high.
Description
Technical Field
The invention relates to the field of food material processing methods, in particular to a processing method, a processing device and a storage device.
Background
Common kitchen utensils include a processor which can form edible thick solid liquid by mechanical stirring after a mixture of food materials and water is heated and boiled, such as coarse cereal porridge formed by mixing water and coarse cereals, soybean milk formed by mixing water and soybeans, corn juice formed by mixing water and corn, and the like.
However, the existing food processor can only be manually operated by a user, and the user can measure the amount of water and food materials added, and then can select processing parameters such as heating temperature, heating time and the like. This cooking machine intelligent degree is not high, because the processing parameter that user oneself selected often is not the best processing parameter of eating the material, leads to the food of decocting out at last not delicious enough, and the taste is also not good, brings relatively poor use for the user and experiences.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a processing method, a processing device and a storage device for solving the above-mentioned drawbacks of the prior art, and to solve the problems that the boiled food is not delicious and the taste is not good due to the fact that the processing parameters manually selected are often not the optimal processing parameters of the food materials.
In order to solve the technical problem, the invention provides a processing method, which comprises the following steps: pre-self-learning a mixture formed by mixing water and food materials in proportion to generate a self-learned processing model; and calculating the boiling time information of the mixture acquired in real time by adopting the processing model to obtain water level information and processing information corresponding to the mixture, and performing corresponding processing on the mixture according to the processing information.
Further, the step of pre-learning the mixture formed by mixing the water and the food materials in proportion to generate a self-learned processing model specifically includes: recording water level information of the mixture poured into the food processor for multiple times, wherein the mixture is formed by mixing water and food materials in proportion, and the water level information of the mixture poured each time is different; recording the boiling time information of the mixture after boiling; recording processing information after the mixture is processed; and generating a processing model.
Further, the step of recording the boiling time information of the mixture after boiling specifically includes: recording first time information T1 when the mixture is heated and reaches a first preset temperature; recording second time information T2 when the mixture continues to be heated and reaches a second preset temperature; and acquiring and recording the boiling time information according to the first time information T1 and the second time information T2.
Further, the first predetermined temperature is 40 degrees, and the second predetermined temperature is 100 degrees.
Further, the water level information comprises the highest water level and the lowest water level of the food processor.
Further, the processing information includes processing time, processing temperature, and rotational stirring speed.
The present invention also provides a processing apparatus comprising: the self-learning unit is used for pre-learning a mixture formed by mixing water and food materials in proportion to generate a self-learned processing model; and the processing unit is used for calculating the boiling time information of the mixture acquired in real time by adopting the processing model to obtain the water level information and the processing information corresponding to the mixture, and performing corresponding processing on the mixture according to the processing information.
Further, the self-learning unit specifically includes: the first recording unit is used for recording water level information of the mixture poured into the food processor for multiple times, the mixture is formed by proportionally mixing water and food materials, and the water level information of the mixture poured each time is different; a second recording unit for recording boiling time information after the mixture is boiled; the third recording unit is used for recording the processing information of the mixture after processing; and the generating unit is used for generating the processing model.
Further, the second recording unit specifically includes: a first time recording unit for recording first time information T1 when the mixture is heated and reaches a first preset temperature; a second time recording unit for recording second time information T2 when the mixture continues to be heated and reaches a second preset temperature; a boiling time recording unit for acquiring and recording the boiling time information according to the first time information T1 and the second time information T2.
Further, the first predetermined temperature is 40 degrees, and the second predetermined temperature is 100 degrees.
Further, the water level information comprises the highest water level and the lowest water level of the food processor.
Further, the processing information includes processing time, processing temperature, and rotational stirring speed.
The invention also provides a processing device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and is characterized in that the processor realizes the steps of the processing method when executing the computer program.
The present invention also provides a storage device storing a computer program executable to implement the steps of the processing method as described above.
