CN110132890A - According to the method and device of the unmanned culinary cuisine operation of food materials optimizing components - Google Patents
According to the method and device of the unmanned culinary cuisine operation of food materials optimizing components Download PDFInfo
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- CN110132890A CN110132890A CN201910421757.0A CN201910421757A CN110132890A CN 110132890 A CN110132890 A CN 110132890A CN 201910421757 A CN201910421757 A CN 201910421757A CN 110132890 A CN110132890 A CN 110132890A
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- 235000013305 food Nutrition 0.000 title claims abstract description 137
- 239000000463 material Substances 0.000 title claims abstract description 134
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000010411 cooking Methods 0.000 claims abstract description 49
- 235000013311 vegetables Nutrition 0.000 claims abstract description 29
- 238000000513 principal component analysis Methods 0.000 claims abstract description 17
- 238000001228 spectrum Methods 0.000 claims abstract description 16
- 235000013372 meat Nutrition 0.000 claims abstract description 10
- 230000008569 process Effects 0.000 claims abstract description 10
- 239000004615 ingredient Substances 0.000 claims abstract description 8
- 239000003242 anti bacterial agent Substances 0.000 claims abstract description 4
- 229940088710 antibiotic agent Drugs 0.000 claims abstract description 4
- 238000010191 image analysis Methods 0.000 claims abstract description 4
- 238000004458 analytical method Methods 0.000 claims description 8
- 230000008859 change Effects 0.000 claims description 8
- 238000004590 computer program Methods 0.000 claims description 8
- 238000002372 labelling Methods 0.000 claims description 6
- 238000003860 storage Methods 0.000 claims description 6
- 238000010438 heat treatment Methods 0.000 claims description 5
- 230000003592 biomimetic effect Effects 0.000 claims description 4
- 238000001816 cooling Methods 0.000 claims description 3
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- 238000004519 manufacturing process Methods 0.000 claims description 3
- 230000001537 neural effect Effects 0.000 claims description 3
- 239000013307 optical fiber Substances 0.000 claims description 3
- 235000013348 organic food Nutrition 0.000 claims description 3
- 238000004611 spectroscopical analysis Methods 0.000 claims description 3
- 238000010238 partial least squares regression Methods 0.000 claims 2
- 238000004566 IR spectroscopy Methods 0.000 claims 1
- 238000005520 cutting process Methods 0.000 claims 1
- 235000010149 Brassica rapa subsp chinensis Nutrition 0.000 abstract 1
- 235000000536 Brassica rapa subsp pekinensis Nutrition 0.000 abstract 1
- 241000499436 Brassica rapa subsp. pekinensis Species 0.000 abstract 1
- 230000033764 rhythmic process Effects 0.000 abstract 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 abstract 1
- 235000013399 edible fruits Nutrition 0.000 description 6
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Classifications
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- 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
- A47J27/00—Cooking-vessels
- A47J27/002—Construction of cooking-vessels; Methods or processes of manufacturing specially adapted for cooking-vessels
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- 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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/02—Food
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- Food Science & Technology (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
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- Manufacturing & Machinery (AREA)
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Abstract
The present invention discloses the method according to the unmanned culinary cuisine operation of food materials optimizing components, establishes foodstuff quality image data base, by using infrared and high spectrum image analysis modeling to veterinary antibiotics class food materials, judges food materials principal component information；Principal component analysis is carried out to the odor characteristics information that meat food materials are additionally obtained by smell sensor and models the ingredient prediction of progress food materials, obtains food materials predictive information；Digital menu is selected by the vegetable order that unmanned kitchen front end is sent, cooking robot selects food materials according to the digital menu, and adjusts culinary art movement according to the predictive information of selected food materials.The judgement of food materials material is set, time and the rhythm of stir-frying are adjusted according to the food materials material for entering pot, such as Chinese cabbage water content from different sources is different, when stir-frying using same system, needs to adjust the stir-frying time.The present invention is by according to the heterogeneity information dynamic adjustment culinary art movement of identical food materials, improving vegetable quality when unmanned kitchen executes cooking process.
Description
Technical field
The present invention relates to technical field of automatic control more particularly to a kind of according to the unmanned culinary cuisine of food materials optimizing components
The method and device of operation.
Background technique
In traditional cooking culture, food, which will generally pass through, the cooking methods such as to be fried, stewes, decocting, boiling and being eaten by people, so far
Until the present, the cooking is still the skill based on experience and craft, higher to operator's technical requirements.Nowadays, automatic dish cooking machine
Appearance, have the function of automatic hot oil, automatic turning and frying etc., as long as cooking robot is put into food and its ingredient, cooking machine
It can be automatically performed cooking process, to allow user that can easily enjoy cuisines, nevertheless, automatic dish cooking machine is in reality
There are still shortcoming in the application of border, for example, a kind of existing cooking machine, system carry it is a variety of cook dish menu, every kind is cooked dish
Menu corresponds to a kind of vegetable, but system only sets single cooking process according to the food materials for constituting vegetable, including cooking time,
The parameters such as heating power be all it is cured, user can not be different according to practical food materials deal and adjust these culinary art parameters, cause
Existing automatic dish cooking machine is single in the presence of culinary art vegetable, the problem of can not being adaptively adjusted according to user's actual need.In addition,
In the application in unmanned kitchen, interventional operations are carried out to entire culinary art link because not needing personnel, how cooking machine is according to food
The quality of material is different and the process of the adjustment culinary art of adaptation to local conditions is that this field should pay attention to solving the problems, such as, it is traditional in, meat,
The detection method of the food materials such as fruits and vegetables generallyd use has gas-chromatography, high performance liquid chromatography, gas chromatography mass spectrometry etc., because it sets
Standby expensive, operation sequence is relative complex, and needs specifically experiment condition and there is certain professional technician to operate, people
Often through measuring and some physicochemical characteristics of analysis correlation of attributes study the qualities of the food materials such as vegetables.Fruit and vegetable
The quality characteristic of dish product includes sense organ (such as color, fragrance), nutrition, chemical component, physical characteristic and defect etc..It is answering
With certain features (or characteristic) of fruits and vegetables being measured often through some instruments to evaluate its quality.Because passing through
These modes can more objectively judge and evaluate the quality of victual, can also reduce the interference of human factor.Vegetables
The optical characteristics of product and its appearance have direct relation, and physical characteristic is closely related with its quality, chemical component and its flavour (taste
Feel and smell) it is related.By way of imitating people and examining victual or some quality characteristics are measured, instrument can be to agricultural product
Quality carry out the judgement of similar people.Although the quality for finally only having the talent to may determine that agricultural product, neck is being studied and detected
Domain is necessary by instrument subsidiary and analysis and the characteristic of correlation of attributes.Detect and control fruits and vegetables
Maturity have become a major issue in fruit industry because fruit pass through the links such as harvest, storage, market circulation, most
The vegetables at end, fruit quality are determined by its maturity.Harvest it is too early or too late, wait vegetables and fruit to reach in consumer's hand
When, quality status may have become very bad.Detection for vegetables and fruit maturity, it was also proposed that many side
Method, but these methods are primary disadvantage is that destructive, it is all to be not suitable in practice.Machine for kitchen use it is intelligent, automatic
Change has become a kind of trend, and the demand of automatic dish cooking machine undoubtedly can be more more and more intense, it is therefore necessary to improve cooking machine
Cooking method, to promote user experience.
Summary of the invention
The present invention is directed at least solve the technical problems existing in the prior art.For this purpose, the invention discloses a kind of bases
The method of food materials optimizing components unmanned culinary cuisine operation, comprising: the foodstuff quality image data base of foundation, by vegetables,
Fruits food materials use infrared and high spectrum image analysis modeling, judge food materials principal component information；Meat food materials are additionally passed through
The odor characteristics information that smell sensor obtains carries out principal component analysis and establishes the ingredient prediction that model carries out food materials, is eaten
Material predictive information；Digital menu is selected by the vegetable order that unmanned kitchen front end is sent, cooking robot is according to the number
Menu selects food materials, and adjusts culinary art movement according to the predictive information of selected food materials.
Further, the foodstuff quality image data base of establishing further comprises: in the mistake cut the dish to food materials
Cheng Zhong collects food materials sample and is pre-processed by multiple scattering bearing calibration to food materials sample data, utilizes Principal Component Analysis
Clustering is carried out to spectroscopic data and obtains each number of principal components evidence；By hyperspectral image data handle to foodstuff quality into
Row classification acquires the diffusing reflection spectrum of food materials, utilization minimum two partially by y-type optical fiber using CCD near infrared light spectra system
Multiply the Quantitative Prediction Model that food materials principal component is established in recurrence (PLSR)；To the primitive character information of the biomimetic tactile information of extraction into
Row principal component analysis (PCA) simultaneously extracts characteristic variable, and linear discriminant analysis, RBF neural and combinational network knot is respectively adopted
Close the identification model that the characteristic information that PCA is extracted establishes meat foodstuff quality freshness.
Further, high spectrum image selects spectrum wave end to sample for 480 nanometers to 810 nanometers of wave band as food materials
Wave band.
Further, the foodstuff quality image data base of establishing further comprises: food materials to purchase and joining
Number label, the parameter includes: the place of production, produces date, food labelling information, cooling time, wherein food labelling information includes
Common food materials, nuisanceless food materials, green food food materials, organic food materials.
Further, and adjusting culinary art movement according to the predictive information of selected food materials further comprises: corresponding different foods
Food materials component content and culinary art movement adjustment variation relationship is arranged in material, and food materials Quality estimation machine is arranged in cooking robot
System, sets the operational threshold of main component, generates food materials according to threshold value belonging to the predictive information of the food materials and is different from generally
The independent cooking operation of digital menu.
Further, adjustment culinary art movement includes: to change that culinary art duration, the adjustment duration and degree of heating, to change lower dish culinary art suitable
Sequence.
The invention also discloses a kind of electronic cooking devices characterized by comprising
Processor；And
Memory, for storing the executable instruction of the processor；
Wherein, the processor is configured to execute basis described in any of the above embodiments via the executable instruction is executed
The method of the unmanned culinary cuisine operation of food materials optimizing components.
The present invention further discloses a kind of computer readable storage mediums, are stored thereon with computer program, feature
It is, the computer program is realized described in any of the above embodiments according to food materials optimizing components unmanned kitchen when being executed by processor
The method of cooking operation.
The present invention more accurately predicts food materials ingredient and quality, according to food by modeling respectively to different types of food materials
The ingredient of material, the dynamic in the cooker in unmanned kitchen adjust digital menu, optimize the quality of every dish product.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
The structure shown according to these attached drawings obtains other attached drawings.
Fig. 1 is the flow chart of the method for the invention according to the unmanned culinary cuisine operation of food materials optimizing components.
Specific embodiment
Below in conjunction with attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that is retouched
The embodiment stated is only a part of the embodiments of the present invention, instead of all the embodiments.Based on the embodiments of the present invention,
Every other embodiment obtained by those of ordinary skill in the art without making creative efforts, belongs to this hair
The range of bright protection.
Embodiment one
Present embodiments provide a kind of method according to the unmanned culinary cuisine operation of food materials optimizing components, comprising: foundation
Foodstuff quality image data base judges food materials by using infrared and high spectrum image analysis modeling to veterinary antibiotics class food materials
Principal component information；Principal component analysis is carried out to the odor characteristics information that meat food materials are additionally obtained by smell sensor and is established
Model carries out the ingredient prediction of food materials, obtains food materials predictive information；Number is selected by the vegetable order that unmanned kitchen front end is sent
Word menu, cooking robot select food materials according to the digital menu, and dynamic according to the adjustment culinary art of the predictive information of selected food materials
Make.
Wherein, for chicken meat sample, the pork sample under different refrigerated conditions, its elastic information and " fingerprint " smell are extracted
The primitive character information of information.The method merged using sensor characteristics layer utilizes the SVM combination principal component point of particle group optimizing
The Fusion Features information of the biomimetic tactile and bionical odor sensing that extract is analysed, the Multi-sensor Fusion of the Meat of foundation is known
Other model.
And color, reflective situation for the food materials of vegetables, mainly by the method for optical analysis, corresponding to vegetables
Equal characteristic informations carry out principal component analysis.
Embodiment two
As shown in Figure 1, present embodiments providing a kind of method according to the unmanned culinary cuisine operation of food materials optimizing components, packet
It includes: the foodstuff quality image data base of foundation, by being built to veterinary antibiotics class food materials using the analysis of infrared and high spectrum image
Mould judges food materials principal component information；To meat food materials additionally by smell sensor obtain odor characteristics information carry out it is main at
The ingredient prediction that model carries out food materials is analyzed and established, food materials predictive information is obtained；The dish sent by unmanned kitchen front end
Product order selects digital menu, and cooking robot selects food materials according to the digital menu, and is believed according to the prediction of selected food materials
Breath adjustment culinary art movement.
Further, the foodstuff quality image data base of establishing further comprises: in the mistake cut the dish to food materials
Cheng Zhong collects food materials sample and is pre-processed by multiple scattering bearing calibration to food materials sample data, utilizes Principal Component Analysis
Clustering is carried out to spectroscopic data and obtains each number of principal components evidence；By hyperspectral image data handle to foodstuff quality into
Row classification acquires the diffusing reflection spectrum of food materials, utilization minimum two partially by y-type optical fiber using CCD near infrared light spectra system
Multiply the Quantitative Prediction Model that food materials principal component is established in recurrence (PLSR)；To the primitive character information of the biomimetic tactile information of extraction into
Row principal component analysis (PCA) simultaneously extracts characteristic variable, and linear discriminant analysis, RBF neural and combinational network knot is respectively adopted
Close the identification model that the characteristic information that PCA is extracted establishes meat foodstuff quality freshness.
Further, high spectrum image selects spectrum wave end to sample for 480 nanometers to 810 nanometers of wave band as food materials
Wave band.
Further, the foodstuff quality image data base of establishing further comprises: food materials to purchase and joining
Number label, the parameter includes: the place of production, produces date, food labelling information, cooling time, wherein food labelling information includes
Common food materials, nuisanceless food materials, green food food materials, organic food materials.
Further, and adjusting culinary art movement according to the predictive information of selected food materials further comprises: corresponding different foods
Food materials component content and culinary art movement adjustment variation relationship is arranged in material, and food materials Quality estimation machine is arranged in cooking robot
System, sets the operational threshold of main component, generates food materials according to threshold value belonging to the predictive information of the food materials and is different from generally
The independent cooking operation of digital menu.
Further, adjustment culinary art movement includes: to change that culinary art duration, the adjustment duration and degree of heating, to change lower dish culinary art suitable
Sequence.
The invention also discloses a kind of electronic cooking devices characterized by comprising
Processor；And
Memory, for storing the executable instruction of the processor；
Wherein, the processor is configured to execute basis described in any of the above embodiments via the executable instruction is executed
The method of the unmanned culinary cuisine operation of food materials optimizing components.
The present invention further discloses a kind of computer readable storage mediums, are stored thereon with computer program, feature
It is, the computer program is realized described in any of the above embodiments according to food materials optimizing components unmanned kitchen when being executed by processor
The method of cooking operation.
After determining vegetable cooking time and vegetable cooking sequence, cooking robot is suitable according to the vegetable culinary art after fine tuning
Sequence, cooking robot launch food materials according to the vegetable cooking sequence after tune.This is to have very with random food materials of launching in the prior art
Different, the present embodiment can be to avoid cooking robot because cooking mode immobilization, for the same vegetable, the same number
The problem of excessively consistent problem of processing method of the menu to food materials, assurance food materials release sequence and its release time, by excellent
The corresponding relationship of helping digestion material and culinary art movement, common cooking robot can also cook the vegetable of high quality, and cooking machine
Device people controls cooking machine and cooks food materials, and the vegetable ratings feedback of user front end is arranged, and improves culinary art according to the actual impression of customer
Process, such as vegetable overdrying then reduce the duration and degree of heating and stir-frying duration within operational threshold.
When practical application, vegetable cooking sequence can be shown by operation interface, give artificial change cooking operation
Interface, cooking robot can be reminded to prepare to launch food materials before the food materials release time to reach at everybody.When feeding intake,
Uncap duration, food materials of cooking robot launch the culinary art effect that the factors such as speed influence whether cooking temp and food materials, therefore this
Inventive embodiments for manual batch carry out vegetable culinary art parameter compensation, reduce cooking robot uncap duration, food materials launch speed
Influence of the factors such as degree to culinary art effect.Such as constituting the food materials of certain vegetable includes three kinds, but these three food materials are woth no need to respectively
It launches, that is to say, that need to uncap in the vegetable cooking process twice, to launch two kinds of food materials respectively, then just needing to
Determining vegetable culinary art parameter is compensated twice, to guarantee to cook effect.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
It include so that the process, method, commodity or the equipment that include a series of elements not only include those elements, but also to wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including described want
There is also other identical elements in the process, method of element, commodity or equipment.
It will be understood by those skilled in the art that embodiments herein can provide as method, system or computer program product.
Therefore, complete hardware embodiment, complete software embodiment or embodiment combining software and hardware aspects can be used in the application
Form.It is deposited moreover, the application can be used to can be used in the computer that one or more wherein includes computer usable program code
The shape for the computer program product implemented on storage media (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Formula.
Although describing the present invention by reference to various embodiments above, but it is to be understood that of the invention not departing from
In the case where range, many changes and modifications can be carried out.Therefore, be intended to foregoing detailed description be considered as it is illustrative and
It is unrestricted, and it is to be understood that following following claims (including all equivalents) is intended to limit spirit and model of the invention
It encloses.The above embodiment is interpreted as being merely to illustrate the present invention rather than limit the scope of the invention.It is reading
After the content of record of the invention, technical staff can be made various changes or modifications the present invention, these equivalence changes and
Modification equally falls into the scope of the claims in the present invention.
Claims (8)
1. a kind of method according to the unmanned culinary cuisine operation of food materials optimizing components, which is characterized in that establish foodstuff quality image
Database judges food materials principal component information by using infrared and high spectrum image analysis modeling to veterinary antibiotics class food materials；
Principal component analysis is carried out to the odor characteristics information that meat food materials are additionally obtained by smell sensor and establishes model, is eaten
The ingredient prediction of material obtains food materials predictive information；Digital menu, culinary art are selected by the vegetable order that unmanned kitchen front end is sent
Robot selects food materials according to the digital menu, and adjusts culinary art movement according to the predictive information of selected food materials.
2. a kind of method according to the unmanned culinary cuisine operation of food materials optimizing components as described in claim 1, which is characterized in that
The foodstuff quality image data base of establishing further comprises: during cutting the dish to food materials, it is logical to collect food materials sample
Excessive scatter correction method pre-processes food materials sample data, carries out cluster point to spectroscopic data using Principal Component Analysis
It analyses and obtains each number of principal components evidence；Classifying to foodstuff quality is handled by hyperspectral image data, it is close using CCD
Infrared spectroscopy system is acquired the diffusing reflection spectrum of food materials by y-type optical fiber, establishes food materials using Partial Least Squares Regression (PLSR)
The Quantitative Prediction Model of principal component；Principal component analysis (PCA) is carried out simultaneously to the primitive character information of the biomimetic tactile information of extraction
Characteristic variable is extracted, the characteristic information that linear discriminant analysis, RBF neural and combinational network combination PCA are extracted is respectively adopted
Establish the identification model of meat foodstuff quality freshness.
3. a kind of method according to the unmanned culinary cuisine operation of food materials optimizing components as claimed in claim 2, which is characterized in that
High spectrum image selects spectrum wave end to sample wave band as food materials for 480 nanometers to 810 nanometers of wave band.
4. a kind of method according to the unmanned culinary cuisine operation of food materials optimizing components as claimed in claim 3, which is characterized in that
The foodstuff quality image data base of establishing further comprises: food materials and progress parameter tags, the parameter to purchase include:
The place of production produces date, food labelling information, cooling time, wherein food labelling information include common food materials, nuisanceless food materials,
Green food food materials, organic food materials.
5. a kind of method according to the unmanned culinary cuisine operation of food materials optimizing components as claimed in claim 4, which is characterized in that
And culinary art movement is adjusted according to the predictive information of selected food materials and further comprises: corresponding different food materials setting food materials component contents with
The culinary art movement adjustment variation relationship, food materials Quality estimation mechanism is arranged in cooking robot, sets the behaviour of main component
Make threshold value, the independent culinary art behaviour that food materials are different from general digital menu is generated according to threshold value belonging to the predictive information of the food materials
Make.
6. a kind of method according to the unmanned culinary cuisine operation of food materials optimizing components as claimed in claim 5, which is characterized in that
The adjustment culinary art movement includes: to change culinary art duration, the adjustment duration and degree of heating, change lower dish cooking sequence.
7. a kind of electronic cooking devices characterized by comprising
Processor；And
Memory, for storing the executable instruction of the processor；
Wherein, the processor is configured to require 1-6 described in any item via executing the executable instruction and carry out perform claim
According to the method for the unmanned culinary cuisine operation of food materials optimizing components.
8. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program quilt
Processor realizes the side described in any one of claims 1-6 according to the unmanned culinary cuisine operation of food materials optimizing components when executing
Method.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110794696A (en) * | 2019-11-06 | 2020-02-14 | 麦维文 | Automatic cooking device, system and method |
| CN110989409A (en) * | 2019-12-10 | 2020-04-10 | 珠海格力电器股份有限公司 | Dish cooking method and device and storage medium |
| CN111248716A (en) * | 2020-01-16 | 2020-06-09 | 珠海格力电器股份有限公司 | Food cooking control method, image processing method and device and cooking equipment |
| CN111257242A (en) * | 2020-02-27 | 2020-06-09 | 西安交通大学 | High-spectrum identification method for pollutant components of insulator |
| CN113491432A (en) * | 2020-04-07 | 2021-10-12 | 添可智能科技有限公司 | Automatic cooking method and system of cooking machine and cooking machine |
| CN113951735A (en) * | 2021-11-22 | 2022-01-21 | 珠海格力电器股份有限公司 | Cooking apparatus, cooking apparatus control method, and storage medium |
| CN116700036A (en) * | 2023-07-28 | 2023-09-05 | 青岛乐博智家科技有限公司 | Intelligent linkage monitoring management system for intelligent kitchen multiple devices |
| CN117045096A (en) * | 2023-08-12 | 2023-11-14 | 广东牧人王电器有限公司 | Control method and system for intelligent chef machine |
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