CN112875827A - Intelligent dosing system and water treatment system based on image recognition and data mining - Google Patents
Intelligent dosing system and water treatment system based on image recognition and data mining Download PDFInfo
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- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F1/00—Treatment of water, waste water, or sewage
- C02F1/52—Treatment of water, waste water, or sewage by flocculation or precipitation of suspended impurities
- C02F1/5281—Installations for water purification using chemical agents
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- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F2209/00—Controlling or monitoring parameters in water treatment
- C02F2209/001—Upstream control, i.e. monitoring for predictive control
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- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F2209/00—Controlling or monitoring parameters in water treatment
- C02F2209/005—Processes using a programmable logic controller [PLC]
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Abstract
The invention provides an intelligent dosing system and a water treatment system based on image recognition and data mining, wherein the intelligent dosing system comprises a collecting device for collecting alum blossom images and water quality parameters, an association model for determining the association relation among the alum blossom characteristics, the water quality parameters and dosing parameters according to the alum blossom characteristics, a dosing parameter determining device for judging the reasonability of the last dosing parameters suitable for the current water quality parameters and a dosing device for executing dosing operation.
Description
Technical Field
The invention relates to the technical field of water treatment, in particular to an intelligent dosing system and a water treatment system based on image recognition and data mining.
Background
In the sewage treatment process, coagulant (dosing) and the like are often added into the sewage to realize coagulation so as to aggregate colloidal particles and micro suspended matters in the sewage. Coagulation is an important link of sewage treatment and has great influence on effluent quality and the like.
In the related art, for sewage treatment, the operations of determining dosing parameters, executing dosing and the like are often performed manually, new dosing parameters need to be determined continuously, dosing operation is performed according to the new dosing parameters, assistance of systematic intelligent tools is lacked, the working efficiency is low, and the cost is high.
Disclosure of Invention
In view of the above drawbacks of the prior art, an object of the present invention is to provide an intelligent dosing system and a water treatment system based on image recognition and data mining, which are used to solve the technical problems of low working efficiency and high cost caused by the traditional method that the dosing parameter determination and dosing execution are performed manually.
In view of the above problems, the present invention provides an intelligent medicine adding system based on image recognition and data mining, comprising:
the acquisition device is used for acquiring alum blossom images and water quality parameters;
the correlation model is used for determining the correlation among the alum blossom characteristics, the water quality parameters and the dosing parameters according to the alum blossom characteristics and the water quality parameters;
the dosing parameter determining device is used for obtaining a last dosing parameter corresponding to a last dosing operation, determining alum blossom characteristics according to the alum blossom image, and judging the rationality of the last dosing parameter according to the alum blossom characteristics, the water quality parameter and the correlation model;
and the dosing device is used for taking the last dosing parameter as an execution dosing parameter when the judgment result is reasonable, and executing dosing operation according to the execution dosing parameter.
Optionally, when the judgment result is reasonable and unreasonable, the dosing parameters of the proposal are determined according to the alum blossom characteristics, the water quality parameters and the correlation model;
and taking the recommended medicine adding parameter as an execution medicine adding parameter, and executing medicine adding operation according to the execution medicine adding parameter.
Optionally, the determining the reasonability of the last dosing parameter according to the alum blossom characteristics, the water quality parameter and the correlation model comprises:
determining the suggested medicine adding parameters according to the alum blossom characteristics, the water quality parameters and the correlation model;
acquiring the difference between the last dosing parameter and the current suggested dosing parameter;
if the difference is less than or equal to a preset difference threshold value, the judgment result is reasonable;
and if the difference is larger than a preset difference threshold value, judging that the result is unreasonable.
Optionally, the apparatus further comprises an input device for at least one of:
acquiring dosing parameter adjusting information, and adjusting the executed dosing parameters according to the dosing parameter adjusting information;
and acquiring water quality parameter adjustment information, and adjusting the water quality parameters according to the water quality parameter adjustment information.
Optionally, the collecting device comprises an image collecting device, the image collecting device comprises a collecting window, a cleaning arm and a cleaning scraping strip, if the collecting window needs to be cleaned, the cleaning arm drives the cleaning scraping strip to scrape off attachments on the surface of the collecting window.
Optionally, the system further comprises a data storage device, configured to store history information, where the history information includes at least one of:
the system comprises a dosing time, a water quality parameter, an alum blossom characteristic, an alum blossom image, a dosing parameter suggested this time, an execution dosing parameter, dosing parameter adjustment information, water quality parameter adjustment information, an acquisition time of the dosing parameter adjustment information, an acquisition time of the water quality parameter adjustment information, an input source of the dosing parameter adjustment information and an input source of the water quality parameter adjustment information.
Optionally, the device further comprises a prompting device, configured to:
prompting to clean the acquisition window at preset time intervals;
the collection device comprises a water quality collection device, and if the water quality parameters collected by the water quality collection device are empty, the collection of the water quality parameters is prompted to be abnormal.
Optionally, the system further comprises a display device for displaying water treatment information, wherein the water treatment information includes at least one of the following:
alum blossom images, alum blossom characteristic information, alum blossom image recognition results, water quality parameters, last dosing parameters, rationality, execution dosing parameters, dosing parameter time trend in a preset time period, water quality parameter time trend in a preset time period and dosing pool effect graphs.
Optionally, the water quality parameter includes a water quality qualification determination parameter, and the intelligent dosing system further includes a function adjusting device, and if the water quality qualification determination parameter is greater than a preset qualification threshold, the executed dosing parameter includes the recommended dosing parameter, and is used for adjusting the correlation model.
The embodiment of the invention also provides a water treatment system, which comprises the intelligent dosing system based on image recognition and data mining.
As mentioned above, the intelligent dosing system and the water treatment system based on image recognition and data mining provided by the invention have the following beneficial effects:
the intelligent dosing system comprises a collecting device for collecting the alum blossom image and the water quality parameters, an association model for determining the association relation among the alum blossom characteristics, the water quality parameters and the dosing parameters according to the alum blossom characteristics, a dosing parameter determining device for judging the reasonability of whether the last dosing parameters are suitable for the current water quality parameters and a dosing device for executing dosing operation, the dosing operation including dosing parameter determination can be completed in an automatic mode, the working efficiency is improved, a worker only needs to pay attention to the working condition of the intelligent dosing system, the experience and the technical level requirements of the worker are not high, the working strength is reduced, and the working cost is reduced.
Drawings
FIG. 1 is a schematic structural diagram of an intelligent dosing system according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a partial structure of an image capturing apparatus according to an embodiment of the present invention;
FIG. 3 is a side schematic view of the structure shown in FIG. 2;
FIG. 4 is a schematic structural diagram of a specific intelligent dosing system according to an embodiment of the present invention;
FIG. 5 is a schematic view illustrating an operation and usage of a specific intelligent dosing system according to a first embodiment of the present invention;
FIG. 6 is a control page diagram;
FIG. 7 is a diagram of an image recognition page;
FIG. 8 is a view of a dosing control page;
FIG. 9 is a view of an image recognition parameter page;
FIG. 10 is a water quality parameter page diagram;
fig. 11 is a large screen display page diagram.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the present embodiment are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated. The structures, proportions, sizes, and other dimensions shown in the drawings and described in the specification are for understanding and reading the present disclosure, and are not intended to limit the scope of the present disclosure, which is defined in the claims, and are not essential to the art, and any structural modifications, changes in proportions, or adjustments in size, which do not affect the efficacy and attainment of the same are intended to fall within the scope of the present disclosure. In addition, the terms "upper", "lower", "left", "right", "middle" and "one" used in the present specification are for clarity of description, and are not intended to limit the scope of the present invention, and the relative relationship between the terms and the terms is not to be construed as a scope of the present invention.
Example one
Referring to fig. 1, an intelligent dosing system based on image recognition and data mining provided by an embodiment of the present invention includes:
the acquisition device 15 is used for acquiring alum blossom images and water quality parameters;
the correlation model is used for determining the correlation among the alum blossom characteristics, the water quality parameters and the dosing parameters;
the dosing parameter determining device 3 is used for acquiring a last dosing parameter corresponding to a last dosing operation, determining alum blossom characteristics according to the alum blossom image, and judging the rationality of the last dosing parameter according to the alum blossom characteristics, the water quality parameter and the correlation model;
and the dosing device 4 is used for taking the last dosing parameter as an execution dosing parameter when the judgment result is reasonable, and executing dosing operation according to the execution dosing parameter.
Optionally, with continued reference to fig. 1, the collecting device 15 comprises:
the image acquisition device 1 is used for acquiring alum blossom images;
and the water quality acquisition device 2 is used for acquiring water quality parameters.
In some embodiments, the image capturing device includes a capturing window, a cleaning arm and a cleaning scraping strip, and if the capturing window needs to be cleaned, the cleaning arm drives the cleaning scraping strip to scrape off the attachments on the surface of the capturing window.
Optionally, referring to fig. 2 and 3, the cleaning arms 5 may be disposed on two opposite sides of the collection window 6, two ends of the cleaning scraping strip 7 are respectively fixedly connected to one cleaning arm 5, and the cleaning scraping strip 7 is driven by the cleaning arms 5 to move to the other side along one side of the collection window 6, so as to scrape off the attachments on the surface of the collection window 6. If better cleaning is desired, the cleaning wiper strip may be reciprocated to enhance cleaning.
