CN107965828A - The air draught condition control method and smoke exhaust ventilator of smoke exhaust ventilator - Google Patents
The air draught condition control method and smoke exhaust ventilator of smoke exhaust ventilator Download PDFInfo
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- CN107965828A CN107965828A CN201711034512.XA CN201711034512A CN107965828A CN 107965828 A CN107965828 A CN 107965828A CN 201711034512 A CN201711034512 A CN 201711034512A CN 107965828 A CN107965828 A CN 107965828A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24C—DOMESTIC STOVES OR RANGES ; DETAILS OF DOMESTIC STOVES OR RANGES, OF GENERAL APPLICATION
- F24C15/00—Details
- F24C15/20—Removing cooking fumes
- F24C15/2021—Arrangement or mounting of control or safety systems
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Abstract
The invention discloses the air draught condition control method and smoke exhaust ventilator of a kind of smoke exhaust ventilator.Wherein, this method includes：Pass through the status information of oil smoke produced by obtaining smoke exhaust ventilator；The control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information；The air draught state of above-mentioned smoke exhaust ventilator is controlled according to above-mentioned control instruction.The present invention, which solves existing smoke exhaust ventilator, to adjust air draught state according to oil smoke concentration and distribution situation, cause the technical problem that smoke absorption effect is bad.
Description
Technical field
The present invention relates to field of intelligent control, a kind of air draught condition control method in particular to smoke exhaust ventilator and
Smoke exhaust ventilator.
Background technology
The suction of conventional extraction hood is needed by manually controlling to adjust, for example, being set by clicking on smoke exhaust ventilator
Either rotary switch increases or reduces the suction of smoke exhaust ventilator the button put, and still, controls by artificial progress and only may be used manually
To control the size of the suction of smoke exhaust ventilator, the oil smoke concentration and oil smoke distribution situation of smoke exhaust ventilator can not be specifically identified, adapt to
Property the problem of adjusting the air draught state of smoke exhaust ventilator, suction deficiency or suction excessive waste of resource often occurs.
Also, control is adjusted in the air draught state that user can not be timely to smoke exhaust ventilator in many cases, for example,
When user has found to need to adjust the suction of Cooker hood, the oil smoke concentration in room may be exceeded, causes smoke exhaust ventilator
Smoking effect is bad, and then has seriously affected the health and usage experience of user.
Air draught state can not be adjusted according to oil smoke concentration and distribution situation for above-mentioned existing smoke exhaust ventilator, cause to inhale
The problem of oil smoke is ineffective, not yet proposes effective solution at present.
The content of the invention
An embodiment of the present invention provides the air draught condition control method and smoke exhaust ventilator of a kind of smoke exhaust ventilator, at least to solve
Existing smoke exhaust ventilator can not adjust air draught state according to oil smoke concentration and distribution situation, cause the technology that smoke absorption effect is bad
Problem.
One side according to embodiments of the present invention, there is provided a kind of air draught condition control method of smoke exhaust ventilator, including：
The status information of oil smoke produced by obtaining smoke exhaust ventilator；The control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information；
The air draught state of above-mentioned smoke exhaust ventilator is controlled according to above-mentioned control instruction.
Further, the status information of oil smoke produced by obtaining smoke exhaust ventilator, including：Obtain the first image of above-mentioned oil smoke
Information；Above-mentioned first image information is analyzed using the first model, determines the first state in above-mentioned first image information
Information, wherein, above-mentioned first model trains to obtain using multi-group data by machine learning, every in above-mentioned multi-group data
Group data include：Status information corresponding to image information and image information.
Further, before the control instruction that above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information, the above method also wraps
Include：Obtain the first oil smoke concentration detected by oil smoke concentration detector；By above-mentioned first concentration and above-mentioned first state information
In the second oil smoke concentration be compared；It is less than the first default threshold in above-mentioned first concentration and the difference of above-mentioned second oil smoke concentration
During value, the control instruction for determining above-mentioned smoke exhaust ventilator is triggered.
Further, before the control instruction that above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information, the above method also wraps
Include：The second image information of above-mentioned oil smoke is obtained, wherein, above-mentioned second image information and above-mentioned first image information are from difference
The image information that angle gathers at the same time；Above-mentioned second image information is analyzed using the first model, determines above-mentioned second figure
As the second status information in information, wherein, above-mentioned first model trains to obtain using multi-group data by machine learning,
Every group of data in above-mentioned multi-group data include：Status information corresponding to image information and image information；According to above-mentioned shape
State information determines the control instruction of above-mentioned smoke exhaust ventilator, including：More above-mentioned first state information and above-mentioned second status information,
And when the difference of above-mentioned first state information and above-mentioned second status information is less than the second predetermined threshold value, from above-mentioned first state
A status information is selected in information and above-mentioned second status information；Status information according to selection determines above-mentioned control instruction.
Further, above-mentioned status information includes：The distributed areas of the concentration of above-mentioned oil smoke, above-mentioned oil smoke.
Further, the control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information, including：Determine and above-mentioned shape
Corresponding first instruction of the concentration of above-mentioned oil smoke in state information, wherein, carry target air volume value in above-mentioned first instruction；Foundation
Above-mentioned control instruction controls the air draught state of above-mentioned smoke exhaust ventilator, including：According to the target air volume value tune in the above-mentioned first instruction
The airflow value of whole above-mentioned smoke exhaust ventilator.
Further, above-mentioned target air volume value determines in the following manner：Obtain the concentration of above-mentioned oil smoke；Use the 3rd mould
Type analyzes the concentration of above-mentioned oil smoke, determines the corresponding airflow value of concentration of above-mentioned oil smoke, wherein, above-mentioned 3rd model is
Trained using multi-group data by machine learning, every group of data in above-mentioned multi-group data include：The concentration of oil smoke
Airflow value corresponding with the concentration of oil smoke.
Further, the control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information, including：In above-mentioned smoke pumping
When machine is provided with smoke deflector, the second instruction corresponding with the distributed areas of above-mentioned oil smoke in above-mentioned status information is determined, wherein, on
State the target aperture that smoke deflector is carried in the second instruction；The air draught shape of above-mentioned smoke exhaust ventilator is controlled according to above-mentioned control instruction
State, including：The aperture of above-mentioned smoke deflector is adjusted according to the target aperture in the above-mentioned second instruction.
