CN107724492B - Feeding robot based on image processing - Google Patents
Feeding robot based on image processing Download PDFInfo
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- CN107724492B CN107724492B CN201710961267.0A CN201710961267A CN107724492B CN 107724492 B CN107724492 B CN 107724492B CN 201710961267 A CN201710961267 A CN 201710961267A CN 107724492 B CN107724492 B CN 107724492B
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- E—FIXED CONSTRUCTIONS
- E03—WATER SUPPLY; SEWERAGE
- E03D—WATER-CLOSETS OR URINALS WITH FLUSHING DEVICES; FLUSHING VALVES THEREFOR
- E03D11/00—Other component parts of water-closets, e.g. noise-reducing means in the flushing system, flushing pipes mounted in the bowl, seals for the bowl outlet, devices preventing overflow of the bowl contents; devices forming a water seal in the bowl after flushing, devices eliminating obstructions in the bowl outlet or preventing backflow of water and excrements from the waterpipe
- E03D11/02—Water-closet bowls ; Bowls with a double odour seal optionally with provisions for a good siphonic action; siphons as part of the bowl
- E03D11/11—Bowls combined with a reservoir, e.g. containing apparatus for disinfecting or for disintegrating
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- E—FIXED CONSTRUCTIONS
- E03—WATER SUPPLY; SEWERAGE
- E03D—WATER-CLOSETS OR URINALS WITH FLUSHING DEVICES; FLUSHING VALVES THEREFOR
- E03D9/00—Sanitary or other accessories for lavatories ; Devices for cleaning or disinfecting the toilet room or the toilet bowl; Devices for eliminating smells
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- E—FIXED CONSTRUCTIONS
- E03—WATER SUPPLY; SEWERAGE
- E03D—WATER-CLOSETS OR URINALS WITH FLUSHING DEVICES; FLUSHING VALVES THEREFOR
- E03D9/00—Sanitary or other accessories for lavatories ; Devices for cleaning or disinfecting the toilet room or the toilet bowl; Devices for eliminating smells
- E03D9/005—Devices adding disinfecting or deodorising agents to the bowl
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
- Y02A50/30—Against vector-borne diseases, e.g. mosquito-borne, fly-borne, tick-borne or waterborne diseases whose impact is exacerbated by climate change
Abstract
The invention relates to a feeding robot based on image processing, which comprises a storage device, a feeding device and a control device, wherein the storage device is used for placing pipeline dredging agents of different types in advance; the flushing starting device is used for automatically discharging water in the toilet water tank; the average water flow detection device is used for detecting the water flow speed of the inner space of the seat of the closestool in real time, acquiring the real-time water flow speed and calculating the average water flow speed in the washing process; a type determination means for determining the type of the pipe opener agent to be released based on the average water flow velocity; an automatic release device for releasing a determined type of a canalizing agent into the seat interior of the toilet to effect dredging of the canalizing agent in the seat interior of the toilet. The invention also relates to a material supply method based on image processing. By the invention, the intelligent supply of dredging materials can be realized, and convenience is provided for the use of a closestool user.
Description
The present application is a divisional application with application number 2017100914181, application date 2017, month 02, and day 21, and title "image processing-based feeding robot and method".
Technical Field
The invention relates to the field of image processing, in particular to a feeding robot based on image processing.
Background
The first detailed text of the toilet is 'wooden horse' in 'Guitian Biao' of the European repair in northern Song dynasty of China, and 'wooden toilet' is explained in 'dictionary source'. The toilet bowl used in ancient China is a round wooden barrel with a cover, and is coated with tung oil or well-finished waterproof vermilion paint.
In 1596, the first practical toilet, a wooden seat with a tank and flush valve, was invented by john hardton, a noble british.
In 1778, the UK inventor developed Joseph Blamel to improve the design of toilets using, for example, a three-ball valve to control the flow of water in the cistern, and a U-bend.
In the 19 th century, the british government made laws that each house had to be equipped with an appropriate sewage treatment robot, and the toilet began to be improved significantly.
In 1861, a plumber in the uk invented an advanced water-saving flushing robot, tomass-krappa, and waste discharge only started to enter the modernization period.
In 1885, tomas earth veefu patented the first full ceramic toilet in the uk, and several tens of improved patents were issued each year thereafter. The first ceramic toilet in china was manufactured in 1914 by the english man in the initiative new ceramic factory in tang shan (predecessor of tang shan ceramic factory).
The 19 th century sixties water closets began to prevail in europe and the united states and later passed to asian countries such as japan, korea and the like.
Therefore, the history of the closestool is long, the basic structure of the closestool is already shaped, however, people still suffer from the following troubles when in use: when the toilet is clogged, the clogging degree and the clogging material in the toilet are not determined, and therefore, when dredging is performed, a scheme has to be selected one by one to perform manual treatment, and in the mean time, the effect of dredging may not be achieved.
Disclosure of Invention
In order to solve the problems, the invention provides a feeding robot based on image processing, which is characterized in that firstly, dredging materials with different dredging forces are prestored in different accommodating spaces on a closestool main body, secondly, the average water flow speed and the type of a target blockage are determined as blockage state determining elements, thirdly, the elements are accurately detected by a high-precision sensor and image recognition equipment, the required dredging materials are determined according to the detection result, and the accommodating space where the required dredging materials are located is automatically opened, so that the automatic dredging of a closestool is realized.
According to an aspect of the invention, there is provided an image processing based feed robot, the robot comprising:
the storage device is used for placing different types of pipeline dredging agents with different chemical compositions into different containing spaces on the closestool in advance;
a flushing starting device for automatically discharging water inside the toilet tank to flush the seat inner space of the toilet;
the average water flow detection device is used for detecting the water flow speed of the inner space of the seat of the closestool in real time to obtain the real-time water flow speed, and calculating the average water flow speed in the washing process based on the real-time water flow speed;
the type determining device is connected with the average water flow detecting device and is used for determining the type of the pipeline dredging agent to be released based on the average water flow speed;
automatic releasing means connected to the type determining means for releasing the determined type of the tube opener into the seat interior space of the toilet to effect the opening of the tube in the seat interior space of the toilet;
wherein, various types of pipeline dredging agents comprise: sodium hydroxide, sodium dichloroisocyanurate, sodium hypochlorite, tartaric acid, nekal BX-78, bentonite and essence, wherein the different chemical compositions of the pipeline dredging agent are that the proportioning percentages of the sodium hydroxide are different, and the pipeline dredging agents of various types are divided into weak pipeline dredging agents, general pipeline dredging agents, strong pipeline dredging agents and quick pipeline dredging agents according to the proportioning percentage of the sodium hydroxide.
More specifically, in the image-processing-based feed robot, the type determining means specifically includes:
the data acquisition unit is used for acquiring high-definition image data of the internal space of the seat of the closestool to obtain a high-definition digital image;
the first filtering unit is connected with the data acquisition unit and used for carrying out edge-preserving filtering on the high-definition digital image so as to remove salt-pepper noise or impulse noise in the high-definition digital image and obtain a first filtering image;
the second filtering unit is connected with the first filtering unit and used for carrying out Gaussian filtering processing on the first filtering image to remove Gaussian noise in the first filtering image and obtain a second filtering image, wherein the Gaussian noise comprises large-amplitude Gaussian noise with a maximum amplitude value exceeding a preset amplitude value and small-amplitude Gaussian noise with a maximum amplitude value smaller than or equal to the preset amplitude value;
the binarization unit is connected with the second filtering unit and is used for carrying out binarization processing on the second filtering image to obtain a binarized image;
the target matching unit is connected with the binarization unit and used for performing target matching processing on the binarization image to determine the type of the blockage in the binarization image and outputting the type of the blockage as a target blockage type, wherein the target matching processing comprises the step of performing shape matching on the binarization image and reference patterns of various types of blockage one by one to determine the type of the blockage in the binarization image;
the type determining unit is respectively connected with the average water flow detection device and the target matching unit and is used for determining the type of the pipeline dredging agent to be released based on the average water flow speed and the target blockage type, wherein the smaller the average water flow speed is, the larger the batching percentage of sodium hydroxide in the pipeline dredging agent of the determined type is, the larger the corrosion difficulty corresponding to the target blockage type is, the larger the batching percentage of sodium hydroxide in the pipeline dredging agent of the determined type is, and when the average water flow speed is larger than a preset water flow threshold value, the pipeline dredging agent of the determined type is absent;
wherein the performing the gaussian filtering process on the first filtered image to remove the gaussian noise in the first filtered image comprises: performing adaptive recursive filtering processing on the first filtered image to remove small-amplitude-value Gaussian noise to obtain an intermediate filtered image, and performing wiener filtering processing on the intermediate filtered image to remove large-amplitude-value Gaussian noise to obtain a second filtered image;
wherein the various types of blockages comprise oil stains, vegetable leaves, tea leaves, hair, toilet paper, excrement, kitchen garbage, plastic bags and cloth.
More specifically, in the image-processing-based feeding robot, the automatic release device specifically includes:
the opening and closing unit is used for opening the opening of the accommodating space where the pipeline dredging agent of the determined type is located so as to automatically release the pipeline dredging agent of the determined type;
when the determined type of the pipeline dredging agent is absent, the opening of the accommodating space where any type of the pipeline dredging agent is located is not opened by the switch unit, and a manual flushing signal is sent out.
More specifically, in the image-processing-based feed robot, it further includes:
the washing frequency determining device is connected with the automatic releasing device and used for determining the frequency of manual washing based on the average water flow speed;
and the display device is respectively connected with the automatic release device and the flushing frequency determining device and used for displaying the manual flushing signal and displaying the frequency of the manual flushing so as to remind a toilet user.
More specifically, in the image-processing-based feed robot, it further includes:
dose detection means for detecting a current dose of the pipeline clearing agent in each of the holding spaces;
and the dosage alarm device is connected with the dosage detection device and used for sending out an insufficient dosage alarm signal when the current dosage of a certain type of pipeline dredging agent is smaller than the preset dosage so as to remind a toilet user to add the corresponding type of pipeline dredging agent.
According to another aspect of the present invention, there is provided a material supply method based on image processing, the method including:
putting different types of pipeline dredging agents with different chemical compositions into different accommodating spaces on a closestool in advance;
automatically discharging water inside a toilet tank to flush a seat interior space of a toilet;
detecting the water flow speed of the inner space of the seat of the closestool in real time to obtain the real-time water flow speed, and calculating the average water flow speed in the washing process based on the real-time water flow speed;
determining a type of pipe opener agent to release based on the average water flow rate;
releasing a determined type of a conduit clearing agent into the seat interior space of the toilet to effect clearing of the conduit in the seat interior space of the toilet;
wherein, various types of pipeline dredging agents comprise: sodium hydroxide, sodium dichloroisocyanurate, sodium hypochlorite, tartaric acid, nekal BX-78, bentonite and essence, wherein the different chemical compositions of the pipeline dredging agent are that the proportioning percentages of the sodium hydroxide are different, and the pipeline dredging agents of various types are divided into weak pipeline dredging agents, general pipeline dredging agents, strong pipeline dredging agents and quick pipeline dredging agents according to the proportioning percentage of the sodium hydroxide.
More specifically, in the image-processing-based material supply method, the determining the type of the pipe opener to be released based on the average water flow velocity specifically includes the steps of:
carrying out high-definition image data acquisition on the internal space of the seat of the closestool to obtain a high-definition digital image; performing edge-preserving filtering on the high-definition digital image to remove salt-pepper noise or impulse noise in the high-definition digital image to obtain a first filtering image;
performing Gaussian filtering processing on the first filtering image to remove Gaussian noise in the first filtering image to obtain a second filtering image, wherein the Gaussian noise comprises large-amplitude Gaussian noise with a maximum amplitude value exceeding a preset amplitude value and small-amplitude Gaussian noise with a maximum amplitude value smaller than or equal to the preset amplitude value; performing binarization processing on the second filtered image to obtain a binarized image;
performing target matching processing on the binary image to determine the type of the blockage in the binary image and outputting the type of the blockage as a target blockage type, wherein the target matching processing comprises performing shape matching on the binary image and reference patterns of various types of blockages one by one to determine the type of the blockage in the binary image;
determining the type of a pipeline dredging agent to be released based on the average water flow speed and the type of the target blockage, wherein the smaller the average water flow speed is, the larger the batching percentage of sodium hydroxide in the pipeline dredging agent of the determined type is, the larger the corrosion difficulty corresponding to the type of the target blockage is, the larger the batching percentage of sodium hydroxide in the pipeline dredging agent of the determined type is, and when the average water flow speed is greater than a preset water flow threshold value, determining that the pipeline dredging agent of the determined type is absent;
wherein the performing the gaussian filtering process on the first filtered image to remove the gaussian noise in the first filtered image comprises: performing adaptive recursive filtering processing on the first filtered image to remove small-amplitude-value Gaussian noise to obtain an intermediate filtered image, and performing wiener filtering processing on the intermediate filtered image to remove large-amplitude-value Gaussian noise to obtain a second filtered image;
wherein the various types of blockages comprise oil stains, vegetable leaves, tea leaves, hair, toilet paper, excrement, kitchen garbage, plastic bags and cloth.
More specifically, in the image processing-based material supply method, the releasing the duct opener of the determined type into the seat inner space of the toilet to effect the opening of the duct in the seat inner space of the toilet specifically includes the steps of:
opening the opening of the accommodating space where the determined type of the pipeline dredging agent is located to automatically release the determined type of the pipeline dredging agent;
when the determined type of the pipeline dredging agent is absent, the opening of the accommodating space where any type of the pipeline dredging agent is located is not opened, and a manual flushing signal is sent.
More specifically, in the image processing-based material supply method, after the releasing of the duct opener of the determined type into the seat inner space of the toilet bowl to effect the opening of the duct in the seat inner space of the toilet bowl, the method further includes the steps of:
determining the number of times of manual flushing is needed based on the average water flow speed; and displaying the number of times of manual flushing while displaying the manual flushing signal so as to remind a toilet user.
More specifically, in the image-processing-based material supply method, the method further includes the steps of: detecting a current dose of the pipeline dredging agent in each accommodating space;
when the current dosage of a certain type of the pipeline dredging agent is smaller than the preset dosage, an insufficient dosage alarm signal is sent out to remind a toilet user to add the corresponding type of the pipeline dredging agent.
In summary, the key points of the invention are as follows:
firstly, various dredging materials with different dredging forces are prestored, and an alarm is given when the dredging materials are insufficient;
secondly, accurately detecting the blocking state of the interior of the closestool, and selecting a proper dredging material based on the blocking state;
and thirdly, a proper dredging material is discharged for automatic dredging, the whole process does not need manual participation, and the full automation of toilet dredging is realized.
Drawings
Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
fig. 1 is a block diagram illustrating a structure of a feed robot based on image processing according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating steps of a material supply method based on image processing according to an embodiment of the present invention.
Reference numerals: 1 a storage device; 2, flushing the starting device; 3 average water flow detection device; 4 type determination means; 5 automatic release device.
Detailed Description
An embodiment of the image processing-based feed robot of the present invention will be described in detail below with reference to the accompanying drawings.
The appearance of the toilet bowl brings great convenience to people, however, when the toilet bowl is blocked, the convenience is all transformed into troubles. People need to start the brains and manually carry out one-by-one common sense of the scheme according to the limited blocking condition observed by the people.
Common dredging schemes are as follows:
1. a manual dredging device (like a spring) is bought in a sundry store, and the sundry store is dredged manually;
2. a mop method: firstly, the mop is placed at the opening of the closestool, and then water is discharged to ensure that the mop is submerged by the water. Then the mop is pressed forcibly and is plugged into the opening of the toilet as much as possible, and finally the mop is lifted at the fastest speed, and the actions are repeated, so that the articles in the toilet can be sucked out;
3. a section of plastic water pipe which is a little longer is found, one end of the plastic water pipe is connected with tap water, the other end of the plastic water pipe is plugged into the mouth of the toilet, the mouth of the toilet is plugged by a cloth or the like, and then the tap water is opened, so that the pipeline can be dredged by utilizing the water pressure;
4. if the closestool is blocked by hard thing, inhale earlier and lower the filth with the closestool, drain simultaneously and lower the plunger, make only clear water in the closestool pond, then be stained with water futilely with the towel, look for a minimalism, for example be the minimalism that makes up, a flashlight, put the minimalism to the bottommost of closestool, the angle of adjustment light source and mirror can see pipeline inside partly, the minimalism can block in the pipeline place that will turn down most inside usually, look for a more suitable iron wire, solve at the minimalism with the iron wire card.
5. And a professional dredging company or a dredging worker is searched for manual dredging.
Therefore, all dredging operations need to be observed manually, dredging materials are selected manually and dredged personally, on one hand, time and labor are consumed, on the other hand, dirt in the dredging process is easily contacted, and more importantly, if the scheme is not right, the problem of blockage cannot be solved, the closestool cannot be used continuously, and inconvenience is brought to life and work of a user.
In order to overcome the defects, the invention builds a feeding robot and a feeding method based on image processing, adopts full-automatic dredging materials to correctly select the dredging materials and automatically dredge leakage, determines the times of needing manual flushing under the condition of judging that the dredging materials are not needed, and timely informs users of the times of needing manual flushing and the flushing times, thereby avoiding the waste of the dredging materials.
Fig. 1 is a block diagram illustrating a structure of a feed robot based on image processing according to an embodiment of the present invention, the robot including:
the storage device is used for placing different types of pipeline dredging agents with different chemical compositions into different containing spaces on the closestool in advance;
a flushing starting device for automatically discharging water inside the toilet tank to flush the seat inner space of the toilet;
the average water flow detection device is used for detecting the water flow speed of the inner space of the seat of the closestool in real time to obtain the real-time water flow speed, and calculating the average water flow speed in the washing process based on the real-time water flow speed;
the type determining device is connected with the average water flow detecting device and is used for determining the type of the pipeline dredging agent to be released based on the average water flow speed;
automatic releasing means connected to the type determining means for releasing the determined type of the tube opener into the seat interior space of the toilet to effect the opening of the tube in the seat interior space of the toilet;
wherein, various types of pipeline dredging agents comprise: sodium hydroxide, sodium dichloroisocyanurate, sodium hypochlorite, tartaric acid, nekal BX-78, bentonite and essence, wherein the different chemical compositions of the pipeline dredging agent are that the proportioning percentages of the sodium hydroxide are different, and the pipeline dredging agents of various types are divided into weak pipeline dredging agents, general pipeline dredging agents, strong pipeline dredging agents and quick pipeline dredging agents according to the proportioning percentage of the sodium hydroxide.
Next, a detailed description will be given of a specific configuration of the image processing-based feed robot according to the present invention.
In the robot, the type determining device specifically includes:
the data acquisition unit is used for acquiring high-definition image data of the internal space of the seat of the closestool to obtain a high-definition digital image;
the first filtering unit is connected with the data acquisition unit and used for carrying out edge-preserving filtering on the high-definition digital image so as to remove salt-pepper noise or impulse noise in the high-definition digital image and obtain a first filtering image;
the second filtering unit is connected with the first filtering unit and used for carrying out Gaussian filtering processing on the first filtering image to remove Gaussian noise in the first filtering image and obtain a second filtering image, wherein the Gaussian noise comprises large-amplitude Gaussian noise with a maximum amplitude value exceeding a preset amplitude value and small-amplitude Gaussian noise with a maximum amplitude value smaller than or equal to the preset amplitude value;
the binarization unit is connected with the second filtering unit and is used for carrying out binarization processing on the second filtering image to obtain a binarized image;
the target matching unit is connected with the binarization unit and used for performing target matching processing on the binarization image to determine the type of the blockage in the binarization image and outputting the type of the blockage as a target blockage type, wherein the target matching processing comprises the step of performing shape matching on the binarization image and reference patterns of various types of blockage one by one to determine the type of the blockage in the binarization image;
the type determining unit is respectively connected with the average water flow detection device and the target matching unit and is used for determining the type of the pipeline dredging agent to be released based on the average water flow speed and the target blockage type, wherein the smaller the average water flow speed is, the larger the batching percentage of sodium hydroxide in the pipeline dredging agent of the determined type is, the larger the corrosion difficulty corresponding to the target blockage type is, the larger the batching percentage of sodium hydroxide in the pipeline dredging agent of the determined type is, and when the average water flow speed is larger than a preset water flow threshold value, the pipeline dredging agent of the determined type is absent;
wherein the performing the gaussian filtering process on the first filtered image to remove the gaussian noise in the first filtered image comprises: performing adaptive recursive filtering processing on the first filtered image to remove small-amplitude-value Gaussian noise to obtain an intermediate filtered image, and performing wiener filtering processing on the intermediate filtered image to remove large-amplitude-value Gaussian noise to obtain a second filtered image;
wherein the various types of blockages comprise oil stains, vegetable leaves, tea leaves, hair, toilet paper, excrement, kitchen garbage, plastic bags and cloth.
In the robot, the automatic release device specifically includes:
the opening and closing unit is used for opening the opening of the accommodating space where the pipeline dredging agent of the determined type is located so as to automatically release the pipeline dredging agent of the determined type;
when the determined type of the pipeline dredging agent is absent, the opening of the accommodating space where any type of the pipeline dredging agent is located is not opened by the switch unit, and a manual flushing signal is sent out.
In the robot, still include:
the washing frequency determining device is connected with the automatic releasing device and used for determining the frequency of manual washing based on the average water flow speed;
and the display device is respectively connected with the automatic release device and the flushing frequency determining device and used for displaying the manual flushing signal and displaying the frequency of the manual flushing so as to remind a toilet user.
In the robot, still include:
dose detection means for detecting a current dose of the pipeline clearing agent in each of the holding spaces;
and the dosage alarm device is connected with the dosage detection device and used for sending out an insufficient dosage alarm signal when the current dosage of a certain type of pipeline dredging agent is smaller than the preset dosage so as to remind a toilet user to add the corresponding type of pipeline dredging agent.
Fig. 2 is a flow chart illustrating steps of a method for image processing-based material feeding, according to an embodiment of the present invention, the method including:
putting different types of pipeline dredging agents with different chemical compositions into different accommodating spaces on a closestool in advance;
automatically discharging water inside a toilet tank to flush a seat interior space of a toilet;
detecting the water flow speed of the inner space of the seat of the closestool in real time to obtain the real-time water flow speed, and calculating the average water flow speed in the washing process based on the real-time water flow speed;
determining a type of pipe opener agent to release based on the average water flow rate;
releasing a determined type of a conduit clearing agent into the seat interior space of the toilet to effect clearing of the conduit in the seat interior space of the toilet;
wherein, various types of pipeline dredging agents comprise: sodium hydroxide, sodium dichloroisocyanurate, sodium hypochlorite, tartaric acid, nekal BX-78, bentonite and essence, wherein the different chemical compositions of the pipeline dredging agent are that the proportioning percentages of the sodium hydroxide are different, and the pipeline dredging agents of various types are divided into weak pipeline dredging agents, general pipeline dredging agents, strong pipeline dredging agents and quick pipeline dredging agents according to the proportioning percentage of the sodium hydroxide.
Next, a detailed flow of the image processing-based material supply method of the present invention will be further described.
In the method, the step of determining the type of the pipe dredging agent to be released based on the average water flow speed specifically comprises the following steps:
carrying out high-definition image data acquisition on the internal space of the seat of the closestool to obtain a high-definition digital image; performing edge-preserving filtering on the high-definition digital image to remove salt-pepper noise or impulse noise in the high-definition digital image to obtain a first filtering image;
performing Gaussian filtering processing on the first filtering image to remove Gaussian noise in the first filtering image to obtain a second filtering image, wherein the Gaussian noise comprises large-amplitude Gaussian noise with a maximum amplitude value exceeding a preset amplitude value and small-amplitude Gaussian noise with a maximum amplitude value smaller than or equal to the preset amplitude value; performing binarization processing on the second filtered image to obtain a binarized image;
performing target matching processing on the binary image to determine the type of the blockage in the binary image and outputting the type of the blockage as a target blockage type, wherein the target matching processing comprises performing shape matching on the binary image and reference patterns of various types of blockages one by one to determine the type of the blockage in the binary image;
determining the type of a pipeline dredging agent to be released based on the average water flow speed and the type of the target blockage, wherein the smaller the average water flow speed is, the larger the batching percentage of sodium hydroxide in the pipeline dredging agent of the determined type is, the larger the corrosion difficulty corresponding to the type of the target blockage is, the larger the batching percentage of sodium hydroxide in the pipeline dredging agent of the determined type is, and when the average water flow speed is greater than a preset water flow threshold value, determining that the pipeline dredging agent of the determined type is absent;
wherein the performing the gaussian filtering process on the first filtered image to remove the gaussian noise in the first filtered image comprises: performing adaptive recursive filtering processing on the first filtered image to remove small-amplitude-value Gaussian noise to obtain an intermediate filtered image, and performing wiener filtering processing on the intermediate filtered image to remove large-amplitude-value Gaussian noise to obtain a second filtered image;
wherein the various types of blockages comprise oil stains, vegetable leaves, tea leaves, hair, toilet paper, excrement, kitchen garbage, plastic bags and cloth.
In the method, the step of releasing the determined type of the pipeline dredging agent into the seat inner space of the closestool to realize the dredging of the pipeline in the seat inner space of the closestool comprises the following steps:
opening the opening of the accommodating space where the determined type of the pipeline dredging agent is located to automatically release the determined type of the pipeline dredging agent;
when the determined type of the pipeline dredging agent is absent, the opening of the accommodating space where any type of the pipeline dredging agent is located is not opened, and a manual flushing signal is sent.
In the method, after the releasing the determined type of the canalizing agent into the seat interior of the toilet to effect the dredging of the canalizing agent in the seat interior of the toilet, the method further comprises the steps of:
determining the number of times of manual flushing is needed based on the average water flow speed; and displaying the number of times of manual flushing while displaying the manual flushing signal so as to remind a toilet user.
The method further comprises the following steps:
detecting a current dose of the pipeline dredging agent in each accommodating space;
when the current dosage of a certain type of pipeline dredging agent is smaller than the preset dosage, an insufficient dosage alarm signal is sent out to remind a toilet user to add the corresponding type of pipeline dredging agent.
In addition, the robot may further include: and the CDMA passing equipment is respectively connected with the automatic release device and the flushing frequency determining device and is used for wirelessly sending the manual flushing signal and the frequency needing manual flushing to a mobile terminal held by a toilet user.
In addition, the method can also comprise the following steps:
and wirelessly transmitting a manual flushing signal and the number of times of manual flushing to a mobile terminal held by a toilet user.
By adopting the feeding robot and the feeding method based on image processing, aiming at the technical problem that the toilet bowl dredging in the prior art requires manual operation and participates in the whole process, the full-automatic dredging of the toilet bowl is completed by accurately detecting the blockage state of the toilet bowl, pre-storing dredging materials, customizing and selecting a dredging material and a coping way when the dredging material is not needed, and meanwhile, timely dosage alarm is carried out when the dredging material is insufficient, so that the intelligent level of the whole toilet bowl is improved.
It is to be understood that while the present invention has been described in conjunction with the preferred embodiments thereof, it is not intended to limit the invention to those embodiments. It will be apparent to those skilled in the art from this disclosure that many changes and modifications can be made, or equivalents modified, in the embodiments of the invention without departing from the scope of the invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.
Claims (1)
1. A feed robot based on image processing, characterized in that the robot comprises:
the storage device is used for placing different types of pipeline dredging agents with different chemical compositions into different accommodating spaces on the closestool in advance;
a flushing starting device for automatically discharging water inside the toilet tank to flush the seat inner space of the toilet;
the average water flow detection device is used for detecting the water flow speed of the inner space of the seat of the closestool in real time to obtain the real-time water flow speed, and calculating the average water flow speed in the washing process based on the real-time water flow speed;
the type determining device is connected with the average water flow detecting device and is used for determining the type of the pipeline dredging agent to be released based on the average water flow speed;
automatic releasing means connected to the type determining means for releasing the determined type of the tube opener into the seat interior space of the toilet to effect the opening of the tube in the seat interior space of the toilet;
wherein, various types of pipeline dredging agents comprise: sodium hydroxide, sodium dichloroisocyanurate, sodium hypochlorite, tartaric acid, nekal BX-78, bentonite and essence, wherein the different chemical compositions of the pipeline dredging agent are that the proportioning percentages of the sodium hydroxide are different, and the pipeline dredging agents of various types are divided into weak pipeline dredging agents, general pipeline dredging agents, strong pipeline dredging agents and quick pipeline dredging agents according to the proportioning percentage of the sodium hydroxide;
the data acquisition unit is used for acquiring high-definition image data of the internal space of the seat of the closestool to obtain a high-definition digital image;
the first filtering unit is connected with the data acquisition unit and used for carrying out edge-preserving filtering on the high-definition digital image so as to remove salt-pepper noise or impulse noise in the high-definition digital image and obtain a first filtering image;
the second filtering unit is connected with the first filtering unit and used for carrying out Gaussian filtering processing on the first filtering image to remove Gaussian noise in the first filtering image and obtain a second filtering image, wherein the Gaussian noise comprises large-amplitude Gaussian noise with a maximum amplitude value exceeding a preset amplitude value and small-amplitude Gaussian noise with a maximum amplitude value smaller than or equal to the preset amplitude value;
the binarization unit is connected with the second filtering unit and is used for carrying out binarization processing on the second filtered image to obtain a binarized image;
the target matching unit is connected with the binarization unit and used for performing target matching processing on the binarization image to determine the type of the blockage in the binarization image and outputting the type of the blockage as a target blockage type, wherein the target matching processing comprises the step of performing shape matching on the binarization image and reference patterns of various types of blockage one by one to determine the type of the blockage in the binarization image;
the type determining unit is respectively connected with the average water flow detection device and the target matching unit and is used for determining the type of the pipeline dredging agent to be released based on the average water flow speed and the target blockage type, wherein the smaller the average water flow speed is, the larger the batching percentage of sodium hydroxide in the pipeline dredging agent of the determined type is, the larger the corrosion difficulty corresponding to the target blockage type is, the larger the batching percentage of sodium hydroxide in the pipeline dredging agent of the determined type is, and when the average water flow speed is larger than a preset water flow threshold value, the pipeline dredging agent of the determined type is absent;
wherein the performing the gaussian filtering process on the first filtered image to remove the gaussian noise in the first filtered image comprises: the first filtered image is subjected to adaptive recursive filtering to remove small-amplitude-value Gaussian noise to obtain an intermediate filtered image, and the intermediate filtered image is subjected to wiener filtering to remove large-amplitude-value Gaussian noise to obtain a second filtered image.
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| CN107217718B (en) * | 2017-02-21 | 2018-03-23 | 张玉红 | Feed robot and method based on image procossing |
| CN108331106B (en) * | 2018-03-18 | 2018-12-28 | 由佳鑫 | Computer picture recognition formula dredging system |
| CN108729517A (en) * | 2018-03-18 | 2018-11-02 | 蔡晓青 | Computer picture recognition formula dredging system and method |
| CN108999259B (en) * | 2018-03-19 | 2019-04-12 | 新昌县勤勉贸易有限公司 | The application method of intelligent device based on computer module |
| CN109406458B (en) * | 2018-03-20 | 2019-06-21 | 上海工业控制安全创新科技有限公司 | Cloud measurement method |
| CN108731772B (en) * | 2018-03-20 | 2019-08-23 | 奥菲(泰州)光电传感技术有限公司 | Liquid level big data measuring system |
| CN109907462A (en) * | 2018-06-06 | 2019-06-21 | 周超强 | Thermostatic control type hair dryer |
| CN109235572A (en) * | 2018-09-26 | 2019-01-18 | 东莞幻鸟新材料有限公司 | A kind of closestool intelligence dredging system |
| CN109602305A (en) * | 2018-12-03 | 2019-04-12 | 余姚市腾翔电子科技有限公司 | The automatic dispatching platform of dredging agent |
| CN109581520A (en) * | 2018-12-05 | 2019-04-05 | 余姚德诚科技咨询有限公司 | Conveying type personnel's scanning system |
| CN111188392A (en) * | 2020-01-15 | 2020-05-22 | 李勇妹 | Method for cleaning intelligent closestool and toilet bowl for puerpera |
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| Publication number | Publication date |
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| CN107217718A (en) | 2017-09-29 |
| CN107254905B (en) | 2018-06-01 |
| CN106836426B (en) | 2017-12-19 |
| CN107724492A (en) | 2018-02-23 |
| CN107254905A (en) | 2017-10-17 |
| CN107217718B (en) | 2018-03-23 |
| CN106836426A (en) | 2017-06-13 |
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