Optionally, continuing to refer to fig. 2 and 3, clean structure still includes scrapes a groove of keeping in 8, scrapes a groove of keeping in 8 and sets up in the one side that is close to collection window 6, and when need not clean, cleaning arm 5 drives and cleans and scrape a 7 and keep in and scrape a groove of keeping in 8, so both can protect and scrape the strip, can not block the image acquisition route of gathering the window again.
Optionally, the scratch strip temporary storage groove can be arranged in front of and behind the movement direction of the cleaning scratch strip.
It should be noted that fig. 2 and 3 are only examples of one cleaning mechanism, and only one cleaning arm may be provided, and the cleaning scraping strip is disposed on the support with higher hardness, and the cleaning arm drives the support to scrape off the attachments on the surface of the collecting window.
Optionally, the movement mode of the wiper strip may be a central rotation mode or the like, besides the translation mode shown in fig. 2 and 3, which is not limited herein.
Optionally, the image acquisition device is arranged underwater and used for shooting water images, and the water images are also the alum blossom images because the water images mainly comprise the alum blossom and the water images are imaged.
Optionally, the image acquisition device includes a camera disposed under water, and the acquisition window may be understood as a lens of the camera. Since many impurities are contained in the water, they may be continuously accumulated and attached to the lens, and the quality of the shot alumen ustum image may be affected, and thus, the lens needs to be cleaned.
The lens can be cleaned by transferring the image acquisition device out of water, such as by spraying or flushing.
The lens cleaning mode can also be that the lens is cleaned directly under water through a cleaning mechanism carried by the image acquisition device.
In some embodiments, the intelligent dosing system is applied to flowing water treatment, and because the pollution degree of water is not likely to change greatly in a short time, whether the last dosing parameter applied to the current water is suitable or not can be determined through the dosing parameter determining device, if so, the last dosing parameter is directly adopted as the dosing execution parameter to carry out dosing operation, unnecessary frequent adjustment on the dosing parameter can be avoided, and resource waste is reduced.
Optionally, the chemical dosing process can be intelligentized and automatic, the situation of the alumen ustum is not needed to be observed by naked eyes manually, the chemical dosing parameters are determined according to experience, the water quality after treatment is stable, and the water treatment effect is good.
Optionally, the water quality parameter may be obtained by a plurality of detection sensors.
Optionally, the water quality parameter includes, but is not limited to, at least one of PH, temperature, inlet water turbidity, dosing tank outlet water turbidity, flow rate, alkalinity, TDS (Total dissolved solids), conductivity, drug concentration, suspended matter concentration, and the like.
Optionally, the agents added to the water include, but are not limited to, coagulants, flocculants, and the like.
Optionally, the dosing parameters include, but are not limited to, the addition amount of coagulant, the addition amount of flocculant.
Alternatively, the association model may be obtained as follows:
and obtaining sample data, and training the initial association model to obtain the association model, wherein the sample data comprises but is not limited to a plurality of groups of alum blossom characteristics, dosing parameters, water quality parameters and the like.
In order to make the relevance model more suitable, the sample data may be acquired under the water environment applied by the water treatment system.
Optionally, the pre-association model may also be implemented by other related technologies, which are not limited herein.
Optionally, the extraction of alum blossom features can be realized based on a method of a related technology, which is not limited herein.
Optionally, the dosing parameter determining device can determine the rationality of the last dosing parameter at intervals of a certain reaction time, so that the last added medicine can fully react with water, and resources are saved.
Alternatively, the reaction time may be set by a person skilled in the art, and is not limited herein.
Optionally, add medicine parameter determination device can be after accomplishing the examination and once adding medicine operation, and direct just confirm the rationality of adding the medicine parameter last time, very transient to reaction time, along with the medicine adds the condition of accomplishing the reaction rapidly, can in time adjust and add the medicine parameter, system flexibility, accuracy are better, and water quality treatment quality is better.
In some embodiments, when the determination result is reasonable and unreasonable, the medicine adding parameter suggested this time is determined according to the alum blossom characteristics, the water quality parameter and the correlation model, the medicine adding parameter suggested this time is used as an execution medicine adding parameter, and the medicine adding operation is executed according to the execution medicine adding parameter.
Optionally, the rationality of the last dosing parameter is judged according to the alum blossom characteristics, the water quality parameters and the correlation model, and the rationality comprises the following steps:
determining the suggested medicine adding parameters according to the alum blossom characteristics, the water quality parameters and a preset alum blossom characteristic-medicine adding parameter correlation model;
acquiring the difference between the last dosing parameter and the current suggested dosing parameter;
if the difference is less than or equal to a preset difference threshold value, the judgment result is reasonable;
if the difference is greater than the preset difference threshold, the result is judged to be unreasonable.
Alternatively, the preset difference threshold may be set by a person skilled in the art, and is not limited herein.
Optionally, the preset difference threshold may be the same for all water quality parameters, or a plurality of preset difference thresholds may be set according to different water quality parameters.
Alternatively, the determination of the reasonableness may be implemented by using other related technologies in the field, and is not limited herein.
Optionally, when the last dosing parameter is no longer suitable for the current water condition, that is, at least one of the current alum blossom characteristics and the water quality parameters is different from the last alum blossom parameters and the water quality parameters corresponding to the last dosing to a greater extent, or due to the optimization of the correlation model, when the last dosing parameter is no longer suitable for the current water condition, the dosing parameter needs to be adjusted again.
Optionally, the medicine adding parameter suggested this time can be directly determined according to the alum blossom characteristics, the water quality parameter and the correlation model, and the medicine adding parameter suggested this time is used as an execution medicine adding parameter to carry out medicine adding operation.
Optionally, the dosing parameter adjustment information may be obtained from the outside, for example, a worker manually inputs a value as an execution dosing parameter to perform a dosing operation.
Optionally, when the rationality is judged to be unreasonable, the user can be prompted at the moment to remind the user to select the suggested medicine adding parameter as the executed medicine adding parameter, or to automatically input the medicine adding parameter adjusting information to determine the executed medicine adding parameter.
Optionally, the wastewater treatment system further comprises an input device for at least one of:
acquiring medicine adding parameter adjusting information, and adjusting and executing medicine adding parameters according to the medicine adding parameter adjusting information;
and acquiring water quality parameter adjustment information, and adjusting the water quality parameters according to the water quality parameter adjustment information.
Alternatively, the input device includes, but is not limited to, a touch screen or the like.
Optionally, the dosing parameter adjustment information includes an increase/decrease amount of the dosing amount, at this time, the executed dosing parameter is adjusted according to the dosing parameter adjustment information, for example, the corresponding dosing amount is increased/decreased, and then the dosing operation is executed according to the executed dosing parameter.
Optionally, the medicine adding parameter adjusting information includes a manually inputted medicine adding amount, at this time, the executed medicine adding parameter is directly adjusted according to the medicine adding parameter adjusting information, the medicine adding parameter adjusting information is used as the executed medicine adding parameter, and then the medicine adding operation is executed according to the executed medicine adding parameter.
Optionally, if quality of water collection system breaks down, can not gather the quality of water parameter, perhaps when the quality of water parameter of gathering is obviously wrong, provide the mode of manual remedy through input device, avoid the quality degradation problem of the water that the intelligent medicine system of leading to because of quality of water collection system trouble was handled, the problem that intelligent medicine system can not normally work even.
Through the setting of input device, this intelligence medicine system can accept manual regulation on the basis of automatic execution adds the medicine operation, when the customer has other proruption demands, can adopt modes such as manual input medicine parameter, realizes the direct control to intelligent medicine system.
In some embodiments, the smart medicating system further comprises a data storage device for storing historical information including, but not limited to, at least one of:
the system comprises a dosing time, a water quality parameter, an alum blossom characteristic, an alum blossom image, a dosing parameter suggested this time, an execution dosing parameter, dosing parameter adjustment information, water quality parameter adjustment information, an acquisition time of the dosing parameter adjustment information, an acquisition time of the water quality parameter adjustment information, an input source of the dosing parameter adjustment information and an input source of the water quality parameter adjustment information.
In the related art, the dosing process usually depends on manual judgment and manual dosing, so that dosing parameters, reflected results and the like cannot be recorded in various data, and subsequent analysis cannot be carried out on the dosing parameters in a quantitative optimization mode. In the embodiment of the invention, historical information is recorded, so that related technicians can be effectively helped to analyze the historical dosing condition, find problems in time and adjust the problems according to data statistics results. For example, based on the error analysis of the executed dosing parameters and the current recommended dosing parameters over a period of time, if the dosing amount in each current recommended dosing parameter is less than the dosing amount of the executed dosing parameters, the preference of the operator controlling the intelligent dosing system can be obtained to hopefully use the least dose, so that the correlation model can be adjusted based on the analysis result to reduce the dosing amount in the dosing parameters corresponding to the water quality parameters and the alum blossom characteristics.
Optionally, the dosing time may be the time for starting dosing, the time for finishing dosing, or a time period from starting dosing to finishing dosing, which can be selected by a person skilled in the art as needed.
Optionally, the information for each dosing operation is stored separately, for example by correlating the identification code or directly correlating the dosing time for subsequent analysis.
Optionally, the time for acquiring the dosing parameter adjustment information and the time for acquiring the water quality parameter adjustment information may be determined based on the time of the intelligent dosing system itself or the network time.
Optionally, the input source of the dosing parameter adjustment information and the input source of the water quality parameter adjustment information may be determined by the account number registered by the control system of the current intelligent dosing system, the dosing parameter adjustment information, the input information filled when the water quality parameter adjustment information is input, and the like.
Optionally, the history information is stored, so that the history processing result of the intelligent dosing system can be traced, the execution effect of the intelligent dosing system can be counted according to the history information, and the intelligent dosing system can be conveniently adjusted and overhauled.
In some embodiments, the smart medicating system further comprises a data transmission device for transmitting the historical information.
Optionally, the data sending device may send the corresponding history information in a targeted manner according to the data request. For example, if the dosing time, the water quality parameter, the alum blossom characteristics, and the alum blossom image information from 1 month and 1 day to 1 month and 30 days are requested, the transmitting device may extract the corresponding history information from the data storage device and transmit the history information to the corresponding requesting device.
Optionally, the historical information sent by the data sending device may be all the historical information of a certain time period, or may be some types of historical information selected by a user or set by default by the system, for example, drug adding parameters and water quality parameters selected to be derived in the last month.
In some embodiments, the apparatus further comprises a prompting device for at least one of:
prompting to clean the acquisition window at preset time intervals;
the collection device comprises a water quality collection device, and if the water quality parameters collected by the water quality collection device are empty, the abnormal collection of the water quality parameters is prompted.
Optionally, the prompting device includes, but is not limited to, at least one of a display screen, a speaker, an indicator light, and the like.
For example, a message prompt is displayed through a display screen, a prompt message is voice-broadcasted through a speaker, a prompt is indicated through an indicator light, and the like.
Optionally, the prompting device comprises a touch screen, and after the touch screen displays the prompting message, the user is guided to execute preset operation on the touch screen, for example, the touch screen prompts that the acquisition window is clean, and at the moment, the touch screen also prompts that the user clicks the screen to start acquiring the window to be clean, so that the operation of the user is facilitated, and the operation is more convenient and faster.
In some embodiments, the wastewater treatment system further comprises a display device for displaying water treatment information including, but not limited to, at least one of:
alum blossom images, alum blossom characteristic information, alum blossom image recognition results, water quality parameters, last dosing parameters, rationality, execution dosing parameters, dosing parameter-time trend within a preset time period, water quality parameter-time trend within a preset time period, and a dosing pool effect graph.
Optionally, the water treatment information may be real-time information or historical information, or the real-time information and the historical information are displayed at the same time, which is not limited herein.
Optionally, the alum blossom image can be a photo or a video.
Optionally, the alum blossom feature information may be obtained by classifying and labeling alum blossom features in advance, and displaying corresponding alum blossom feature information identification information.
Optionally, the dosing execution parameter may be any one of the last dosing parameter, the current suggested dosing parameter, and the dosing execution parameter adjusted according to the dosing parameter adjustment information.
Optionally, the last dosing parameter and the current suggested dosing parameter may be displayed simultaneously, and the user may adopt the current suggested dosing parameter as the executed dosing parameter directly as required, or may input the dosing parameter adjustment information to obtain the executed dosing parameter according to the dosing parameter adjustment information.
Optionally, the results with rationality "reasonable" and "unreasonable" are displayed differently, for example, the "unreasonable" is highlighted in red.
Optionally, the dosing parameter time trend within the preset time period includes at least one of the last dosing parameter, the current suggested dosing parameter, and the executed dosing parameter within the preset time period, which are displayed as a line graph or a bar graph according to the time sequence.
Optionally, the effect graph of the dosing tank can display the structure of the dosing tank in a modeling manner.
Optionally, the time trend of the water quality parameters in the preset time period includes that one or more water quality parameters in the preset time period are displayed as a line graph or a bar graph according to a time sequence.
Optionally, the dosing parameter time trend in the preset time period and the water quality parameter time trend in the preset time period may adopt a duplex coordinate axis and be displayed in the same icon.
In some embodiments, the water quality parameter includes a water quality qualification determination parameter, and the intelligent dosing system further includes a function adjusting device, and if the water quality qualification determination parameter is greater than a preset qualification threshold, the executed dosing parameter includes the current recommended dosing parameter for adjusting the correlation model.
Optionally, the water quality qualification judgment parameter includes the turbidity of the outlet water of the dosing tank, at this time, if the turbidity of the outlet water of the dosing tank is too high, the qualification threshold is excessively preset, obviously, the problem of insufficient dosing amount exists, which indicates that the current suggested dosing parameter determined based on the correlation model is not accurate, therefore, the correlation model can be adjusted in real time through the function adjusting device, the dosing amount in the output current suggested dosing parameter is improved, so as to prevent the following rationality judged based on the correlation model and the provided current suggested dosing parameter continuity error from affecting the treatment effect of the sewage treatment system.
The correlation model is adjusted in real time in the working process, the treatment quality of the intelligent dosing system can be further improved, and when the condition of sewage is different from the training set in the training process of the correlation model by a large margin, the correlation model can also be adjusted by using the current operation result, so that the system is more flexible, and the application range is wider.
Optionally, the intelligent dosing system provided by the embodiment of the invention can be applied to water treatment processes in a plurality of fields such as industry and municipal administration.
In some embodiments, the input device, the prompt device and the display device may be integrated on the touch screen, the dosing parameter adjustment information and/or the water quality parameter adjustment information may be input by clicking or sliding the touch screen, and the display information may be displayed on the touch screen to prompt the user.
The embodiment of the invention provides an intelligent dosing system, which comprises an acquisition device for acquiring alum blossom images and water quality parameters, an association model for determining association relations among alum blossom characteristics, water quality parameters and dosing parameters according to the alum blossom characteristics and the water quality parameters, a dosing parameter determination device for judging reasonability of the last dosing parameters under the current water quality parameters, and a dosing device for executing dosing operation.
The embodiment of the invention also provides a water treatment system, which comprises the intelligent dosing system based on image recognition and data mining.
The relevant benefits of the water treatment system can be seen from the above description of the intelligent dosing system, and are not described in detail here.
The intelligent dosing system provided by the above embodiments is further illustrated by a specific embodiment below.
Referring to fig. 4, the intelligent dosing system for realizing unmanned intelligent dosing for water treatment based on image recognition and data mining technology provided by the invention comprises a camera 9 as an image acquisition device, a plurality of sensors 10 as a water quality acquisition device, a display screen 11 integrated with a prompt device and a display device, a dosing device 12, a processor 13 as a dosing parameter determination device, and an input device 14.
Referring to fig. 5, the specific smart dosing system operates in the following manner:
s501: and logging in the account, and entering a control page for operation.
Optionally, the browser can be used for opening a website to enter an account login page of the control system of the intelligent dosing system, logging in by using an account password, and entering the console for operation after successful logging in. And the account login of the intelligent dosing system can also be realized by using a client and the like.
Optionally, the control page displayed after login may be as shown in fig. 6, and the top operation bar includes real-time monitoring, historical data, identification information and user head portrait. Identification information includes, but is not limited to, a smart dosing system logo, a customer logo, a Segma logo, and the like. After the real-time monitoring is selected, switching the display page to a real-time monitoring page; after the historical data is selected, switching the display page to a historical data page; and after the head portrait of the user is selected, a quit prompt box pops up, and the relevant software of the sewage treatment system can quit by selecting the prompt box. With continued reference to fig. 6, the real-time monitoring page (page below the top operating bar) includes the underwater image, the image recognition result, the dosing parameter setting, the image parameter and the water quality parameter.
S502: and acquiring an alum blossom image by a camera.
Optionally, underwater alum blossom images and real-time underwater videos are obtained through a camera.
S503: and checking an image recognition result and reminding the camera to clean.
Optionally, the image recognition result is clicked and viewed on the real-time monitoring interface.
As shown in fig. 7, a user may view a real-time underwater image 701 and an image recognition result 702 therein.
With continued reference to fig. 7, a setting control is further included above the interface of the real-time underwater image 701, the frequency of cleaning the camera can be set, and when the set time arrives, a pop-up camera is popped up to clean a pop-up window to remind of cleaning the camera, as shown by a pop-up box 610 in fig. 6.
S504: and (5) displaying relevant dosing parameters.
Referring to fig. 8, the display device displays the dosing related parameters in a centralized manner, the dosing related parameters include two types, namely a flocculant and a coagulant, the dosing related parameters include the last dosing parameter, namely the "current dosing amount" in fig. 8, the rationality, namely the "proper or not" in fig. 8, and the current suggested dosing parameter, namely the "suggested dosing amount" in fig. 8. Wherein the rationality is determined based on a correlation model.
Meanwhile, the medicine adding device also comprises an input control 801, and after a user clicks the input control for manually adjusting the text sample, medicine adding parameter adjusting information can be input through an input device.
S505: the reaction time was confirmed.
Optionally, the user is prompted to confirm the medicament reaction time, and the user may set the medicament reaction time by himself, for example, 20 minutes.
Optionally, the water quality parameter used for judging the rationality is related to the reaction time, and if the reaction time is set to be 20 minutes, the water quality parameter obtained at an interval of 20 minutes after the dosing is taken as a reference basis for judging the rationality. Therefore, the reaction time is reasonably set, the judgment of rationality can be effectively promoted, and the quality and the efficiency of water quality treatment are further promoted.
S506: adjusting the dosing mode.
Optionally, the sewage treatment system provides a way for a user to select and adjust a dosing mode. The system provides two dosing modes of manual adjustment and system automatic adjustment, the user automatically fills and adjusts dosing parameters through the input device in the manual mode, and then adjustment of executed dosing parameters is achieved, the system calculates proper current recommended dosing parameters in the automatic mode, and the current recommended dosing parameters are directly used as the executed dosing parameters to be automatically added.
S507: choose whether to ignore the reaction time.
Optionally, the user may also choose whether to ignore the reaction time. In the medicament reaction time, namely after the last dosing is finished, due to the fact that a certain reaction time is set in front of the system, the reasonability judgment cannot be carried out at the moment, and a user can choose to ignore the reaction time or not to ignore the reaction time in the reaction tongue tip.
S508: and judging the rationality.
If the reaction time is not ignored, the processor can start the rationality judgment work after the set reaction time, and the rationality of the last medicine adding parameter (medicine adding amount) is determined by adopting the real-time water quality parameter and alum blossom characteristics based on the correlation model.
If the reaction time is neglected, the water quality parameters and the alum blossom images are collected immediately, and the rationality of the last dosing parameters is determined by the processor based on the water quality parameters, the alum blossom characteristics and the correlation model.
S509: and (5) displaying alum blossom characteristic information.
Optionally, the user may view the latest alumen ustum feature information, that is, the user may view the current image parameter. An interface for displaying image recognition parameters is shown in fig. 9, and the image parameters may include several ones, which are not limited herein. In addition, the interface only provides parameter information, and the parameter information is a preset visual label corresponding to the alum blossom characteristics.
S510: and setting a water quality parameter source.
Optionally, the water quality parameters are obtained, the sewage treatment system provides an automatic mode and a manual mode, the data of the water quality parameters in the automatic mode directly come from the sensor, the water quality parameters transmitted by the sensor cannot be received in the manual mode, the water quality parameter adjustment information is input by the input device, and the water quality parameters are adjusted by the water quality parameter adjustment information to obtain new water quality parameters.
S511: and acquiring water quality parameters.
Optionally, in the process of obtaining the water quality parameters, if the water quality parameters are successfully obtained, a popup window prompts that the water quality parameters are successfully obtained, and if the water quality parameters are unsuccessfully obtained, a failure prompt is generated.
S512: and (5) displaying the water quality parameters.
Referring to fig. 10, a user may be presented with current water quality parameters and modify them.
The water quality parameter adjustment information is input by clicking the water quality parameter editing pop-up panel through the input device to adjust the water quality parameters, as shown in fig. 10.
And clicking the water quality qualified standard popup box by a user to adjust the effluent turbidity qualified value of the intelligent dosing tank in the water quality parameters.
S513: and viewing and analyzing historical information.
Optionally, the user may perform historical information viewing and historical information analysis.
Optionally, the user can view the dosing parameter time trend graphs of the coagulant and the flocculant through a historical data interface. The last week of data may be presented by default and the span range may be set to a maximum of one month.
Optionally, the user can check the history of each adjustment time node, including the alum blossom image and the water quality parameter, and execute the dosing parameter, the current suggested dosing parameter, the last dosing parameter and the like.
Optionally, the executed dosing parameter, the current suggested dosing parameter and the last dosing parameter all include a dosing name, a dosing amount and the like.
S514: and (4) deriving historical information.
Alternatively, the user may perform the derivation of the data.
And (4) clicking a data export button by a user to pop up time span screening, exporting the data selected according to the time span game, wherein the default time span of the system is one month.
S515: and displaying the information to be displayed on a large screen.
Optionally, the intelligent dosing system can display the water treatment information on a large screen through a display device.
As shown in fig. 11, the display device displays the effect diagram of the dosing tank in a large-screen display mode, the data of the currently added flocculant and coagulant, the data of saved medicament, the saving proportion, the water quality standard reaching rate and the water quality improvement rate in the same month and other information.
With continued reference to fig. 11, the display device will present the underwater image, the image recognition result, the current water quality assessment and the image information in a large screen presentation.
With reference to fig. 11, the display device displays the intelligent decision information and the drug dosing comparison record in a large-screen display manner, and the intelligent decision information displays the current dosing amount (last dosing parameter), the suggested dosing amount (present suggested dosing parameter), and the decision result (rationality). And determining the medicine adding parameters, and simultaneously executing the medicine adding parameters to be sent to the medicine adding device, directly adjusting the medicine adding parameters, and performing medicine adding operation.
The embodiment of the invention provides a specific intelligent dosing system based on image recognition and data mining, which is characterized in that underwater images (videos and photos) and alum blossom images are collected through a camera; the camera of the camera is timely cleaned through the prompt of the display screen; the control of dosing parameters is realized through the processor, specifically, the dosing process is realized, a correlation model among water quality parameters, alum blossom characteristics and the dosing parameters is established through a big data technology to obtain the correlation model, the self-adaptive adjustment adjusting device is established based on a deep neural network technology, and the correlation model can be adjusted when the water quality qualification judgment parameters are larger than a preset qualification threshold value in time. In addition, the sewage treatment system also provides an automatic mode which takes the medicine adding parameter suggested this time as an execution medicine adding parameter, directly executes medicine adding operation according to the medicine adding parameter suggested this time, inputs medicine adding parameter adjustment information through an input device, adjusts the execution medicine adding parameter, and executes the medicine adding operation according to the adjusted execution medicine adding parameter.