The processing method, the processing device and the storage device have the advantages that the processing model is generated through self-learning of the mixture, then the water level information and the processing information corresponding to the mixture can be obtained through calculation of the processing model according to the boiling time of the added mixture during each use, the mixture can be processed according to the processing information, the intelligent degree is high, the processing information obtained through the processing model is the optimal processing information of the mixture, finally processed food is more delicious, the mouthfeel is better, and excellent use experience is brought to users.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a block flow diagram of the process of the present invention;
FIG. 2 is a schematic view of the food processor of the present invention;
FIG. 3 is a block flow diagram of the present invention for generating a process model;
FIG. 4 is a block diagram of the process of recording boiling time information in accordance with the present invention;
FIG. 5 is a block diagram showing the structure of a processing apparatus according to the present invention;
FIG. 6 is a block diagram of the self-learning unit of the present invention;
fig. 7 is a block diagram of a second recording unit according to the present invention.
Detailed Description
The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
The processing method generates the processing model through self-learning of the mixture, then, during each use, according to the boiling time of the added mixture, the processing model is adopted to calculate and obtain the water level information and the processing information corresponding to the mixture, namely, the mixture can be processed according to the processing information, the intelligent degree is high, the processing information obtained through the processing model is the optimal processing information of the mixture, and finally processed food is more delicious and better in taste, and excellent use experience is brought to a user.
Example one
In this embodiment, a processing method is provided, and referring to fig. 1, the processing method includes the following steps:
step 1, pre-self-learning a mixture formed by mixing water and food materials in proportion to generate a self-learned processing model; and
and 2, calculating the boiling time information of the mixture acquired in real time by adopting the processing model to obtain water level information and processing information corresponding to the mixture, and performing corresponding processing on the mixture according to the processing information.
The processing method is applied to a food processor which can be used as a corn machine, a soybean milk machine, a coarse cereal machine, a porridge cooking machine and the like, and the mixture of water and food materials is cooked into edible thick solid liquid. It should be noted that, food processors of different models are dedicated to different food materials, and the processing method needs to be applied to different food processors. Or, the integrated setting processor can be used for different food materials respectively, the user selects the corresponding food material before using, and the integrated setting processor can execute the operation corresponding to the food material.
Firstly, the food processor self-learns a mixture formed by mixing water and food materials in proportion in advance to generate a learned processing model, and the process is completed before the food processor leaves a factory. It is worth mentioning that the water and the food materials are mixed according to the same proportion each time, the food materials are more matched when the water is more, the food materials are less matched when the water is less, and the proportion of the water and the food materials is kept consistent each time. Then, in the actual use process, a user pours a variable amount of water and food materials into the food processor, and the food processor heats the mixture formed by the water and the food materials. After the mixture is boiled, the cooking machine calculates the boiling time information of the mixture acquired in real time by adopting the generated processing model to obtain the water level information and the processing information corresponding to the mixture, and the cooking machine performs corresponding processing on the mixture according to the processing information to finally obtain the food which can be eaten by the user.
In the actual use process, a user only needs to add water and food materials according to the proportion, and does not need to select corresponding processing information. The cooking machine heats the mixture formed by the water and the food materials, after the boiling time information of the mixture is known, the water level information and the processing information corresponding to the boiling time information can be obtained through the processing model, and then the mixture is processed correspondingly according to the processing information. Therefore, the user only needs fool one-key operation, and after the food processor is started, the food processor automatically processes the mixture in the whole process. Because the processing information obtained by the processing model is obtained according to the mixture formed by the water and the food materials poured by the user, the processing information is the optimal processing information of the mixture under the corresponding water level information, and after the processing process is finished, delicious food with good taste can be obtained for the user to enjoy.
Referring to fig. 2, a schematic diagram of a food processor is shown. The cooking machine includes upper cover 11, casing 12 and lower cover 13, upper cover 11 rotates and sets up on casing 12, rotates upper cover 11 back, can pour water and edible material into casing 12. Be provided with temperature sensor 121 and stirring module in the casing 12, the inside temperature information of casing can be known to temperature sensor 121, the stirring module can provide the stirring effect for the casing is inside, provides the stirring effect for the mixture that water and edible material formed promptly. The lower cover 13 is provided with a control panel, a storage module, a heating module and a time detection module, wherein the storage module, the heating module and the time detection module are respectively connected with the control panel, the control panel plays a role of master control, the storage module is provided with a processing model, the heating module can be used for heating the inside of the shell, and the time detection module can detect the heating time.
Example two
On the basis of the first embodiment, referring to fig. 3, the step of self-learning a mixture formed by mixing water and food materials in proportion in advance to generate a self-learned processing model in the second embodiment specifically includes:
12, recording boiling time information of the mixture after boiling;
and 14, generating a processing model.
Before the food processer leaves a factory, the self-learning process of the food processer needs to be completed. Firstly, pouring water and food materials into a food processor in proportion, and recording water level information of a mixture formed by the water and the food materials by the food processor. The processor then heats the mixture and records the boiling time information of the mixture. Then the processor processes the mixture and records the processing information of the mixture. And continuously repeating the operations, and finally generating a processing model when the water level information of the mixture formed by the poured water and the food materials is different every time.
The mixture of different water level information means that the information of the required boiling time is different, and the two information are corresponding to each other. Moreover, the mixture of different water level information means that the optimum processing information is different, and both are also corresponding to each other. Therefore, in the subsequent use process of the food processor, the user pours the water and the food materials into the food processor, but the user does not need to know the water level information of the mixture formed by the water and the food materials, and does not need to select the processing information of the food processor. The cooking machine heats the mixture, obtains boiling time information after the mixture is boiled, obtains corresponding water level information and processing information through the processing model, and can carry out corresponding processing to the mixture according to the processing information.
EXAMPLE III
On the basis of the second embodiment, referring to fig. 4, the step of recording boiling time information of the mixture after boiling in the third embodiment specifically includes:
and 123, acquiring and recording the boiling time information according to the first time information T1 and the second time information T2.
Wherein, the cooking machine heats the mixture formed by the water and the food materials after the water and the food materials are poured into the cooking machine. When the mixture is heated to the first preset temperature, the first time information T1 is recorded. The mixture is then heated, and second time information T2 is recorded when the mixture is heated to a second preset temperature. Then, the time difference between the first time information T1 and the second time information T2, which is the boiling time information of the mixture, is known.
The mixture does not need to be subjected to time detection before the first preset temperature is not reached. If the time required for the mixture to boil from the normal temperature is taken as the boiling time information, the time difference between the normal temperature and the boiling is large, the accuracy of the finally formed processing model is poor, and the water level information of the poured mixture may be estimated in the subsequent practical use. And the time difference of the more proper boiling time information is determined, which is beneficial to generating a more accurate processing model. The processing method sets the first preset temperature and the second preset temperature for the mixture, the time difference of the time required for the mixture to reach the first preset temperature and the second preset temperature is small and more suitable, and the finally formed processing model is more accurate.
Example four
On the basis of the third embodiment, the first preset temperature of the fourth embodiment is 40 degrees, and the second preset temperature is 100 degrees. Of course, the first preset temperature and the second preset temperature may be other temperatures, which is not described herein in detail.
EXAMPLE five
On the basis of the second embodiment, the water level information of the second embodiment includes the highest water level and the lowest water level of the food processor.
The HWM in FIG. 2 is "High water mark", i.e., the highest water level; LWM is "Low water mark", i.e., the lowest water level. The food processor limits the water level information of the mixture formed by the water and the food materials. In the self-learning process, only the processing models corresponding to the highest water level and the lowest water level are generated. In the subsequent use process, the user also adds water and food materials in proportion until the mixture formed by the water and the food materials reaches the lowest water level or the highest water level, and the food processor learns the processing information corresponding to the lowest water level or the processing information corresponding to the highest water level through the processing model. In this way, only a simplified processing model needs to be generated.
EXAMPLE six
On the basis of the first to fifth embodiments, the processing information of the sixth embodiment includes processing time, processing temperature, and rotational stirring speed. The processing time does not include boiling time information, but only includes time information required after the mixture is boiled.
EXAMPLE seven
The seventh embodiment provides a processing apparatus, referring to fig. 5, the processing apparatus includes:
the self-learning unit 100 is used for pre-learning a mixture formed by mixing water and food materials in proportion and generating a self-learned processing model; and
and the processing unit 200 is configured to calculate, by using the processing model, the boiling time information of the mixture obtained in real time to obtain water level information and processing information corresponding to the mixture, and perform corresponding processing on the mixture according to the processing information.
The processing device is applied to a food processor which can be used as a corn machine, a soybean milk machine, a coarse cereal machine, a porridge cooking machine and the like, and the mixture of water and food materials is cooked into edible thick solid liquid. It should be noted that, food processors of different models are dedicated to different food materials, and the processing device needs to be applied to different food processors. Or, the integrated setting processor can be used for different food materials respectively, the user selects the corresponding food material before using, and the integrated setting processor can execute the operation corresponding to the food material.
Firstly, the food processor self-learns the mixture formed by mixing water and food materials in proportion in advance through the self-learning unit 100 to generate a learned processing model, and the process is completed before the food processor leaves the factory. It is worth mentioning that the water and the food materials are mixed according to the same proportion each time, the food materials are more matched when the water is more, the food materials are less matched when the water is less, and the proportion of the water and the food materials is kept consistent each time. Then, through the processing unit 200, in the actual use process, the user pours a variable amount of water and food material into the food processor, and the food processor heats the mixture formed by the water and the food material. After the mixture is boiled, the cooking machine calculates the boiling time information of the mixture acquired in real time by adopting the generated processing model to obtain the water level information and the processing information corresponding to the mixture, and the cooking machine performs corresponding processing on the mixture according to the processing information to finally obtain the food which can be eaten by the user.
In the actual use process, a user only needs to add water and food materials according to the proportion, and does not need to select corresponding processing information. The cooking machine heats the mixture formed by the water and the food materials, after the boiling time information of the mixture is known, the water level information and the processing information corresponding to the boiling time information can be obtained through the processing model, and then the mixture is processed correspondingly according to the processing information. Therefore, the user only needs fool one-key operation, and after the food processor is started, the food processor automatically processes the mixture in the whole process. Because the processing information obtained by the processing model is obtained according to the mixture formed by the water and the food materials poured by the user, the processing information is the optimal processing information of the mixture under the corresponding water level information, and after the processing process is finished, delicious food with good taste can be obtained for the user to enjoy.
Referring to fig. 2, a schematic diagram of a food processor is shown. The cooking machine includes upper cover 11, casing 12 and lower cover 13, upper cover 11 rotates and sets up on casing 12, rotates upper cover 11 back, can pour water and edible material into casing 12. Be provided with temperature sensor 121 and stirring module in the casing 12, the inside temperature information of casing can be known to temperature sensor 121, the stirring module can provide the stirring effect for the casing is inside, provides the stirring effect for the mixture that water and edible material formed promptly. The lower cover 13 is provided with a control panel, a storage module, a heating module and a time detection module, wherein the storage module, the heating module and the time detection module are respectively connected with the control panel, the control panel plays a role of master control, the storage module is provided with a processing model, the heating module can be used for heating the inside of the shell, and the time detection module can detect the heating time.
Example eight
On the basis of the seventh embodiment, referring to fig. 6, the self-learning unit 100 of the eighth embodiment specifically includes:
a first recording unit 110 for recording water level information of the mixture poured into the food processor for a plurality of times, the mixture being formed by mixing water and food materials in proportion, and the water level information of the mixture poured each time being different;
a second recording unit 120 for recording boiling time information after the mixture is boiled;
a third recording unit 130 for recording processing information after the mixture is processed;
the generating unit 140 is configured to generate a processing model.
