An integrated sewage treatment device based on deep learning

Abstract

The present invention belongs to the technical field of sewage treatment devices, and specifically relates to an integrated sewage treatment device based on deep learning, including a detection chamber, a reagent kit, an electrode chamber, a symbiotic chamber, and a filter chamber. The reagent kit is arranged in the detection chamber, the electrode chamber is connected to the symbiotic chamber, the detection chamber is connected to the electrode chamber through a pipeline, the symbiotic chamber is connected to the filter chamber through a pipeline, and the filter chamber is connected to the electrode chamber through a pipeline. The present invention divides pollutants into large groups and small groups according to the treatment methods and multi-dimensional conditions of different pollutants, and finds the optimal current density, pH concentration, H concentration, and pH concentration of the corresponding treatment group. 2 O 2 Concentration and PMS concentration, through the kit and variable power supply to adjust the voltage of traditional chemical electrodes and biochemical electrodes, each group of pollutants in the sewage can be accurately and efficiently treated.

Description

Technical Field

[0001] The present invention belongs to the technical field of sewage treatment devices, and specifically relates to an integrated sewage treatment device based on deep learning. Background Art

[0002] At present, many sewage treatment plants use a set of traditional treatment methods, which are not targeted at pollutants, occupy lifting capacity, shorten effective retention time, increase energy consumption, require a lot of hydraulic and electrical energy, and form a vicious cycle. When some pollutants are too high to be treated in one go, the existing sewage treatment method is to continue to cycle through a certain stage of treatment, and the entire process will consume additional electricity and chemical feeds. In addition, sewage treatment plants still require a lot of manual participation, resulting in a lack of technical personnel, which in turn reduces the efficiency of sewage treatment and makes it impossible to repair in time. Summary of the invention

[0003] In response to the technical problems that many of the above-mentioned sewage treatment plants have no targeted treatment of pollutants, consume a lot of energy, and require a lot of manpower, the present invention provides an integrated sewage treatment device based on deep learning that has strong targeted treatment of pollutants, low energy consumption, and high intelligence.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0005] An integrated sewage treatment device based on deep learning includes a detection chamber, a test kit, an electrode chamber, a symbiosis chamber, and a filtration chamber. The test kit is arranged in the detection chamber, the electrode chamber is communicated with the symbiosis chamber, the detection chamber is connected to the electrode chamber through a pipeline, the symbiosis chamber is connected to the filtration chamber through a pipeline, and the filtration chamber is connected to the electrode chamber through a pipeline.

[0006] A sensor probe is provided in the detection chamber, the sensor probe is electrically connected to a single-chip microcomputer through a wire, the single-chip microcomputer adopts an STM32F103ZET6 chip, the single-chip microcomputer is electrically connected to a power module, the power module is connected to a 220V power supply, the single-chip microcomputer is electrically connected to a display screen, the single-chip microcomputer is connected to a server through a wireless communication method, and the server is connected to a user end through a wireless communication method.

[0007] The kit includes an acid adjustment kit, an alkaline adjustment kit, a H2O2 adjustment kit and a PMS adjustment kit. The acid adjustment kit, the alkaline adjustment kit, the H2O2 adjustment kit and the PMS adjustment kit are respectively provided with a first solenoid valve, the first solenoid valve is electrically connected to a second relay, and the second relay is electrically connected to a single-chip microcomputer.

[0008] An electrode fixing frame is arranged in the electrode chamber, and 50 porous carbon electrodes are arranged on the electrode fixing frame, 25 of which are connected to a first variable power supply, and a voltage of 1.2-2.2V is applied to the 25 porous carbon electrodes through the first variable power supply to form traditional chemical electrodes; 10 of which are connected to a second variable power supply, and a voltage of 0.5-1.1V is applied to the 10 porous carbon electrodes through the second variable power supply to form biochemical electrodes; 15 of which are respectively connected to the first variable power supply and the second variable power supply, and a first relay is connected between the 15 porous carbon electrodes and the first variable power supply and the second variable power supply to form a variable electrode, the contact of the first relay is a single-pole double-throw contact, and the two output ends of the single-pole double-throw contact of the first relay are respectively connected to the first variable power supply and the second variable power supply, and the first relay is electrically connected to the single-chip microcomputer.

[0009] The symbiotic chamber is provided with an insertable grille, natural aquatic plants are arranged in the insertable grille, and artificial aquatic plants soaked in algae liquid are hung on the side wall of the symbiotic chamber.

[0010] An aeration device is arranged at the bottom of the symbiosis chamber, and the aeration device adopts low-pressure and low-speed oxygen supply. A lamp post and a constant temperature controller are arranged on the side wall of the symbiosis chamber.

[0011] A water pump is arranged on the pipeline between the electrode chamber and the detection chamber, a water inlet is arranged on the detection chamber, a second solenoid valve is arranged on the water inlet of the detection chamber, a third solenoid valve is arranged on the pipeline between the symbiosis chamber and the filtration chamber, three water outlets are arranged on the detection chamber, fourth solenoid valves are arranged on the three water outlets respectively, the second solenoid valve is electrically connected to a third relay, the third solenoid valve is electrically connected to a fourth relay, the fourth solenoid valve is electrically connected to a fifth relay, and the third relay, the fourth relay and the fifth relay are all electrically connected to the single-chip computer through wires.

[0012] The outer side of the water inlet is connected to a water diversion pool, and floating plants and emergent plants are arranged in the water diversion pool. The plants in the water diversion pool and the symbiotic chamber are taken out and placed in an algae and water plants recycling device. The algae and water plants recycling device is connected to a power supply device through a biogas generator, and the power supply device is connected to a solar power generation panel. The power supply device is electrically connected to the detection room, electrode room, symbiotic room and algae and water plants recycling device respectively.

[0013] Two groups of membrane components are arranged in the filtration chamber, one group of membrane components adopts nanofiltration membrane, and the other group of membrane components adopts reverse osmosis membrane.

[0014] A treatment method of an integrated sewage treatment device based on deep learning, comprising the following steps:

[0015] S1. Detect the pollutant types, pollutant concentrations, pH concentrations, H2O2 concentrations and PMS concentrations of sewage in the testing room;

[0016] S2. The pollutants are grouped into major categories according to the treatment methods of different pollutants, which include traditional chemical electrode treatment and biochemical electrode treatment. The two treatment methods are respectively a large group. The variable electrodes in the electrode chamber are regulated according to the ratio of heavy metal ions and organic matter in the sewage, so that the traditional chemical electrodes and biochemical electrodes in the electrode chamber reach the optimal ratio. Under each treatment method, the multi-dimensional conditions of current density, voltage, pH concentration, H2O2 concentration and PMS concentration are comprehensively considered, and the pollutants with similar optimal treatment conditions are found as a small group;

[0017] S3, adjusting the pH value to the optimum pH value of a group in S2, and finding the optimum current density, pH concentration, H2O2 concentration and PMS concentration of the corresponding treatment group;

[0018] S4, sewage is adjusted for pH, H2O2 and PMS through the kit;

[0019] S5, sewage enters the electrode chamber, and the voltages of the conventional chemical electrode and the biochemical electrode are adjusted respectively by the first variable power supply and the second variable power supply according to the optimum current density of the heavy metal ions and the organic matter in the corresponding treatment group; the first variable power supply correspondingly controls the conventional chemical electrode, and adjusts the voltage of the conventional chemical electrode to the optimum voltage of the heavy metal ions in the corresponding treatment group; the second variable power supply correspondingly controls the biochemical electrode, and adjusts the voltage of the biochemical electrode to the optimum voltage of the organic matter in the corresponding treatment group, and the heavy metal ions and the organic matter in the corresponding treatment group are treated simultaneously in the electrode chamber;

[0020] S6, enter the detection room again to detect whether the pollutants of a group have reached the pretreatment standard. If so, enter step S3 to cycle and remove the pollutants of the next group until all the pollutants of the groups reach the pretreatment standard, and then enter step S7; if not, return to step S4;

[0021] S7, adjusting the pH value of the sewage to neutral through the test kit, and then filtering and circulating through the membrane assembly, electrode chamber and symbiotic chamber;

[0022] S8. Perform a test in the test room to check whether the sewage meets the discharge standard. If so, discharge it; if not, return to step S2.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] 1. The present invention groups pollutants into large categories according to different treatment methods of pollutants. The treatment methods include traditional chemical electrode treatment and biochemical electrode treatment. The two treatment methods are respectively a large group. The variable electrode in the electrode chamber is regulated according to the ratio of heavy metal ions and organic matter in the sewage, so that the traditional chemical electrode and the biochemical electrode in the electrode chamber reach the optimal ratio; in each treatment method, the multi-dimensional conditions of current density, voltage, pH concentration, H2O2 concentration and PMS concentration are comprehensively considered, and pollutants with similar optimal treatment conditions are found as a group, and then the pH, H2O2 and PMS of the corresponding treatment group are adjusted through the kit. According to the optimal current density of heavy metal ions and organic matter in the corresponding treatment group, the voltage of the traditional chemical electrode and the biochemical electrode are adjusted respectively through the first variable power supply and the second variable power supply; the first variable power supply corresponding to the traditional chemical electrode is used to adjust the voltage of the traditional chemical electrode to the optimal voltage of the heavy metal ions in the corresponding treatment group; the second variable power supply corresponding to the biochemical electrode is used to adjust the voltage of the biochemical electrode to the optimal voltage of the organic matter in the corresponding treatment group, and the heavy metal ions and organic matter in the corresponding treatment group are treated in the electrode chamber at the same time.

[0025] 2. The present invention adopts intelligent analysis, deep learning algorithms, and fully automated design, and does not require professional operation. The present invention designs a fully automatic detection system through an app and a monitoring platform. When a problem occurs, the display screen shows the location of the problem, realizing intelligent analysis and prediction, efficient decision-making analysis, and remote data synchronization. Except for maintenance and material replacement, the entire device does not require manual labor, reducing manpower consumption.

[0026] 3. The present invention can estimate the content of various pollutants in water in the future, so that users can calculate the consumption of various raw materials and personnel needs in the future in advance, and adjust the planning in time by using the advance time.

[0027] 4. The present invention has collected a large amount of data on pollutant treatment results under different conditions by reviewing papers, experimental tests and other methods. On the basis of big data, interpolation methods such as cubic spline interpolation and fitting methods such as four-parameter fitting are used to obtain pollutant treatment results under specific conditions. At the same time, the present invention intends to use deep learning and other machine learning methods to predict future water quality, use online learning ideas, and update the model in stages to expand the data set and improve prediction accuracy. While ensuring the complexity of the model, it is intended to try to use regularization methods such as weight decay and temporary retreat to reduce overfitting as much as possible and improve generalization ability. The combination of the water purification system and the Internet ensures the possibility of faster realization of the system's normal operation under different water qualities and different river basins, making it universal.

[0028] 5. The present invention uses the results of big data integration and analysis. Based on the overall idea of ​​acidic and alkaline pollutant treatment, the product can analyze the decision in a very short time to save costs and ensure the removal rate. This function ensures the overall practicality of the whole system.

[0029] 6. The symbiotic chamber of the present invention combines artificial aquatic plants soaked in algae liquid with natural aquatic plants, and utilizes the eutrophication of artificial aquatic plants soaked in algae liquid and natural aquatic plants to treat nitrogen N and phosphorus P pollutants in sewage; and the water inlet of the present invention is connected to a water diversion pool, and various pollutants are treated by floating plants and emergent plants planted in the water diversion pool, thereby further improving the purification range.

[0030] 7. The outlet of the present invention has three branches. The first outlet meets the discharge standard and directly discharges the treated water; the second outlet meets the irrigation standard and the discharged water is used for agricultural irrigation; the third outlet meets the drinking standard and the discharged water is used for daily drinking, so that the discharged sewage can meet a variety of needs.

[0031] 8. The present invention detects sewage through a sensor probe in a detection chamber, and adjusts the optimal conditions of pH, H2O2, and PMS respectively through an acid adjustment kit, an alkaline adjustment kit, a H2O2 adjustment kit, and a PMS adjustment kit according to the detection results, thereby improving the sewage treatment efficiency. In addition, the present invention adjusts the pH to neutral before the sewage enters the filter chamber to protect the membrane assembly in the filter chamber from damage and extend the life of the membrane assembly.

[0032] 9. The plants in the water diversion pool and the symbiotic room of the present invention are taken out and placed in the algae and waterweed recycling device. The algae and waterweed recycling device extracts the algae and waterweed extract by squeezing. A part of the extract is used to promote seed germination, which is beneficial to agriculture; the other part of the extract is added to the animal and straw for biogas fermentation, and the power is transmitted to the power supply device through the biogas generator. The residue of biogas fermentation is used as biological fertilizer, which is beneficial to agriculture. The power supply device is powered by a biogas generator and a solar panel, and the power supply device transmits the power to the sewage treatment device, realizing the recyclable utilization of energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0034] The structures, proportions, sizes, etc. illustrated in this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with the technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantial technical significance. Any structural modification, change in proportion or adjustment of size shall still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0035] Figure 1 It is the overall structural diagram of the present invention;

[0036] Figure 2 It is a single chip microcomputer control circuit diagram of the present invention;

[0037] Figure 3 It is a structural schematic diagram of the present invention;

[0038] Figure 4 It is a structural schematic diagram of the filter chamber of the present invention;

[0039] Figure 5 This is a schematic diagram of the structure of the symbiotic base of the present invention;

[0040] Figure 6 It is the overall flow chart of the present invention;

[0041] Figure 7 A flowchart of deep learning of the present invention;

[0042] Figure 8 It is a data analysis block diagram of the present invention.

[0043] Among them: 1 is a detection chamber, 2 is a reagent kit, 3 is an electrode chamber, 4 is a symbiotic chamber, 5 is a filtration chamber, 6 is a single-chip microcomputer, 101 is a sensor probe, 201 is an acid adjustment kit, 202 is an alkaline adjustment kit, 203 is a H2O2 adjustment kit, 204 is a PMS adjustment kit, 301 is an electrode fixing frame, 302 is a porous carbon electrode, 303 is a first relay, 205 is a first solenoid valve, 206 is a second relay, 401 is an insertion type grille, 402 is natural aquatic plants, 7 is a water pump, 102 is a water inlet, 103 is a second solenoid valve, 8 is a third solenoid valve, 501 is a water outlet, 502 is a fourth solenoid valve, 104 is a third relay, 9 is a fourth relay, 503 is a fifth relay, 504 is a membrane assembly, 601 is a power module, 10 is a water diversion pool, 11 is an algae and aquatic plant recycling device, 12 is a power supply device, 13 is a solar power panel, and 14 is a biogas generator. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. These descriptions are only to further illustrate the features and advantages of the present invention, rather than to limit the claims of the present invention. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0045] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0046] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0047] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0048] like Figure 1-6As shown, sewage enters the detection chamber 1 through the water inlet 102 of the detection chamber 1. After the sewage enters the detection chamber 1, the single chip computer 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 according to the detection results, the acid adjustment kit 201, the alkaline adjustment kit 202, the H2O2 adjustment kit 203 and the PMS adjustment kit 204 of the test kit 2 are used to adjust the optimal conditions of pH, H2O2 and PMS respectively, and then the sewage enters the electrode chamber 3 through the pipeline. 25 of the porous carbon electrodes 302 in the electrode chamber 3 form traditional chemical electrodes by applying a voltage of 1.2-2.2V through a variable power supply, and 10 of the porous carbon electrodes 302 form biochemical electrodes by applying a voltage of 0.5-1.1V through a variable power supply; 15 of the porous carbon electrodes 302 are respectively connected to a first variable power supply and a second variable power supply, and a first relay 303 is connected between the 15 porous carbon electrodes 302 and the first variable power supply and the second variable power supply. The variable electrode can be converted into a traditional chemical electrode or a biochemical electrode by switching the single-pole double-throw contacts of the first relay 303. The traditional chemical electrode in the electrode chamber 3 processes heavy metal ions in sewage, and the biochemical electrode in the electrode chamber 3 processes organic matter in sewage. The variable electrode in the electrode chamber 3 can adjust the proportion of traditional chemical electrodes and biochemical electrodes according to the proportion of heavy metal ions and organic matter in sewage. Then the sewage enters the symbiotic chamber 4, and the artificial water grass and natural water grass 402 soaked in algae liquid are combined to treat nitrogen N and phosphorus P pollutants in the sewage by eutrophication. 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 detection chamber 1 is used for re-detection. If the sewage quality meets the pretreatment standard, the pH of the sewage is adjusted to neutral through the reagent kit 2, and then the single chip computer 6 controls the third electromagnetic valve 8 to open through the fourth relay 9, so that the sewage enters the filter chamber 5. The sewage is filtered through two sets of membrane components 504 in the filter chamber 5, and the filtered sewage returns to the electrode chamber 3 through the pipeline. The standard of the sewage is determined by the detection chamber 1. According to the standard detected by the detection chamber 1, the single-chip computer 6 controls the fourth solenoid valve 502 through the fifth relay 503 to open one of the three water outlets 501. The first water outlet 501 meets the discharge standard and directly discharges the treated water; the second water outlet 501 meets the irrigation standard, and the discharged water is used for agricultural irrigation; the third water outlet 501 meets the drinking standard, and the discharged water is used for daily drinking.

[0049] Furthermore, in this embodiment, the natural aquatic plants 402 in the symbiotic chamber 4 are arranged on the symbiotic base 401, and energy saving and dissolved oxygen utilization are achieved by using an aeration device with low pressure and low speed oxygen supply in the symbiotic chamber 4. The lamp post and thermostat controller in the symbiotic chamber 4 are used to control the temperature and light in the symbiotic chamber 4 to promote the growth of organisms in the symbiotic chamber.

[0050] Furthermore, in the present embodiment, preferably, artificial aquatic plants have better effects on ammonia nitrogen, COD, total nitrogen and total phosphorus when the pH value is in the range of 8.0-8.5; artificial aquatic plants have the highest removal efficiency for COD and ammonia hydrogen when the dissolved oxygen concentration is in the range of 3-5 mg / L; and for total nitrogen, the removal rate of artificial aquatic plants is the highest when the dissolved oxygen concentration is 6-8 mg / L.

[0051] Furthermore, in this embodiment, the single chip computer 6 uses the STM32F103ZET6 chip, which has a better processing effect, and the 220V power supply converts the 220V AC power into 12V DC power through the power module 601, and the STM32F103ZET6 chip is powered by the 12V DC power. When a problem occurs, the location of the problem is displayed on the display screen, and remote real-time monitoring and scheduling of the user end are realized through the server and the wireless network.

[0052] Furthermore, in this embodiment, the nanofiltration membrane and the reverse osmosis membrane in the membrane assembly 504 deeply purify the sewage and remove the impurities that are difficult to remove in the end to meet the discharge standard. In addition, since the sewage has been adjusted to neutral before entering the filter chamber 5, the nanofiltration membrane and the reverse osmosis membrane can be used for three years or even longer and replaced.

[0053] Furthermore, in this embodiment, the water inlet 102 is connected to the water diversion pool 10, and the floating plants and emergent plants planted in the water diversion pool are used to treat various pollutants, further improving the purification range. The plants in the water diversion pool 10 and the symbiotic chamber 4 are taken out and placed in the algae and waterweed recycling device 11. The algae and waterweed recycling device 11 extracts the extract of the algae and waterweed by squeezing. A part of the extract is used to promote seed germination, and the other part of the extract is added to the animal and straw for biogas fermentation. The power is transmitted to the power supply device 12 through the biogas generator 14, and the residue of the biogas fermentation is used as a biological fertilizer. The power supply device 12 is powered by the biogas generator 14 and the solar panel 13. The power supply device 12 transmits power to the sewage treatment device, realizing the recyclable utilization of energy.

[0054] Further, in this embodiment, preferably, the floating plants in the water diversion pool 10 are water lilies due to their strong purification ability; preferably, the emergent plants in the water diversion pool 10 are reeds, Phragmites australis, cattails and cannas.

[0055] The processing method of the present invention, such as Figure 7As shown, the following steps are included: S1, detecting the pollutant type, pollutant concentration, pH concentration, H2O2 concentration and PMS concentration of the sewage in the detection room; S2, grouping the pollutants into major categories according to the treatment methods of different pollutants, the treatment methods include traditional chemical electrode treatment and biochemical electrode treatment, and the two treatment methods are respectively a large group, and the variable electrode in the electrode chamber is regulated according to the ratio of heavy metal ions and organic matter in the sewage, so that the traditional chemical electrode and biochemical electrode in the electrode chamber reach the optimal ratio; in each treatment method, the current density, voltage, pH concentration, H2O2 concentration and PMS concentration multi-dimensional conditions are comprehensively considered, and the pollutants with similar optimal treatment conditions are found as a group; S3, adjusting the pH value to the optimal pH value of a group in S2, and finding the optimal current density, pH concentration, H2O2 concentration and PMS concentration of the corresponding treatment group; S4, the sewage is adjusted for pH, H2O2 and PMS through the test kit; S5, the sewage enters the electrode chamber, and according to the optimal current density of heavy metal ions and organic matter in the corresponding treatment group, it is respectively passed through the first A variable power supply and a second variable power supply adjust the voltage of the traditional chemical electrode and the biochemical electrode; the first variable power supply corresponding to the traditional chemical electrode is used to adjust the voltage of the traditional chemical electrode to the optimum voltage of the heavy metal ions in the corresponding treatment group; the second variable power supply corresponding to the biochemical electrode is used to adjust the voltage of the biochemical electrode to the optimum voltage of the organic matter in the corresponding treatment group, and the heavy metal ions and organic matter in the corresponding treatment group are treated simultaneously in the electrode chamber; S6, enter the detection chamber again to detect whether the pollutants in a group have reached the pretreatment standard. If the pretreatment standard is reached, enter step S3 to circulate and remove the pollutants in the next group until the pollutants in all groups reach the pretreatment standard, and enter step S7; if the pretreatment standard is not reached, return to step S4; S7, adjust the pH value of the sewage to neutral through the reagent kit, and then filter and circulate through the membrane assembly, electrode chamber and symbiotic chamber; S8, detect in the detection chamber to detect whether the sewage reaches the discharge standard. If it reaches the discharge standard, it is discharged; if it does not reach the discharge standard, return to step S2.

[0056] like Figure 8 As shown, the present invention combines the device with deep learning, the Internet of Things and the Internet to achieve the following functions:

[0057] 1. Real-time data monitoring:

[0058] By connecting to the Internet, the detection equipment can send data to the server and the app user end in real time. After analysis, corresponding pictures can be generated for intuitive display or operation suggestions can be made. Only through the mobile phone screen, the user can grasp the overall situation of the entire system.

[0059] 2. Big data integration and analysis:

[0060] By reviewing papers, conducting experimental tests and other methods, the project team collected a large amount of data on pollutant treatment results under different conditions. Based on big data, interpolation methods such as cubic spline interpolation and fitting methods such as four-parameter fitting are used to obtain pollutant treatment results under specific conditions. At the same time, the project team plans to use deep learning and other machine learning methods to predict future water quality, using online learning ideas to update the model in stages to expand the data set and improve prediction accuracy. While ensuring the complexity of the model, it is planned to try to use regularization methods such as weight decay and temporary retreat to reduce overfitting as much as possible and improve generalization capabilities. The combination of the water purification system and the Internet ensures that the system can operate normally under different water qualities and different river basins, and makes it possible to realize it more quickly, making it universal.

[0061] 4. Intelligent analysis and prediction:

[0062] The product can estimate the content of various pollutants in the water in the future, allowing users to calculate the consumption of various raw materials and personnel needs in advance, and use the "advance amount" of time to adjust plans in a timely manner.