Optionally, the sewage treatment system further provides a data processing function, the historical information can be stored through the data storage device, meanwhile, the historical information can be effectively backtracked, the historical information is analyzed, and sending of the historical information is supported, namely the historical information is exported.
Optionally, the intelligent dosing system provided by the embodiment of the invention applies an image recognition technology, a big data technology and a neural network technology to the traditional artificial dosing process for water treatment, greatly reduces the main working experience of control dosing technicians and the influence of elements on the water treatment result, and realizes an efficient, rapid and intelligent dosing process for water treatment. Meanwhile, the invention has wide application scenes and can be applied to water treatment processes in various fields of industry, municipal administration and the like.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. The utility model provides an intelligence medicine system based on image recognition and data mining which characterized in that includes:
the acquisition device is used for acquiring alum blossom images and water quality parameters;
the correlation model is used for determining the correlation among the alum blossom characteristics, the water quality parameters and the dosing parameters according to the alum blossom characteristics and the water quality parameters;
the dosing parameter determining device is used for obtaining a last dosing parameter corresponding to a last dosing operation, determining alum blossom characteristics according to the alum blossom image, and judging the rationality of the last dosing parameter according to the alum blossom characteristics, the water quality parameter and the correlation model;
and the dosing device is used for taking the last dosing parameter as an execution dosing parameter when the judgment result is reasonable, and executing dosing operation according to the execution dosing parameter.
2. The intelligent dosing system based on image recognition and data mining as claimed in claim 1, wherein when the determination result is reasonable and unreasonable, the suggested dosing parameters are determined according to the alum blossom characteristics, the water quality parameters and the correlation model;
and taking the recommended medicine adding parameter as an execution medicine adding parameter, and executing medicine adding operation according to the execution medicine adding parameter.
3. The intelligent dosing system based on image recognition and data mining of claim 1, wherein determining the reasonability of the last dosing parameter according to the alum blossom characteristics, the water quality parameter and the correlation model comprises:
determining the suggested medicine adding parameters according to the alum blossom characteristics, the water quality parameters and the correlation model;
acquiring the difference between the last dosing parameter and the current suggested dosing parameter;
if the difference is less than or equal to a preset difference threshold value, the judgment result is reasonable;
and if the difference is larger than a preset difference threshold value, judging that the result is unreasonable.
4. The intelligent dosing system based on image recognition and data mining of claim 1, further comprising an input device for at least one of:
acquiring dosing parameter adjusting information, and adjusting the executed dosing parameters according to the dosing parameter adjusting information;
and acquiring water quality parameter adjustment information, and adjusting the water quality parameters according to the water quality parameter adjustment information.
5. The intelligent dosing system based on image recognition and data mining as claimed in claim 1, wherein the collection device comprises an image collection device, the image collection device comprises a collection window, a cleaning arm and a cleaning scraping strip, and if the collection window needs to be cleaned, the cleaning arm drives the cleaning scraping strip to scrape off attachments on the surface of the collection window.
6. The intelligent dosing system based on image recognition and data mining of claim 4, further comprising a data storage device for storing historical information, the historical information comprising at least one of:
the system comprises a dosing time, a water quality parameter, an alum blossom characteristic, an alum blossom image, a dosing parameter suggested this time, an execution dosing parameter, dosing parameter adjustment information, water quality parameter adjustment information, an acquisition time of the dosing parameter adjustment information, an acquisition time of the water quality parameter adjustment information, an input source of the dosing parameter adjustment information and an input source of the water quality parameter adjustment information.
7. The intelligent dosing system based on image recognition and data mining of any one of claims 1-6, further comprising a prompting device for at least one of:
prompting to clean the acquisition window at preset time intervals;
the collection device comprises a water quality collection device, and if the water quality parameters collected by the water quality collection device are empty, the collection of the water quality parameters is prompted to be abnormal.
8. The intelligent dosing system based on image recognition and data mining of any one of claims 1-6, further comprising a display device for displaying water treatment information, the water treatment information comprising at least one of:
alum blossom images, alum blossom characteristic information, alum blossom image recognition results, water quality parameters, last dosing parameters, rationality, execution dosing parameters, dosing parameter time trend in a preset time period, water quality parameter time trend in a preset time period and dosing pool effect graphs.
9. The intelligent dosing system based on image recognition and data mining as claimed in any one of claims 1 to 6, wherein the water quality parameter comprises a water quality qualification determination parameter, the intelligent dosing system further comprises a function adjustment device, and if the water quality qualification determination parameter is greater than a preset qualification threshold, the executed dosing parameter comprises the current recommended dosing parameter for adjusting the correlation model.
10. A water treatment system comprising an intelligent dosing system based on image recognition and data mining as claimed in any one of claims 1 to 9.
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