CN106930055A - Washing machine and for washing machine foam volume detection method and device - Google Patents
Washing machine and for washing machine foam volume detection method and device Download PDFInfo
- Publication number
- CN106930055A CN106930055A CN201710057048.XA CN201710057048A CN106930055A CN 106930055 A CN106930055 A CN 106930055A CN 201710057048 A CN201710057048 A CN 201710057048A CN 106930055 A CN106930055 A CN 106930055A
- Authority
- CN
- China
- Prior art keywords
- foam volume
- washing machine
- foam
- interior bucket
- neural network
- 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.)
- Pending
Links
Classifications
-
- D—TEXTILES; PAPER
- D06—TREATMENT OF TEXTILES OR THE LIKE; LAUNDERING; FLEXIBLE MATERIALS NOT OTHERWISE PROVIDED FOR
- D06F—LAUNDERING, DRYING, IRONING, PRESSING OR FOLDING TEXTILE ARTICLES
- D06F34/00—Details of control systems for washing machines, washer-dryers or laundry dryers
- D06F34/14—Arrangements for detecting or measuring specific parameters
- D06F34/22—Condition of the washing liquid, e.g. turbidity
-
- D—TEXTILES; PAPER
- D06—TREATMENT OF TEXTILES OR THE LIKE; LAUNDERING; FLEXIBLE MATERIALS NOT OTHERWISE PROVIDED FOR
- D06F—LAUNDERING, DRYING, IRONING, PRESSING OR FOLDING TEXTILE ARTICLES
- D06F33/00—Control of operations performed in washing machines or washer-dryers
Landscapes
- Engineering & Computer Science (AREA)
- Textile Engineering (AREA)
- Control Of Washing Machine And Dryer (AREA)
Abstract
The invention discloses a kind of washing machine and for washing machine foam volume detection method and device, the described method comprises the following steps：Obtain the present image in the interior bucket of washing machine；Obtain the neural network parameter of description foam measure feature；According to the foam volume in bucket in present image and neural network parameter acquisition.The method according to the invention, using image procossing and neutral net, can automatically and accurately obtain the foam volume in interior bucket, so that the situation intelligently according to foam volume is controlled to washing machine such that it is able to improve the clean result of washing machine.
Description
Technical field
The present invention relates to household electrical appliance technical field, the detection method of more particularly to a kind of foam volume for washing machine,
The detection means and a kind of washing machine of a kind of foam volume for washing machine.
Background technology
As the continuous improvement of people's living standard, washing machine come into huge numbers of families, become people's daily life
In it is essential as household electrical appliance.User using during laundry washer, foam volume number may turn into
Influence the key factor of laundry effect.If foam volume is very few, show that the detergent that user delivers is very few, clothing can be caused difficult
To clean, detergent is thus required supplementation with；If foam volume is excessive, show that the detergent that user delivers is excessive, can cause to wash
Wash agent to remain on clothing, thus need to strengthen rinsing.
At present, the method for conventional measurement foam volume can be water-pressure survey method, that is, be measured by foam by sensor
The change of the hydraulic pressure for causing so be inferred to foam volume number, but the water surface in laundry processes rises and falls and rocks, and
The distribution of foam is heteropical, and these can bring extreme influence to the accuracy for measuring.Therefore, how to cause that laundry is quick-witted
Judge that the foam volume of washing machine inner tub is the problem of current urgent need to resolve in energy ground.
The content of the invention
It is contemplated that at least solving one of technical problem in above-mentioned technology to a certain extent.Therefore, of the invention
One purpose is the detection method for proposing a kind of foam volume for washing machine, and the method can automatically and accurately obtain interior
Foam volume in bucket, so that the situation intelligently according to foam volume is controlled to washing machine such that it is able to improve washing machine
Clean result.
Second object of the present invention is the detection means for proposing a kind of foam volume for washing machine.
Third object of the present invention is to propose a kind of washing machine.
To reach above-mentioned purpose, first aspect present invention embodiment proposes a kind of detection of the foam volume for washing machine
Method, comprises the following steps：Obtain the present image in the interior bucket of the washing machine；Obtain the nerve net of description foam measure feature
Network parameter；The foam volume in the interior bucket is obtained according to the present image and the neural network parameter.