Further, above-mentioned target aperture determines in the following manner：Obtain the distributed areas of above-mentioned oil smoke；Use the 4th
Model analyzes the distributed areas of above-mentioned oil smoke, determines the corresponding aperture in distributed areas of above-mentioned oil smoke, wherein, above-mentioned
Four models train to obtain using multi-group data by machine learning, and every group of data in above-mentioned multi-group data include：Oil
The distributed areas of cigarette and target aperture corresponding with the distributed areas of oil smoke.
Another aspect according to embodiments of the present invention, additionally provides a kind of smoke exhaust ventilator, including：Image collecting device, is used
In the image information for obtaining oil smoke produced by smoke exhaust ventilator, and from above-mentioned image information extract oil smoke status information；Processing
Device, for determining the control instruction of above-mentioned smoke exhaust ventilator according to above-mentioned status information；And according in the control of above-mentioned control instruction
State the air draught state of smoke exhaust ventilator.
In embodiments of the present invention, by the way of intelligent control, the state of oil smoke produced by obtaining smoke exhaust ventilator is passed through
Information；The control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information；Above-mentioned oil pumping is controlled according to above-mentioned control instruction
The air draught state of smoke machine, has reached according to oil smoke concentration and distribution situation, controls the purpose of the air draught state of above-mentioned smoke exhaust ventilator,
It is achieved thereby that improve kitchen ventilator smoke absorption effect, reduce the technique effect of energy consumption, so solve existing smoke exhaust ventilator without
Method adjusts air draught state according to oil smoke concentration and distribution situation, causes the technical problem that smoke absorption effect is bad.
Brief description of the drawings
Attached drawing described herein is used for providing a further understanding of the present invention, forms the part of the application, this hair
Bright schematic description and description is used to explain the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings：
Fig. 1 is a kind of step flow chart of the air draught condition control method of smoke exhaust ventilator according to embodiments of the present invention；
Fig. 2 is a kind of step flow of the air draught condition control method of optional smoke exhaust ventilator according to embodiments of the present invention
Figure；
Fig. 3 is a kind of structure diagram of smoke exhaust ventilator according to embodiments of the present invention；And
Fig. 4 is a kind of structure diagram of the air draught behavior control device of smoke exhaust ventilator according to embodiments of the present invention.
Embodiment
In order to make those skilled in the art more fully understand the present invention program, below in conjunction with the embodiment of the present invention
Attached drawing, is clearly and completely described the technical solution in the embodiment of the present invention, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
Member's all other embodiments obtained without making creative work, should all belong to the model that the present invention protects
Enclose.
It should be noted that term " first " in description and claims of this specification and above-mentioned attached drawing, "
Two " etc. be for distinguishing similar object, without for describing specific order or precedence.It should be appreciated that so use
Data can exchange in the appropriate case, so as to the embodiment of the present invention described herein can with except illustrating herein or
Order beyond those of description is implemented.In addition, term " comprising " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, be not necessarily limited to for example, containing the process of series of steps or unit, method, system, product or equipment
Those steps or unit clearly listed, but may include not list clearly or for these processes, method, product
Or the intrinsic other steps of equipment or unit.
First, understand the embodiment of the present invention for convenience, below by part term or noun involved in the present invention into
Row illustrates：
Pixel：It is the least unit that can be shown on computer screen, for representing the unit of image, referring to show
Horizontal and vertical pixel array, the pixel in screen is more, and the resolution ratio of picture is higher, and image is finer and smoother and forces
Very；Pixel：Refer to the numerical value of pixel.
Binaryzation：Refer to the picture to camera shooting, most of is coloured image, and coloured image information contained amount is huge
Greatly, for the content of picture, it can simply be divided into prospect and background, first cromogram is handled, picture there was only prospect
Information and background information, it is black that can simply define foreground information, and background information is white, and here it is binary picture.
CNN：Convolutional neural networks, refer to describe the operation to input picture, one group of output describes point of picture material
Class or the probability of classification, i.e., be identified the image of input, with the probability of the object in output image；Pass through a series of convolution
Level builds up more abstract concept, including establishes multiple neurons, and establishes corresponding input layer and output layer, so that will
The node of input is constantly associated by neuron, obtains optimization object, can generally include convolutional layer, filter layer, by preceding to biography
Lead, loss function, backward conduction and function renewal be used as a learning cycle, to each trained picture, program will repeat admittedly
Fixed number purpose periodic process, to continue to optimize trained learning outcome.
To scheme to search figure：Refer to after image is got, result is ranked up by deep learning, and pass through user record
Triple data (inquiry picture, click on picture and do not click on picture) carry out the sequence loss function of training pattern, so as to obtain
Ranking results, after an image is inputted, model can detect main body automatically, and it is related right then to be discharged according to ranking score height
The result of elephant.
Transfer learning：Essence is images match, is applied model in every field by transfer learning, is specifically data
The vector representation X of picture in storehouse is moved on the image X1 in other field by linear transformation, by quoting random Fourier
Function, is changed into nonlinear function, the image then needed by migration conversion.
Naive Bayesian：It is to show a pictures, can be classified with returning an object value, using picture recognition as a simple state
Degree, to obtain corresponding object.
Dependency grammar：Refer to build the relation between subject term and the word for describing subject term, do not have in dependency grammar phrase this
Level, each node is corresponding with the word in sentence, can directly handle the relation in sentence between word and word, in order to
Analysis and information extraction.
Decision tree：Referring to be classified according to feature, each node proposes a problem, splits data into two classes, and after
Continuous to put question to, these problems are the learning trainings in existing data, with when putting into new data, on the tree according to where data
The problem of, data are divided on corresponding leaf.
Deep learning：It is that a kind of method based on to data progress representative learning, concept come from artificial god in machine learning
Research through network, its motivation are the neutral net for establishing, simulating human brain progress analytic learning, and the mechanism that it imitates human brain is come
Explain data, such as image, sound and text.By combine low-level feature formed it is more abstract it is high-rise represent attribute classification or
Feature, to find that the distributed nature of data represents, the multilayer perceptron containing more hidden layers is exactly a kind of deep learning structure.
KNN algorithms：If the sample of the k in feature space, a sample most like (i.e. closest in feature space)
In it is most of belong to some classification, then the sample falls within this classification.In KNN algorithms, selected neighbours are
Object through correctly classifying.
Embodiment 1
According to embodiments of the present invention, there is provided a kind of air draught condition control method embodiment of smoke exhaust ventilator is, it is necessary to illustrate
, step shown in the flowchart of the accompanying drawings can hold in the computer system of such as a group of computer-executable instructions
OK, although also, show logical order in flow charts, in some cases, can be with different from order herein
Perform shown or described step.
Fig. 1 is according to a kind of step flow chart of the air draught condition control method of smoke exhaust ventilator of the embodiment of the present application, such as
Shown in Fig. 1, this method comprises the following steps：
Step S102, the status information of oil smoke produced by obtaining smoke exhaust ventilator；
Step S104, the control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information；
Step S106, the air draught state of above-mentioned smoke exhaust ventilator is controlled according to above-mentioned control instruction.
In the embodiment of the present application, by the way of intelligent control, the state of oil smoke produced by obtaining smoke exhaust ventilator is passed through
Information；The control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information；Above-mentioned oil pumping is controlled according to above-mentioned control instruction
The air draught state of smoke machine, has reached oil smoke concentration and distribution situation according to smoke exhaust ventilator, controls the air draught state of smoke exhaust ventilator
Purpose, it is achieved thereby that improve kitchen ventilator smoke absorption effect, reduce the technique effect of energy consumption, and then solve existing oil pumping
Smoke machine can not adjust air draught state according to oil smoke concentration and distribution situation, cause the technical problem that smoke absorption effect is bad.
In a kind of optional embodiment, above-mentioned status information includes：The distributed area of the concentration of above-mentioned oil smoke, above-mentioned oil smoke
Domain.
As a kind of optional embodiment, above-mentioned steps S102, the status information of oil smoke produced by obtaining smoke exhaust ventilator, bag
Include：Obtain the first image information of above-mentioned oil smoke；Above-mentioned first image information is analyzed using the first model, is determined above-mentioned
First state information in first image information, wherein, above-mentioned first model is to be trained using multi-group data by machine learning
Obtain, every group of data in above-mentioned multi-group data include：Status information corresponding to image information and image information.
In the embodiment of the present application, one or more can be set in the specified region being provided with the room of above-mentioned smoke exhaust ventilator
A image collecting device, (for example, camera), to gather the image information of oil smoke, the setting position in the application for camera
Put and do not limit, for example, by taking above-mentioned smoke exhaust ventilator is arranged on ordinarily resident family as an example, can be, but not limited to the stir-fry in kitchen
At the top of the house of pot region, it is close but not at the smoke exhaust ventilator suction opening, a camera is set respectively；But if
Above-mentioned smoke exhaust ventilator is arranged on large-scale dining room, and hotel, the setting number and deployment scope of above-mentioned camera, then need according to possible
There is a situation where the setting of oil smoke adaptability.
In one alternate embodiment, image collecting device can also be arranged on smoke exhaust ventilator, for example, being arranged on oil pumping
At the suction opening of smoke machine, alternatively, being arranged on the marginal position of smoke exhaust ventilator.
Camera by being arranged on diverse location can gather the image of the oil smoke of region respectively, in collection image
When, can shoot an image every preset time period (for example, every one minute), then be produced according to above-mentioned graphical analysis
The status information of oil smoke, and determine according to above-mentioned status information the control instruction of above-mentioned smoke exhaust ventilator, and then according to above-mentioned control
Instruction controls the air draught state of above-mentioned smoke exhaust ventilator.
It should be noted that the classification of the image in the application for shooting does not limit, include but not limited to：Artwork master
As (gray level image), coloured image (RGB image)., can be according to binary image processing mode analysis chart when analyzing image
Information as in, specifically, in analysis, can carry out the pixel position in multiple pixels in image and history image
Compare, whether, to determine the pixel having differences, then the pixel there will be difference distinguishes, obtain depositing in image
In the image information of oil smoke.
Wherein, above-mentioned first image information can refer to the image of the oil smoke photographed, and image is sent to database
In.In embodiment provided herein, can by multiple cameras respectively with smoke exhaust ventilator, server and subscriber household
The gateway device in (dining room, restaurant, hotel etc.) establishes network connection, and after the image of oil smoke is collected, sends above-mentioned oil
The image of cigarette is into database, to facilitate server to analyze and process the image information of oil smoke.It is it should be noted that above-mentioned
Gateway device can include but is not limited to：Wireless network card, bluetooth, Wi-Fi etc..
As an alternative embodiment, the application can prestore one in server or database in advance
Predetermined template image, for example, in advance shooting one oil smoke image, using the image as predetermined template image, it is necessary to explanation
It is that the application is not especially limited for the predetermined template image to prestore, can is but be not limited to any one smoke exhaust ventilator
All prestore a (one or multiple) predetermined template image, for being compared with the image information got afterwards, but
It is due to that may be provided with multiple smoke exhaust ventilators in a region, for example, multiple smoke exhaust ventilators are communicated using internet,
And then can cooperate with or divide the work and carry out smoke pumping, therefore, can be in the number with above-mentioned multiple smoke exhaust ventilators there are connection relation
According to a predetermined template image that prestores in storehouse.
After above-mentioned first image information is acquired, the first image information and predetermined template image can be compared
Compared with so as to analyze difference, foundation difference determines the first state information in above-mentioned first image information.Wherein, pre- solid plate
It can include multiple information in image, can include but is not limited to：Oil smoke, the concentration of oil smoke are (for example, can pass through the face of picture
Color depth is shallow to be determined), the letter such as the distributed areas (for example, can be determined by the distribution of the shade of picture) of oil smoke
Breath, multiple information in predetermined template image is analyzed, and predetermined template image and template image information are stored in
State in the first model, the image information for the oil smoke to photographing afterwards is analyzed.
Wherein, when analyzing the difference of oil smoke image and predetermined template image of current shooting, can be by binaryzation at
Reason mode pre-processes image, and to extract, there are the place of notable difference in image.In binary conversion treatment, Ke Yifen
The pixel difference and color distortion where each pixel in image are analysed, so that it is determined that going out difference existing for overall image.
As an alternative embodiment, above-mentioned database or server can be prestored in predetermined template image
The multiple characteristic informations prestored, so that the image information of the oil smoke acquired in analysis and the difference of predetermined template image
When, it can determine to have differences part by comparative feature information.
Wherein it is possible to using CNN algorithms, multiple characteristic informations of oil smoke are extracted from the image information photographed,
During extraction, can will input is into neutral net in image, with by establishing corresponding neuron, and according between neuron
Preset function (such as Sigmoid functions) determines characteristics of image and image feature maps, so that according to definite Feature Mapping, output
Multiple features of image.In addition, analysis the image difference different time, deep learning can be used, establish the first preset model and then
When secondary progress user identity feature and user characteristics extract, it can utilize and be clapped in the method search database to scheme to search figure with current
The similar image of image is taken the photograph, and extracts oil smoke characteristic information in image, further, it is also possible to be extracted using NB Algorithm
Oil smoke characteristic information.
In the destination object in analyzing image, deep learning or KNN algorithms can be utilized, will be existed in image information
The image information of same characteristic features filters out, and with the characteristic information being had differences, and then obtains the image information and template of oil smoke
The different information of image.For example, the image information of oil smoke is being photographed, by image information compared with predetermined template image,
If judge in image that there are destination object (oil smoke), air draught state that can not be to smoke exhaust ventilator to be adjusted, such as
The fruit smoke exhaust ventilator is in opening, it is also an option that closing the smoke exhaust ventilator；, can be with if judging there are destination object
The control instruction of smoke exhaust ventilator is determined according to the status information of oil smoke, and then controls the air draught state of the smoke exhaust ventilator.
The application analyze oil smoke image when, can be, but not limited to use in a manner of scheming to search figure, by model with ought
The image zooming-out that preceding image has similar features comes out, and by transfer learning algorithm, determines immediate image.And in oil smoke
The corresponding smoke exhaust ventilator of status information control instruction, and control according to above-mentioned control instruction the air draught shape of above-mentioned smoke exhaust ventilator
During state, the air draught state of the corresponding smoke exhaust ventilator of above-mentioned control instruction can be extracted by KNN algorithms.In above-mentioned air draught state
Air draught air quantity, direction and speed, the aperture of smoke deflector, can be (large-scale, small-sized, indoor according to the type of smoke exhaust ventilator
Type, outdoor version, family expenses, hotel with etc. type) carry out in advance distinguish set.
When establishing above-mentioned first model, can be believed by the image information and image of the oil smoke shot in historical time section
The corresponding status information of breath, indicates oil smoke image tag.It can be extracted emphatically in the image information of shooting dense comprising oil smoke
Degree and the image information of distributed areas, and by corresponding user images label and the storage of oil smoke image in the database, to allow machine
Device learning training, so that after the image of newest oil smoke is photographed, can analyze in image according to the image information of input
Oil smoke status information, and then determine above-mentioned smoke exhaust ventilator control instruction.
It should be noted that the second model, the 3rd model and the 4th model that occur in any one following embodiment
Establish mode, and the mode analyzed corresponding data can be, but not limited to the side of above-mentioned first model analysis data
Formula.
Furthermore it is possible to establish each user or smoke exhaust ventilator adjustment ginseng that family (dining room, restaurant, hotel etc.) is correspondingly arranged
Number, and identity matches and deposits in the database, and establishes one by supplemental characteristic and user or family (dining room, restaurant, hotel etc.)
A data model, after user or family (dining room, restaurant, hotel etc.) identity information is determined, to extract corresponding smoke pumping
Machine adjusting parameter, so as to effectively control the air draught state of smoke exhaust ventilator, strengthens the experience sense of user.
In a kind of optional embodiment, as shown in Fig. 2, determining the control of above-mentioned smoke exhaust ventilator according to above-mentioned status information
Before instruction, the above method further includes following steps：
Step S202, obtains the first oil smoke concentration detected by oil smoke concentration detector；
Step S204, the second oil smoke concentration in above-mentioned first concentration and above-mentioned first state information is compared；
Step S206, when above-mentioned first concentration and the difference of above-mentioned second oil smoke concentration are less than the first predetermined threshold value, is touched
Hair determines the control instruction of above-mentioned smoke exhaust ventilator.
In order to improve the accuracy of the air draught state of control kitchen ventilator, the usage experience of user is improved, according to above-mentioned setting
The mode of one or more cameras obtains the first image information of oil smoke, using the first model to above-mentioned first image information into
Row analysis, determines the first state information in above-mentioned first image information, wherein, included at least in above-mentioned first state information：
Second oil smoke concentration.In addition, the first oil smoke concentration that the application can also be detected by oil smoke concentration detector, and
When one concentration and the difference of above-mentioned second oil smoke concentration are less than the first predetermined threshold value, trigger and determine that the control of above-mentioned smoke exhaust ventilator refers to
The air draught state to smoke extractor is made to be controlled.
By identifying the generating region of oil smoke, and according to the oil smoke concentration detected, determine the control of corresponding smoke exhaust ventilator
System instruction, it is possible to achieve targetedly control is adjusted in the air draught state to smoke exhaust ventilator, is inhaled so as to improve kitchen ventilator
Oil smoke effect, reduces the consumption of the energy.
In optional embodiment provided herein, the control of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information
Before instruction, the above method further includes：
The second image information of above-mentioned oil smoke is obtained, wherein, above-mentioned second image information and above-mentioned first image information are
The image information gathered at the same time from different perspectives；
Above-mentioned second image information is analyzed using the first model, determines the second shape in above-mentioned second image information
State information, wherein, above-mentioned first model trains to obtain using multi-group data by machine learning, in above-mentioned multi-group data
Every group of data include：Status information corresponding to image information and image information；
It should be noted that above-mentioned second image information can be but be not limited to the acquisition side of above-mentioned first image information
Formula is acquired, and may refer to above-mentioned the first image information of acquisition, and determines the associated description of first state information, herein
Repeat no more.
As a kind of optional embodiment, the control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information, including：
More above-mentioned first state information and above-mentioned second status information, and in above-mentioned first state information and above-mentioned second status information
Difference when being less than the second predetermined threshold value, a state letter is selected from above-mentioned first state information and above-mentioned second status information
Breath；Status information according to selection determines above-mentioned control instruction.
In order to improve the accuracy of the air draught state of control kitchen ventilator, the usage experience of user is improved, and then can basis
The image information of the oil smoke acquired twice, and the first state information analyzed by corresponding analysis model and
Second status information is compared, and is less than second in the difference of above-mentioned first state information and above-mentioned second status information and is preset
During threshold value, a status information is selected, and above-mentioned control instruction is determined according to selected status information.
In another optional embodiment, the control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information,
Including：Determine the first instruction corresponding with the concentration of above-mentioned oil smoke in above-mentioned status information, wherein, carried in above-mentioned first instruction
There is target air volume value；The air draught state of above-mentioned smoke exhaust ventilator is controlled according to above-mentioned control instruction, including：According to the above-mentioned first instruction
In target air volume value adjust the airflow value of above-mentioned smoke exhaust ventilator.
Since above-mentioned status information includes：The concentration of oil smoke and the distributed areas of oil smoke, therefore, in definite above-mentioned state
After information, processing can be distinguished to above-mentioned status information, above-mentioned status information be oil smoke concentration when, determine with it is upper
Corresponding first instruction of concentration of above-mentioned oil smoke in status information is stated, and according to the target air volume value adjustment in the above-mentioned first instruction
The airflow value of above-mentioned smoke exhaust ventilator.
In a kind of optional embodiment, the airflow value of above-mentioned smoke exhaust ventilator can be not provided with specific gear, Ye Jiwu
Gear, is different from existing fixation according to fast gear and slow gear control mode, according to the concentration of oil smoke and distributed areas, no shelves
Position carries out Boiler pressure control, it is possible to achieve the effect of more accurate adjustment control.
In an alternative embodiment, the airflow value of above-mentioned smoke exhaust ventilator can be with adjustment air quantity of the prior art
The air quantity gear of value matches, and then can be by way of according to the above-mentioned first instruction control air quantity gear, can be more accurate
The air draught state of true adjustment control smoke exhaust ventilator.
By above-described embodiment, control, Jin Erke is adjusted in air draught state that can be targetedly to smoke exhaust ventilator
To achieve the purpose that to control the air draught state of smoke exhaust ventilator according to the oil smoke concentration of smoke exhaust ventilator, it is achieved thereby that improving kitchen ventilator
Smoke absorption effect, reduces the technique effect of energy consumption.
As a kind of optional embodiment, above-mentioned target air volume value determines in the following manner：Obtain the dense of above-mentioned oil smoke
Degree；The concentration of above-mentioned oil smoke is analyzed using the 3rd model, determines the corresponding airflow value of concentration of above-mentioned oil smoke, wherein,
Above-mentioned 3rd model trains to obtain using multi-group data by machine learning, and every group of data in above-mentioned multi-group data are wrapped
Include：The concentration of oil smoke and airflow value corresponding with the concentration of oil smoke.
Optionally, the concentration of above-mentioned oil smoke can be but be not limited to the mode of above-mentioned the first concentration of acquisition, for example, can lead to
Oil smoke concentration detector is crossed to detect to obtain.
It should be noted that above-mentioned analyze the concentration of above-mentioned oil smoke using the 3rd model, so that it is determined that above-mentioned oil
The embodiment of the corresponding airflow value of concentration of cigarette, may refer to the first model of above-mentioned use and above-mentioned first image information is carried out
Analysis, determines the associated description of the first state information in above-mentioned first image information, details are not described herein again.
In a kind of optional embodiment, the control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information, including：
When above-mentioned smoke exhaust ventilator is provided with smoke deflector, corresponding with the distributed areas of above-mentioned oil smoke in above-mentioned status information second is determined
Instruction, wherein, carry the target aperture of smoke deflector in above-mentioned second instruction；Above-mentioned smoke pumping is controlled according to above-mentioned control instruction
The air draught state of machine, including：The aperture of above-mentioned smoke deflector is adjusted according to the target aperture in the above-mentioned second instruction.
, can be with if concentration is compared in oil smoke distributed areas in above-mentioned status information as a kind of optional embodiment
The smoke deflector set in above-mentioned smoke exhaust ventilator is arranged to compared with small guide vane, if correspondingly, oil smoke is distributed in above-mentioned status information
Region is more dispersed, then above-mentioned smoke deflector can be arranged to larger aperture.Specifically, can be according to the distribution of above-mentioned oil smoke
Region carries out adaptability adjusting to the aperture size of above-mentioned smoke deflector.
The above embodiments of the present application, lead by identifying the generating region of oil smoke, and according to the control of detection oil smoke distributed areas
Aerofoil stretches to form different suction, and air draught state that can be targetedly to smoke exhaust ventilator is adjusted control, and then can be with
Achieve the purpose that the air draught state that smoke exhaust ventilator is controlled according to the oil smoke concentration of smoke exhaust ventilator, inhaled it is achieved thereby that improving kitchen ventilator
Oil smoke effect, reduces the technique effect of energy consumption.
In addition, being illustrated below by way of a kind of optional embodiment, above-mentioned target aperture how is determined：Obtain above-mentioned
The distributed areas of oil smoke；The distributed areas of above-mentioned oil smoke are analyzed using the 4th model, determine the distributed area of above-mentioned oil smoke
The corresponding aperture in domain, wherein, above-mentioned 4th model trains to obtain using multi-group data by machine learning, above-mentioned multigroup number
Every group of data in include：The distributed areas of oil smoke and target aperture corresponding with the distributed areas of oil smoke.
Optionally, in the embodiment of the present application, can be, but not limited to obtain above-mentioned oil smoke by way of shooting image
Distributed areas.
It should be noted that above-mentioned analyze the distributed areas of above-mentioned oil smoke using the 4th model, so that it is determined that on
The embodiment of the corresponding aperture in distributed areas of oil smoke is stated, the first model of above-mentioned use is may refer to and above-mentioned first image is believed
Breath is analyzed, and determines the associated description of the first state information in above-mentioned first image information, details are not described herein again.
Embodiment 2
The embodiment of the present application, additionally provides a kind of oil pumping for the air draught condition control method for being used to implement above-mentioned smoke exhaust ventilator
Smoke machine, Fig. 3 be according to a kind of structure diagram of smoke exhaust ventilator of the embodiment of the present application, as shown in figure 3, above-mentioned smoke exhaust ventilator,
Including：Image collecting device 30 and processor 32, wherein,
Image collecting device 30, for the image information of oil smoke produced by obtaining smoke exhaust ventilator, and from above-mentioned image information
The status information of middle extraction oil smoke；Processor 32, for determining the control instruction of above-mentioned smoke exhaust ventilator according to above-mentioned status information；
And the air draught state of above-mentioned smoke exhaust ventilator is controlled according to above-mentioned control instruction.
, can be with it should be noted that the air draught condition control method of any one smoke exhaust ventilator in above-described embodiment 1
Perform or realize in the smoke exhaust ventilator that the present embodiment is provided.
In addition, it is still necessary to which explanation, the optional or preferred embodiment of the present embodiment may refer to the phase in embodiment 1
Description is closed, details are not described herein again.
Embodiment 3
According to embodiments of the present invention, a kind of air draught condition control method for being used to implement above-mentioned smoke exhaust ventilator is additionally provided
Device, Fig. 4 are a kind of structure diagrams of the air draught behavior control device of smoke exhaust ventilator according to embodiments of the present invention, such as Fig. 4
It is shown, the air draught behavior control device of above-mentioned smoke exhaust ventilator, including：Acquisition module 40, determining module 42 and control module 44, its
In,
Acquisition module 40, the status information for oil smoke produced by obtaining smoke exhaust ventilator；Determining module 42, for according to
State the control instruction that status information determines above-mentioned smoke exhaust ventilator；Control module 44, it is above-mentioned for being controlled according to above-mentioned control instruction
The air draught state of smoke exhaust ventilator.
Herein it should be noted that above-mentioned acquisition module 40, determining module 42 and control module 44 correspond in embodiment 1
Step S102 to step S106, three modules are identical with example and application scenarios that corresponding step is realized, but are not limited to
1 disclosure of that of above-described embodiment.It should be noted that above-mentioned module may operate in computer as a part for device
In terminal.
It should be noted that the optional or preferred embodiment of the present embodiment may refer to the associated description in embodiment 1,
Details are not described herein again.
The air draught behavior control device of above-mentioned smoke exhaust ventilator can also include processor and memory, above-mentioned acquisition module
40th, determining module 42 and control module 44 etc. store in memory as program unit, are performed and are stored in by processor
Above procedure unit in reservoir realizes corresponding function.
Kernel is included in processor, is gone in memory to transfer corresponding program unit by kernel.Kernel can set one
Or more, the operating parameter of smoke exhaust ventilator is adjusted by adjusting kernel parameter, with the suction of reasonable, accurate adjustment smoke exhaust ventilator
Wind state and air quantity.
Memory may include computer-readable medium in volatile memory, random access memory (RAM) and/
Or the form such as Nonvolatile memory, such as read-only storage (ROM) or flash memory (flash RAM), memory includes at least one deposit
Store up chip.
The embodiment of the present application additionally provides a kind of storage medium.Alternatively, in the present embodiment, above-mentioned storage medium includes
The program of storage, wherein, equipment where above-mentioned storage medium is controlled when above procedure is run performs any one above-mentioned oil pumping
The air draught condition control method of smoke machine.
Alternatively, in the present embodiment, above-mentioned storage medium can be located in computer network Computer terminal group
In any one terminal, or in any one mobile terminal in mobile terminal group.
The embodiment of the present application additionally provides a kind of processor.Alternatively, in the present embodiment, above-mentioned processor is used to run
Program, wherein, above procedure performs the air draught condition control method of any one above-mentioned smoke exhaust ventilator when running.
The embodiment of the present application provides a kind of equipment, and equipment includes processor, memory and storage on a memory and can
The program run on a processor, when processor executive program, realize following steps：The shape of oil smoke produced by obtaining smoke exhaust ventilator
State information；The control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information；Above-mentioned pumping is controlled according to above-mentioned control instruction
The air draught state of kitchen ventilator.
Alternatively, during above-mentioned processor executive program, the first image information of above-mentioned oil smoke can also be obtained；Use first
Model analyzes above-mentioned first image information, determines the first state information in above-mentioned first image information, wherein, it is above-mentioned
First model trains to obtain using multi-group data by machine learning, and every group of data in above-mentioned multi-group data include：
Status information corresponding to image information and image information.
Alternatively, during above-mentioned processor executive program, the first oil detected by oil smoke concentration detector can also be obtained
Smoke density；The second oil smoke concentration in above-mentioned first concentration and above-mentioned first state information is compared；It is dense above-mentioned first
When the difference of degree and above-mentioned second oil smoke concentration is less than the first predetermined threshold value, the control instruction for determining above-mentioned smoke exhaust ventilator is triggered.
Alternatively, during above-mentioned processor executive program, the second image information of above-mentioned oil smoke can also be obtained, wherein, on
It is the image information from different perspectives while gathered to state the second image information and above-mentioned first image information；Use the first model pair
Above-mentioned second image information is analyzed, and determines the second status information in above-mentioned second image information, wherein, above-mentioned first mould
Type trains to obtain using multi-group data by machine learning, and every group of data in above-mentioned multi-group data include：Image is believed
Status information corresponding to breath and image information；The control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information, including：
More above-mentioned first state information and above-mentioned second status information, and in above-mentioned first state information and above-mentioned second status information
Difference when being less than the second predetermined threshold value, a state letter is selected from above-mentioned first state information and above-mentioned second status information
Breath；Status information according to selection determines above-mentioned control instruction.
Alternatively, during above-mentioned processor executive program, the concentration with above-mentioned oil smoke in above-mentioned status information can also be determined
Corresponding first instruction, wherein, carry target air volume value in above-mentioned first instruction；Above-mentioned pumping is controlled according to above-mentioned control instruction
The air draught state of kitchen ventilator, including：The airflow value of above-mentioned smoke exhaust ventilator is adjusted according to the target air volume value in the above-mentioned first instruction.
Alternatively, during above-mentioned processor executive program, the concentration of above-mentioned oil smoke can also be obtained；Using the 3rd model to upper
The concentration for stating oil smoke is analyzed, and determines the corresponding airflow value of concentration of above-mentioned oil smoke, wherein, above-mentioned 3rd model is using more
Group data are trained by machine learning, and every group of data in above-mentioned multi-group data include：The concentration of oil smoke and with oil
The corresponding airflow value of concentration of cigarette.
Alternatively, during above-mentioned processor executive program, can also when above-mentioned smoke exhaust ventilator is provided with smoke deflector, determine with
Corresponding second instruction in the distributed areas of above-mentioned oil smoke in above-mentioned status information, wherein, carried in above-mentioned second instruction and lead cigarette
The target aperture of plate；The air draught state of above-mentioned smoke exhaust ventilator is controlled according to above-mentioned control instruction, including：According to the above-mentioned second instruction
In target aperture adjust the aperture of above-mentioned smoke deflector.
Alternatively, during above-mentioned processor executive program, the distributed areas of above-mentioned oil smoke can also be obtained；Use the 4th model
The distributed areas of above-mentioned oil smoke are analyzed, determine the corresponding aperture in distributed areas of above-mentioned oil smoke, wherein, above-mentioned 4th mould
Type trains to obtain using multi-group data by machine learning, and every group of data in above-mentioned multi-group data include：Oil smoke
Distributed areas and target aperture corresponding with the distributed areas of oil smoke.
Present invention also provides a kind of computer program product, when being performed on data processing equipment, is adapted for carrying out just
The program of beginningization there are as below methods step：The status information of oil smoke produced by obtaining smoke exhaust ventilator；It is true according to above-mentioned status information
The control instruction of fixed above-mentioned smoke exhaust ventilator；The air draught state of above-mentioned smoke exhaust ventilator is controlled according to above-mentioned control instruction.
Alternatively, during above computer program product executive program, the first image information of above-mentioned oil smoke can also be obtained；
Above-mentioned first image information is analyzed using the first model, determines the first state information in above-mentioned first image information,
Wherein, above-mentioned first model trains to obtain using multi-group data by machine learning, every group of number in above-mentioned multi-group data
According to including：Status information corresponding to image information and image information.
Alternatively, during above computer program product executive program, it can also obtain and be detected by oil smoke concentration detector
The first oil smoke concentration；The second oil smoke concentration in above-mentioned first concentration and above-mentioned first state information is compared；Upper
When stating the difference of the first concentration and above-mentioned second oil smoke concentration and being less than the first predetermined threshold value, the control for determining above-mentioned smoke exhaust ventilator is triggered
System instruction.
Alternatively, during above computer program product executive program, the second image information of above-mentioned oil smoke can also be obtained,
Wherein, above-mentioned second image information and above-mentioned first image information are the image information gathered at the same time from different perspectives；Use
One model analyzes above-mentioned second image information, determines the second status information in above-mentioned second image information, wherein, on
State the first model to train to obtain by machine learning using multi-group data, every group of data in above-mentioned multi-group data are wrapped
Include：Status information corresponding to image information and image information；The control of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information
Instruction, including：More above-mentioned first state information and above-mentioned second status information, and in above-mentioned first state information and above-mentioned
When the difference of two-state information is less than the second predetermined threshold value, selected from above-mentioned first state information and above-mentioned second status information
One status information；Status information according to selection determines above-mentioned control instruction.
Alternatively, during above computer program product executive program, can also determine and above-mentioned oil in above-mentioned status information
Corresponding first instruction of concentration of cigarette, wherein, carry target air volume value in above-mentioned first instruction；According to above-mentioned control instruction control
The air draught state of above-mentioned smoke exhaust ventilator is made, including：Above-mentioned smoke exhaust ventilator is adjusted according to the target air volume value in the above-mentioned first instruction
Airflow value.
Alternatively, during above computer program product executive program, the concentration of above-mentioned oil smoke can also be obtained；Use the 3rd
Model analyzes the concentration of above-mentioned oil smoke, determines the corresponding airflow value of concentration of above-mentioned oil smoke, wherein, above-mentioned 3rd model
Train to obtain by machine learning using multi-group data, every group of data in above-mentioned multi-group data include：Oil smoke it is dense
Degree and airflow value corresponding with the concentration of oil smoke.
Alternatively, during above computer program product executive program, above-mentioned smoke exhaust ventilator can also be provided with smoke deflector
When, determine the second instruction corresponding with the distributed areas of above-mentioned oil smoke in above-mentioned status information, wherein, taken in above-mentioned second instruction
Target aperture with smoke deflector；The air draught state of above-mentioned smoke exhaust ventilator is controlled according to above-mentioned control instruction, including：According to above-mentioned
Target aperture in second instruction adjusts the aperture of above-mentioned smoke deflector.
Alternatively, during above computer program product executive program, the distributed areas of above-mentioned oil smoke can also be obtained；Use
4th model analyzes the distributed areas of above-mentioned oil smoke, determines the corresponding aperture in distributed areas of above-mentioned oil smoke, wherein, on
State the 4th model to train to obtain by machine learning using multi-group data, every group of data in above-mentioned multi-group data are wrapped
Include：The distributed areas of oil smoke and target aperture corresponding with the distributed areas of oil smoke.
Using the embodiment of the present application, there is provided a kind of scheme of the air draught state control of smoke exhaust ventilator.Pumped by obtaining
The status information of oil smoke produced by smoke machine；The control instruction of above-mentioned smoke exhaust ventilator is determined according to above-mentioned status information；According to above-mentioned
Control instruction controls the air draught state of above-mentioned smoke exhaust ventilator, has reached according to oil smoke concentration and distribution situation, has controlled above-mentioned oil pumping
The purpose of the air draught state of smoke machine, it is achieved thereby that improving kitchen ventilator smoke absorption effect, reduces the technique effect of energy consumption, and then solve
Existing smoke exhaust ventilator of having determined can not adjust air draught state according to oil smoke concentration and distribution situation, cause smoke absorption effect bad
Technical problem.
The embodiments of the present invention are for illustration only, do not represent the quality of embodiment.
In the above embodiment of the present invention, the description to each embodiment all emphasizes particularly on different fields, and does not have in some embodiment
The part of detailed description, may refer to the associated description of other embodiment.
In several embodiments provided herein, it should be understood that disclosed technology contents, can pass through others
Mode is realized.Wherein, device embodiment described above is only schematical, such as the division of the unit, Ke Yiwei
A kind of division of logic function, can there is an other dividing mode when actually realizing, for example, multiple units or component can combine or
Person is desirably integrated into another system, or some features can be ignored, or does not perform.Another, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be INDIRECT COUPLING or communication link by some interfaces, unit or module
Connect, can be electrical or other forms.
The unit illustrated as separating component may or may not be physically separate, be shown as unit
The component shown may or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
On unit.Some or all of unit therein can be selected to realize the purpose of this embodiment scheme according to the actual needs.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, can also
That unit is individually physically present, can also two or more units integrate in a unit.Above-mentioned integrated list
Member can both be realized in the form of hardware, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and is used as independent production marketing or use
When, it can be stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially
The part to contribute in other words to the prior art or all or part of the technical solution can be in the form of software products
Embody, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can be personal computer, server or network equipment etc.) perform each embodiment the method for the present invention whole or
Part steps.And foregoing storage medium includes：USB flash disk, read-only storage (ROM, Read-Only Memory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), mobile hard disk, magnetic disc or CD etc. are various can be with store program codes
Medium.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (10)
- A kind of 1. air draught condition control method of smoke exhaust ventilator, it is characterised in that including：The status information of oil smoke produced by obtaining smoke exhaust ventilator；The control instruction of the smoke exhaust ventilator is determined according to the status information；The air draught state of the smoke exhaust ventilator is controlled according to the control instruction.
- 2. according to the method described in claim 1, it is characterized in that, the status information of oil smoke produced by obtaining smoke exhaust ventilator, bag Include：Obtain the first image information of the oil smoke；Described first image information is analyzed using the first model, determines the first state letter in described first image information Breath, wherein, first model trains to obtain using multi-group data by machine learning, every group in the multi-group data Data include：Status information corresponding to image information and image information.
- 3. according to the method described in claim 2, it is characterized in that, the control of the smoke exhaust ventilator is determined according to the status information Before system instruction, the method further includes：Obtain the first oil smoke concentration detected by oil smoke concentration detector；By in the first concentration and the first state information Second oil smoke concentration is compared；It is less than the first predetermined threshold value in first concentration and the difference of second oil smoke concentration When, trigger the control instruction for determining the smoke exhaust ventilator.
- 4. according to the method described in claim 2, it is characterized in that,Before the control instruction that the smoke exhaust ventilator is determined according to the status information, the method further includes：Obtain the oil Second image information of cigarette, wherein, second image information and described first image information are to gather at the same time from different perspectives Image information；Second image information is analyzed using the first model, determines in second image information Two-state information, wherein, first model trains to obtain using multi-group data by machine learning, the multi-group data In every group of data include：Status information corresponding to image information and image information；The control instruction of the smoke exhaust ventilator is determined according to the status information, including：Compare the first state information and institute The second status information is stated, and is less than the second predetermined threshold value in the difference of the first state information and second status information When, a status information is selected from the first state information and second status information；Status information according to selection Determine the control instruction.
- 5. according to the method described in claim 1, it is characterized in that, the status information includes：It is the concentration of the oil smoke, described The distributed areas of oil smoke.
- 6. according to the method described in claim 5, it is characterized in that,The control instruction of the smoke exhaust ventilator is determined according to the status information, including：Described in the definite and status information Corresponding first instruction of concentration of oil smoke, wherein, carry target air volume value in first instruction；The air draught state of the smoke exhaust ventilator is controlled according to the control instruction, including：According to the target in the described first instruction Airflow value adjusts the airflow value of the smoke exhaust ventilator.
- 7. according to the method described in claim 6, it is characterized in that, the target air volume value determines in the following manner：Obtain the concentration of the oil smoke；The concentration of the oil smoke is analyzed using the 3rd model, determines the corresponding airflow value of concentration of the oil smoke, wherein, 3rd model trains to obtain using multi-group data by machine learning, and every group of data in the multi-group data are wrapped Include：The concentration of oil smoke and airflow value corresponding with the concentration of oil smoke.
- 8. according to the method described in claim 5, it is characterized in that,The control instruction of the smoke exhaust ventilator is determined according to the status information, including：It is provided with the smoke exhaust ventilator and leads cigarette During plate, the second instruction corresponding with the distributed areas of oil smoke described in the status information is determined, wherein, in second instruction Carry the target aperture of smoke deflector；The air draught state of the smoke exhaust ventilator is controlled according to the control instruction, including：According to the target in the described second instruction Aperture adjusts the aperture of the smoke deflector.
- 9. according to the method described in claim 6, it is characterized in that, the target aperture determines in the following manner：Obtain the distributed areas of the oil smoke；The distributed areas of the oil smoke are analyzed using the 4th model, determines that the distributed areas of the oil smoke are corresponding and opens Degree, wherein, the 4th model trains to obtain using multi-group data by machine learning, every group in the multi-group data Data include：The distributed areas of oil smoke and target aperture corresponding with the distributed areas of oil smoke.
- A kind of 10. smoke exhaust ventilator, it is characterised in that including：Image collecting device, for the image information of oil smoke produced by obtaining smoke exhaust ventilator, and is extracted from described image information The status information of oil smoke；Processor, for determining the control instruction of the smoke exhaust ventilator according to the status information；And refer to according to the control Order controls the air draught state of the smoke exhaust ventilator.
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| Publication number | Publication date |
|---|---|
| CN107965828B (en) | 2019-06-14 |
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