[0063] 5. Efficient decision analysis:

[0064] By using the results of big data integration and analysis, the product can analyze the overall idea of ​​acidic and alkaline pollutant treatment in a very short time to make decisions that both save costs and ensure removal rates. This function ensures the overall practicality of the entire system.

[0065] 6. Remote data synchronization:

[0066] First, systems in different regions share monitored data through the Internet and can obtain more complete data sets in a relatively short period of time, which alleviates the urgent need for large amounts of data in deep learning prediction modules.

[0067] Secondly, the project team has developed a relatively complete server, which is connected to the Internet. The mechanical equipment testing equipment is also connected to the Internet. As an intermediary for information transmission, the Internet enables the entire system to achieve remote real-time monitoring and scheduling.

[0068] Only the preferred embodiments of the present invention are described in detail above, but the present invention is not limited to the above embodiments. Various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of the present invention, and various changes should be included in the protection scope of the present invention.

Claims

1. An integrated sewage treatment device based on deep learning, characterized in that: The invention comprises a detection chamber (1), a reagent box (2), an electrode chamber (3), a symbiotic chamber (4), and a filtration chamber (5); the reagent box (2) is arranged in the detection chamber (1); the electrode chamber (3) is connected to the symbiotic chamber (4); the detection chamber (1) is connected to the electrode chamber (3) through a pipeline; the symbiotic chamber (4) is connected to the filtration chamber (5) through a pipeline; and the filtration chamber (5) is connected to the electrode chamber (3) through a pipeline; a sensor probe (101) is arranged in the detection chamber (1); the sensor probe (101) 01) is electrically connected to a single-chip computer (6) through a wire, the single-chip computer (6) adopts an STM32F103ZET6 chip, the single-chip computer (6) is electrically connected to a power module (601), the power module (601) is connected to a 220V power supply, the single-chip computer (6) is electrically connected to a display screen, the single-chip computer (6) is connected to a server through a wireless communication method, and the server is connected to a user end through a wireless communication method; the reagent kit (2) includes an acid adjustment reagent kit (201) , an alkaline adjustment kit (202), a H2O2 adjustment kit (203) and a PMS adjustment kit (204), wherein the acid adjustment kit (201), the alkaline adjustment kit (202), the H2O2 adjustment kit (203) and the PMS adjustment kit (204) are respectively provided with a first solenoid valve (205), the first solenoid valve (205) is electrically connected to a second relay (206), and the second relay (206) is electrically connected to the single chip computer (6); the electrode chamber (3) An electrode fixing frame (301) is provided inside, and 50 porous carbon electrodes (302) are provided on the electrode fixing frame (301), wherein 25 porous carbon electrodes (302) are connected to a first variable power supply, and the 25 porous carbon electrodes (302) are applied with a voltage of 1.2-2.2V by the first variable power supply to form a traditional chemical electrode; wherein 10 porous carbon electrodes (302) are connected to a second variable power supply, and the 10 porous carbon electrodes (302) are applied with a voltage of 0.5-1.A voltage of 1V constitutes a biochemical electrode; wherein 15 porous carbon electrodes (302) are respectively connected to a first variable power supply and a second variable power supply, a first relay (303) is connected between the 15 porous carbon electrodes (302) and the first variable power supply and the second variable power supply to constitute a variable electrode, the contact of the first relay (303) is a single-pole double-throw contact, and the two output ends of the single-pole double-throw contact of the first relay (303) are respectively connected to the first variable power supply and the second variable power supply, and the first relay (303) is electrically connected to a single-chip computer (6); a water pump (7) is arranged on the pipeline between the electrode chamber (3) and the detection chamber (1), and a water inlet (102) is arranged on the detection chamber (1). A second electromagnetic valve (103) is provided on the water inlet (102) of the detection chamber (1), a third electromagnetic valve (8) is provided on the pipeline between the symbiosis chamber (4) and the filter chamber (5), three water outlets (501) are provided on the detection chamber (1), and fourth electromagnetic valves (502) are respectively provided on the three water outlets (501), the second electromagnetic valve (103) is electrically connected to a third relay (104), the third electromagnetic valve (8) is electrically connected to a fourth relay (9), the fourth electromagnetic valve (502) is electrically connected to a fifth relay (503), and the third relay (104), the fourth relay (9) and the fifth relay (503) are all electrically connected to the single chip computer (6) through wires.

2. The integrated sewage treatment device based on deep learning according to claim 1, characterized in that: An insertable grille (401) is arranged in the symbiosis chamber (4), natural aquatic plants (402) are arranged in the insertable grille (401), and artificial aquatic plants soaked in algae liquid are hung on the side wall of the symbiosis chamber (4).

3. The integrated sewage treatment device based on deep learning according to claim 1, characterized in that: An aeration device is provided at the bottom of the symbiosis chamber (4), and the aeration device adopts low-pressure and low-speed oxygen supply. A lamp post and a constant temperature controller are provided on the side wall of the symbiosis chamber (4).

4. The integrated sewage treatment device based on deep learning according to claim 1, characterized in that: The outer side of the water inlet (102) is connected to a water diversion pool (10), and floating plants and emergent plants are arranged in the water diversion pool (10). The plants in the water diversion pool (10) and the symbiosis chamber (4) are taken out and placed in an algae and waterweed recycling device (11). The algae and waterweed recycling device (11) is connected to a power supply device (12) via a biogas generator (14), and the power supply device (12) is connected to a solar power generation panel (13). The power supply device (12) is electrically connected to the detection chamber (1), the electrode chamber (3), the symbiosis chamber (4) and the algae and waterweed recycling device (11), respectively.

5. The integrated sewage treatment device based on deep learning according to claim 1, characterized in that: Two groups of membrane components (504) are arranged in the filtration chamber (5), one group of membrane components (504) uses a nanofiltration membrane, and the other group of membrane components (504) uses a reverse osmosis membrane.

6. A treatment method for an integrated sewage treatment device based on deep learning according to any one of claims 1 to 5, characterized in that: The following steps are involved: S1. Detect the pollutant types, pollutant concentrations, pH concentrations, H2O2 concentrations and PMS concentrations of sewage in the testing room; S2. The pollutants are grouped into major categories according to the treatment methods of different pollutants, which include traditional chemical electrode treatment and biochemical electrode treatment. The two treatment methods are respectively a large group. The variable electrodes in the electrode chamber are regulated according to the ratio of heavy metal ions and organic matter in the sewage, so that the traditional chemical electrodes and biochemical electrodes in the electrode chamber reach the optimal ratio. Under each treatment method, the multi-dimensional conditions of current density, voltage, pH concentration, H2O2 concentration and PMS concentration are comprehensively considered, and the pollutants with similar optimal treatment conditions are found as a small group; S3, adjusting the pH value to the optimum pH value of a group in S2, and finding the optimum current density, pH concentration, H2O2 concentration and PMS concentration of the corresponding treatment group; S4, sewage is adjusted for pH, H2O2 and PMS through the kit; S5, sewage enters the electrode chamber, and the voltages of the conventional chemical electrode and the biochemical electrode are adjusted respectively by the first variable power supply and the second variable power supply according to the optimum current density of the heavy metal ions and the organic matter in the corresponding treatment group; the first variable power supply correspondingly controls the conventional chemical electrode, and adjusts the voltage of the conventional chemical electrode to the optimum voltage of the heavy metal ions in the corresponding treatment group; the second variable power supply correspondingly controls the biochemical electrode, and adjusts the voltage of the biochemical electrode to the optimum voltage of the organic matter in the corresponding treatment group, and the heavy metal ions and the organic matter in the corresponding treatment group are treated simultaneously in the electrode chamber; S6, enter the detection room again to detect whether the pollutants of a group have reached the pretreatment standard. If so, enter step S3 to cycle and remove the pollutants of the next group until all the pollutants of the groups reach the pretreatment standard, and then enter step S7; if not, return to step S4; S7, adjusting the pH value of the sewage to neutral through the test kit, and then filtering and circulating through the membrane assembly, electrode chamber and symbiotic chamber; S8. Perform a test in the test room to check whether the sewage meets the discharge standard. If so, discharge it; if not, return to step S2.

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