CN209013288U - A kind of kitchen ventilator having filtering functions vision-based detection module - Google Patents
A kind of kitchen ventilator having filtering functions vision-based detection module Download PDFInfo
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Abstract
A kind of kitchen ventilator having filtering functions vision-based detection module, is provided with smoke machine main body and the vision-based detection module for detecting oil smoke size, vision-based detection module is electrically connected with smoke machine main body；The vision-based detection module is provided with the optical filtering portion and vision-based detection portion of filtering visible light, and optical filtering portion is assemblied in vision-based detection portion, and vision-based detection portion is electrically connected with smoke machine main body, the corresponding cooking stove region of vision-based detection module direction.Vision-based detection module can filter visible light while light compensating apparatus being used to carry out light filling, nature light source and stroboscopic light source bring interference problem can be eliminated, also there is preferable effect to interference such as the shadows, while not turning on light under the conditions of the poor lightings such as cloudy day and can also detect smog size.A kind of oil smoke concentration detection method, vision-based detection module is handled based on the initial pictures for the before and after frames that imaging device acquires, initial pictures are grayscale image, while can realize the non-contact real-time detection of oil smoke concentration, have many advantages, such as high accuracy and real-time.
Description
Technical field
The utility model relates to kitchen ventilator field, in particular to a kind of kitchen ventilator for having filtering functions vision-based detection module.
Background technique
The vision system of kitchen ventilator needs stabilized light source, and natural light is mainly visible light because the fluctuation of visible light compared with
Greatly, in the different environment such as cloudy day, evening, it be easy to cause vision system applicability weak, in the prior art using general
Logical sight lamp is lighting system, will also result in the brightness that vision system collects between the before and after frames of image and has differences,
And be easy to bring some external interferences into, it in turn results in Smoke Detection or vision system other function generates erroneous judgement.
In the prior art, for the detection of kitchen fume concentration, mainly there are infrared projection method and physical measure.Infrared throwing
It penetrates method and infrared light is emitted by one end, the other end is received, and judges that oil smoke concentration is big by the infrared luminous intensity received
It is small.But there is uncertainty since oil smoke drifts, can also there be manpower in practice and the interference such as block, therefore, it need to be in different location
Multiple infrared transmitters are installed just and can guarantee relatively accurate, the higher cost of oil smoke detection, installation site are required also higher.Object
The principle that detection method is similar to smoke alarm is managed, oil smoke concentration, but this method are judged by floating particle number in detection air
There are two disadvantages can not achieve remote detection first is that detection must just can be carried out when oil smoke touches alarm；Second is that working as
Float in air when being oil smoke but water mist can not detect.
Therefore in view of the shortcomings of the prior art, providing a kind of kitchen ventilator and oil smoke concentration for having filtering functions vision-based detection module
Detection method is very necessary to solve prior art deficiency.
Utility model content
The purpose of this utility model is that providing a kind of tool filtering functions vision inspection in place of avoiding the deficiencies in the prior art
Survey the kitchen ventilator of module.The kitchen ventilator of the tool filtering functions vision-based detection module has high anti-jamming capacity.
The above-mentioned purpose of the utility model is realized by following technical measures:
A kind of kitchen ventilator having filtering functions vision-based detection module is provided, smoke machine main body and big for detecting oil smoke is provided with
Small vision-based detection module, vision-based detection module are electrically connected with smoke machine main body.
The vision-based detection module is provided with the optical filtering portion and vision-based detection portion of filtering visible light, and optical filtering portion is assemblied in vision
Test section, vision-based detection portion are electrically connected with smoke machine main body, the corresponding cooking stove region of vision-based detection module direction.
The utility model tool filtering functions vision-based detection module kitchen ventilator, be additionally provided with for correspond to cooking stove region into
The light compensating apparatus of row light filling, light compensating apparatus are electrically connected in smoke machine main body, the corresponding cooking stove region of light compensating apparatus direction.
Preferably, above-mentioned light compensating apparatus is infrared light compensating apparatus.
The vision-based detection module is assemblied in smoke machine main body；Or
The vision-based detection module is assemblied in cooking stove；Or
The vision-based detection module is assemblied in wall.
The light compensating apparatus is assemblied in smoke machine main body；Or
The light compensating apparatus is assemblied in cooking stove；Or
The light compensating apparatus is assemblied in wall.
Preferably, above-mentioned optical filtering portion is visible filter.
Preferably, above-mentioned light compensating apparatus is the infrared lamp group that wavelength is 940nm.
Preferably, above-mentioned light compensating apparatus is set as infrared lamp group.
Preferably, above-mentioned vision-based detection module is handled and is serialized by the initial pictures acquired, is passed sequentially through
The initial pictures of frame and the initial pictures of previous frame are handled afterwards, and obtain the moment locating for each rear frame initial pictures works as forward galley
Oil smoke concentration.
Preferably, above-mentioned infrared lamp group is provided with multiple groups.
Preferably, above-mentioned vision-based detection portion is provided with camera lens, the expansion bracket for focal length to be arranged, mounting seat, photosensitive core
Piece and pcb board, for camera lens fixing assembling in expansion bracket, expansion bracket is assemblied in mounting seat, and sensitive chip is welded in pcb board, installation
Pedestal is assemblied in pcb board, and optical filtering portion is assemblied in the top of sensitive chip, from top to bottom successively camera lens, expansion bracket, mounting seat,
Optical filtering portion, sensitive chip and pcb board.
Another preferred, above-mentioned vision-based detection portion is provided with camera lens, the expansion bracket for focal length to be arranged, mounting seat, sense
Optical chip and pcb board, optical filtering portion are assemblied in the top of camera lens, and for camera lens fixing assembling in expansion bracket, expansion bracket is assemblied in installation bottom
Seat, sensitive chip is welded in pcb board, and mounting seat is assemblied in pcb board, from top to bottom successively optical filtering portion, camera lens, expansion bracket, peace
Fill pedestal, sensitive chip and pcb board.
A kind of kitchen ventilator of tool filtering functions vision-based detection module of the utility model, is provided with smoke machine main body and for examining
The vision-based detection module of oil smoke size is surveyed, vision-based detection module is electrically connected with smoke machine main body；The vision-based detection module is provided with
The optical filtering portion and vision-based detection portion of visible light are filtered, optical filtering portion is assemblied in vision-based detection portion, vision-based detection portion and smoke machine main body electricity
Connection, the corresponding cooking stove region of vision-based detection module direction.The vision-based detection module of the utility model can filter visible light simultaneously
Light filling is carried out using light compensating apparatus, nature light source and stroboscopic light source bring interference problem can be eliminated, it is dry to shadow etc.
Disturbing also has preferable effect, while not turning on light under the conditions of the poor lightings such as cloudy day and can also detect smog size.
Detailed description of the invention
The utility model is further described using attached drawing, but the content in attached drawing is not constituted to the utility model
Any restrictions.
Fig. 1 is a kind of schematic cross-section of the kitchen ventilator of tool filtering functions vision-based detection module of embodiment 1.
Fig. 2 is vision-based detection module decomposition diagram.
The assembly that Fig. 3 is Fig. 2 is illustrated.
Fig. 4 is a kind of schematic diagram of the kitchen ventilator of tool filtering functions vision-based detection module of embodiment 2.
Fig. 5 is the vision-based detection module decomposition diagram of embodiment 4.
Fig. 6 is the oil smoke region of the method segmentation of the utility model and the schematic diagram of interference region.
Fig. 1 includes into Fig. 6:
Vision-based detection module 1,
Optical filtering portion 11,
Vision-based detection portion 12,
Camera lens 121, expansion bracket 122, mounting seat 123, sensitive chip 124, pcb board 125,
Light compensating apparatus 2,
Smoke machine main body 3,
Cooking stove 4.
Specific embodiment
The technical solution of the utility model is described further with the following Examples.
Embodiment 1.
A kind of kitchen ventilator having filtering functions vision-based detection module 1 is provided with smoke machine main body 3 and uses as shown in Figures 1 to 3
In the vision-based detection module 1 of detection oil smoke size, vision-based detection module 1 is electrically connected with smoke machine main body 3.
Vision-based detection module 1 is provided with the optical filtering portion 11 and vision-based detection portion 12 of filtering visible light, and optical filtering portion 11 is assemblied in
Vision-based detection portion 12, vision-based detection portion 12 are electrically connected with smoke machine main body 3, and vision-based detection module 1 is towards corresponding 4 region of cooking stove.
The light compensating apparatus of the utility model is infrared light compensating apparatus.
The kitchen ventilator of the tool filtering functions vision-based detection module 1 of the utility model is additionally provided with for corresponding to 4 region of cooking stove
The light compensating apparatus 2 of light filling is carried out, light compensating apparatus 2 is electrically connected in smoke machine main body 3, and light compensating apparatus 2 is towards correspondence 4 region of cooking stove.
The vision-based detection module 1 of the utility model is handled and is serialized by the initial pictures acquired, is successively led to
Later the initial pictures of frame and the initial pictures of previous frame are handled, and obtain the current kitchen at moment locating for each rear frame initial pictures
Room oil smoke concentration.Vision-based detection module 1 passes through internal Shot Detection kitchen fume situation simultaneously, then vision-based detection module 1
Arithmetic unit obtain current kitchen fume concentration through algorithm.
There are three types of the assembly methods of the light compensating apparatus 2 of the utility model, the first is assemblied in smoke machine main body for light compensating apparatus 2
3.Second is that light compensating apparatus 2 is assemblied in cooking stove 4.The third is assemblied in wall for light compensating apparatus 2, specific light compensating apparatus 2
Assembly method according to the actual situation depending on.The present embodiment is that light compensating apparatus 2 is assemblied in smoke machine main body 3.
The assembly method of the vision-based detection module 1 of the utility model has also three kinds, the first is the assembly of vision-based detection module 1
In smoke machine main body 3.Second is that vision-based detection module 1 is assemblied in cooking stove 4.The third is assemblied in wall for vision-based detection module 1,
The assembly method of specific vision-based detection module 1 according to the actual situation depending on.The present embodiment is that vision-based detection module 1 is assemblied in cigarette
Owner's body 3.
The optical filtering portion 11 of the utility model is visible filter.Light compensating apparatus 2 is the infrared lamp group that wavelength is 940nm.
Through a large amount of experimental verification, when the precision that the vision-based detection module 1 that wavelength is 940nm detects smog is best.
The light compensating apparatus 2 of the utility model is set as infrared lamp group.
Vision-based detection module 1 is handled and is serialized by the initial pictures acquired, and the initial of rear frame is passed sequentially through
Image and the initial pictures of previous frame are handled, and the current kitchen fume concentration at moment locating for each rear frame initial pictures is obtained.
Vision-based detection portion 12 is provided with camera lens 121, the expansion bracket 122 for focal length to be arranged, mounting seat 123, photosensitive core
Piece 124 and pcb board 125, for 121 fixing assembling of camera lens in expansion bracket 122, expansion bracket 122 is assemblied in mounting seat 123, photosensitive core
Piece 124 is welded in pcb board 125, and mounting seat 123 is assemblied in pcb board 125, and optical filtering portion 11 is assemblied in the upper of sensitive chip 124
Side, from top to bottom successively camera lens 121, expansion bracket 122, mounting seat 123, optical filtering portion 11, sensitive chip 124 and pcb board 125.
It should be noted that the sensitive chip 124 of the utility model is common knowledge, as long as realizing that light is captured and is converted to
The function of electronic signal can serve as the sensitive chip 124 of the utility model, therefore the model of sensitive chip 124 is herein no longer
It is tired to state.
The kitchen ventilator of the tool filtering functions vision-based detection module 1 is provided with smoke machine main body 3 and for detecting oil smoke size
Vision-based detection module 1, vision-based detection module 1 are electrically connected with smoke machine main body 3；It is visible that the vision-based detection module 1 is provided with filtering
The optical filtering portion 11 and vision-based detection portion 12 of light, optical filtering portion 11 are assemblied in vision-based detection portion 12, vision-based detection portion 12 and smoke machine main body 3
Electrical connection, vision-based detection module 1 is towards corresponding 4 region of cooking stove.The vision-based detection module 1 of the utility model can filter visible light
Light filling is carried out using light compensating apparatus 2 simultaneously, nature light source and stroboscopic light source bring interference problem can be eliminated, to the shadow
Smog size can also be detected by not turning on light under the conditions of waiting interference also to have the poor lightings such as preferable effect, while cloudy day.
Embodiment 2.
A kind of kitchen ventilator having filtering functions vision-based detection module 1, as shown in figure 4, other features are same as Example 1,
The difference is that: light compensating apparatus 2 is assemblied in wall, and vision-based detection module 1 is assemblied in cooking stove 4.The utility model it is infrared
Lamp group is provided with multiple groups, and the present embodiment is specially 4 groups, it should be noted that wanting, the infrared lamp group of the utility model can be set to 4
The case where group, may be set to be the arbitrary number greater than 2, specific implementation according to the actual situation depending on.
Compared with Example 1, the spirit of the assembly method for improving vision-based detection module 1 and light compensating apparatus 2 of the present embodiment
Activity.
Embodiment 3.
A kind of kitchen ventilator having filtering functions vision-based detection module 1, as shown in figure 5, other features are same as Example 1,
The difference is that: vision-based detection portion 12 is provided with camera lens 121, the expansion bracket 122 for focal length to be arranged, mounting seat 123, sense
Optical chip 124 and pcb board 125, optical filtering portion 11 are assemblied in the top of camera lens 121, and 121 fixing assembling of camera lens is stretched in expansion bracket 122
Contracting frame 122 is assemblied in mounting seat 123, and sensitive chip 124 is welded in pcb board 125, and mounting seat 123 is assemblied in pcb board 125,
Successively optical filtering portion 11, camera lens 121, expansion bracket 122, mounting seat 123, sensitive chip 124 and pcb board 125 from top to bottom.
Compared with Example 1, the optical filtering portion 11 of the present embodiment is assemblied in the top in vision-based detection portion 12, can increase optical filtering
The Installation Flexibility in portion 11.
Embodiment 4.
A kind of oil smoke concentration detection method, vision-based detection module 1 based on the initial pictures that imaging device acquires into
Row processing, initial pictures are grayscale image, and initial pictures collected are serialized, and pass sequentially through the initial pictures and previous frame of rear frame
Initial pictures handled, obtain it is each after the moment locating for frame initial pictures current kitchen fume concentration.In this way,
The oil smoke concentration situation that can also obtain the present frame moment in real time also can according to need even if monitoring each moment current frame image
Oil smoke concentration situation, provide foundation for the automatic smoking dynamics of kitchen ventilator.
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) carries out statistics of histogram respectively, is divided according to statistical result
Oil smoke concentration grade.Statistical method can be statistics of histogram, also can choose other statistical methods.
In step (1), to collected initial pictures carry out frame difference operate to obtain frame difference image be specifically: vision-based detection mould
A later frame image is made the difference with previous frame image according to the sequencing of the initial pictures received, obtains dynamic area height by block 1
Bright frame difference image.Due in the two field pictures of front and back static region be it is constant, (such as oil smoke drifts, and manpower is waved for dynamic area
Move) it is variation, so black is presented in static region after frame difference, the highlight bar of edge blurry is shown as after dynamic area frame difference
Domain, therefore the frame difference image highlighted by the available dynamic area of frame difference.
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,jRepresent frame
I-th row, the corresponding gray value of jth column pixel in difference image D, the subregion in frame difference image D where the i-th row, jth column pixel are
DSi,j；
In frame difference image, | dhi,j|=0 region is in black；|dhi,j| ≠ 0 region is in be highlighted.
After the operation of frame difference, (2) are entered step.Denoising is carried out using opening operation to frame difference image, obtains denoising image,
It is carried out especially by such as under type: etching operation first being carried out to frame difference image, to eliminate noise and the tiny spine in image, broken
Open narrow connection；Expansive working is carried out to the image after corrosion again, restores the smoke characteristics in former frame difference image.
Etching operation 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.
Image noise can be eliminated using opening operation, the separating objects at very thin point, smooth biggish object boundary, simultaneously
Also it can guarantee that the area of highlight regions in original image is basically unchanged, guarantee that the accuracy of subsequent detection is unaffected.
Step (3) carries out edge detection to denoising image, and marker motion region is as initial area-of-interest, specifically:
Using wavelet transformation, the edge for detecting frame difference image highlight regions is simultaneously marked, using the region marked as initially feeling emerging
Interesting region.
Since the gray value of image border and the gray value of neighbor pixel can generate biggish gray value gradient, according to side
This feature of edge sets a filter, traverses frame difference image with the filter.Step (3) carries out as follows:
3-1 defines a filter Y, and filter is t*t matrix, and t is odd number.Filter selects odd matrix, to ensure
Only one central point, preferably 3*3 matrix, have the characteristics that calculation amount is small.
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, the pixel institute that 1≤f≤t, 1≤g≤t, e are filter at each position
Denoising image gray value；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.
Because people is when cooking operation, hand can brandished always, can include oil smoke and manpower in the image after frame difference is complete
The interference region of the moving objects such as operation, needs the influence in exclusive PCR region, this is also before carrying out oil smoke concentration identification
Where the difficult point of the utility model patent.
But the direction of motion of oil smoke has randomness, the direction of motion of manpower, slice is relatively unambiguous and feature is different,
Numerically performance is exactly that grey value difference is larger, thus:
1) oil smoke moving region is lower than the brightness of manpower, slice moving region on the image after frame difference, so corresponding oil
The gray value mean value in cigarette district domain is also below manpower, the gray average of slice moving region；
2) grey value profile of oil smoke moving region is relatively concentrated on the image after frame difference, and the moving region of manpower, slice
The gray value on boundary is larger compared with the jump of the central area in region, so the image in the region is not smooth enough, corresponding gray value
Variance is larger.
Using the two characteristics, step (4) is specifically to carry out gray average, segment smoothing to each initial area-of-interest
Degree calculates, and obtains the corresponding gray average of each initial area-of-interest and gray scale smoothness, and satisfaction simultaneously is calculated
Gray average is less than gray threshold, gray scale smoothness is less than the initial area-of-interest of gray scale smoothness threshold as region of interest
Other initial area-of-interests are determined as interference region by domain.
Gray threshold, gray scale smoothness threshold magnitude can flexible setting according to specific needs, details are not described herein.Step
Suddenly (4) complete the identification in oil smoke region and the exclusion of interference region.
Fig. 6 illustrates the schematic diagram of the oil smoke region that a method using the utility model is divided and interference region, can
See, the method for the utility model can effectively exclude interference region.
The area-of-interest extracted in step (5) to step (4) carries out statistics of histogram respectively, is tied according to statistics
Fruit divides oil smoke concentration grade, specifically:
By all pixels in region of interest area image, according to the size of gray value, the frequency of its appearance is counted；
Further according to the concentration scale quantity that needs divide, 10 are taken as siding-to-siding block length, counts the pixel in each gray scale interval
Number is put, the corresponding oil smoke that divides of the pixel number in each gray scale interval is corresponding concentration scale.
It should be noted that the selection of siding-to-siding block length is not limited to 10, other quantity also can choose.
The criteria for classifying of oil smoke concentration can specifically be set, such as setting dense smoke, medium grade cigarette or low cigarette, specific value with
Subject to actual demand, details are not described herein.
The oil smoke concentration detection method of the utility model provides a kind of infrared projection method and physical measure of being different from
A kind of oil smoke concentration detection method.The oil smoke concentration detection method, the influence of hardly examined distance is, it can be achieved that oil smoke concentration
Non-contact real-time detection, have many advantages, such as high accuracy and real-time.
The utility model oil smoke concentration detection method, can be set in kitchen ventilator, be set by the imaging that kitchen ventilator is arranged
The image of standby acquisition kitchen ventilator stove head region, and be delivered to vision-based detection module 1, vision-based detection module 1 is by the oil smoke grade of processing
Structure is delivered to main control unit, and main control unit controls smoke machine extracting force according to the oil smoke grade of smoke machine.More accurately to kitchen
Room oil smoke carries out suction process.
Finally it should be noted that above embodiments are only to illustrate the technical solution of the utility model rather than to this is practical
The limitation of novel protected range, although being explained in detail referring to preferred embodiment to the utility model, the common skill of this field
Art personnel, which should be appreciated that, can be modified or replaced equivalently technical solutions of the utility model, practical new without departing from this
The spirit and scope of type technical solution.
Claims (11)
1. a kind of kitchen ventilator for having filtering functions vision-based detection module, it is characterised in that: it is provided with smoke machine main body and for detecting
The vision-based detection module of oil smoke size, vision-based detection module are electrically connected with smoke machine main body；
The vision-based detection module is provided with the optical filtering portion and vision-based detection portion of filtering visible light, and optical filtering portion is assemblied in vision-based detection
Portion, vision-based detection portion are electrically connected with smoke machine main body, the corresponding cooking stove region of vision-based detection module direction.
2. the kitchen ventilator of tool filtering functions vision-based detection module according to claim 1, it is characterised in that: it is additionally provided with use
The light compensating apparatus of light filling is carried out in corresponding cooking stove region, light compensating apparatus is electrically connected in smoke machine main body, and light compensating apparatus direction is corresponding
Cooking stove region.
3. the kitchen ventilator of tool filtering functions vision-based detection module according to claim 2, it is characterised in that: the light filling dress
It is set to infrared light compensating apparatus.
4. the kitchen ventilator of tool filtering functions vision-based detection module according to claim 3, it is characterised in that: the vision inspection
It surveys module and is assemblied in smoke machine main body；Or
The vision-based detection module is assemblied in cooking stove；Or
The vision-based detection module is assemblied in wall.
5. the kitchen ventilator of tool filtering functions vision-based detection module according to claim 4, it is characterised in that: the light filling dress
It sets and is assemblied in smoke machine main body；Or
The light compensating apparatus is assemblied in cooking stove；Or
The light compensating apparatus is assemblied in wall.
6. the kitchen ventilator of tool filtering functions vision-based detection module according to claim 5, it is characterised in that: the optical filtering portion
For visible filter.
7. the kitchen ventilator of tool filtering functions vision-based detection module according to claim 6, it is characterised in that: the light filling dress
It is set to the infrared lamp group that wavelength is 940nm.
8. the kitchen ventilator of tool filtering functions vision-based detection module according to claim 7, it is characterised in that: the light filling dress
It installs and is set to infrared lamp group.
9. the kitchen ventilator of tool filtering functions vision-based detection module according to claim 8, it is characterised in that: the vision inspection
Module is surveyed to be handled and be serialized by the initial pictures of acquisition, pass sequentially through rear frame initial pictures and previous frame it is initial
Image is handled, and the current kitchen fume concentration at moment locating for each rear frame initial pictures is obtained；
The infrared lamp group is provided with multiple groups.
10. the kitchen ventilator of tool filtering functions vision-based detection module according to claim 9, it is characterised in that: the vision
Test section is provided with camera lens, the expansion bracket for focal length to be arranged, mounting seat, sensitive chip and pcb board, camera lens fixing assembling in
Expansion bracket, expansion bracket are assemblied in mounting seat, and sensitive chip is welded in pcb board, and mounting seat is assemblied in pcb board, optical filtering portion dress
Top assigned in sensitive chip, from top to bottom successively camera lens, expansion bracket, mounting seat, optical filtering portion, sensitive chip and pcb board.
11. the kitchen ventilator of tool filtering functions vision-based detection module according to claim 9, it is characterised in that: the vision
Test section is provided with camera lens, the expansion bracket for focal length to be arranged, mounting seat, sensitive chip and pcb board, optical filtering portion and is assemblied in mirror
The top of head, for camera lens fixing assembling in expansion bracket, expansion bracket is assemblied in mounting seat, and sensitive chip is welded in pcb board, installs bottom
Seat is assemblied in pcb board, from top to bottom successively optical filtering portion, camera lens, expansion bracket, mounting seat, sensitive chip and pcb board.
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| CN109084350A (en) * | 2018-09-29 | 2018-12-25 | 佛山市云米电器科技有限公司 | A kind of kitchen ventilator and oil smoke concentration detection method having filtering functions vision-based detection module |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109084350A (en) * | 2018-09-29 | 2018-12-25 | 佛山市云米电器科技有限公司 | A kind of kitchen ventilator and oil smoke concentration detection method having filtering functions vision-based detection module |
| CN109084350B (en) * | 2018-09-29 | 2024-01-09 | 佛山市云米电器科技有限公司 | Range hood with optical filtering function visual detection module and range hood concentration detection method |
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