CN114506981A - Sewage treatment plant integrates based on degree of depth learning - Google Patents

Abstract

The invention belongs to the technical field of sewage treatment devices, and particularly relates to an integrated sewage treatment device based on deep learning. The invention divides the pollutants into large groups and small groups according to the treatment modes and multidimensional conditions of different pollutants, and searches the optimal current of the corresponding treatment small groupDensity, pH concentration, H₂O₂The concentration and PMS concentration are adjusted to the traditional chemical electrode and biochemical electrode voltage through a kit and a variable power supply, and each group of pollutants in the sewage is accurately and efficiently treated.

Description

Sewage treatment plant integrates based on degree of depth learning

Technical Field

The invention belongs to the technical field of sewage treatment devices, and particularly relates to an integrated sewage treatment device based on deep learning.

Background

At present, a plurality of sewage treatment plants adopt a set of traditional treatment methods, have no pertinence to pollutants, occupy the improvement capacity, shorten the effective retention time, increase the energy consumption, need a large amount of water power and electric energy and form a vicious circle. When the content of part of pollutants is too much and the pollutants cannot be treated at one time, the existing sewage treatment method is to continuously and circularly carry out treatment at a certain stage, and extra electric energy and chemical feeding materials are consumed when a whole set of flow is carried out. And at present, a sewage treatment plant still needs a large amount of manual work, so that the problem of missing of technicians is caused, and the sewage treatment efficiency is reduced and the sewage treatment plant cannot be overhauled in time.

Disclosure of Invention

Aiming at the technical problems of no pertinence to pollutants, high energy consumption and large labor amount of many sewage treatment plants, the invention provides the deep learning-based integrated sewage treatment device which is high in pertinence to pollutants, low in energy consumption and high in intelligence.

In order to solve the technical problems, the invention adopts the technical scheme that:

the utility model provides a sewage treatment plant integrates based on degree of depth study, includes detection room, kit, electrode room, intergrowth room, filter chamber, the kit sets up in the detection room, the electrode room is linked together with the intergrowth room, the detection room passes through the pipeline and is connected with the electrode room, the intergrowth room passes through the pipeline and is connected with the filter chamber, the filter chamber passes through the pipeline and is connected with the electrode room.

The indoor sensor probe that is provided with of detection, sensor probe has the singlechip through wire electric connection, the singlechip adopts STM32F103ZET6 chip, singlechip electric connection has power module, power module connects on the 220V power supply, electric connection has the display screen on the singlechip, the singlechip is connected with the server through wireless communication mode, the server passes through wireless communication mode and connects at the user side.

The kit comprises an acidity regulation kit, an alkalinity regulation kit and H₂O₂Regulating kit and PMS regulating kit, and acidity regulating kit, alkalinity regulating kit and H₂O₂The adjusting kit and the PMS adjusting kit are respectively provided with a first solenoid valve, the first solenoid valve is electrically connected with a second relay, and the second relay is electrically connected to the single chip microcomputer.

An electrode fixing frame is arranged in the electrode chamber, 50 porous carbon electrodes are arranged on the electrode fixing frame, 25 porous carbon electrodes are connected with a first variable power supply, and the 25 porous carbon electrodes apply 1.2-2.2V voltage through the first variable power supply to form a traditional chemical electrode; wherein 10 porous carbon electrodes are connected with a second variable power supply, and the 10 porous carbon electrodes form a biochemical electrode by applying 0.5-1.1V voltage through the second variable power supply; wherein 15 porous carbon electrodes are connected with first variable power supply and second variable power supply respectively, be connected with first relay between 15 porous carbon electrodes and first variable power supply, the second variable power supply, constitute variable electrode, the contact of first relay is the single-pole double-throw contact, two outputs of the single-pole double-throw contact of first relay are connected with first variable power supply, second variable power supply respectively, first relay electric connection is on the singlechip.

Be provided with bayonet grid in the intergrowth room, be provided with natural pasture and water in the bayonet grid, hang on the lateral wall of intergrowth room and be equipped with the artifical pasture and water that has soaked the algae liquid.

The bottom of the symbiotic chamber is provided with an aeration device, the aeration device adopts low-pressure low-speed oxygen supply, and the side wall of the symbiotic chamber is provided with a lamp post and a constant temperature controller.