Before the food processer leaves a factory, the self-learning process of the food processer needs to be completed. First, the water and the food materials are poured into the food processor in proportion through the first recording unit 110, and the water level information of the mixture formed by the water and the food materials is recorded by the food processor. Then, the cooker heats the mixture through the second recording unit 120, and records the boiling time information of the mixture. Then, the processor processes the mixture through the third recording unit 130, and records the processing information of the mixture. The above operations are repeated continuously, and the water level information of the mixture formed by the poured water and the food materials is different each time, and finally, the processing model can be generated through the generating unit 140.
The mixture of different water level information means that the information of the required boiling time is different, and the two information are corresponding to each other. Moreover, the mixture of different water level information means that the optimum processing information is different, and both are also corresponding to each other. Therefore, in the subsequent use process of the food processor, the user pours the water and the food materials into the food processor, but the user does not need to know the water level information of the mixture formed by the water and the food materials, and does not need to select the processing information of the food processor. The cooking machine heats the mixture, obtains boiling time information after the mixture is boiled, obtains corresponding water level information and processing information through the processing model, and can carry out corresponding processing to the mixture according to the processing information.
Example nine
On the basis of the eighth embodiment, referring to fig. 7, the second recording unit 120 of the ninth embodiment specifically includes:
a first time recording unit 121 for recording first time information T1 when the mixture is heated and reaches a first preset temperature;
a second time recording unit 122 for recording second time information T2 when the mixture continues to be heated and reaches a second preset temperature;
a boiling time recording unit 123 for acquiring and recording the boiling time information according to the first time information T1 and the second time information T2.
Wherein, the cooking machine heats the mixture formed by the water and the food materials after the water and the food materials are poured into the cooking machine. By means of the first time recording unit 121, first time information T1 is recorded when the mixture is heated to the first preset temperature. The mixture is then heated by the second time recording unit 122, and second time information T2 is recorded when the mixture is heated to a second preset temperature. Then, the boiling time recording unit 123 knows the time difference between the first time information T1 and the second time information T2, which is the boiling time information of the mixture.
The mixture does not need to be subjected to time detection before the first preset temperature is not reached. If the time required for the mixture to boil from the normal temperature is taken as the boiling time information, the time difference between the normal temperature and the boiling is large, the accuracy of the finally formed processing model is poor, and the water level information of the poured mixture may be estimated in the subsequent practical use. And the time difference of the more proper boiling time information is determined, which is beneficial to generating a more accurate processing model. The processing device sets the first preset temperature and the second preset temperature for the mixture, the time difference of the time required for the mixture to reach the first preset temperature and the second preset temperature is small and more suitable, and the finally formed processing model is more accurate.
Example ten
On the basis of the ninth embodiment, the first preset temperature of the tenth embodiment is 40 degrees, and the second preset temperature is 100 degrees. Of course, the first preset temperature and the second preset temperature may be other temperatures, which is not described herein in detail.
EXAMPLE eleven
On the basis of embodiment eight, the water level information of this embodiment eleven includes the highest water level and the lowest water level of the food processor.
The HWM in FIG. 2 is "High water mark", i.e., the highest water level; LWM is "Low water mark", i.e., the lowest water level. The food processor limits the water level information of the mixture formed by the water and the food materials. In the self-learning process, only the processing models corresponding to the highest water level and the lowest water level are generated. In the subsequent use process, the user also adds water and food materials in proportion until the mixture formed by the water and the food materials reaches the lowest water level or the highest water level, and the food processor learns the processing information corresponding to the lowest water level or the processing information corresponding to the highest water level through the processing model. In this way, only a simplified processing model needs to be generated.
Example twelve
On the basis of the seventh to eleventh embodiments, the processing information of the twelfth embodiment includes processing time, processing temperature, and rotational stirring speed. The processing time does not include boiling time information, but only includes time information required after the mixture is boiled.
EXAMPLE thirteen
A thirteenth embodiment provides a processing apparatus, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the steps of the processing method according to the first to sixth embodiments. Wherein, processing apparatus establishes in the cooking machine.
Example fourteen
A fourteenth embodiment provides a storage device, which stores a computer program that can be executed to implement the steps of the processing method according to the first to sixth embodiments.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A processing method is characterized by comprising the following steps:
pre-self-learning a mixture formed by mixing water and food materials in proportion to generate a self-learned processing model; and
calculating boiling time information of the mixture acquired in real time by adopting the processing model to obtain water level information and processing information corresponding to the mixture, and performing corresponding processing on the mixture according to the processing information, wherein the processing information comprises processing time, processing temperature and rotating and stirring speed;
the method comprises the following steps of mixing water and food materials in proportion in advance to form a mixture, carrying out self-learning, and generating a processing model which is finished by the self-learning, wherein the method specifically comprises the following steps:
recording water level information of the mixture poured into the food processor for multiple times, wherein the mixture is formed by mixing water and food materials in proportion, and the water level information of the mixture poured each time is different;
recording the boiling time information of the mixture after boiling;
recording processing information after the mixture is processed;
generating a processing model;
wherein, the step of recording the boiling time information after the mixture is boiled specifically comprises:
recording first time information T1 when the mixture is heated and reaches a first preset temperature;
recording second time information T2 when the mixture continues to be heated and reaches a second preset temperature;
and acquiring and recording the boiling time information according to the first time information T1 and the second time information T2.
2. The process of claim 1, wherein the first predetermined temperature is 40 degrees and the second predetermined temperature is 100 degrees.
3. The processing method according to claim 1, wherein the water level information includes a maximum water level and a minimum water level of the food processor.
4. A processing apparatus, comprising:
the self-learning unit is used for pre-learning a mixture formed by mixing water and food materials in proportion to generate a self-learned processing model; and
the processing unit is used for calculating boiling time information of the mixture acquired in real time by adopting the processing model to obtain water level information and processing information corresponding to the mixture, and performing corresponding processing on the mixture according to the processing information, wherein the processing information comprises processing time, processing temperature and rotating stirring speed;
wherein, the self-learning unit specifically comprises:
the first recording unit is used for recording water level information of the mixture poured into the food processor for multiple times, the mixture is formed by proportionally mixing water and food materials, and the water level information of the mixture poured each time is different;
a second recording unit for recording boiling time information after the mixture is boiled;
the third recording unit is used for recording the processing information of the mixture after processing;
a generating unit configured to generate a processing model;
wherein the second recording unit specifically includes:
a first time recording unit for recording first time information T1 when the mixture is heated and reaches a first preset temperature;
a second time recording unit for recording second time information T2 when the mixture continues to be heated and reaches a second preset temperature;
a boiling time recording unit for acquiring and recording the boiling time information according to the first time information T1 and the second time information T2.
5. The processing device of claim 4, wherein the first predetermined temperature is 40 degrees and the second predetermined temperature is 100 degrees.
6. The processing device of claim 4, wherein the water level information comprises a maximum water level and a minimum water level of the processor.
7. A processing apparatus comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the processing method according to any one of claims 1 to 3 when executing the computer program.