The detection method of the foam volume for washing machine according to embodiments of the present invention, first, obtains the interior bucket of washing machine
Interior present image, then, obtains the neural network parameter of description foam measure feature, finally, according to the present image after treatment
The foam volume in interior bucket is obtained with neural network parameter.The method utilizes image procossing and neutral net, can be automatically and accurate
Ground obtains the foam volume in interior bucket, so that the situation intelligently according to foam volume is controlled to washing machine such that it is able to improve
The clean result of washing machine.
In addition, the detection method of the foam volume for washing machine proposed according to the above embodiment of the present invention can also have
Following additional technical characteristic：
According to one embodiment of present invention, the interior bucket is obtained according to the present image and the neural network parameter
Interior foam volume, including：The present image is processed；According to the present image after treatment and the neural network parameter
Obtain the foam volume in the interior bucket.
According to one embodiment of present invention, the neural network parameter of description foam measure feature is obtained, including：Obtain described
Multiple sample images in the interior bucket of washing machine；The multiple sample image is processed；By describing foam measure feature
Neutral net to treatment after the multiple sample image be trained, with obtain it is described description foam measure feature neutral net
Parameter.
According to one embodiment of present invention, the present image or the sample image are processed, including：To institute
State at least one that present image or the sample image are carried out during illumination compensation, background elimination and color simplify.
According to one embodiment of present invention, the foam volume in the interior bucket is obtained, including：Obtain the bubble in the interior bucket
Foam volume grade residing for foam amount.
To reach above-mentioned purpose, second aspect present invention embodiment proposes a kind of detection of the foam volume for washing machine
Device, including：Photographing module, the photographing module is used to obtain the present image in the interior bucket of the washing machine；Acquisition module,
The acquisition module is used to obtain the neural network parameter of description foam measure feature；Main control module, the main control module is used for root
The foam volume in the interior bucket is obtained according to the present image and the neural network parameter.
The detection means of the foam volume for washing machine according to embodiments of the present invention, washing machine is obtained by photographing module
Interior bucket in present image, then, by acquisition module obtain description foam measure feature neural network parameter, finally, lead to
Main control module is crossed according to the foam volume in bucket in present image and neural network parameter acquisition.The device utilizes image procossing and god
Through network, the foam volume in interior bucket can be automatically and accurately obtained, so that situation intelligently according to foam volume is to washing machine
It is controlled such that it is able to improve the clean result of washing machine.
In addition, the detection means of the foam volume for washing machine proposed according to the above embodiment of the present invention can also have
Following additional technical characteristic：
According to one embodiment of present invention, the main control module is used to process the present image, and according to
Present image and the neural network parameter after treatment obtain the foam volume in the interior bucket.
According to one embodiment of present invention, the multiple in interior bucket that the photographing module is additionally operable to obtain the washing machine
Sample image, the main control module is additionally operable to process the multiple sample image, and the acquisition module is additionally operable to pass through
The sample image after the neutral net of foam measure feature is described to treatment is trained, special to obtain the description foam volume
The neural network parameter levied.
According to one embodiment of present invention, the main control module is additionally operable to the present image or the sample image
Carry out the one kind during illumination compensation, background elimination and color simplify.
According to one embodiment of present invention, the main control module is additionally operable to obtain residing for the foam volume in the interior bucket
Foam volume grade.
To reach above-mentioned purpose, third aspect present invention embodiment proposes a kind of washing machine, including above-mentioned for washing
The detection means of the foam volume of clothing machine.
Washing machine according to embodiments of the present invention, by the detection means of the above-mentioned foam volume for washing machine, utilizes
Image procossing and neutral net, can automatically and accurately obtain the foam volume in interior bucket, so as to intelligently according to foam volume
Situation is controlled to washing machine such that it is able to improve the clean result of washing machine.
Brief description of the drawings
Fig. 1 is the flow chart of the detection method of the foam volume for washing machine according to embodiments of the present invention；
Fig. 2 is the flow chart of the acquisition neural network parameter according to one specific embodiment of the present invention；
Fig. 3 is according to a flow chart for the detection method of the foam volume for washing machine of specific embodiment of the invention；
Fig. 4 is the block diagram of the detection means of the foam volume for washing machine according to embodiments of the present invention；And
Fig. 5 is the block diagram of washing machine according to embodiments of the present invention.
Specific embodiment
Embodiments of the invention are described below in detail, the example of the embodiment is shown in the drawings, wherein from start to finish
Same or similar label represents same or similar element or the element with same or like function.Below with reference to attached
It is exemplary to scheme the embodiment of description, it is intended to for explaining the present invention, and be not considered as limiting the invention.
The washing machine of the embodiment of the present invention and the detection method of foam volume for washing machine described below in conjunction with the accompanying drawings
And device.
Fig. 1 is the flow chart of the detection method of the foam volume for washing machine according to embodiments of the present invention.Such as Fig. 1 institutes
Show that the detection method of the foam volume for washing machine of the embodiment of the present invention is comprised the following steps：
S1, obtains the present image in the interior bucket of washing machine.
Specifically, during current laundry machine runs, can be by the camera head that is arranged on in washing machine drum
To being taken pictures to obtain the present image in the interior bucket in laundry processes in the interior bucket of the washing machine during current laundry.
S2, obtains the neural network parameter of description foam measure feature.
Specifically, before current laundry process, for example, can need to obtain description foam volume spy before washing machine dispatches from the factory
The neural network parameter levied.Can be by being arranged on interior bucket of the camera head in washing machine drum to the washing machine in training process
Inside taken pictures with the multiple sample images in the interior bucket for obtaining washing machine, multiple sample images are processed, and by retouching
Multiple sample images after the neutral net of foam measure feature is stated to treatment are trained, to obtain the god of description foam measure feature
Through network parameter.
Further, obtain washing machine interior bucket in multiple sample images after, can be to multiple sample images at
Multiple sample images are such as carried out at least one during illumination compensation, background elimination and color simplify by reason.Wherein, specifically how
Sample image is carried out illumination compensation can using method of the image irradiation of more conventional self adaptation compensation etc., specifically how
Method that background elimination can be eliminated using more conventional Gauss model background etc. is carried out to sample image, background is eliminated can disappear
Except content larger with foam color gap in sample image.Color simplifies can carry out color to the foam color in sample image
Simplify.
After processing multiple sample images, can be many after describing the neutral net of foam measure feature to treatment
Individual sample image is trained, and the foam volume in sample image is divided into multiple foam volume grades, to obtain description image
The neural network parameter of corresponding relation and foam volume grade between.Wherein, foam volume grade can be divided according to actual conditions,
For example, foam volume excessive (such as 2 grades of 1 grade of foam volume and foam volume), appropriate foam volume (such as 3 grades of foam volume) and foam can be divided into
Amount is very few (4 grades of 3 grades of foam volume and foam volume).
In order that those skilled in the art are better understood upon the present invention, Fig. 2 is according to a specific embodiment of the invention
Obtain the flow chart of neural network parameter.As shown in Fig. 2 the acquisition neural network parameter of the embodiment of the present invention may include：
S201, during washing machine runs, takes pictures in the interior bucket by camera head to washing machine.
S202, obtains the multiple sample images in the interior bucket of washing machine.
Multiple sample images are processed by S203.
S204, the multiple sample images after describing the neutral net of foam measure feature to treatment are trained, and will
Foam volume in multiple sample images is divided into multiple foam volume grades.
S205, obtains corresponding neural network parameter between description image and foam volume grade.
S3, according to the foam volume in bucket in present image and neural network parameter acquisition.
Specifically, present image can be processed, and is obtained according to the present image after treatment and neural network parameter
The grade residing for foam volume in the interior bucket of washing machine.
Further, after the present image in the interior bucket for obtaining washing machine, present image can be processed, such as to working as
Preceding image carries out at least one during illumination compensation, background elimination and color simplify.Wherein, specifically how present image is carried out
Illumination compensation can be using method of the image irradiation of more conventional self adaptation compensation etc..Specifically how present image is carried out
Background eliminates the method that can be eliminated using more conventional Gauss model background etc., background eliminate can eliminate in present image with
The larger content of foam color gap.Color simplifies can carry out color simplification to the foam color in present image.
After processing present image, be able to can be directly obtained according to the present image and neural network parameter after treatment
The grade residing for foam volume in the interior bucket of washing machine.
If for example, when the foam volume in the interior bucket of washing machine is in appropriate state, washing machine is carried out normally
Washing, otherwise carries out foam processing stage.Wherein, foam processing stage be directed to the situation of multiple foam volume grades and processed
, if the foam volume in laundry processes in interior bucket is very few, show that the detergent that user delivers is very few, clean result can be caused
Difference is, it is necessary to be automatically replenished detergent；If the foam volume in interior bucket in laundry processes is excessive, show the washing of user's input
Agent is excessive, detergent can be caused to remain, it is necessary to obtain the foam volume in interior bucket automatically, and carried out at froth breaking to foam volume automatically
Reason, while increasing the number of times of rinsing.
It should be noted that when foam volume is excessive, the intensity of foam treatment, foam can be controlled according to the grade of foam volume
Amount is more, and alignment processing intensity is also bigger, if foam volume grade is 1 grade of foam volume, control process intensity is stronger, if
Foam volume grade is 2 grades of foam volume, then control process intensity is weaker.When foam volume is very few, can be according to the grade control of foam volume
The input of detergent processed, foam volume is fewer, and the detergent of input is also more.If foam volume grade is 4 grades of foam volume, control
The a small amount of detergent of system input, if foam volume grade is 5 grades of foam volume, the detergent of control input volume.
After processing foam volume, step S1-S3 can be again performed, until the foam volume in interior bucket is appropriate
State, the clean result thus, it is possible to improve washing machine.
Further, in order that those skilled in the art are better understood upon the present invention, Fig. 3 is specific according to the present invention one
The flow chart of the detection method of the foam volume for washing machine of embodiment.As shown in figure 3, the embodiment of the present invention for doing washing
The detection method of the foam volume of machine may include following steps：
S101, washing machine run during, by camera head to laundry processes in interior bucket in take pictures.
S102, obtains the present image in the interior bucket in laundry processes.
S103, is processed present image.
S104, according to the foam volume grade in bucket in the present image after treatment and neural network parameter acquisition.
S105, judges whether foam volume is appropriate.If it is, performing step S106；If not, performing step S107.
S106, Normal Wash.
S107, judges whether foam volume is excessive.If it is, foam volume is excessive, step S108 is performed；If it is not, then bubble
Foam amount is very few, performs step S109.
S108, carries out defoaming treatment, and increase the number of times of rinsing.
S109, puts into detergent.
In sum, the detection method of the foam volume for washing machine according to embodiments of the present invention, first, obtains laundry
Present image in the interior bucket of machine, then, obtains the neural network parameter of description foam measure feature, finally, according to present image
The foam volume in interior bucket is obtained with neural network parameter.The method utilizes image procossing and neutral net, can be automatically and accurate
Ground obtains the foam volume in interior bucket, so that the situation intelligently according to foam volume is controlled to washing machine such that it is able to improve
The clean result of washing machine.
Fig. 4 is the block diagram of the detection means of the foam volume for washing machine according to embodiments of the present invention.Such as Fig. 4
It is shown, the detection means of the foam volume for washing machine of the embodiment of the present invention, including：Photographing module 10, the and of acquisition module 20
Main control module 30.
Wherein, photographing module 10 is used to obtain the present image in the interior bucket of washing machine.At to present image
Reason.Acquisition module 20 is used to obtain the neural network parameter of description foam measure feature.Main control module 30 is used for according to present image
The foam volume in interior bucket is obtained with neural network parameter.
Specifically, during current laundry machine runs, can be by the photographing module that is arranged on in washing machine drum
Taken pictures in 10 pairs of washing machine inner tubs of current laundry machine with the present image in the interior bucket for obtaining washing machine.
Further, after the present image in the interior bucket in obtaining laundry processes by photographing module 10, can be by master
Control module 30 carries out at least one during illumination compensation, background elimination and color simplify to present image.Wherein, it is specifically how right
Present image carries out illumination compensation can be using method of the image irradiation of more conventional self adaptation compensation etc..It is specific how right
Present image carries out method that background elimination can be eliminated using more conventional Gauss model background etc., and background is eliminated and can eliminated
The content larger with foam color gap in present image.Color simplifies can carry out color letter to the foam color in present image
Change.
In one embodiment of the invention, photographing module 10 can also be used to obtain the multiple samples in the interior bucket of washing machine
Image, main control module 30 can also be used to process multiple sample images, and acquisition module 20 is additionally operable to by describing foam volume
The neutral net of feature to treatment after multiple sample images be trained, with obtain description foam measure feature neutral net join
Number.
Specifically, before current laundry process, for example, can need to obtain description foam volume spy before washing machine dispatches from the factory
The neural network parameter levied.Can be by the photographing module 10 that is arranged on in washing machine drum to the washing machine in training process
Taken pictures in interior bucket with the multiple sample images in the interior bucket for obtaining washing machine.
Further, after the sample image in the interior bucket in obtaining multiple laundry processes by photographing module 10, can lead to
Cross at least one that main control module 30 is carried out during illumination compensation, background elimination and color simplify to sample image.Wherein, specifically such as
What carries out method that illumination compensation can be compensated using the image irradiation of more conventional self adaptation etc. to sample image, specifically such as
What carries out method that background elimination can be eliminated using more conventional Gauss model background etc. to sample image, and background is eliminated can
The content larger with foam color gap in elimination sample image.Color simplifies can carry out face to the foam color in sample image
Color simplifies.
After being processed by the multiple sample images of main control module 30 pairs, can be by describing the nerve net of foam measure feature
Network to treatment after multiple sample images be trained, and the foam volume in sample image is divided into multiple foam volume grades,
Corresponding neural network parameter between description image and foam volume grade is obtained by acquisition module 20.Wherein, foam volume grade
Can be divided according to actual conditions, for example, foam volume excessive (such as 2 grades of 1 grade of foam volume and foam volume), foam volume can be divided into
(such as 3 grades of foam volume) and foam volume are very few (4 grades of 3 grades of foam volume and foam volume) in right amount.
Specifically, the present image in the interior bucket for obtaining washing machine by photographing module 10, by main control module 30 pairs
Present image is processed, and after acquisition module 20 obtains the neural network parameter of description foam volume, by main control module
30 according to residing for present image and neural network parameter after treatment can directly obtain the foam volume in the interior bucket of washing machine etc.
Level.
If for example, when the foam volume in the interior bucket of washing machine is in appropriate state, washing machine is carried out normally
Washing, otherwise carries out foam processing stage.Wherein, foam processing stage be directed to the situation of multiple foam volume grades and processed
, if the foam volume in laundry processes in interior bucket is very few, show that the detergent that user delivers is very few, clean result can be caused
Difference is, it is necessary to be automatically replenished detergent；If the foam volume in interior bucket in laundry processes is excessive, show the washing that user delivers
Agent is excessive, detergent can be caused to remain, it is necessary to obtain the foam volume in interior bucket automatically, and process foam volume automatically, together
The number of times of Shi Zengjia rinsings.
It should be noted that when foam volume is excessive, the intensity of foam treatment, foam can be controlled according to the grade of foam volume
Amount is more, and alignment processing intensity is also bigger, if foam volume grade is 1 grade of foam volume, control process intensity is stronger, if
Foam volume grade is 2 grades of foam volume, then control process intensity is weaker.When foam volume is very few, can be according to the grade control of foam volume
The input of detergent processed, foam volume is fewer, and the detergent of input is also more.If foam volume grade is 4 grades of foam volume, control
System increases a small amount of detergent, if foam volume grade is 5 grades of foam volume, control increases the detergent of volume.
After processing foam volume, the current figure in the interior bucket of washing machine can be obtained again by photographing module 10
Picture, is processed present image by main control module 30, and the neutral net of description foam volume is obtained by acquisition module 20
Parameter, until the foam volume in the interior bucket of washing machine is in appropriate state, the clean result thus, it is possible to improve washing machine.
The detection means of the foam volume for washing machine according to embodiments of the present invention, washing machine is obtained by photographing module
Interior bucket in present image, and present image is processed by image processing module, then, obtained by acquisition module
The neural network parameter of foam measure feature is described, finally, is obtained according to present image and neural network parameter by main control module
Foam volume in interior bucket.The device utilizes image procossing and neutral net, can automatically and accurately obtain the foam in interior bucket
Amount, so that the situation intelligently according to foam volume is controlled to washing machine such that it is able to improve the clean result of washing machine.
Based on above-described embodiment, the invention allows for a kind of washing machine 1000.
Fig. 5 is the block diagram of washing machine according to embodiments of the present invention.As shown in figure 5, the embodiment of the present invention is washed
Clothing machine 1000 may include the above-mentioned detection means 100 for washing machine foam amount.
It should be noted that the details not disclosed in the washing machine 1000 of the embodiment of the present invention, refer to of the invention real
The details disclosed in the detection means 100 for washing machine foam amount of example is applied, specific I will not elaborate.
Washing machine according to embodiments of the present invention, by the detection means of the above-mentioned foam volume for washing machine, utilizes
Image procossing and neutral net, can automatically and accurately obtain the foam volume in interior bucket, so as to intelligently according to foam volume
Situation is controlled to washing machine such that it is able to improve the clean result of washing machine.
In the description of the invention, it is to be understood that term " " center ", " longitudinal direction ", " transverse direction ", " length ", " width ",
" thickness ", " on ", D score, "front", "rear", "left", "right", " vertical ", " level ", " top ", " bottom ", " interior ", " outward ", " up time
The orientation or position relationship of the instruction such as pin ", " counterclockwise ", " axial direction ", " radial direction ", " circumference " be based on orientation shown in the drawings or
Position relationship, is for only for ease of the description present invention and simplifies description, must rather than the device or element for indicating or imply meaning
With specific orientation, with specific azimuth configuration and operation, therefore must be not considered as limiting the invention.
Additionally, term " first ", " second " are only used for describing purpose, and it is not intended that indicating or implying relative importance
Or the implicit quantity for indicating indicated technical characteristic.Thus, define " first ", the feature of " second " can express or
Implicitly include one or more this feature.In the description of the invention, " multiple " is meant that two or more,
Unless otherwise expressly limited specifically.
In the present invention, unless otherwise clearly defined and limited, term " installation ", " connected ", " connection ", " fixation " etc.
Term should be interpreted broadly, for example, it may be fixedly connected, or be detachably connected, or integrally；Can be that machinery connects
Connect, or electrically connect；Can be joined directly together, it is also possible to be indirectly connected to by intermediary, can be in two elements
The connection in portion or two interaction relationships of element.For the ordinary skill in the art, can be according to specific feelings
Condition understands above-mentioned term concrete meaning in the present invention.
In the present invention, unless otherwise clearly defined and limited, fisrt feature second feature " on " or D score can be with
It is the first and second feature directly contacts, or the first and second features are by intermediary mediate contact.And, fisrt feature exists
Second feature " on ", " top " and " above " but fisrt feature are directly over second feature or oblique upper, or be merely representative of
Fisrt feature level height is higher than second feature.Fisrt feature second feature " under ", " lower section " and " below " can be
One feature is immediately below second feature or obliquely downward, or is merely representative of fisrt feature level height less than second feature.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means to combine specific features, structure, material or spy that the embodiment or example are described
Point is contained at least one embodiment of the invention or example.In this manual, to the schematic representation of above-mentioned term not
Identical embodiment or example must be directed to.And, the specific features of description, structure, material or feature can be with office
Combined in an appropriate manner in one or more embodiments or example.Additionally, in the case of not conflicting, the skill of this area
Art personnel can be tied the feature of the different embodiments or example described in this specification and different embodiments or example
Close and combine.
Although embodiments of the invention have been shown and described above, it is to be understood that above-described embodiment is example
Property, it is impossible to limitation of the present invention is interpreted as, one of ordinary skill in the art within the scope of the invention can be to above-mentioned
Embodiment is changed, changes, replacing and modification.
Claims (11)
1. the detection method of a kind of foam volume for washing machine, it is characterised in that comprise the following steps：
Obtain the present image in the interior bucket of the washing machine；
Obtain the neural network parameter of description foam measure feature；
The foam volume in the interior bucket is obtained according to the present image and the neural network parameter.
2. the detection method of the foam volume for washing machine according to claim 1, it is characterised in that according to described current
Image and the neural network parameter obtain the foam volume in the interior bucket, including：
The present image is processed；
The foam volume in the interior bucket is obtained according to the present image after treatment and the neural network parameter.
3. the detection method of the foam volume for washing machine according to claim 2, it is characterised in that obtain description foam
The neural network parameter of measure feature, including：
Obtain the multiple sample images in the interior bucket of the washing machine；
The multiple sample image is processed；
The multiple sample image after describing the neutral net of foam measure feature to treatment is trained described to obtain
The neural network parameter of foam measure feature is described.
4. the detection method of the foam volume for washing machine according to claim 3, it is characterised in that to the current figure
Picture or the sample image are processed, including：
At least one during illumination compensation, background elimination and color simplify is carried out to the present image or the sample image.
5. the detection method of the foam volume for washing machine according to any one of claim 1-4, it is characterised in that obtain
The foam volume in the interior bucket is taken, including：
Obtain the foam volume grade residing for the foam volume in the interior bucket.
6. the detection means of a kind of foam volume for washing machine, it is characterised in that including：
Photographing module, the photographing module is used to obtain the present image in the interior bucket of the washing machine；
Acquisition module, the acquisition module is used to obtain the neural network parameter of description foam measure feature；
Main control module, the main control module is used to be obtained in the interior bucket according to the present image and the neural network parameter
Foam volume.
7. the detection means of the foam volume for washing machine according to claim 6, it is characterised in that the main control module
For processing the present image, and obtained in described according to the present image after treatment and the neural network parameter
Foam volume in bucket.
8. the detection means of the foam volume for washing machine according to claim 7, it is characterised in that the photographing module
The multiple sample images in interior bucket for being additionally operable to obtain the washing machine, the main control module is additionally operable to the multiple sample graph
As being processed, the acquisition module is additionally operable to the multiple sample after the neutral net for describing foam measure feature is to treatment
This image is trained, to obtain the neural network parameter of the description foam measure feature.
9. the detection means of the foam volume for washing machine according to claim 8, it is characterised in that the main control module
It is additionally operable to carry out the present image or the sample image one kind during illumination compensation, background elimination and color simplify.
10. the detection means of the foam volume for washing machine according to any one of claim 6-9, it is characterised in that
The main control module is additionally operable to obtain the foam volume grade residing for the foam volume in the interior bucket.
11. a kind of washing machines, it is characterised in that including the bubble for washing machine according to any one of claim 6-10
The detection means of foam amount.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710057048.XA CN106930055A (en) | 2017-01-22 | 2017-01-22 | Washing machine and for washing machine foam volume detection method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710057048.XA CN106930055A (en) | 2017-01-22 | 2017-01-22 | Washing machine and for washing machine foam volume detection method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106930055A true CN106930055A (en) | 2017-07-07 |
Family
ID=59424299
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710057048.XA Pending CN106930055A (en) | 2017-01-22 | 2017-01-22 | Washing machine and for washing machine foam volume detection method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106930055A (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109371633A (en) * | 2018-11-29 | 2019-02-22 | 余姚市朗硕电器科技有限公司 | Foam spreads condition detecting system |
| CN109468798A (en) * | 2017-09-08 | 2019-03-15 | 青岛海尔滚筒洗衣机有限公司 | Debubbling method and clothes treatment device for clothes treatment device |
| CN109468808A (en) * | 2017-09-08 | 2019-03-15 | 青岛海尔滚筒洗衣机有限公司 | Debubbling method and clothes treatment device for clothes treatment device |
| CN109468797A (en) * | 2017-09-08 | 2019-03-15 | 青岛海尔滚筒洗衣机有限公司 | Debubbling method and clothes treatment device for clothes treatment device |
| CN109554882A (en) * | 2018-12-04 | 2019-04-02 | 余姚市朗硕电器科技有限公司 | Automate two-tub washing machine |
| CN110670296A (en) * | 2019-10-08 | 2020-01-10 | 重庆特斯联智慧科技股份有限公司 | Intelligent control method for smart home |
| CN110777505A (en) * | 2019-11-30 | 2020-02-11 | 蒋晓云 | Rinsing control platform of automatic washing machine |
| CN111549486A (en) * | 2019-01-24 | 2020-08-18 | 珠海格力电器股份有限公司 | Detergent dosage determining method and device, storage medium and washing machine |
| CN112575513A (en) * | 2020-12-01 | 2021-03-30 | 珠海格力电器股份有限公司 | Defoaming control method and device for washing machine |
| US11739463B2 (en) | 2020-11-04 | 2023-08-29 | Haier Us Appliance Solutions, Inc. | Method of using image recognition processes for improved operation of a laundry appliance |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103334265A (en) * | 2013-06-19 | 2013-10-02 | 松下家电研究开发（杭州）有限公司 | Intelligent washing machine, washing control method and remote monitoring method |
-
2017
- 2017-01-22 CN CN201710057048.XA patent/CN106930055A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103334265A (en) * | 2013-06-19 | 2013-10-02 | 松下家电研究开发（杭州）有限公司 | Intelligent washing machine, washing control method and remote monitoring method |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109468798A (en) * | 2017-09-08 | 2019-03-15 | 青岛海尔滚筒洗衣机有限公司 | Debubbling method and clothes treatment device for clothes treatment device |
| CN109468808A (en) * | 2017-09-08 | 2019-03-15 | 青岛海尔滚筒洗衣机有限公司 | Debubbling method and clothes treatment device for clothes treatment device |
| CN109468797A (en) * | 2017-09-08 | 2019-03-15 | 青岛海尔滚筒洗衣机有限公司 | Debubbling method and clothes treatment device for clothes treatment device |
| CN109371633A (en) * | 2018-11-29 | 2019-02-22 | 余姚市朗硕电器科技有限公司 | Foam spreads condition detecting system |
| CN109554882A (en) * | 2018-12-04 | 2019-04-02 | 余姚市朗硕电器科技有限公司 | Automate two-tub washing machine |
| CN109554882B (en) * | 2018-12-04 | 2020-11-24 | 义乌市志群拉链有限公司 | Automatic double-drum washing machine |
| CN111549486A (en) * | 2019-01-24 | 2020-08-18 | 珠海格力电器股份有限公司 | Detergent dosage determining method and device, storage medium and washing machine |
| CN111549486B (en) * | 2019-01-24 | 2021-08-31 | 珠海格力电器股份有限公司 | Detergent dosage determining method and device, storage medium and washing machine |
| CN110670296A (en) * | 2019-10-08 | 2020-01-10 | 重庆特斯联智慧科技股份有限公司 | Intelligent control method for smart home |
| CN110777505A (en) * | 2019-11-30 | 2020-02-11 | 蒋晓云 | Rinsing control platform of automatic washing machine |
| US11739463B2 (en) | 2020-11-04 | 2023-08-29 | Haier Us Appliance Solutions, Inc. | Method of using image recognition processes for improved operation of a laundry appliance |
| CN112575513A (en) * | 2020-12-01 | 2021-03-30 | 珠海格力电器股份有限公司 | Defoaming control method and device for washing machine |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106930055A (en) | Washing machine and for washing machine foam volume detection method and device | |
| CN105177922B (en) | Control method, device and the washing machine of washing machine | |
| CN102535098B (en) | There is clothes washing method and the washing machine thereof that Turbidity measurement judges | |
| CN108729114B (en) | Method for reminding of shortage of detergent and washing machine | |
| CN106854808A (en) | Washing machine and its control method of washing and device | |
| CN105177920B (en) | Washing machine and its control method | |
| WO2017004787A1 (en) | Intelligent washing machine and control method thereof | |
| CN107574625A (en) | Washing methods, device, storage device, mobile terminal and the washing machine of clothing | |
| CN105088649B (en) | The control method and device of the washing machine detected based on turbidity and electrical conductivity | |
| CN106676822A (en) | Washing machine, washing control method and device of washing machine based on clothes natures | |
| EP3268529B1 (en) | Method for operating a washing machine having an electrochemical sensor and washing machine suitable therefor | |
| CN106757976A (en) | Washing machine and its control method of washing and device based on image recognition clothing volume | |
| CN110735284A (en) | Washing machine and clothes washing control method thereof | |
| EP3268528B1 (en) | Method for operating a washing machine having an impedance sensor and washing machine suitable therefor | |
| CN105200715A (en) | Washing machine control method and device as well as washing machine | |
| CN105088650B (en) | The control method and device of the washing machine detected based on turbidity and electrical conductivity | |
| IT201900008847A1 (en) | Method and system for the preparation and execution of a laundry washing cycle | |
| DE102007041069B4 (en) | Process for the detection of fabric softener in a washing machine and this suitable program-controlled washing machine | |
| EP3495545A1 (en) | A washing method for washing machines | |
| EP2408958B1 (en) | Method for optimizing a rinsing phase in a washing machine and washing machine suitable therefor | |
| CN108998920A (en) | Washing machine, the control method of washing machine and device | |
| CN106841302A (en) | Clothes drying device and clothing humidity method of discrimination, the device for clothes drying device | |
| CN106381643A (en) | Washing machine as well as time displaying method and device thereof | |
| EP3268530B1 (en) | Method for operating a washing machine having an improved rinsing phase and washing machine suitable therefor | |
| JP3212103B2 (en) | Washing machine operation display |
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 | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20190806 Address after: 214028 No. 18 Changjiang South Road, Wuxi National High-tech Development Zone, Jiangsu Province Applicant after: Wuxi Little Swan Electric Co.,Ltd. Address before: 214028 Wuxi Changjiang Road, New District, Jiangsu, No. 18 Applicant before: WUXI LITTLE SWAN Co.,Ltd. |
|
| TA01 | Transfer of patent application right | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170707 |
|
| RJ01 | Rejection of invention patent application after publication |