The utility model discloses a water pump, including electrode room and detection room, be provided with the water pump on the pipeline between electrode room and the detection room, be provided with the water inlet on the detection room, be provided with the second solenoid valve on the water inlet of detection room, be provided with the third solenoid valve on the pipeline between intergrowth room and the filter chamber, be provided with three delivery port on the detection room, it is three be provided with the fourth solenoid valve on the delivery port respectively, second solenoid valve electric connection has the third relay, third solenoid valve electric connection has the fourth relay, fourth solenoid valve electric connection has the fifth relay, third relay, fourth relay and fifth relay all pass through wire electric connection on the singlechip.

The device comprises a water inlet, a water diversion tank, a floating plant, an emergent aquatic plant, a power supply device, a detection chamber, an electrode chamber, a symbiotic chamber and an algae water plant recycling device, wherein the outer side of the water inlet is connected with the water diversion tank, the floating plant and the emergent aquatic plant are arranged in the water diversion tank, plants in the water diversion tank and the symbiotic chamber are taken out and placed in the algae water plant recycling device, the algae water plant recycling device is connected with the power supply device through a methane generator, the power supply device is connected with a solar power generation panel, and the power supply device is electrically connected with the detection chamber, the electrode chamber, the symbiotic chamber and the algae water plant recycling device respectively.

Two groups of membrane assemblies are arranged in the filtering chamber, one group of membrane assemblies adopts a nanofiltration membrane, and the other group of membrane assemblies adopts a reverse osmosis membrane.

A treatment method of an integrated sewage treatment device based on deep learning comprises the following steps:

s1, detecting the pollutant types, pollutant concentration, pH concentration and H of the sewage in the detection room₂O₂Concentration and PMS concentration;

s2, carrying out large-class grouping on the pollutants according to different pollutant treatment modes, wherein the treatment modes comprise traditional chemical electrode treatment and biochemical electrode treatment, and the two treatment modes are respectively a large group and a rootThe variable electrode in the electrode chamber is regulated and controlled according to the proportion of heavy metal ions and organic matters in the sewage, so that the traditional chemical electrode and the biochemical electrode in the electrode chamber reach the optimal proportion; the current density, voltage, pH concentration and H are comprehensively considered under each treatment mode₂O₂Under the multidimensional conditions of concentration and PMS concentration, finding out pollutants with similar optimal treatment conditions as a small group;

s3, adjusting the pH value to the optimum pH value of one subgroup in S2, and searching the optimum current density, pH concentration and H of the corresponding treatment subgroup₂O₂Concentration and PMS concentration;

s4, carrying out pH and H treatment on sewage through a kit₂O₂And PMS regulation;

s5, enabling the sewage to enter an electrode chamber, and respectively adjusting the voltage of the traditional chemical electrode and biochemical electrode through a first variable power supply and a second variable power supply according to the optimal current density of heavy metal ions and organic matters in the corresponding treatment group; correspondingly controlling a first variable power supply of the traditional chemical electrode, and adjusting the voltage of the traditional chemical electrode to the optimum voltage of the heavy metal ions in the corresponding processing group; correspondingly controlling a second variable power supply of the biochemical electrode, adjusting the voltage of the biochemical electrode to the optimum voltage of the organic matters in the corresponding treatment group, and simultaneously treating the heavy metal ions and the organic matters in the corresponding treatment group in the electrode chamber;

s6, entering a detection chamber again to detect whether the pollutants of one group reach the pretreatment standard, if so, entering a step S3 to circularly remove the pollutants of the next group until the pollutants of all groups reach the pretreatment standard, and entering a step S7; if the preprocessing standard is not met, returning to the step S4;

s7, adjusting the pH value of the sewage to be neutral through a kit, and then performing filtration circulation through a membrane module, an electrode chamber and a symbiotic chamber;

s8, detecting in a detection chamber, detecting whether the sewage reaches the discharge standard, and discharging if the sewage reaches the discharge standard; if the emission standard is not met, the process returns to step S2.

Compared with the prior art, the invention has the following beneficial effects:

1. the invention carries out the large-class grouping on the pollutants according to the treatment modes of different pollutants, wherein the treatment modes comprise the traditional chemical electrode treatment and the biochemical electrode treatment, the two treatment modes are respectively a large group, and the variable electrode in the electrode chamber is regulated and controlled according to the proportion of heavy metal ions and organic matters in the sewage, so that the traditional chemical electrode and the biochemical electrode in the electrode chamber reach the optimal proportion; the current density, voltage, pH concentration and H are comprehensively considered under each treatment mode₂O₂Multidimensional conditions of concentration and PMS concentration, searching for pollutants with similar optimal treatment conditions as a group, and then treating the pH and H of the corresponding treatment group by using a kit₂O₂And PMS, regulating the voltages of the traditional chemical electrode and biochemical electrode respectively by a first variable power supply and a second variable power supply according to the optimal current densities of the heavy metal ions and the organic matters in the corresponding treatment group; correspondingly controlling a first variable power supply of the traditional chemical electrode, and adjusting the voltage of the traditional chemical electrode to the optimum voltage of the heavy metal ions in the corresponding processing group; and correspondingly controlling a second variable power supply of the biochemical electrode, adjusting the voltage of the biochemical electrode to the optimal voltage of the organic matters in the corresponding treatment group, and simultaneously treating the heavy metal ions and the organic matters in the corresponding treatment group in the electrode chamber.

2. The invention adopts intelligent analysis, incorporates deep learning algorithm, adopts full automatic design and does not need professional operation. According to the invention, a full-automatic detection system is designed through the app and the monitoring platform, and when a problem occurs, the problem is displayed through the display screen, so that intelligent analysis and prediction, efficient decision analysis and remote data synchronization are realized. Except maintenance and reloading, other parts of the whole device do not need manpower, and the labor consumption is reduced.

3. The invention can estimate the content of each pollutant in water in a period of time in the future, so that a user can calculate the consumption of each raw material in the period of time in the future and the demand of personnel in advance, namely, the advance of the available time can be used for timely adjusting the project.

4. According to the invention, a large amount of data of pollutant treatment results under different conditions are collected by methods such as paper checking, experimental testing and the like. On the basis of big data, fitting methods such as cubic spline interpolation and the like and four-parameter fitting and the like are carried out, so that a pollutant treatment result under a specific condition is obtained. Meanwhile, the invention adopts deep learning and other machine learning methods to predict the future water quality, and uses the online learning idea to update the model in stages so as to expand the data set and improve the prediction precision. While the complexity of the model is guaranteed, regularization methods such as weight attenuation and temporary regression are tried to be adopted, overfitting is weakened as much as possible, and generalization capability is improved. The combination of the water purification system and the internet ensures that the system can normally run under different water qualities and different watersheds, and the possibility of guarantee and quick realization is provided, so that the system has universality.

5. The invention integrates and analyzes the result by utilizing big data, and the product can be analyzed in a short time on the whole idea of separating the acidic and alkaline pollutant treatment, thereby saving the cost and ensuring the decision of the removal rate. The function ensures the practicability of the whole set of system as a whole.

6. The symbiotic chamber treats nitrogen N and phosphorus P pollutants in sewage by utilizing the eutrophication of the artificial waterweeds and the natural waterweeds soaked with the algae liquid through the combination of the artificial waterweeds and the natural waterweeds soaked with the algae liquid; in addition, the water inlet of the device is connected with the water diversion tank, and various pollutants are treated by floating plants and emergent plants planted in the water diversion tank, so that the purification range is further widened.

7. The water outlet of the invention has three branches, the first water outlet reaches the discharge standard and directly discharges the treated water; the second water outlet reaches the irrigation standard, and the discharged water is used for agricultural irrigation; the third reaches the drinking standard from the water outlet, and the discharged water is used for daily drinking, so that the discharged sewage can meet various requirements.

8. The invention detects the sewage through a sensor probe in a detection room, and the sewage is detected through an acidity regulation kit, an alkalinity regulation kit and H according to the detection result₂O₂Conditioning kit and PMThe S regulating kit respectively regulates pH and H₂O₂The optimal condition of the PMS improves the sewage treatment efficiency, and the pH of the sewage is adjusted to be neutral before the sewage enters the filtering chamber so as to protect a membrane component in the filtering chamber from being damaged and prolong the service life of the membrane component.

9. According to the invention, plants in the drainage pool and the symbiotic chamber are taken out and placed in the algae float grass recycling device, the algae float grass recycling device extracts the extracting solution of the algae float grass by a squeezing method, and a part of the extracting solution is used for promoting seed germination, so that the method is beneficial to agriculture; the other part of the extracting solution is added with animals and straws for biogas fermentation, the power is transmitted to a power supply device through a biogas generator, and the remainder of the biogas fermentation is used as a bio-fertilizer, thereby being beneficial to agriculture. The power supply device adopts the methane generator and the solar power generation panel to supply power, and the power supply device transmits the power into the sewage treatment device, so that the recyclable utilization of the energy is realized.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.

The structures, ratios, sizes, and the like shown in the present specification are only used for matching with the contents disclosed in the specification, so that those skilled in the art can understand and read the present invention, and do not limit the conditions for implementing the present invention, so that the present invention has no technical significance, and any structural modifications, changes in the ratio relationship, or adjustments of the sizes, without affecting the functions and purposes of the present invention, should still fall within the scope of the present invention.

FIG. 1 is a block diagram of the overall structure of the present invention;

FIG. 2 is a circuit diagram of the single chip microcomputer control circuit of the present invention;

FIG. 3 is a schematic structural view of the present invention;

figure 4 is a schematic structural view of the filtering chamber of the present invention;

FIG. 5 is a schematic view of the construction of the symbiotic base of the present invention;

FIG. 6 is a general flow chart of the present invention;

FIG. 7 is a flow chart of deep learning according to the present invention;

FIG. 8 is a block diagram of data analysis in accordance with the present invention.

Wherein: 1 is a detection chamber, 2 is a kit, 3 is an electrode chamber, 4 is a symbiotic chamber, 5 is a filter chamber, 6 is a singlechip, 101 is a sensor probe, 201 is an acidity regulation kit, 202 is an alkalinity regulation kit, and 203 is H₂O₂The regulating kit comprises a PMS regulating kit 204, an electrode fixing frame 301, a porous carbon electrode 302, a first relay 303, a first electromagnetic valve 205, a second relay 206, an insertion type grid 401, a natural aquatic weed 402, a water pump 7, a water inlet 102, a second electromagnetic valve 103, a third electromagnetic valve 8, a water outlet 501, a fourth electromagnetic valve 502, a third relay 104, a fourth relay 9, a fifth relay 503, a membrane assembly 504, a power module 601, a diversion basin 10, an algae aquatic weed recycling device 11, a power supply device 12, a solar power generation panel 13 and a methane generator 14.

Detailed Description

To make the objects, technical solutions and advantages of the embodiments of the present invention clearer and more complete, the technical solutions in the embodiments of the present invention will be described below, obviously, the described embodiments are only a part of the embodiments of the present application, but not all embodiments, and the description is only for further explaining the features and advantages of the present invention, and not for limiting the claims of the present invention; all other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.

The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless otherwise specified.

Throughout the description of the present application, it is to be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood in a specific case by those of ordinary skill in the art.

As shown in fig. 1-6, sewage enters the detection chamber 1 through the water inlet 101 of the detection chamber 1, and after the sewage enters the detection chamber 1, the single chip microcomputer 6 controls the second electromagnetic valve 103 to close through the third relay 104. The sensor probe 101 in the detection chamber 1 detects the sewage, and the detected result passes through the acidity regulation kit 201, the alkalinity regulation kit 202 and the H of the kit 2₂O₂The pH and H of the adjusting kit 203 and the PMS adjusting kit 204 are respectively adjusted₂O₂PMS, and then the sewage enters the electrode chamber 3 through a pipeline. 25 porous carbon electrodes 302 in the electrode chamber 3 are applied with a voltage of 1.2-2.2V through a variable power supply to form a traditional chemical electrode, and 10 porous carbon electrodes 302 are applied with a voltage of 0.5-1.1V through the variable power supply to form a biochemical electrode; wherein 15 porous carbon electrodes 302 are connected with first variable power supply and second variable power supply respectively, connect first relay 303 between 15 porous carbon electrodes 302 and first variable power supply, the second variable power supply, the variable electrode can become traditional chemical electrode or biochemical electrode through the switch of first relay 303 single-pole double-throw contact, traditionization in the electrode room 3Heavy metal ions in the sewage are treated by the chemical electrode, organic matters in the sewage are treated by the biochemical electrode in the electrode chamber 3, and the proportion of the traditional chemical electrode to the biochemical electrode can be adjusted by the variable electrode in the electrode chamber 3 according to the proportion of the heavy metal ions and the organic matters in the sewage. Then the sewage enters the symbiotic chamber 4, and nitrogen N and phosphorus P pollutants in the sewage are treated by utilizing the eutrophication of the artificial waterweeds soaked with the algae liquid and the natural waterweeds 402 through the combination of the artificial waterweeds soaked with the algae liquid and the natural waterweeds 402. The water pump 7 between the electrode chamber 3 and the detection chamber 1 pumps the sewage back to the detection chamber 1, and the sewage is detected again through the detection chamber 1, if the sewage quality reaches the pretreatment standard, the pH of the sewage is adjusted to be neutral through the kit 2, and then the singlechip 6 controls the third electromagnetic valve 8 to be opened through the fourth relay 9, so that the sewage enters the filter chamber 5. The sewage is filtered by two groups of membrane modules 504 in the filter chamber 5, the filtered sewage returns to the detection chamber 1 through a pipeline, the standard of the sewage is judged by the detection of the detection chamber 1, the singlechip 6 controls the fourth electromagnetic valve 502 to open one of the three water outlets 501 through the fifth relay 503 according to the standard detected by the detection chamber 1, the first water outlet 201 reaches the discharge standard, and the treated water is directly discharged; the second water outlet 501 reaches the irrigation standard, and the discharged water is used for agricultural irrigation; the third reaches the water outlet 501 to the drinking standard, and the discharged water is used for daily drinking.

Further, in this embodiment, the symbiotic plants 402 in the symbiotic chamber 4 are installed on the symbiotic base 401, and energy saving and dissolved oxygen utilization are achieved by using a low-pressure low-speed oxygen supply aeration device in the symbiotic chamber 4. The temperature and the illumination in the symbiotic chamber 4 are controlled by a lamp post and a thermostatic controller in the symbiotic chamber 4 to promote the growth of organisms in the symbiotic chamber.

Further, in this embodiment, preferably, the artificial aquatic weeds have good effects on ammonia nitrogen, COD, total nitrogen and total phosphorus at a pH value of 8.0-8.5; when the dissolved oxygen concentration is within the range of 3-5mg/L, the removal efficiency of the artificial aquatic weed on COD and ammonia hydrogen is the highest; the removal rate of the artificial aquatic weed is the highest when the dissolved oxygen concentration is 6-8mg/L for the total nitrogen.

Further, in this embodiment, singlechip 6 chooses for use STM32F103ZET6 chip, and the treatment effect is better to 220V supplies power and passes through power module 601 and convert the 220V alternating current into 12V direct current, supplies power for STM32F103ZET6 chip through 12V direct current, when the problem appeared, shows the place of problem through the display screen, and realized the long-range real time monitoring and the dispatch of user's end through server and wireless network.

Further, in this embodiment, the nanofiltration membrane and the reverse osmosis membrane in the membrane module 504 deeply purify the sewage to remove the impurities that are difficult to remove finally, so as to reach the discharge standard. And the nanofiltration membrane and the reverse osmosis membrane can be replaced for three years or even more because the sewage is adjusted to be neutral before entering the filtering chamber 5.

Further, in this embodiment, the water inlet 102 is connected to the diversion basin 10, and various pollutants are treated by floating plants and emergent plants planted in the diversion basin, so that the purification range is further expanded. And the plants in the diversion basin 10 and the symbiotic chamber 4 are taken out and placed in the algae and water weed recycling device 11, the algae and water weed recycling device 11 extracts the extracting solution of the algae and water weeds by a squeezing method, one part of the extracting solution is used for promoting seed germination, the other part of the extracting solution is used for carrying out biogas fermentation by adding animals, straws and the like respectively, the power is transmitted to the power supply device 12 through the biogas generator 14, and the remainder of the biogas fermentation is used as biological fertilizer. The power supply device 12 adopts the methane generator 14 and the solar power generation panel 13 to supply power, and the power supply device 12 transmits the power into the sewage treatment device, so that the energy can be recycled.

Further, in this embodiment, preferably, because the purifying capacity of water lily is strong, the water lily is selected as the floating plant in the diversion basin 10; preferably, the emergent aquatic plants in the diversion basin 10 are selected from reed, giant reed leaves, cattail and canna.

The processing method of the present invention, as shown in fig. 7, includes the following steps: s1, detecting the pollutant types, pollutant concentration, pH concentration and H of the sewage in the detection room₂O₂Concentration and PMS concentration; s2, grouping the pollutants according to the treatment modes of different pollutants, wherein the treatment modes compriseThe method comprises the following steps of traditional chemical electrode treatment and biochemical electrode treatment, wherein the two treatment modes are respectively a large group, and a variable electrode in an electrode chamber is regulated and controlled according to the proportion of heavy metal ions and organic matters in sewage, so that the traditional chemical electrode and the biochemical electrode in the electrode chamber reach the optimal proportion; the current density, voltage, pH concentration and H are comprehensively considered under each treatment mode₂O₂Under the multidimensional conditions of concentration and PMS concentration, finding out pollutants with similar optimal treatment conditions as a small group; s3, adjusting the pH value to the optimum pH value of one subgroup in S2, and searching the optimum current density, pH concentration and H of the corresponding treatment subgroup₂O₂Concentration and PMS concentration; s4, carrying out pH and H treatment on sewage through a kit₂O₂And PMS regulation; s5, enabling the sewage to enter an electrode chamber, and respectively adjusting the voltage of the traditional chemical electrode and biochemical electrode through a first variable power supply and a second variable power supply according to the optimal current density of heavy metal ions and organic matters in the corresponding treatment group; correspondingly controlling a first variable power supply of the traditional chemical electrode, and adjusting the voltage of the traditional chemical electrode to the optimum voltage of the heavy metal ions in the corresponding processing group; correspondingly controlling a second variable power supply of the biochemical electrode, adjusting the voltage of the biochemical electrode to the optimum voltage of the organic matters in the corresponding treatment group, and simultaneously treating the heavy metal ions and the organic matters in the corresponding treatment group in the electrode chamber; s6, entering a detection chamber again to detect whether the pollutants of one group reach the pretreatment standard, if so, entering a step S3 to circularly remove the pollutants of the next group until the pollutants of all groups reach the pretreatment standard, and entering a step S7; if the preprocessing standard is not met, returning to the step S4; s7, adjusting the pH value of the sewage to be neutral through a kit, and then performing filtration circulation through a membrane module, an electrode chamber and a symbiotic chamber; s8, detecting in a detection chamber, detecting whether the sewage reaches the discharge standard, and discharging if the sewage reaches the discharge standard; if the emission standard is not met, the process returns to step S2.

As shown in fig. 8, the present invention combines the device with deep learning, internet of things, and internet to achieve the following functions:

1. monitoring real-time data:

the detection device can send data to the server and the app user side in real time through connection with the internet, and can generate corresponding pictures for visual display or propose operation suggestions after analysis. The user can grasp the whole system overall situation only through the mobile phone screen.

2. Big data integration analysis:

by means of methods such as paper checking and experimental testing, a project group collects a large amount of data of pollutant treatment results under different conditions. On the basis of big data, fitting methods such as cubic spline interpolation and the like and four-parameter fitting and the like are carried out, so that a pollutant treatment result under a specific condition is obtained. Meanwhile, the project group adopts deep learning and other machine learning methods to predict the future water quality, and uses an online learning idea to update the model in stages so as to expand a data set and improve the prediction precision. While the complexity of the model is guaranteed, regularization methods such as weight attenuation and temporary regression are tried to be adopted, overfitting is weakened as much as possible, and generalization capability is improved. The combination of the water purification system and the internet ensures that the system can normally run under different water qualities and different watersheds, and the possibility of guarantee and quick realization is provided, so that the system has universality.

4. Intelligent analysis and prediction:

the product can predict the content of each pollutant in water in a period of time in the future, so that a user can calculate the consumption of each raw material in the period of time in the future in advance, and the requirements of personnel, namely the 'lead' of available time can be adjusted and planned in time.

5. Efficient decision analysis:

by utilizing the result of big data integration analysis, on the whole thinking of separating acidic and alkaline pollutant treatment, the product can be analyzed in a very short time, so that the cost is saved, and the decision of the removal rate is ensured. The function ensures the practicability of the whole set of system as a whole.

6. Remote data synchronization:

firstly, systems in different regions share monitored data through the Internet, and a more complete data set can be obtained in a relatively short time, so that the urgent need of a deep learning prediction module for a large amount of data is relieved.

Secondly, a complete server has been developed by the project group, the server is connected with the internet, the mechanical equipment detection equipment is also connected with the internet as an intermediary for information transmission, and the internet enables the whole set of system to realize remote real-time monitoring and scheduling.

Although only the preferred embodiments of the present invention have been described in detail, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those skilled in the art, and all changes are encompassed in the scope of the present invention.

Claims (10)

1. The utility model provides a sewage treatment plant integrates based on degree of depth study which characterized in that: including detecting room (1), kit (2), electrode room (3), intergrowth room (4), filter chamber (5), kit (2) set up in detecting room (1), electrode room (3) are linked together with intergrowth room (4), detect room (1) and be connected with electrode room (3) through the pipeline, intergrowth room (4) are connected with filter chamber (5) through the pipeline, filter chamber (5) are connected with electrode room (3) through the pipeline.

2. The integrated sewage treatment device based on deep learning of claim 1, wherein: be provided with sensor probe (101) in detection room (1), sensor probe (101) have singlechip (6) through wire electric connection, singlechip (6) adopt STM32F103ZET6 chip, singlechip (6) electric connection has power module (601), power module (601) are connected on the 220V power supply, electric connection has the display screen on singlechip (6), singlechip (6) are connected with the server through wireless communication mode, the server passes through wireless communication mode and connects at the user side.

3. The integrated sewage treatment device based on deep learning of claim 1, wherein: the kit(2) Comprises an acidity regulation kit (201), an alkalinity regulation kit (202) and H₂O₂A regulating kit (203) and a PMS regulating kit (204), the acidity regulating kit (201), the alkalinity regulating kit (202), and H₂O₂The adjusting kit (203) and the PMS adjusting kit (204) are respectively provided with a first electromagnetic valve (205), the first electromagnetic valve (205) is electrically connected with a second relay (206), and the second relay (206) is electrically connected to the single chip microcomputer (6).

4. The integrated sewage treatment device based on deep learning of claim 1, wherein: an electrode fixing frame (301) is arranged in the electrode chamber (3), 50 porous carbon electrodes (302) are arranged on the electrode fixing frame (301), 25 porous carbon electrodes (302) are connected with a first variable power supply, and the 25 porous carbon electrodes (302) form a traditional chemical electrode by applying a voltage of 1.2-2.2V through the first variable power supply; wherein 10 porous carbon electrodes (302) are connected with a second variable power supply, and the 10 porous carbon electrodes (302) form a biochemical electrode by applying a voltage of 0.5-1.1V through the second variable power supply; wherein 15 porous carbon electrodes (302) are connected with first variable power supply and second variable power supply respectively, be connected with first relay (303) between 15 porous carbon electrodes (302) and first variable power supply, the second variable power supply, constitute variable electrode, the contact of first relay (303) is the single-pole double-throw contact, two outputs of the single-pole double-throw contact of first relay (303) are connected with first variable power supply, second variable power supply respectively, first relay (303) electric connection is on singlechip (6).

5. The integrated sewage treatment device based on deep learning of claim 1, wherein: an inserted grid (401) is arranged in the symbiotic chamber (4), natural aquatic weeds (402) are arranged in the inserted grid (401), and artificial aquatic weeds soaked with algae liquid are hung on the side wall of the symbiotic chamber (4).

6. The integrated sewage treatment device based on deep learning of claim 1, wherein: the bottom of the symbiotic chamber (4) is provided with an aeration device, the aeration device adopts low-pressure low-speed oxygen supply, and the side wall of the symbiotic chamber (4) is provided with a lamp post and a constant temperature controller.

7. The integrated sewage treatment device based on deep learning of claim 1, wherein: a water pump (7) is arranged on a pipeline between the electrode chamber (3) and the detection chamber (1), a water inlet (102) is arranged on the detection chamber (1), a second electromagnetic valve (103) is arranged on the water inlet (101) of the detection chamber (1), a third electromagnetic valve (8) is arranged on a pipeline between the symbiotic chamber (4) and the filter chamber (5), three water outlets (501) are arranged on the detection chamber (1), fourth electromagnetic valves (502) are respectively arranged on the three water outlets (501), the second electromagnetic valve (103) is electrically connected with a third relay (104), the third electromagnetic valve (8) is electrically connected with a fourth relay (9), the fourth electromagnetic valve (502) is electrically connected with a fifth relay (503), and the third relay (104), the fourth relay (9) and the fifth relay (503) are electrically connected to the single chip microcomputer (6) through conducting wires.

8. The integrated sewage treatment device based on deep learning of claim 7, wherein: the device comprises a water inlet (101), a water diversion tank (10) is connected to the outer side of the water inlet (101), floating plants and emergent aquatic plants are arranged in the water diversion tank (10), plants in the water diversion tank (10) and a symbiotic chamber (4) are taken out and placed in an algae aquatic weed recycling device (11), the algae aquatic weed recycling device (11) is connected with an electric power supply device (12) through a methane generator (14), the electric power supply device (12) is connected with a solar power generation panel (13), and the electric power supply device (12) is electrically connected with a detection chamber (1), an electrode chamber (3), the symbiotic chamber (4) and the algae aquatic weed recycling device (11) respectively.

9. The integrated sewage treatment device based on deep learning of claim 1, wherein: two groups of membrane assemblies (504) are arranged in the filtering chamber (5), one group of membrane assemblies (504) adopt nanofiltration membranes, and the other group of membrane assemblies (504) adopt reverse osmosis membranes.

10. The treatment method of the advanced learning-based integrated wastewater treatment plant according to any one of claims 1 to 9, wherein: comprises the following steps:

s1, detecting the pollutant types, pollutant concentration, pH concentration and H of the sewage in the detection room₂O₂Concentration and PMS concentration;

s2, grouping the pollutants according to different pollutant treatment modes, wherein the treatment modes comprise traditional chemical electrode treatment and biochemical electrode treatment, the two treatment modes are respectively a large group, and the variable electrode in the electrode chamber is regulated and controlled according to the proportion of heavy metal ions and organic matters in the sewage, so that the traditional chemical electrode and the biochemical electrode in the electrode chamber reach the optimal proportion; the current density, voltage, pH concentration and H are comprehensively considered under each treatment mode₂O₂Under the multidimensional conditions of concentration and PMS concentration, finding out pollutants with similar optimal treatment conditions as a small group;

s3, adjusting the pH value to the optimum pH value of one subgroup in S2, and searching the optimum current density, pH concentration and H of the corresponding treatment subgroup₂O₂Concentration and PMS concentration;

s4, carrying out pH and H treatment on sewage through a kit₂O₂And PMS regulation;

s5, enabling the sewage to enter an electrode chamber, and respectively adjusting the voltage of the traditional chemical electrode and biochemical electrode through a first variable power supply and a second variable power supply according to the optimal current density of heavy metal ions and organic matters in the corresponding treatment group; correspondingly controlling a first variable power supply of the traditional chemical electrode, and adjusting the voltage of the traditional chemical electrode to the optimum voltage of the heavy metal ions in the corresponding processing group; correspondingly controlling a second variable power supply of the biochemical electrode, adjusting the voltage of the biochemical electrode to the optimum voltage of the organic matters in the corresponding treatment group, and simultaneously treating the heavy metal ions and the organic matters in the corresponding treatment group in the electrode chamber;

s6, entering a detection chamber again to detect whether the pollutants of one group reach the pretreatment standard, if so, entering a step S3 to circularly remove the pollutants of the next group until the pollutants of all groups reach the pretreatment standard, and entering a step S7; if the preprocessing standard is not met, returning to the step S4;

s7, adjusting the pH value of the sewage to be neutral through a kit, and then performing filtration circulation through a membrane module, an electrode chamber and a symbiotic chamber;

s8, detecting in a detection chamber, detecting whether the sewage reaches the discharge standard, and discharging if the sewage reaches the discharge standard; if the emission standard is not met, the process returns to step S2.

Images