8. A storage device, characterized in that it stores a computer program executable to implement the steps of the processing method according to any one of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910542288.8A CN112107231B (en) | 2019-06-21 | 2019-06-21 | Processing method and device and storage device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910542288.8A CN112107231B (en) | 2019-06-21 | 2019-06-21 | Processing method and device and storage device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112107231A CN112107231A (en) | 2020-12-22 |
| CN112107231B true CN112107231B (en) | 2022-01-04 |
Family
ID=73796375
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910542288.8A Active CN112107231B (en) | 2019-06-21 | 2019-06-21 | Processing method and device and storage device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112107231B (en) |
Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101406364A (en) * | 2008-10-20 | 2009-04-15 | 方大同 | Household diet processing device and method for preparing soybean milk thereof |
| CN101828680A (en) * | 2009-03-08 | 2010-09-15 | 李红霞 | Intelligent micro-pressure full-automatic soybean milk machine |
| WO2011090326A3 (en) * | 2010-01-22 | 2011-12-29 | 주식회사 오쿠 | Cooking method using an automatic pressure-controlled double boiler |
| CN102824099A (en) * | 2012-09-20 | 2012-12-19 | 张捷 | Internet of things full-automatic self-learning electric cooker and implementation method thereof |
| CN103892695A (en) * | 2014-04-24 | 2014-07-02 | 苏州西顿家用自动化有限公司 | Automatic cooking method and intelligent cooking stove capable of achieving automatic cooking |
| CN105877491A (en) * | 2016-06-17 | 2016-08-24 | 九阳股份有限公司 | Food processing method for high-speed wall-breaking food processer |
| CN105942887A (en) * | 2015-12-30 | 2016-09-21 | 九阳股份有限公司 | High speed wall-breaking smashing method for food processor |
| CN105955338A (en) * | 2016-07-19 | 2016-09-21 | 浙江绍兴苏泊尔生活电器有限公司 | Plateau self-adaptive method for food processor |
| CN106955013A (en) * | 2017-03-30 | 2017-07-18 | 上海斐讯数据通信技术有限公司 | A kind of method of intelligent kitchen cooking system and intelligent auxiliary cooking |
| CN107426262A (en) * | 2016-05-24 | 2017-12-01 | 佛山市顺德区美的电热电器制造有限公司 | Control method, terminal, server and the system of cooking appliance |
| CN107577176A (en) * | 2017-08-16 | 2018-01-12 | 珠海格力电器股份有限公司 | Control method, the device and system of cooking apparatus |
| CN108185800A (en) * | 2018-01-27 | 2018-06-22 | 深圳市赛亿科技开发有限公司 | Intelligent electric rice cooker and its control method |
| CN108224894A (en) * | 2018-01-08 | 2018-06-29 | 合肥美的智能科技有限公司 | Food material freshness identification method and device based on deep learning, refrigerator and medium |
| CN108514346A (en) * | 2018-05-28 | 2018-09-11 | 九阳股份有限公司 | A kind of pulping process of soy bean milk making machine |
| CN108742157A (en) * | 2018-05-16 | 2018-11-06 | 九阳股份有限公司 | A kind of pulping process of soy bean milk making machine |
| CN109199115A (en) * | 2017-06-30 | 2019-01-15 | 佛山市顺德区美的电热电器制造有限公司 | Water detects control method, water detection control apparatus and cooking equipment |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102016110710A1 (en) * | 2016-06-10 | 2017-12-14 | Vorwerk & Co. Interholding Gmbh | Method for operating a food processor |
| CN108354435A (en) * | 2017-01-23 | 2018-08-03 | 上海长膳智能科技有限公司 | Automatic cooking apparatus and the method cooked using it |
| CN109739139A (en) * | 2019-01-15 | 2019-05-10 | 鲁班嫡系机器人（深圳）有限公司 | System, method, control device, storage medium and the equipment of food material processing |
| CN209486485U (en) * | 2019-01-15 | 2019-10-11 | 鲁班嫡系机器人（深圳）有限公司 | A kind of food material processing system |
-
2019
- 2019-06-21 CN CN201910542288.8A patent/CN112107231B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101406364A (en) * | 2008-10-20 | 2009-04-15 | 方大同 | Household diet processing device and method for preparing soybean milk thereof |
| CN101828680A (en) * | 2009-03-08 | 2010-09-15 | 李红霞 | Intelligent micro-pressure full-automatic soybean milk machine |
| WO2011090326A3 (en) * | 2010-01-22 | 2011-12-29 | 주식회사 오쿠 | Cooking method using an automatic pressure-controlled double boiler |
| CN102824099A (en) * | 2012-09-20 | 2012-12-19 | 张捷 | Internet of things full-automatic self-learning electric cooker and implementation method thereof |
| CN103892695A (en) * | 2014-04-24 | 2014-07-02 | 苏州西顿家用自动化有限公司 | Automatic cooking method and intelligent cooking stove capable of achieving automatic cooking |
| CN105942887A (en) * | 2015-12-30 | 2016-09-21 | 九阳股份有限公司 | High speed wall-breaking smashing method for food processor |
| CN107426262A (en) * | 2016-05-24 | 2017-12-01 | 佛山市顺德区美的电热电器制造有限公司 | Control method, terminal, server and the system of cooking appliance |
| CN105877491A (en) * | 2016-06-17 | 2016-08-24 | 九阳股份有限公司 | Food processing method for high-speed wall-breaking food processer |
| CN105955338A (en) * | 2016-07-19 | 2016-09-21 | 浙江绍兴苏泊尔生活电器有限公司 | Plateau self-adaptive method for food processor |
| CN106955013A (en) * | 2017-03-30 | 2017-07-18 | 上海斐讯数据通信技术有限公司 | A kind of method of intelligent kitchen cooking system and intelligent auxiliary cooking |
| CN109199115A (en) * | 2017-06-30 | 2019-01-15 | 佛山市顺德区美的电热电器制造有限公司 | Water detects control method, water detection control apparatus and cooking equipment |
| CN107577176A (en) * | 2017-08-16 | 2018-01-12 | 珠海格力电器股份有限公司 | Control method, the device and system of cooking apparatus |
| CN108224894A (en) * | 2018-01-08 | 2018-06-29 | 合肥美的智能科技有限公司 | Food material freshness identification method and device based on deep learning, refrigerator and medium |
| CN108185800A (en) * | 2018-01-27 | 2018-06-22 | 深圳市赛亿科技开发有限公司 | Intelligent electric rice cooker and its control method |
| CN108742157A (en) * | 2018-05-16 | 2018-11-06 | 九阳股份有限公司 | A kind of pulping process of soy bean milk making machine |
| CN108514346A (en) * | 2018-05-28 | 2018-09-11 | 九阳股份有限公司 | A kind of pulping process of soy bean milk making machine |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112107231A (en) | 2020-12-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109008592B (en) | Cooking control method and device of micro-steaming and baking all-in-one machine and micro-steaming and baking all-in-one machine | |
| JP6654737B2 (en) | Food processing apparatus, control device and operation method | |
| WO2019033843A1 (en) | Method, apparatus and system for controlling cooking utensil | |
| CN104510329B (en) | Recipe generation system of cooking utensil and cooking utensil | |
| JP6265382B2 (en) | kitchenware | |
| EP3145375B1 (en) | Air heating device | |
| CN107536482B (en) | Cooking method, cooking appliance and computer storage medium | |
| CN105686612B (en) | Cooking apparatus and the method for judging food type in cooking apparatus | |
| JP2007135884A (en) | Rice cooker | |
| CN109619965A (en) | A kind of cooking methods and cooking equipment | |
| CN110353469B (en) | Cooking appliance, cooking method and computer storage medium | |
| CN107361625A (en) | Cooking apparatus and the method cooked using cooking apparatus | |
| CN112107231B (en) | Processing method and device and storage device | |
| JP6184526B2 (en) | Method and apparatus for calculating the total time of a food cooking process and cooking method | |
| CN107374313A (en) | Cooking apparatus and the method cooked using cooking apparatus | |
| CN108851944A (en) | Cooking methods, control device and the intelligent appliance of intelligent appliance | |
| CN107865575A (en) | Cooking apparatus and the cooking methods cooked using the cooking apparatus | |
| CN107361624A (en) | Cooking apparatus and the method cooked using cooking apparatus | |
| CN107361627A (en) | Cooking apparatus and the method cooked using cooking apparatus | |
| CN114145654A (en) | Cooking control method of electric chafing dish, computer device and readable storage medium | |
| CN112754302A (en) | Heating method and heating system of cook machine and cook machine | |
| CN108931946A (en) | Method and apparatus, storage medium and the cooking apparatus of display culinary art count down time | |
| CN110115487B (en) | Cooking control method, control device, cooking appliance and readable storage medium | |
| CN109691903B (en) | Heating method of frying and baking machine, heating device, frying and baking machine and computer storage medium | |
| CN109953634A (en) | Cooking methods, cooker, cooking apparatus and computer readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |