CN109813713A - A kind of smoke machine with multiple independent harmful substance detection mould groups - Google Patents
A kind of smoke machine with multiple independent harmful substance detection mould groups Download PDFInfo
- Publication number
- CN109813713A CN109813713A CN201811630888.1A CN201811630888A CN109813713A CN 109813713 A CN109813713 A CN 109813713A CN 201811630888 A CN201811630888 A CN 201811630888A CN 109813713 A CN109813713 A CN 109813713A
- Authority
- CN
- China
- Prior art keywords
- module
- polycyclic aromatic
- detection
- smoke machine
- aromatic hydrocarbon
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Investigating Or Analysing Materials By Optical Means (AREA)
- Air Conditioning Control Device (AREA)
Abstract
A kind of smoke machine with multiple independent harmful substance detection mould groups, is provided with detection mould group, control assembly and the smoke machine ontology for detecting smoke machine ambient enviroment；Above-mentioned, control assembly is connect with detection mould group and smoke machine ontology respectively, and detection mould group is sent to control assembly for detecting smoke machine ambient enviroment, and by the detection information of ambient enviroment, and control assembly controls smoke machine ontology according to the detection information received.Detection mould group is provided with temperature sensing module；Detection mould group is additionally provided with the vision capture detection module for obtaining generating oil smoke size to the image analysis of cooking zone oil smoke and in real time, detection mould group is additionally provided with organic volatile detection module, detection mould group is additionally provided with particulate matter detection module, and detection mould group is additionally provided with the first polycyclic aromatic hydrocarbons (PAH) computing module.The smoke machine with multiple independent harmful substance detection mould groups is able to detect a variety of different pernicious gases in kitchen environment, call user's attention protection.
Description
Technical field
The present invention relates to machine for kitchen use technical fields, more particularly to one kind there are multiple independent harmful substances to detect mould group
Smoke machine.
Background technique
Kitchen ventilator is one of essential electric appliance in family now.Kitchen ventilator is mounted on the top of kitchen gas stove, uses
The oil smoke generated when absorbing and cooking keeps oil smoke discharge outdoor, reduces the air pollution in kitchen.But it can be produced when culinary cuisine
Raw a variety of different pernicious gases, pernicious gas can generate very big harm, such as cancer to human body, include in soot gas
There is multiring aromatic hydrocarbon substance, has considerable part that there is carcinogenicity to make such as benzo [α] pyrene in current in multiring aromatic hydrocarbon substance
Simply oil smoke can only be aspirated in kitchen ventilator, cannot identify the state of soot gas, greatly limitation and restriction
The yearning lived for modern healthy of people.
Therefore, in view of the shortcomings of the prior art, provide a kind of smoke machine with multiple independent harmful substances detection mould groups with gram
It is very necessary to take prior art deficiency.
Summary of the invention
It is provided a kind of with multiple independent harmful substances it is an object of the invention to avoid the deficiencies in the prior art place
The smoke machine of mould group is detected, this has the smoke machine of multiple independent harmful substance detection mould groups can be in a variety of situations to kitchen
Pernicious gas in oil smoke is precisely identified, the detection error under the detection mould group of independent smoke machine is avoided.
Above-mentioned purpose of the invention is realized by following technological means.
A kind of smoke machine with multiple independent harmful substance detection mould groups is provided, is provided with more sets for detecting around smoke machine
Detection mould group, control assembly and the smoke machine ontology of environment；Above-mentioned, control assembly is connect respectively with every set detection Mo Zu, is controlled
Component is connect with smoke machine ontology.
Above-mentioned, every set detection Mo Zu is used to detect respectively smoke machine ambient enviroment, and the detection information of ambient enviroment is sent
To control assembly, control assembly controls smoke machine ontology according to the detection information received.
Preferably, every set detection mould group is provided with temperature sensing module；Temperature sensing module respectively with control assembly, smoke machine
Ontology connection；
Temperature sensing module induction detection smoke machine ambient enviroment obtains temperature output signal and is transmitted to control assembly.
Preferably, every set detection mould group is additionally provided with for obtaining to the image analysis of cooking zone oil smoke and in real time generating oil
The vision capture detection module of cigarette size, vision capture detection module are connect with control assembly, smoke machine ontology respectively；
Above-mentioned, the cooking zone oil smoke image around vision capture detection module acquisition smoke machine obtains oil smoke output signal simultaneously
It is transmitted to control module.
Preferably, every set detection mould group is additionally provided with organic volatile detection module, organic volatile detection module difference
It is connect with control assembly, smoke machine ontology；
Above-mentioned, organic volatile detection module detects the concentration values of the organic volatile around smoke machine main body, and will have
The concentration values of machine volatile matter are sent to control module.
Preferably, every set detection mould group is additionally provided with particulate matter detection module, particulate matter detection module respectively with control
Component, the connection of smoke machine ontology；Particulate matter detection module detects the concentration value of the particulate matter around smoke machine main body, and by particulate matter
Concentration value is sent to control module.
Preferably, every set detection mould group is additionally provided with the first polycyclic aromatic hydrocarbons (PAH) computing module, polycyclic aromatic hydrocarbons (PAH) detection module
It is connect respectively with the output end of the output end of temperature sensing module, vision capture detection module；
Above-mentioned, temperature detection information is sent to the first polycyclic aromatic hydrocarbons (PAH) computing module by the output end of temperature sensing module,
The image data that the output end of vision capture detection module will test is sent to the first polycyclic aromatic hydrocarbons (PAH) computing module, more than first
Aromatic hydrocarbon ring computing module calculates the polycyclic aromatic hydrocarbon concentration in culinary cuisine region according to information is received.
Preferably, the first polycyclic aromatic hydrocarbons (PAH) computing module be construct to obtain with mathematical modeling about temperature and oil smoke size with
In oil smoke in pernicious gas the mathematical relationship of polycyclic aromatic hydrocarbon concentration computation model；Or
Another preferred, computation model is lienar for computing module, NONLINEAR CALCULATION module, exponential type computing module, power
Type computing module, logarithmic computing module, neural network computing module, machine learning computing module or deep learning calculate
Module.
Or
Another preferred, the calculation formula of computation model is formula (I),
CPolycyclic aromatic hydrocarbon+ 475.1 formula (I) of+0.0033 κ λ of+0.0005 λ of=0.05 κ,
Wherein CPolycyclic aromatic hydrocarbonFor the multiring aromatic hydrocarbon gas total concentration in cooking zone, κ is the output data of temperature sensing module, λ
For the output data of vision capture detection module.
Or
Another preferred, the calculation formula of computation model is formula (II),
CPolycyclic aromatic hydrocarbon=0.05 κ0.98+0.0005λ1.05+ 469.5 formula of+0.0033 κ λ (II),
Wherein CPolycyclic aromatic hydrocarbonFor the multiring aromatic hydrocarbon gas total concentration in cooking zone, κ is the output data of temperature sensing module, λ
For the output data of vision capture detection module.
Preferably, computation model carries out Environmental Health grade classification according to polycyclic aromatic hydrocarbon concentration；
Be averaged limiting concentration and polycyclic aromatic hydrocarbon concentrations versus of benzo [a] pyrene of national regulations carries out environmental rating division；
Work as CPolycyclic aromatic hydrocarbon< CBenzo [a] pyreneWhen, it is determined as Health Category, works as CPolycyclic aromatic hydrocarbon≥CBenzo [a] pyreneWhen, it is determined as unhealthy grade；
Wherein CBenzo [a] pyreneIt is averaged limiting concentration, and C for benzo [a] pyrene of national regulationsBenzo [a] pyrene=1ng/m3。
Benzo [a] pyrene of polycyclic aromatic hydrocarbon concentration and national regulations be averaged limiting concentration be divided by carry out Environmental Health grade draw
Point, such as formula (III):
As 0≤ε≤0.5, then it is determined as Health Category, as 0 < ε≤1, is then determined as good level, as ε > 1,
Then it is determined as unhealthy grade.
Or
Another preferred, Environmental Health grade classification is with the result after the total yield virulence factor weighting of polycyclic aromatic hydrocarbon concentration
Carry out Environmental Health grade classification；
By formula (IV) count polycyclic aromatic hydrocarbon concentration total yield virulence factor:
Wherein BEQ is the total yield virulence factor of polycyclic aromatic hydrocarbon, and μ is the label of polycyclic aromatic hydrocarbon type, 1≤μ≤ξ and μ and ξ
For natural number, beqμFor the equivalent toxic concentration of the content of μ kind polycyclic aromatic hydrocarbon, beqμIt is counted by formula (V),
beqμ=Cμ*TEFμFormula (V),
CμFor the concentration of the content of μ kind polycyclic aromatic hydrocarbon, TEFμFor the corresponding equivalent virulence factor of μ kind polycyclic aromatic hydrocarbon；Or
Benzo [a] pyrene of polycyclic aromatic hydrocarbon concentration and total yield virulence factor product and national regulations be averaged limiting concentration comparison
Carry out environmental rating division；
Work as BEQ*CPolycyclic aromatic hydrocarbon< CBenzo [a] pyreneWhen, it is determined as Health Category, works as BEQ*CPolycyclic aromatic hydrocarbon≥CBenzo [a] pyreneWhen, judgement then determines
For unhealthy grade；Or
Benzo [a] pyrene of the polycyclic aromatic hydrocarbon concentration and total yield virulence factor product and national regulations limiting concentration that is averaged is divided by
Environmental Health grade classification is carried out, such as formula (III):
As 0≤δ≤0.5, then it is determined as Health Category, as 0 < δ≤1, is then determined as good level, as δ > 1,
Then it is determined as unhealthy grade.
Preferably, control assembly is provided with kitchen ventilator speed adjusting module, firepower adjustment module and reminding module；It reminds
The output end of the output end of module and computing module, the output end of organic volatile detection module and particulate matter detection module connects
It connects, reminding module receives the calculated result of computing module, the testing result of organic volatile detection module and particle quality testing
Display alarm is carried out after surveying the testing result of module；
Preferably, the kitchen ventilator speed adjusting module exhausting component with the output end of computation model, kitchen ventilator ontology respectively
Connection, the output end output signal that kitchen ventilator speed adjusting module receives computation model is unhealthy grade, then controls enhancing
Or the operating power of starting exhausting component；Firepower adjustment module respectively with the output end of temperature sensing module, organic volatile quality testing
Survey the output end of module, the output end of computation model and solenoid valve connection；Firepower adjustment module receives temperature sensing module
Output end, the output end of organic volatile detection module, computation model output end information, according to the information content control electromagnetism
The switch of valve.
Preferably, temperature sensing module is connect with the wired or wireless signal of control assembly, and temperature sensing module is set as non-
Intrusive temperature sensor or intrusive temperature sensor；
Preferably, non-invasive temperature sensor is set as dot matrix infrared temperature sensor, array temperature sensor
Or any one or more in thermal imaging temperature sensor；
Preferably, vision capture detection module is set as camera.
Preferably, organic volatile detection module is configured to measure the concentration VOC sensing of many volatile organic matters
Device.
Preferably, particulate matter detection module is set as PM10 sensor, PM2.5 sensor, PM1 sensor, PM0.1 sensing
Any one or more in device or particulate matter sensors less than 0.1 μm.
Preferably, intrusive temperature sensor is set as thermocouple temperature sensor.
Smoke machine with multiple independent harmful substance detection mould groups of the invention, is provided with more sets for detecting around smoke machine
Detection mould group, control assembly and the smoke machine ontology of environment；Above-mentioned, control assembly detects mould groups and smoke machine ontology with more sets respectively
Connection, more set detection Mo Zu are used to detect respectively smoke machine ambient enviroment, and the detection information of ambient enviroment is respectively sent to control
Component processed, control assembly control smoke machine ontology according to the detection information received.Every set detection mould group is provided with temperature sensing mould
Block；Every set detection mould group is additionally provided with the vision for obtaining generating oil smoke size to the image analysis of cooking zone oil smoke and in real time
Detection module is captured, every set detection mould group is additionally provided with organic volatile detection module, and every set detection mould group is additionally provided with particle
Analyte detection module, every set detection mould group are additionally provided with the first polycyclic aromatic hydrocarbons (PAH) computing module.This has multiple independent harmful substances
The smoke machine for detecting mould group can precisely detect a variety of different pernicious gases in detection kitchen environment, remind user's note
Meaning protection.
Detailed description of the invention
Using attached drawing, the present invention is further illustrated, but the content in attached drawing is not constituted to any limit of the invention
System.
Fig. 1 is the structural schematic diagram of the embodiment of the present invention 1.
Fig. 2 is the structural schematic diagram of the embodiment of the present invention 2.
Fig. 3 is the structural schematic diagram of the embodiment of the present invention 3.
Fig. 4 is the structural schematic diagram of the embodiment of the present invention 4.
Fig. 5 is the structural schematic diagram of the embodiment of the present invention 11.
In Fig. 1 into Fig. 5, comprising:
Detect mould group 100, temperature sensing module 101, vision capture detection module 102, machine volatile matter detection module 103,
Particulate matter detection module 104, the first polycyclic aromatic hydrocarbons (PAH) computing module 105；
Control assembly 200, kitchen ventilator speed adjusting module 201, firepower adjustment module 202, reminding module 203；
Smoke machine ontology 300.
Specific embodiment
The invention will be further described with the following Examples.
Embodiment 1.
A kind of smoke machine with multiple independent harmful substance detection mould groups, as shown in Figure 1, being provided with more sets for detecting cigarette
Detection mould group 100, control assembly 200 and the smoke machine ontology 300 of machine ambient enviroment；Control assembly 200 and every set detect mould group
100 are separately connected, and control assembly 200 is connect with smoke machine ontology 300.
Above-mentioned, every set detection mould group 100 is respectively used to detection smoke machine ambient enviroment, and the detection information of ambient enviroment is sent out
It send to control assembly 200, control assembly 200 controls smoke machine ontology 300 according to the detection information received.
Specifically, every set detection mould group 100 is provided with temperature sensing module 101；Temperature sensing module 101 respectively with control
Component 200, smoke machine ontology 300 connect；
Temperature sensing module induction detection smoke machine ambient enviroment obtains temperature output signal and is transmitted to control assembly 200.
Specifically, every set detection mould group 100 is additionally provided with for being produced to the image analysis of cooking zone oil smoke and in real time
The vision capture detection module 102 of oil generation cigarette size, vision capture detection module 102 respectively with control assembly 200, smoke machine ontology
300 connections；
Above-mentioned, the cooking zone oil smoke image that vision capture detection module 102 acquires around smoke machine obtains oil smoke output letter
Number and be transmitted to control module.
Vision capture detection module 102 acquires in cooking process the case where generating oil smoke in real time, specially acquisition pair in real time
It answers the picture in region and handles current kitchen fume concentration,
The processing method of vision capture detection module 102 are as follows:
Vision capture detection module 102 is handled based on the initial pictures that imaging device acquires, initial pictures
For grayscale image, initial pictures collected are serialized, and the initial pictures of the initial pictures and previous frame that pass sequentially through rear frame carry out
Processing obtains the current kitchen fume concentration at moment locating for each rear frame initial pictures
It is handled every time by the initial pictures of rear frame and the initial pictures of previous frame, when obtaining locating for rear frame initial pictures
The step process for the current kitchen fume concentration carved is as follows:
(1) initial pictures of rear frame and the initial pictures of previous frame frame difference is carried out to handle to obtain frame difference image；
(2) denoising is carried out to frame difference image in a manner of opening operation, obtains denoising image；
(3) edge detection is carried out to denoising image, marker motion region is as initial area-of-interest；
(4) gray average calculating is carried out to initial area-of-interest and segment smoothing degree calculates, it is equal gray scale will to be met simultaneously
The region of value and smoothness requirements is as next step area-of-interest, and other regions are as interference elimination；
(5) area-of-interest extracted to step (4) counts respectively, obtains oil smoke concentration according to statistical result and assigns
Value.
In step (1), to collected initial pictures carry out frame difference operate to obtain frame difference image be specifically:
Vision capture detection module 102 according to the sequencings of the initial pictures received, by a later frame image with it is previous
Frame image makes the difference, and obtains the highlighted frame difference image in dynamic area.
Wherein step (2) carries out denoising using opening operation to frame difference image, denoising image is obtained, especially by as follows
Mode carries out: first carrying out etching operation to frame difference image and disconnects narrow company to eliminate noise and the tiny spine in image
It connects；Expansive working is carried out to the image after corrosion again, restores the smoke characteristics in former frame difference image.
Wherein step (3) carries out edge detection to denoising image, and marker motion region is as initial area-of-interest, specifically
Be: the edge of detection frame difference image highlight regions is simultaneously marked, using the region marked as initial area-of-interest.
Wherein step (4) is specifically to carry out gray average, the calculating of segment smoothing degree to each initial area-of-interest, is obtained
Each initial corresponding gray average of area-of-interest and gray scale smoothness, will meet the gray average being calculated simultaneously and are less than
Gray threshold, gray scale smoothness be less than gray scale smoothness threshold initial area-of-interest be used as area-of-interest, will it is other at the beginning of
Beginning area-of-interest is determined as interference region.
Wherein step (5) be specifically, for the area-of-interest that step (4) extracts, by each region of interest area image
In the gray scales of all pixels carry out read group total and obtain the gray value of each region of interest area image, then by each region of interest
The gray value of area image is summed, and oil smoke concentration assignment is obtained.
The target area of imaging device acquisition indicates that any one frame initial pictures are the imaging of corresponding region S with region S.
Initial pictures are made of m*n pixel,
The gray value of the pixel of frame initial pictures A is indicated afterwards with matrix A H, AH={ ahi,j, ahi,jFrame initial graph after representative
As the i-th row, the corresponding gray value of jth column pixel in A, i is the row where pixel, and j is the column where pixel, 1≤i≤m, 1≤j
≤n；The subregion in frame initial pictures A where the i-th row, jth column pixel is AS afterwardsi,j。
The gray value of the pixel of previous frame initial pictures B indicates with matrix B H, BH={ bhi,j, bhi,jRepresent previous frame initial graph
As the i-th row, the corresponding gray value of jth column pixel in B, the subregion in previous frame initial pictures B where the i-th row, jth column pixel is
BSi,j。
The grey scale pixel value of frame difference image D indicates with matrix D H, DH={ dhi,j}={ | ahi,j-bhi,j|, dhi,jIt represents
I-th row, the corresponding gray value of jth column pixel in frame difference image D, the subregion in frame difference image D where the i-th row, jth column pixel
For DSi,j。
In frame difference image, | dhi,j|=0 region is in black；|dhi,j| ≠ 0 region is in be highlighted.
Etching operation wherein is carried out to frame difference image in step (2), is specifically comprised the following steps:
2-11 arbitrarily defines a convolution kernel θ；
Convolution kernel θ and frame difference image are carried out convolution by 2-12；When convolution kernel θ traverses frame difference image, convolution kernel institute is extracted
The pixel grey scale minimum value p of the convolution results and pixel C being overlapped with convolution kernel center in overlay area；
The gray scale of pixel C passes through Matrix C H={ ck,qIndicate, k, q are the row serial number and column serial number of pixel C,
Obtain the convolution results minimum value pixel matrix P obtained in convolution kernel θ traversal frame difference image process, minimum value
The gray scale of pixel matrix P passes through matrix PH={ pk,qIndicate；
The corresponding imparting pixel C of the gray scale of pixel matrix P is obtained corrosion image by 2-13；
Expansive working is carried out to corrosion image in step (2), is specifically comprised the following steps:
2-21 arbitrarily defines a convolution kernel β；
Convolution kernel β and corrosion image are carried out convolution by 2-22；When convolution kernel β traverses corrosion image, convolution kernel institute is extracted
The pixel grey scale maximum value o of the convolution results and pixel R being overlapped with convolution kernel center in overlay area；
The gray scale of pixel R passes through matrix RH={ rl,vIndicate, l, v are the row serial number and column serial number of pixel R,
Obtain the convolution results maximum value pixel matrix O obtained in convolution kernel β traversal corrosion image process, maximum value
The gray scale of pixel matrix O passes through matrix OH={ ol,vIndicate；
The corresponding imparting pixel R of the gray scale of maximum value pixel matrix O is obtained expanding image, obtained expansion by 2-13
Image is to denoise image.
Wherein step (3) carries out as follows:
3-1 defines a filter Y, and filter is t*t matrix, and t is odd number；
3-2 makes filter Y traversal denoising image, calculates filter and go where the central pixel point at each position
It makes an uproar the gray values of other pixels in the gray value and center pixel vertex neighborhood of image, and filter is calculated according to formula (I)
The edge detection value X of central pixel point at each positionz, z is label when filter Y traversal denoises image,
F, g is the matrix serial number of pixel, and 1≤f≤t, 1≤g≤t, e are pixel of the filter at each position
The gray value of the denoising image at place；α is weight coefficient, corresponding with filter location；
3-3, by central pixel point edge detection value X of the filter at each positionzWith center pixel vertex neighborhood its
The gray value of its pixel subtracts each other, and judges whether the absolute value of difference is greater than threshold value Δ；
Statistics is greater than the quantity of threshold value, if quantity is more thanDetermine the central pixel point pair of filter present position
The pixel position for the denoising image answered is marginal point, and is marked；
3-4, complete denoising image of filter traversal, obtains the markd marginal point of institute, obtains preliminary area-of-interest.
T is 3.
It should be noted that the processing method of above-mentioned vision capture detection module is only to propose one kind of processing side
Method, the vision capture detection module for being merely able to obtain cooking zone for the processing method of other vision capture detection modules export
The method of data can be applied to the kitchen ventilator that can identify pernicious gas in oil smoke of the invention, should all fall into guarantor of the invention
Protect range.
It should be noted that vision capture detection module of the invention is to be carried out using camera to cooking zone oil smoke size
Detection, as long as can be realized above-mentioned function of the invention all can serve as vision capture detection module of the invention.
The smoke machine with multiple independent harmful substance detection mould groups can detect kitchen by multiple independent detection mould groups
The concentration of the harmful substance in room region, and user is further reminded, have the characteristics that structure is simple, easy to use.
Embodiment 2.
A kind of smoke machine with multiple independent harmful substance detection mould groups, other structures are same as Example 1, difference
It is, as shown in Fig. 2, this has smoke machine of multiple independent harmful substance detection mould groups, every set detection mould group 100 is additionally provided with the
One polycyclic aromatic hydrocarbons (PAH) computing module 105；, polycyclic aromatic hydrocarbons (PAH) detection module respectively with the output end of temperature sensing module 101, vision
Capture the output end connection of detection module 102；
Above-mentioned, temperature detection information is sent to the first polycyclic aromatic hydrocarbons (PAH) and calculates mould by the output end of temperature sensing module 101
Block 105；, the image data that the output end of vision capture detection module 102 will test be sent to the first polycyclic aromatic hydrocarbons (PAH) calculating
Module 105；, the first polycyclic aromatic hydrocarbons (PAH) computing module 105；It is dense according to the polycyclic aromatic hydrocarbon for receiving information calculating culinary cuisine region
Degree.
Specifically, the first polycyclic aromatic hydrocarbons (PAH) computing module 105；It is big about temperature and oil smoke to construct to obtain with mathematical modeling
The small computation model with the mathematical relationship of polycyclic aromatic hydrocarbon concentration in pernicious gas in oil smoke.
First polycyclic aromatic hydrocarbons (PAH) computing module of the invention is to calculate current culinary art by temperature signal and oil smoke signal
The polycyclic aromatic hydrocarbon concentration in region, the computing module are that calculator or the module for having computing function can be used as meter of the invention
Module is calculated, the computing module for this type is the common knowledge of the computing module in industrial production, those skilled in the art
It is to be understood that details are not described herein.
Smoke machine the first polycyclic aromatic hydrocarbons (PAH) computing module with multiple independent harmful substance detection mould groups calculates currently
The concentration of the polycyclic aromatic hydrocarbon of environment easily obtains testing result convenient for people are more specific.
Embodiment 3.
A kind of smoke machine with multiple independent harmful substance detection mould groups, other structures are identical as embodiment 1 or 2, different
Place is, as shown in figure 3, detection mould group 100 is additionally provided with organic volatile detection module 103, organic volatile analyte detection mould
Block 103 is connect with control assembly 200, smoke machine ontology 300 respectively；
Above-mentioned, organic volatile detection module 103 detects the concentration values of the organic volatile around smoke machine main body, and will
The concentration values of organic volatile are sent to control module.
Specifically, the concentration VOC that organic volatile detection module 103 is configured to measure many volatile organic matters is passed
Sensor.
The detection type for increasing the detection pernicious gas of kitchen ventilator by being provided with organic volatile detection module.
Embodiment 4.
A kind of smoke machine with multiple independent harmful substance detection mould groups, other structures and embodiment 1-3 any one phase
Together, the difference is that, as shown in figure 4, detection mould group 100 is additionally provided with particulate matter detection module 104, particulate matter detects mould
Block is connect with control assembly 200, smoke machine ontology 300 respectively；Particulate matter detection module 104 detects the particulate matter around smoke machine main body
Concentration value, and the concentration value of particulate matter is sent to control module.
Specifically, particulate matter detection module 104 is set as PM10 sensor, PM2.5 sensor, PM1 sensor, PM0.1
Any one or more in sensor or particulate matter sensors less than 0.1 μm.
The concentration for understanding the particulate matter in kitchen in time is allowed users to by being provided with particulate matter detection module, is improved
The air quality in kitchen.
Embodiment 5.
A kind of smoke machine with multiple independent harmful substance detection mould groups, other structures and embodiment 1-4 any one phase
Together, the difference is that, computation model is lienar for computing module, NONLINEAR CALCULATION module, exponential type computing module, power type meter
It calculates module, logarithmic computing module, neural network computing module, machine learning computing module or deep learning and calculates mould
Block.
Embodiment 6.
A kind of smoke machine with multiple independent harmful substance detection mould groups, other structures and embodiment 1-5 any one phase
Together, the difference is that, the calculation formula of computation model is formula (I),
CPolycyclic aromatic hydrocarbon+ 475.1 formula (I) of+0.0033 κ λ of+0.0005 λ of=0.05 κ,
Wherein CPolycyclic aromatic hydrocarbonFor the multiring aromatic hydrocarbon gas total concentration in cooking zone, κ is the output data of temperature sensing module, λ
For the output data of vision capture detection module 102.
When κ ∈ (0 DEG C, 200 DEG C), (0,30000) λ ∈, C(2-3)=70%CPolycyclic aromatic hydrocarbon,C(4)=20%CPolycyclic aromatic hydrocarbon,C(5-6)
=10%CPolycyclic aromatic hydrocarbon。
When κ ∈ (200 DEG C, 240 DEG C), (30000,50000) λ ∈, C(2-3)=60%CPolycyclic aromatic hydrocarbon,C(4)=25%CPolycyclic aromatic hydrocarbon,
C(5-6)=15%CPolycyclic aromatic hydrocarbon。
Wherein C(2-3)For the concentration of two ring polycyclic aromatic hydrocarbons and three ring polycyclic aromatic hydrocarbons, C(4)For the concentration of four ring polycyclic aromatic hydrocarbons,
C(5-6)For the concentration of five ring polycyclic aromatic hydrocarbons and six ring polycyclic aromatic hydrocarbons.
The kitchen ventilator of the present embodiment can be calculated by the oil smoke size of detection kitchen tools temperature and cooking zone
The polycyclic aromatic hydrocarbon concentration of current cooking zone, can calculate two ring polycyclic aromatic hydrocarbons, three ring polycyclic aromatic hydrocarbons, four in current environment
The concentration of ring polycyclic aromatic hydrocarbon, five ring polycyclic aromatic hydrocarbons and six ring polycyclic aromatic hydrocarbons.
Embodiment 7.
A kind of smoke machine with multiple independent harmful substance detection mould groups, other structures and embodiment 1-6 any one phase
Together, the difference is that, the calculation formula of computation model is formula (II),
CPolycyclic aromatic hydrocarbon=0.05 κ0.98+0.0005λ1.05+ 469.5 formula of+0.0033 κ λ (II),
Wherein CPolycyclic aromatic hydrocarbonFor the multiring aromatic hydrocarbon gas total concentration in cooking zone, κ is the output data of temperature sensing module, λ
For the output data of vision capture detection module 102.
When κ ∈ (0 DEG C, 200 DEG C), (0,30000) λ ∈, C(2-3)=70%CPolycyclic aromatic hydrocarbon,C(4)=20%CPolycyclic aromatic hydrocarbon,C(5-6)
=10%CPolycyclic aromatic hydrocarbon。
When κ ∈ (200 DEG C, 240 DEG C), (30000,50000) λ ∈, C(2-3)=60%CPolycyclic aromatic hydrocarbon,C(4)=25%CPolycyclic aromatic hydrocarbon,
C(5-6)=15%CPolycyclic aromatic hydrocarbon。
Wherein C(2-3)For the concentration of two ring polycyclic aromatic hydrocarbons and three ring polycyclic aromatic hydrocarbons, C(4)For the concentration of four ring polycyclic aromatic hydrocarbons,
C(5-6)For the concentration of five ring polycyclic aromatic hydrocarbons and six ring polycyclic aromatic hydrocarbons.
The kitchen ventilator of the present embodiment can be calculated by the oil smoke size of detection kitchen tools temperature and cooking zone
The polycyclic aromatic hydrocarbon concentration of current cooking zone, can calculate two ring polycyclic aromatic hydrocarbons, three ring polycyclic aromatic hydrocarbons, four in current environment
The concentration of ring polycyclic aromatic hydrocarbon, five ring polycyclic aromatic hydrocarbons and six ring polycyclic aromatic hydrocarbons.
Embodiment 8.
A kind of smoke machine with multiple independent harmful substance detection mould groups, other structures and embodiment 1-7 any one phase
Together, the difference is that, computation model carries out Environmental Health grade classification according to polycyclic aromatic hydrocarbon concentration；
Be averaged limiting concentration and polycyclic aromatic hydrocarbon concentrations versus of benzo [a] pyrene of national regulations carries out environmental rating division；
Work as CPolycyclic aromatic hydrocarbon< CBenzo [a] pyreneWhen, it is determined as Health Category, works as CPolycyclic aromatic hydrocarbon≥CBenzo [a] pyreneWhen, it is determined as unhealthy grade；
Wherein CBenzo [a] pyreneIt is averaged limiting concentration, and C for benzo [a] pyrene of national regulationsBenzo [a] pyrene=1ng/m3。
Benzo [a] pyrene of polycyclic aromatic hydrocarbon concentration and national regulations be averaged limiting concentration be divided by carry out Environmental Health grade draw
Point, such as formula (III):
As 0≤ε≤0.5, then it is determined as Health Category, as 0 < ε≤1, is then determined as good level, as ε > 1,
Then it is determined as unhealthy grade.
Wherein CBenzo [a] pyreneIt is averaged limiting concentration, and C for benzo [a] pyrene of national regulationsBenzo [a] pyrene=1ng/m3。
The present embodiment carries out Environmental Health grade classification according to polycyclic aromatic hydrocarbon concentration, can more intuitively go to judge current
The air quality of cooking environments.
Embodiment 9.
A kind of smoke machine with multiple independent harmful substance detection mould groups, other structures and embodiment 1-8 any one phase
Together, the difference is that, Environmental Health grade classification weighted with the total yield virulence factor of polycyclic aromatic hydrocarbon concentration after result into
Row Environmental Health grade classification；
By formula (IV) count polycyclic aromatic hydrocarbon concentration total yield virulence factor:
Wherein BEQ is the total yield virulence factor of polycyclic aromatic hydrocarbon, and μ is the label of polycyclic aromatic hydrocarbon type, 1≤μ≤ξ and μ and ξ
For natural number, beqμFor the equivalent toxic concentration of the content of μ kind polycyclic aromatic hydrocarbon, beqμIt is counted by formula (V),
beqμ=Cμ*TEFμFormula (V),
CμFor the concentration of the content of μ kind polycyclic aromatic hydrocarbon, TEFμFor the corresponding equivalent virulence factor of μ kind polycyclic aromatic hydrocarbon；No
Equivalent virulence factor with polycyclic aromatic hydrocarbon is as shown in table 1:
Table 1 is the equivalent virulence factor of various polycyclic aromatic hydrocarbons
This embodiment introduces the equivalent virulence factors of different polycyclic aromatic hydrocarbons, because for the toxicity of different polycyclic aromatic hydrocarbons
Difference, thus harm to the human body is also different.
Embodiment 10.
A kind of smoke machine with multiple independent harmful substance detection mould groups, other structures and embodiment 1-9 any one phase
Together, the difference is that, benzo [a] pyrene of polycyclic aromatic hydrocarbon concentration and total yield virulence factor product and national regulations averagely limits
Concentrations versus carries out environmental rating division；
Work as BEQ*CPolycyclic aromatic hydrocarbon< CBenzo [a] pyreneWhen, it is determined as Health Category, works as BEQ*CPolycyclic aromatic hydrocarbon≥CBenzo [a] pyreneWhen, judgement then determines
For unhealthy grade；Or
Benzo [a] pyrene of the polycyclic aromatic hydrocarbon concentration and total yield virulence factor product and national regulations limiting concentration that is averaged is divided by
Environmental Health grade classification is carried out, such as formula (III):
As 0≤δ≤0.5, then it is determined as Health Category, as 0 < δ≤1, is then determined as good level, as δ > 1,
Then it is determined as unhealthy grade.
The present embodiment carries out Environmental Health grade classification according to polycyclic aromatic hydrocarbon concentration, can more intuitively go to judge current
The air quality of cooking environments.
Embodiment 11.
A kind of smoke machine with multiple independent harmful substance detection mould groups, other structures and embodiment 1-10 any one phase
Together, the difference is that, as shown in figure 5, control assembly 200 is provided with kitchen ventilator speed adjusting module 201, firepower adjustment module
202 and reminding module 203；The output of the output end, organic volatile detection module 103 of reminding module 203 and computing module
The connection of the output end of end and particulate matter detection module 104, reminding module 203 receive the calculated result, organic of computing module
Display alarm is carried out after the testing result of volatile matter detection module 103 and the testing result of particulate matter detection module 104；
Specifically, the pumping with the output end of computation model, kitchen ventilator ontology 300 respectively of kitchen ventilator speed adjusting module 201
The connection of wind component, the output end output signal that kitchen ventilator speed adjusting module 201 receives computation model is unhealthy grade, then
The operating power of control enhancing or starting exhausting component；The output with temperature sensing module 101 respectively of firepower adjustment module 202
End, the output end of organic volatile detection module 103, the output end of computation model and solenoid valve connection；Firepower adjustment module
202 receive the output end of the output end of temperature sensing module 101, the output end of organic volatile detection module 103, computation model
Information, according to the information content control solenoid valve switch.
Control assembly is provided with kitchen ventilator speed adjusting module, firepower adjustment module and reminding module, so that this
Smoke machine can change and improve the air quality in kitchen.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention rather than protects to the present invention
The limitation of range, although the invention is described in detail with reference to the preferred embodiments, those skilled in the art should be managed
Solution, can with modification or equivalent replacement of the technical solution of the present invention are made, without departing from technical solution of the present invention essence and
Range.
Claims (10)
1. a kind of smoke machine with multiple independent harmful substance detection mould groups, it is characterised in that:
It is provided with detection mould group, control assembly and the smoke machine ontology more covered for detecting smoke machine ambient enviroment；The control group
Part is connect respectively with every set detection Mo Zu, and the control assembly is connect with the smoke machine ontology；
Every set detection Mo Zu detects smoke machine ambient enviroment respectively, and the detection information of ambient enviroment is sent to the control group
Part, the control assembly control the smoke machine ontology according to the detection information received.
2. the smoke machine according to claim 1 with multiple independent harmful substance detection mould groups, it is characterised in that: every set inspection
It surveys Mo Zu and is provided with temperature sensing module respectively；The temperature sensing module respectively with the control assembly, the smoke machine ontology
Connection；
Temperature sensing module induction detection smoke machine ambient enviroment obtains temperature output signal and is transmitted to the control assembly.
3. the smoke machine according to claim 2 with multiple independent harmful substance detection mould groups, it is characterised in that:
Every set detection mould group is additionally provided with the view for obtaining generating oil smoke size to the image analysis of cooking zone oil smoke and in real time
Feel and capture detection module, the vision capture detection module is connect with the control assembly, the smoke machine ontology respectively；
Cooking zone oil smoke image around the vision capture detection module acquisition smoke machine obtains oil smoke output signal and transmits
To the control module.
4. the smoke machine according to claim 3 with multiple independent harmful substance detection mould groups, it is characterised in that:
Every set detection mould group is additionally provided with organic volatile detection module, the organic volatile detection module respectively with the control
Component processed, smoke machine ontology connection；
The organic volatile detection module detects the concentration values of the organic volatile around the smoke machine main body, and will be organic
The concentration values of volatile matter are sent to the control module.
5. the smoke machine according to claim 4 with multiple independent harmful substance detection mould groups, it is characterised in that:
Every set detection mould group is additionally provided with particulate matter detection module, the particulate matter detection module respectively with the control group
Part, smoke machine ontology connection；The particulate matter detection module detects the concentration value of the particulate matter around the smoke machine main body, and
The concentration value of particulate matter is sent to the control module.
6. the smoke machine according to claim 5 with multiple independent harmful substance detection mould groups, it is characterised in that:
Every set detection mould group is additionally provided with the first polycyclic aromatic hydrocarbons (PAH) computing module, the polycyclic aromatic hydrocarbons (PAH) detection module respectively with institute
State the output end connection of the output end, the vision capture detection module of temperature sensing module；
Temperature detection information is sent to the first polycyclic aromatic hydrocarbons (PAH) computing module, institute by the output end of the temperature sensing module
The image data that stating the output end of vision capture detection module will test is sent to the first polycyclic aromatic hydrocarbons (PAH) computing module,
The first polycyclic aromatic hydrocarbons (PAH) computing module calculates the polycyclic aromatic hydrocarbon concentration in culinary cuisine region according to information is received.
7. the smoke machine according to claim 6 with multiple independent harmful substance detection mould groups, it is characterised in that:
The first polycyclic aromatic hydrocarbons (PAH) computing module is to construct to obtain about in temperature and oil smoke size and oil smoke with mathematical modeling
The computation model of the mathematical relationship of polycyclic aromatic hydrocarbon concentration in pernicious gas；Or
The computation model be lienar for computing module, NONLINEAR CALCULATION module, exponential type computing module, power type computing module,
Logarithmic computing module, neural network computing module, machine learning computing module or deep learning computing module；Or
The calculation formula of the computation model is formula (I),
CPolycyclic aromatic hydrocarbon+ 0.0033 κ λ+475.1........ formula (I) of+0.0005 λ of=0.05 κ；
Wherein CPolycyclic aromatic hydrocarbonFor the multiring aromatic hydrocarbon gas total concentration in cooking zone, κ is the output data of temperature sensing module, and λ is view
Feel the output data for capturing detection module；Or
The calculation formula of the computation model is formula (II),
CPolycyclic aromatic hydrocarbon=0.05 κ0.98+0.0005λ1.05+ 0.0033 κ λ+469.5...... formula (II)；
Wherein CPolycyclic aromatic hydrocarbonFor the multiring aromatic hydrocarbon gas total concentration in cooking zone, κ is the output data of temperature sensing module, and λ is view
Feel the output data for capturing detection module.
8. the smoke machine according to claim 7 with multiple independent harmful substance detection mould groups, it is characterised in that: the meter
It calculates model and Environmental Health grade classification is carried out according to polycyclic aromatic hydrocarbon concentration；
Be averaged limiting concentration and polycyclic aromatic hydrocarbon concentrations versus of benzo [a] pyrene of national regulations carries out environmental rating division；
Work as CPolycyclic aromatic hydrocarbon: < CBenzo [a] pyreneWhen, it is determined as Health Category, works as CPolycyclic aromatic hydrocarbon: >=CBenzo [a] pyreneWhen, it is determined as unhealthy grade；
Wherein CBenzo [a] pyreneIt is averaged limiting concentration, and C for benzo [a] pyrene of national regulationsBenzo [a] pyrene=1ng/m3。
Benzo [a] pyrene of the polycyclic aromatic hydrocarbon concentration and national regulations limiting concentration that is averaged is divided by and carries out Environmental Health grade classification, such as
Formula (III):
As 0≤ε≤0.5, then it is determined as Health Category, as 0 < ε≤1, is then determined as good level, as ε > 1, then sentences
It is set to unhealthy grade；Or
The Environmental Health grade classification carries out environment with the result after the total yield virulence factor weighting of polycyclic aromatic hydrocarbon concentration and is good for
Health grade classification；
By formula (IV) count polycyclic aromatic hydrocarbon concentration total yield virulence factor:
Wherein BEQ is the total yield virulence factor of polycyclic aromatic hydrocarbon, and μ is the label of polycyclic aromatic hydrocarbon type, and 1≤μ≤ξ and μ and ξ are certainly
So number, beqμFor the equivalent toxic concentration of the content of μ kind polycyclic aromatic hydrocarbon, beqμIt is counted by formula (V),
beqμ=Cμ*TEFμ... formula (V)；
CμFor the concentration of the content of μ kind polycyclic aromatic hydrocarbon, TEFμFor the corresponding equivalent virulence factor of μ kind polycyclic aromatic hydrocarbon；Or
Benzo [a] pyrene of polycyclic aromatic hydrocarbon concentration and total yield virulence factor product and national regulations be averaged limiting concentration comparison carry out
Environmental rating divides；
Work as BEQ*CPolycyclic aromatic hydrocarbon< CBenzo [a] pyreneWhen, it is determined as Health Category, works as BEQ*CPolycyclic aromatic hydrocarbon≥CBenzo [a] pyreneWhen, judgement is then determined as not
Health Category；Or
Benzo [a] pyrene of the polycyclic aromatic hydrocarbon concentration and total yield virulence factor product and national regulations limiting concentration that is averaged is divided by progress
Environmental Health grade classification, such as formula (III):
As 0≤δ≤0.5, then it is determined as Health Category, as 0 < δ≤1, is then determined as good level, as δ > 1, then sentences
It is set to unhealthy grade.
9. the smoke machine according to claim 8 with multiple independent harmful substance detection mould groups, it is characterised in that:
The control assembly is provided with kitchen ventilator speed adjusting module, firepower adjustment module and reminding module；The prompting mould
The output end and the particulate matter detection module of the output end of block and the computing module, the organic volatile detection module
Output end connection, the reminding module receives the calculated result of the computing module, the organic volatile detection module
Testing result and the particulate matter detection module testing result after carry out display alarm；
The kitchen ventilator speed adjusting module exhausting component with the output end of the computation model, the kitchen ventilator ontology respectively
Connection, the output end output signal that the kitchen ventilator speed adjusting module receives the computation model is unhealthy grade, then
Control enhancing or the operating power for starting the exhausting component；The firepower adjustment module respectively with the temperature sensing module
Output end, the output end of organic volatile detection module, the output end of the computation model and solenoid valve connection；The firepower
Adjustment module receives the output end of the temperature sensing module, the output end of organic volatile detection module, the computation model
Output end information, the switch of the solenoid valve is controlled according to the information content.
10. the smoke machine according to claim 9 with multiple independent harmful substance detection mould groups, it is characterised in that:
The temperature sensing module is connect with the wired or wireless signal of the control assembly, and the temperature sensing module is set as non-
Intrusive temperature sensor or intrusive temperature sensor；
The non-invasive temperature sensor be set as dot matrix infrared temperature sensor, array temperature sensor or heat at
As any one or more in temperature sensor；
The vision capture detection module is set as camera,
The organic volatile detection module is configured to measure the concentration VOC sensor of many volatile organic matters,
The particulate matter detection module is set as PM10 sensor, PM2.5 sensor, PM1 sensor, PM0.1 sensor or small
In 0.1 μm of particulate matter sensors any one or more；
The intrusive mood temperature sensor is set as thermocouple temperature sensor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811630888.1A CN109813713B (en) | 2018-12-29 | 2018-12-29 | Smoke machine with multiple independent harmful substance detection modules |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811630888.1A CN109813713B (en) | 2018-12-29 | 2018-12-29 | Smoke machine with multiple independent harmful substance detection modules |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109813713A true CN109813713A (en) | 2019-05-28 |
| CN109813713B CN109813713B (en) | 2021-08-31 |
Family
ID=66601511
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811630888.1A Active CN109813713B (en) | 2018-12-29 | 2018-12-29 | Smoke machine with multiple independent harmful substance detection modules |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109813713B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111443164A (en) * | 2020-03-19 | 2020-07-24 | 浙江大学宁波理工学院 | Gas simulation experiment device based on machine vision |
| CN111750462A (en) * | 2020-06-04 | 2020-10-09 | 华帝股份有限公司 | Control method of range hood air conditioner and range hood air conditioner |
| CN112255141A (en) * | 2020-10-26 | 2021-01-22 | 光谷技术股份公司 | Thermal imaging gas monitoring system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN204880283U (en) * | 2015-06-03 | 2015-12-16 | 中山市士林电器有限公司 | Intelligence smoke ventilator |
| CN205079296U (en) * | 2015-10-16 | 2016-03-09 | 沈阳英林特电器有限公司 | Range hood |
| CN109028223A (en) * | 2018-09-29 | 2018-12-18 | 佛山市云米电器科技有限公司 | Have the kitchen ventilator and oil smoke concentration detection method of gesture control vision-based detection function |
-
2018
- 2018-12-29 CN CN201811630888.1A patent/CN109813713B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN204880283U (en) * | 2015-06-03 | 2015-12-16 | 中山市士林电器有限公司 | Intelligence smoke ventilator |
| CN205079296U (en) * | 2015-10-16 | 2016-03-09 | 沈阳英林特电器有限公司 | Range hood |
| CN109028223A (en) * | 2018-09-29 | 2018-12-18 | 佛山市云米电器科技有限公司 | Have the kitchen ventilator and oil smoke concentration detection method of gesture control vision-based detection function |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111443164A (en) * | 2020-03-19 | 2020-07-24 | 浙江大学宁波理工学院 | Gas simulation experiment device based on machine vision |
| CN111443164B (en) * | 2020-03-19 | 2022-08-23 | 浙江大学宁波理工学院 | Gas simulation experiment device based on machine vision |
| CN111750462A (en) * | 2020-06-04 | 2020-10-09 | 华帝股份有限公司 | Control method of range hood air conditioner and range hood air conditioner |
| CN111750462B (en) * | 2020-06-04 | 2021-12-21 | 华帝股份有限公司 | Control method of range hood air conditioner and range hood air conditioner |
| CN112255141A (en) * | 2020-10-26 | 2021-01-22 | 光谷技术股份公司 | Thermal imaging gas monitoring system |
| CN112255141B (en) * | 2020-10-26 | 2021-05-11 | 光谷技术有限公司 | Thermal imaging gas monitoring system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109813713B (en) | 2021-08-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109813713A (en) | A kind of smoke machine with multiple independent harmful substance detection mould groups | |
| CN109655585A (en) | A kind of kitchen ventilator that can identify kitchen air quality | |
| CN209623754U (en) | A kind of smoke machine changeable type polycyclic aromatic hydrocarbon detection device | |
| CN112146761A (en) | Human body temperature measurement compensation method based on machine learning | |
| CN109884049A (en) | A kind of harmful substance detection device being able to detect kitchen fume | |
| CN109579096A (en) | A kind of kitchen ventilator with temperature sensor | |
| CN109882899B (en) | Range hood controlled according to working environment | |
| CN209655389U (en) | It is a kind of that the automatic cigarette stove system that food data bank compares can be sought with health | |
| CN109654559A (en) | A kind of healthy cooking system that can identify steam and oil smoke | |
| CN109657640A (en) | It is a kind of can according to use food materials carry out Health Category division kitchen ventilator | |
| CN109631111A (en) | It is a kind of that the automatic cigarette stove system that food data bank compares can be sought with health | |
| CN109654561B (en) | Infrared temperature and vision cooperative detection cooking system | |
| CN209655388U (en) | It is a kind of can according to use oils carry out kitchen air quality assessment kitchen ventilator | |
| CN109798565A (en) | A kind of oil absorption system with harmful substance function in identification oil smoke | |
| CN109669007A (en) | A kind of equipment of the online food detection of household non-invasive | |
| CN109654562A (en) | A kind of and mobile united kitchen ventilator of photographing device | |
| CN109632796A (en) | A kind of harmful substance detection device and its application with infrared temperature sensor | |
| CN109631118A (en) | A kind of kitchen ventilator that can identify pernicious gas in oil smoke | |
| CN109655586A (en) | A kind of oil smoke volatile organic matter detecting and controlling system and its application | |
| CN109654565A (en) | A kind of kitchen ventilator with thermal imaging device | |
| CN109654560A (en) | It is a kind of can according to use oils carry out kitchen air quality assessment kitchen ventilator | |
| CN109654563A (en) | A kind of cooking system with a variety of detection functions synergistic effect | |
| CN109813841A (en) | A kind of kitchen fume formula polycyclic aromatic hydrocarbon detection device | |
| CN109654545A (en) | It can be according to the stove and firepower control judgment method of cooking environments air quality control | |
| CN210720309U (en) | Oil smoke volatile organic compounds detects control system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |