A low-temperature water treatment decomposition system based on a deep learning model

Abstract

The application relates to the field of water purification treatment technology, in particular to a low-temperature water treatment decomposition system based on a deep learning model, which comprises a model analysis module, a treatment decomposition module and a detection module. The model analysis module is used to determine the standard output rate of purified water and the standard vertical height of a stirring paddle according to a deep learning model. The treatment decomposition module is connected with the model analysis module and is used to treat and decompose source water to output purified water and gas products. The detection module is connected with the treatment decomposition module and is used to detect the concentration of pollutants in the purified water, the concentration of treatment agents in the purified water and the temperature of the mixed solution respectively. The control module is connected with the model analysis module, the treatment decomposition module and the detection module respectively and is used to determine the output rate of the purified water when the treatment stability of the source water is determined to be not up to the requirements according to the variance of the concentration of pollutants in the purified water. The application improves the treatment stability of the source water.

Description

Technical Field

[0001] This invention relates to the field of water purification technology, and in particular to a low-temperature water treatment decomposition system based on a deep learning model. Background Technology

[0002] In existing technologies, source water supply increasingly uses wastewater discharged from domestic or industrial production. Because it contains various impurities and metals, it needs to be treated to meet the standards for reuse. Purification technologies are needed to optimize the water treatment process and improve the water quality of source water supply.

[0003] In the process of conceiving and implementing this application, the applicant discovered that due to the sedimentation effect of impurities in the source water supply and the instability of component concentration, the detection accuracy during the water purification process will gradually decrease, resulting in insufficient stability in the treatment of source water supply. Summary of the Invention

[0004] To alleviate the above problems, this invention provides a low-temperature water treatment decomposition system based on a deep learning model, comprising: a model analysis module for determining the standard output rate of purified water, the standard vertical height of the agitator, and the standard interval between heating and cooling times based on a deep learning model; and a treatment decomposition module connected to the model analysis module for treating and decomposing the source water supply to output purified water and gaseous products, including a reaction component for providing a reaction site, a stirring component connected to the reaction component for mixing the source water supply and the treatment agent to output a mixture, a heating component connected to the reaction component for heating the reaction process, and a conveying component connected to the reaction component for conveying purified water, wherein the reaction component is a reactor, and the stirring component includes components for stirring the source water supply and the treatment agent. The system includes: a mixing impeller; a detection module connected to the treatment and decomposition module for detecting the concentrations of pollutants, treatment agents, and the temperature of the mixture in the purified water; a control module connected to the model analysis module, the treatment and decomposition module, and the detection module, for determining the output rate of the purified water or initially determining that the mixing effectiveness of the source water and treatment agent is not satisfactory based on the variance of the pollutant concentration in the purified water, and then making a secondary determination of the mixing effectiveness based on the average concentration difference of the treatment agent in the purified water; and, when the secondary determination of the mixing effectiveness of the source water and treatment agent is not satisfactory, determining the vertical height of the impeller or adjusting the interval between heating and cooling times based on the temperature rise rate of the mixture.

[0005] Furthermore, the processing and decomposition module also includes a cooling component connected to the reaction component for cooling the purified water after the reaction is completed.

[0006] Furthermore, the stirring assembly includes: A stirring shaft, which is located inside the reactor, is used to control the stirring height; An electric telescopic rod, connected to the stirring shaft, changes the vertical height of the stirring paddle by altering its telescopic length.

[0007] Furthermore, the conveying assembly includes: A first delivery pipe, which is connected to the reactor, is used to deliver the purified water; An electric valve, connected to the first delivery pipe, is used to control the output rate of purified water.

[0008] Furthermore, the detection module includes: A high-performance liquid chromatograph is installed at the output end of the first delivery tube to detect the concentration of pollutants in the purified water and the concentration of the treatment agent in the purified water, respectively. A temperature sensor, connected to the inner wall of the reactor, is used to detect the temperature of the mixture inside the reactor.

[0009] Furthermore, the control module is connected to the high performance liquid chromatograph to calculate the variance of the pollutant concentration in the purified water based on the concentration of pollutants in the purified water within several treatment cycles, and to determine that the treatment stability of the source water supply does not meet the requirements when the variance of the pollutant concentration in the purified water meets the first variance condition or the second variance condition. The control module is connected to the high performance liquid chromatograph and is used to initially determine that the mixing effectiveness of the source water supply and the treatment agent does not meet the requirements when the variance of the pollutant concentration in the purified water only meets the first variance condition, and to make a second determination on the mixing effectiveness of the source water supply and the treatment agent based on the average concentration difference of the treatment agent in the purified water. Wherein, the first variance condition is that the variance of the pollutant concentration in the purified water is greater than a preset first variance and less than or equal to a preset second variance; the second variance condition is that the variance of the pollutant concentration in the purified water is greater than a preset second variance.

[0010] Furthermore, the control module is connected to the electric valve to reduce the output rate of the purified water when the variance of the pollutant concentration in the purified water only meets the second variance condition; The reduced output rate is determined by the difference between the variance of the pollutant concentration in the purified water and the preset second variance.

[0011] Furthermore, the control module is connected to the high-performance liquid chromatograph and is used to make a secondary determination that the mixing effectiveness of the source water and the treatment agent does not meet the requirements when the average concentration difference of the treatment agent in the purified water meets the first difference condition or the second difference condition; and to make a preliminary determination that the heating effect does not meet the requirements when the average concentration difference of the treatment agent in the purified water only meets the second difference condition, and to make a secondary determination of the heating effect based on the temperature rise rate of the mixture. The control module is connected to the stirring assembly and is used to reduce the vertical height of the stirring paddle when the average concentration difference of the treatment agent in the purified water only meets the first difference condition. Wherein, the first difference condition is that the average concentration difference of the treatment agent in the purified water is greater than a preset first difference and less than or equal to a preset second difference; the second difference condition is that the average concentration difference of the treatment agent in the purified water is greater than a preset second difference.

[0012] Furthermore, the adjustment range of the vertical height of the stirring paddle is determined by the difference between the average concentration difference of the treatment agent in the purified water and a preset first difference.

[0013] Furthermore, the control module is connected to the temperature sensor to determine for the second time that the heating effect does not meet the requirements when the temperature rise rate of the mixture is greater than the preset rise rate, and to increase the interval between the heating time and the cooling time. The increased interval between heating and cooling times is determined by the difference between the temperature rise rate of the mixture and the preset rise rate.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: The system of the present invention, by setting up a model analysis module, a processing decomposition module, a detection module, and a control module, determines the operation mode of the conveying component based on the variance of the pollutant concentration in the water. By reducing the output rate of purified water in the reactor, materials with attached pollutants can sink to the bottom of the first conveying pipe, thereby improving the accuracy of pollutant concentration detection. By determining the working mode of the stirring component based on the average concentration difference of the treatment agent in the purified water, and by reducing the vertical height of the stirring paddle, the stirring paddle can be stirred at a position far from the bottom of the reactor, thereby improving the mixing effectiveness of the source water and the treatment agent. By adjusting the interval between heating and cooling according to the temperature rise rate of the mixed liquid, and by increasing the interval between heating and cooling, the heat in the reactor is present for a longer period of time, thereby increasing the mixing reaction time of the source water and the treatment agent, improving the mixing effect of the source water and the treatment agent, and achieving improved treatment stability of the source water.

[0015] Furthermore, the system of the present invention adjusts the output rate of purified water by setting a preset first variance and a preset second variance. By reducing the output rate of purified water in the reactor, the material with attached pollutants sinks to the bottom of the first delivery pipe, thereby further improving the accuracy of pollutant concentration detection and improving the stability of source water supply treatment.

[0016] Furthermore, the system of the present invention adjusts the vertical height of the stirring paddle by setting a preset first difference amount and a preset second difference amount. By reducing the vertical height of the stirring paddle, the stirring paddle is made to stir at a position far from the bottom of the reactor, thereby improving the mixing effectiveness of the source water supply and the treatment agent, and further improving the treatment stability of the source water supply.

[0017] Furthermore, the system of the present invention adjusts the interval between heating and cooling by setting a preset rise rate. By increasing the interval between heating and cooling, the duration of heat presence in the reactor is increased, thereby increasing the mixing reaction time of the source water and the treatment agent, improving the mixing effect of the source water and the treatment agent, and further improving the treatment stability of the source water. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall structure of the low-temperature water treatment decomposition system based on a deep learning model according to an embodiment of the present invention.

[0019] Figure 2 This is a block diagram of the overall structure of the low-temperature water treatment decomposition system based on a deep learning model according to an embodiment of the present invention.

[0020] Figure 3 This is a block diagram of the processing and decomposition module of the low-temperature water treatment and decomposition system based on a deep learning model, according to an embodiment of the present invention.

[0021] Figure 4 This is a block diagram showing the connection structure between the processing and decomposition module and the control module of the low-temperature water treatment decomposition system based on a deep learning model, according to an embodiment of the present invention.

[0022] The attached diagram is labeled as follows: 1-reactor, 2-electric telescopic rod, 3-stirring shaft, 4-temperature sensor, 5-first delivery pipe, 6-second delivery pipe, 7-high performance liquid chromatograph, 8-storage tank, 9-condenser, 10-electric valve, 11-heater, 12-stirring paddle. Detailed Implementation

[0023] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0024] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0025] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0026] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0027] Please see Figure 1 , Figure 2 , Figure 3 as well as Figure 4 The figures shown are, respectively, a schematic diagram of the overall structure, a block diagram of the overall structure, a block diagram of the specific structure of the processing and decomposition module, and a block diagram of the connection structure between the processing and decomposition module and the control module of the low-temperature water treatment decomposition system based on a deep learning model according to an embodiment of the present invention. The present invention provides a low-temperature water treatment decomposition system based on a deep learning model, comprising: The model analysis module is used to determine the standard output rate of purified water, the standard vertical height of the agitator 12, and the standard interval between heating and cooling times based on the deep learning model. The processing and decomposition module, connected to the model analysis module, is used to process and decompose the source water supply according to the deep learning model to output purified water and gas products. It includes a reaction component for providing a reaction site, a stirring component connected to the reaction component for mixing the source water supply and the treatment agent to output a mixture, a heating component connected to the reaction component for heating the reaction process, and a conveying component connected to the reaction component for conveying purified water. The reaction component is a reactor 1, and the stirring component includes a stirring paddle 12 for stirring and mixing the source water supply and the treatment agent. The detection module, which is connected to the processing and decomposition module, is used to detect the concentration of pollutants in the purified water, the concentration of the treatment agent in the purified water, and the temperature of the mixed solution, respectively. The control module, which is connected to the model analysis module, the processing decomposition module and the detection module respectively, is used to determine the output rate of the purified water or to preliminarily determine that the mixing effectiveness of the source water and the treatment agent does not meet the requirements when the treatment stability of the source water supply does not meet the requirements based on the variance of the pollutant concentration in the purified water. It also makes a secondary determination of the mixing effectiveness of the source water supply and the treatment agent based on the average concentration difference of the treatment agent in the purified water. Furthermore, when the mixing effectiveness of the source water and the treatment agent is not satisfactory in the second determination, the vertical height of the agitator 12 is determined or the interval between the heating and cooling times is adjusted according to the rate of temperature rise of the mixture.

[0028] Specifically, the heating component is heater 11.

[0029] Specifically, heater 11 can be an electric heater, a gas heater, or a steam heater, with an electric heater being the preferred embodiment.

[0030] Specifically, the cooling component is the condenser 9.

[0031] Specifically, the condenser 9 can be an air-cooled condenser, a water-cooled condenser, or a spray-type condenser. The model of the condenser 9 can be appropriately replaced without affecting the water treatment supply from the source.

[0032] Specifically, the conveying assembly also includes a second conveying pipe 6 connected to the condenser 9 for conveying the condensed purified water.

[0033] Specifically, the low-temperature water treatment decomposition system based on a deep learning model also includes a storage tank 8 connected to the second delivery pipe 6 for storing purified water.

[0034] Specifically, deep learning models improve the effectiveness of source water treatment by monitoring water quality and temperature data in real time during the source water treatment process and regulating the treatment process.

[0035] Specifically, deep learning models can be convolutional neural networks, deep reinforcement learning models, and recurrent neural networks.

[0036] Specifically, the process by which the deep learning model determines the standard output rate of purified water involves the deep learning model adjusting the output rate of purified water based on the concentration of pollutants collected in the purified water.

[0037] Specifically, the process by which the deep learning model determines the standard vertical height of the agitator involves the deep learning model adjusting the vertical height of the agitator based on the concentration of the treatment agent in the purified water.

[0038] Specifically, the process by which the deep learning model determines the standard interval between heating and cooling times involves the deep learning model determining the interval between heating and cooling times based on the collected temperature of the mixture.

[0039] Specifically, the pollutants include pesticides, industrial solvents, and detergents, with industrial solvents being a preferred embodiment.

[0040] Optionally, the treatment agent can be an inhibitor, disinfectant, pH adjuster, or microorganism, with microorganism being a preferred embodiment.

[0041] Specifically, the system automatically memorizes and analyzes the water quality data, temperature data, pH data, oxygen content data, catalyst dosage data, and agitator 12 height data monitored in real time during the source water supply treatment process. By analyzing the water quality change data before and after source water supply treatment, the system automatically adjusts the temperature, pH, oxygen content, catalyst dosage, or agitator 12 height during the source water supply treatment process to change the growth environment of the microorganisms and further control the iterative direction of the microorganisms.

[0042] For example, during the data monitoring and collection process, sensors and online analytical instruments can be used to collect data to monitor water quality data (such as suspended solids, organic matter, heavy metal content, etc.), temperature, pH value, oxygen content, catalyst dosage, and impeller height in real time.

[0043] For example, during data storage and analysis, data analysis algorithms, such as machine learning and artificial intelligence, are used to analyze the data to identify patterns and trends in water quality changes. The system can automatically memorize this data and store it in a database.

[0044] For example, during the automatic adjustment and optimization process, based on data analysis results, the system automatically adjusts key parameters in the water treatment process, such as temperature, pH, oxygen content, catalyst dosage, and agitator height. For instance, if data analysis shows an increase in organic matter content in the water, the system may increase the temperature and oxygen content to promote the decomposition by microorganisms.

[0045] For example, in the process of iterative control of microorganisms, the system can control the growth environment and metabolic pathways of microorganisms by changing water treatment conditions. For instance, adjusting pH and oxygen levels can promote the growth of certain types of microorganisms, which may more effectively degrade specific pollutants.

[0046] For example, the system continuously monitors the water treatment effect and feeds new data back to the analysis system. If the treatment effect does not meet expectations, the system will continue to adjust parameters until the optimal treatment conditions are found. The system can periodically generate water treatment reports, including water quality analysis, treatment efficiency, energy consumption, etc. Sensors and instruments are regularly maintained to ensure data accuracy and system stability.

[0047] By employing advanced data analysis and automatic adjustment technologies, the efficiency and effectiveness of water treatment can be improved. In this way, the water treatment system can automatically adapt to constantly changing water quality conditions, optimize the treatment process, improve water quality, and reduce energy and chemical consumption.

[0048] Specifically, the gaseous products include hydrogen, oxygen, carbon dioxide, and nitrogen.

[0049] Specifically, the interval between heating and cooling refers to the time between when heating of the source water stops and when cooling begins.

[0050] In implementation, the system of this invention, by setting up a model analysis module, a processing decomposition module, a detection module, and a control module, determines the operation mode of the conveying components based on the variance of pollutant concentration in the purified water. By reducing the output rate of purified water in reactor 1, the material with attached pollutants sinks to the bottom of the first conveying pipe 5, improving the accuracy of pollutant concentration detection. By determining the working mode of the stirring components based on the average concentration difference of the treatment agent in the purified water, and by reducing the vertical height of the stirring paddle 12, the stirring paddle 12 is made to stir at a position away from the bottom of reactor 1, thereby improving the mixing effectiveness of the source water and treatment agent. By adjusting the interval between heating and cooling times according to the temperature rise rate of the mixed liquid, and by increasing the interval between heating and cooling times, the heat in reactor 1 is increased for a longer period, thereby increasing the mixing reaction time of the source water and treatment agent, improving the mixing effect of the source water and treatment agent, and achieving improved treatment stability of the source water.

[0051] Specifically, the processing and decomposition module also includes a cooling component connected to the reaction component for cooling the purified water after the reaction is completed.

[0052] Specifically, the stirring assembly includes: A stirring shaft 3 is disposed inside the reactor 1 to control the stirring height; The electric telescopic rod 2, which is connected to the stirring shaft 3, changes the vertical height of the stirring paddle 12 by changing its telescopic length.

[0053] Specifically, the conveying assembly includes: The first conveying pipe 5 is connected to the reactor 1 and is used to convey the purified water; An electric valve 10, which is connected to the first delivery pipe 5, is used to control the output rate of purified water.

[0054] Specifically, the detection module includes: A high-performance liquid chromatograph 7 is installed at the output end of the first delivery tube 5 to detect the concentration of pollutants in the purified water and the concentration of the treatment agent in the purified water, respectively. Temperature sensor 4 is connected to the inner wall of reactor 1 to detect the temperature of the mixture inside reactor 1.

[0055] Specifically, the high-performance liquid chromatograph 7 is connected to the second delivery tube 6.

[0056] Specifically, the control module is connected to the high performance liquid chromatograph 7 and is used to calculate the variance of the pollutant concentration in the purified water based on the concentration of pollutants in the purified water within several treatment cycles, and to determine that the treatment stability of the source water supply does not meet the requirements when the variance of the pollutant concentration in the purified water meets the first variance condition or the second variance condition. The control module is connected to the high performance liquid chromatograph 7 and is used to initially determine that the mixing effectiveness of the source water supply and the treatment agent does not meet the requirements when the variance of the pollutant concentration in the purified water only meets the first variance condition, and to make a second determination on the mixing effectiveness of the source water supply and the treatment agent based on the average concentration difference of the treatment agent in the purified water. Wherein, the first variance condition is that the variance of the pollutant concentration in the purified water is greater than a preset first variance and less than or equal to a preset second variance; the second variance condition is that the variance of the pollutant concentration in the purified water is greater than a preset second variance.

[0057] It is understandable that the three intervals corresponding to the preset first variance and the preset second variance correspond to three situations. The first situation is that the variance of the pollutant concentration in the purified water is less than or equal to the preset first variance, and the treatment stability of the source water supply is determined to meet the requirements. The second situation is that the variance of the pollutant concentration in the purified water is greater than the preset first variance but less than or equal to the preset second variance, and the mixing effectiveness of the source water supply and the treatment agent is initially determined to be unsatisfactory. The mixing effectiveness of the source water supply and the treatment agent is then re-evaluated based on the average concentration difference of the treatment agent in the purified water. The third situation is that the variance of the pollutant concentration in the purified water is greater than the preset second variance, and the purified water is transported according to the aforementioned operating mode.

[0058] Preferably, the first variance Q1 is preset to 15 (mg / L). 2 The second variance is assumed to be Q2 = 18 (mg / L). 2 .

[0059] Specifically, the variance of the pollutant concentration in the purified water is denoted as Q, and the difference between the variance of the pollutant concentration in the purified water and the preset second variance is denoted as ΔQ, and ΔQ is set as Q-Q2.

[0060] Specifically, the variance of pollutant concentration in purified water is the variance of pollutant concentration in purified water over several treatment cycles. The calculation method for the variance of pollutant concentration in purified water is a conventional technique well-known to those skilled in the art, so the calculation process for the variance of pollutant concentration in purified water will not be elaborated here.

[0061] In practice, the system of the present invention determines the treatment stability of source water supply by setting a preset first variance and a preset second variance, thereby further improving the treatment stability of source water supply.

[0062] Specifically, the control module is connected to the electric valve 10 and is used to reduce the output rate of the purified water when the variance of the pollutant concentration in the purified water only meets the second variance condition. The reduced output rate is determined by the difference between the variance of the pollutant concentration in the purified water and the preset second variance.

[0063] Specifically, the process of determining the output rate of purified water by the difference between the variance of pollutant concentration in the purified water and a preset second variance is as follows: If △Q≤△Q0, the control module uses a preset second output rate adjustment coefficient to adjust the output rate of the purified water to the first output rate; If △Q>△Q0, the control module uses a preset first output rate adjustment coefficient to adjust the output rate of the purified water to the second output rate; Wherein, the preset first output rate adjustment coefficient is less than the preset second output rate.

[0064] Preferably, the preset variance difference ΔQ0 = 2 (mg / L) 2 .

[0065] Preferably, the first output rate adjustment coefficient α1 is preset to 0.8, and the second output rate adjustment coefficient α2 is preset to 0.9.

[0066] Specifically, the output rate of purified water is denoted as V, and the reduced output rate of purified water is denoted as V'. V' is set to V×αi, where αi is the preset output rate adjustment coefficient for the i-th time, and i is set to 1, 2.

[0067] Specifically, the reduction V of the output rate of purified water is determined by the preset i-th output rate adjustment coefficient αi.

[0068] In practice, the system of the present invention adjusts the output rate of purified water by setting a preset first variance and a preset second variance. By reducing the output rate of purified water in reactor 1, the material with attached pollutants sinks to the bottom of the first conveying pipe 5, thereby further improving the accuracy of pollutant concentration detection and further improving the stability of the source water supply treatment.

[0069] Specifically, the control module is connected to the high performance liquid chromatograph 7 and is used to make a secondary determination that the mixing effectiveness of the source water and the treatment agent does not meet the requirements when the average concentration difference of the treatment agent in the purified water meets the first difference condition or the second difference condition; and to make a preliminary determination that the heating effect does not meet the requirements when the average concentration difference of the treatment agent in the purified water only meets the second difference condition, and to make a secondary determination of the heating effect based on the temperature rise rate of the mixture. The control module is connected to the stirring assembly and is used to reduce the vertical height of the stirring paddle when the average concentration difference of the treatment agent in the purified water only meets the first difference condition. Wherein, the first difference condition is that the average concentration difference of the treatment agent in the purified water is greater than a preset first difference and less than or equal to a preset second difference; the second difference condition is that the average concentration difference of the treatment agent in the purified water is greater than a preset second difference.

[0070] It is understandable that the three intervals corresponding to the preset first difference amount and the preset second difference amount correspond to three situations. The first situation is that the average concentration difference of the treatment agent in the purified water is less than or equal to the preset first difference amount, and the mixing effectiveness of the source water and the treatment agent is deemed to meet the requirements. The second situation is that the average concentration difference of the treatment agent in the purified water is greater than the preset first difference amount and less than or equal to the preset second difference amount, and the source water and the treatment agent are stirred and mixed according to the working method described above. The third situation is that the average concentration difference of the treatment agent in the purified water is greater than the preset second difference amount, and the heating effect is initially deemed to be unsatisfactory. The heating effect is then reassessed based on the rate of temperature increase of the mixed liquid.

[0071] Preferably, the first difference amount P1 is preset to 20ppm and the second difference amount P2 is preset to 22ppm.

[0072] Specifically, the average concentration difference of the treatment agent in the purified water is denoted as P, and the difference between the average concentration difference of the treatment agent in the purified water and the preset first difference is denoted as ΔP, and ΔP is set as P-P1.

[0073] Specifically, the formula for calculating the average concentration difference of the treatment agent in purified water is as follows:

[0074] Where P is the average concentration difference of the treatment agent in the purified water, |X a -X a-1 | represents the absolute value of the difference between the concentration of the treatment agent in the purified water during the a-th treatment cycle and the concentration of the treatment agent in the purified water during the (a-1)-th treatment cycle, where n is the number of treatment cycles and n is a natural number greater than or equal to 2.

[0075] In practice, the system of the present invention performs a secondary determination on the mixing effectiveness of the source water supply and the treatment agent by setting a preset first difference amount and a preset second difference amount, thereby further improving the treatment stability of the source water supply.

[0076] Specifically, the adjustment range of the vertical height of the stirring paddle 12 is determined by the difference between the average concentration difference of the treatment agent in the purified water and a preset first difference.

[0077] Specifically, the process of determining the vertical height of the agitator 12 by the difference between the average concentration difference of the treatment agent in the purified water and the preset first difference is as follows: If △P≤△P0, the control module uses a preset second vertical height adjustment coefficient to adjust the vertical height of the stirring paddle 12 to the first vertical height; If △P>△P0, the control module uses a preset first vertical height adjustment coefficient to adjust the vertical height of the stirring paddle 12 to the second vertical height; Wherein, the preset first vertical height adjustment coefficient is less than the preset second vertical height adjustment coefficient.

[0078] Preferably, the preset difference value △P0 = 3ppm.

[0079] Preferably, the first vertical height adjustment coefficient β1 is preset to 0.7, and the second vertical height adjustment coefficient β2 is preset to 0.8.

[0080] Specifically, the vertical height of the stirring paddle 12 is denoted as H, and the reduced vertical height of the stirring paddle 12 is denoted as H'. H' is set to H×βj, where βj is the preset vertical height adjustment coefficient for the j-th vertical height, and j is set to 1, 2.

[0081] Specifically, the reduction in the vertical height H of the agitator 12 is determined by a preset vertical height adjustment coefficient βj.

[0082] In practice, the system of the present invention adjusts the vertical height of the stirring paddle 12 by setting a preset first difference amount and a preset second difference amount. By reducing the vertical height of the stirring paddle 12, the stirring paddle 12 is made to stir at a position far from the bottom of the reactor 1, thereby improving the mixing effectiveness of the source water supply and the treatment agent, and further improving the treatment stability of the source water supply.

[0083] Specifically, the control module is connected to the temperature sensor 4 and is used to determine for the second time that the heating effect does not meet the requirements when the temperature rise rate of the mixture is greater than the preset rise rate, and to increase the interval between the heating time and the cooling time.

[0084] It is understandable that the two intervals corresponding to the preset temperature rise rate correspond to two situations. The first situation is that the temperature rise rate of the mixture is less than or equal to the preset temperature rise rate, and the heating effect is deemed to meet the requirements in the second determination. The second situation is that the temperature rise rate of the mixture is greater than the preset temperature rise rate, and the interval between the heating time and the cooling time is increased.

[0085] Preferably, the preset rising rate Y0 = 5℃ / h.

[0086] Specifically, the rate of temperature increase of the mixture is denoted as Y, and the difference between the rate of temperature increase of the mixture and the preset rate of increase is denoted as ΔY, with ΔY = Y0 - Y.

[0087] Specifically, the formula for calculating the rate of temperature rise of the mixture is:

[0088] Where Y is the rate of temperature increase of the mixture, K1 is the temperature of the mixture at the beginning of a single heating cycle, K2 is the temperature of the mixture at the end of a single heating cycle, and T is the duration of a single heating cycle.

[0089] In practice, the system of the present invention performs a secondary judgment on the heating effect by setting a preset heating rate, thereby reducing the impact of inaccurate secondary judgment on the heating effect on the stability of the source water supply treatment and further improving the stability of the source water supply treatment.

[0090] Specifically, the increased interval between heating and cooling times is determined by the difference between the temperature rise rate of the mixture and the preset rise rate.

[0091] Specifically, the process of determining the interval between heating and cooling moments by the difference between the temperature rise rate of the mixture and the preset rise rate is as follows: If △Y≤△Y0, the control module uses a preset first interval duration adjustment coefficient to adjust the interval duration between the heating moment and the cooling moment to the first interval duration; If △Y>△Y0, the control module uses a preset second interval duration adjustment coefficient to adjust the interval duration between the heating moment and the cooling moment to the second interval duration; Wherein, the preset first interval duration adjustment coefficient is less than the preset second interval duration adjustment coefficient.

[0092] Preferably, the preset rise rate difference ΔY0 = 1℃ / h.

[0093] Preferably, the first interval duration adjustment coefficient γ1 is preset to 1.2, and the second interval duration adjustment coefficient γ2 is preset to 1.4.

[0094] Specifically, the interval between heating and cooling is denoted as L, and the increased interval between heating and cooling is denoted as L'. L' is set to L×γm, where γm is the preset interval length adjustment coefficient, and m is set to 1 or 2.

[0095] Specifically, the increase in the interval L between the heating and cooling times is determined by a preset interval length adjustment coefficient γm.

[0096] In practice, the system of the present invention adjusts the interval between heating and cooling by setting a preset rise rate. By increasing the interval between heating and cooling, the heat in the reactor is present for a longer period of time, thereby increasing the mixing reaction time of the source water and the treatment agent, improving the mixing effect of the source water and the treatment agent, and further improving the treatment stability of the source water.

[0097] Example 1 In this embodiment 1, a low-temperature water treatment decomposition system based on deep learning is used to treat the source water supply. The control module adjusts the output rate of the purified water according to the difference between the variance of the pollutant concentration in the purified water and a preset second variance. The preset first output rate adjustment coefficient is denoted as α1, the preset second output rate adjustment coefficient is denoted as α2, and the output rate of the purified water is denoted as V, where 0 < α1 < α2 < 1. α1 = 0.8, α2 = 0.9, and ΔQ0 = 2 (mg / L) are set. 2 V=4L / h, Q=21 (mg / L) 2 Q2 = 18 (mg / L) 2 , △Q=Q-Q2.

[0098] In Example 1, ΔQ was calculated to be 3 (mg / L). 2 The control module determines that △Q > △Q0 and uses a preset first output rate adjustment coefficient to adjust the output rate of the purified water to the second output rate, and calculates V' = 4L / h × 0.8 = 3.2L / h.

[0099] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A low-temperature water treatment decomposition system based on a deep learning model, characterized in that, include: The model analysis module is used to determine the standard output rate of purified water, the standard vertical height of the agitator, and the standard interval between heating and cooling based on the deep learning model. The processing and decomposition module, connected to the model analysis module, is used to process and decompose the source water supply to output purified water and gaseous products. It includes a reaction component for providing a reaction site, a stirring component connected to the reaction component for mixing the source water supply and the treatment agent to output a mixture, a heating component connected to the reaction component for heating the reaction process, and a conveying component connected to the reaction component for conveying purified water. The reaction component is a reactor, and the stirring component includes a stirring paddle for stirring and mixing the source water supply and the treatment agent. The detection module, which is connected to the processing and decomposition module, is used to detect the concentration of pollutants in the purified water, the concentration of the treatment agent in the purified water, and the temperature of the mixed solution, respectively. The control module, which is connected to the model analysis module, the processing decomposition module and the detection module respectively, is used to determine the output rate of the purified water or to preliminarily determine that the mixing effectiveness of the source water and the treatment agent does not meet the requirements when the treatment stability of the source water supply does not meet the requirements based on the variance of the pollutant concentration in the purified water. It also makes a secondary determination of the mixing effectiveness of the source water supply and the treatment agent based on the average concentration difference of the treatment agent in the purified water. Furthermore, when the mixing effectiveness of the source water and the treatment agent is not satisfactory in the secondary determination, the vertical height of the agitator is determined or the interval between heating and cooling times is adjusted according to the rate of temperature rise of the mixture.

2. The low-temperature water treatment decomposition system based on a deep learning model according to claim 1, characterized in that, The processing and decomposition module also includes a cooling component connected to the reaction component for cooling the purified water after the reaction is completed.

3. The low-temperature water treatment decomposition system based on a deep learning model according to claim 2, characterized in that, The stirring assembly includes: A stirring shaft, which is located inside the reactor, is used to control the stirring height; An electric telescopic rod, connected to the stirring shaft, changes the vertical height of the stirring paddle by altering its telescopic length.

4. The low-temperature water treatment separation system based on a deep learning model according to claim 3, characterized in that, The conveying assembly includes: A first delivery pipe, which is connected to the reactor, is used to deliver the purified water; An electric valve, connected to the first delivery pipe, is used to control the output rate of purified water.

5. The low-temperature water treatment separation system based on a deep learning model according to claim 4, characterized in that, The detection module includes: A high-performance liquid chromatograph is installed at the output end of the first delivery tube to detect the concentration of pollutants in the purified water and the concentration of the treatment agent in the purified water, respectively. A temperature sensor, connected to the inner wall of the reactor, is used to detect the temperature of the mixture inside the reactor.

6. The low-temperature water treatment separation system based on a deep learning model according to claim 5, characterized in that, The control module is connected to the high performance liquid chromatograph and is used to calculate the variance of the pollutant concentration in the purified water based on the concentration of pollutants in the purified water within several treatment cycles, and to determine that the treatment stability of the source water supply does not meet the requirements when the variance of the pollutant concentration in the purified water meets the first variance condition or the second variance condition. The control module is connected to the high performance liquid chromatograph and is used to initially determine that the mixing effectiveness of the source water supply and the treatment agent does not meet the requirements when the variance of the pollutant concentration in the purified water only meets the first variance condition, and to make a second determination on the mixing effectiveness of the source water supply and the treatment agent based on the average concentration difference of the treatment agent in the purified water. Wherein, the first variance condition is that the variance of the pollutant concentration in the purified water is greater than a preset first variance and less than or equal to a preset second variance; the second variance condition is that the variance of the pollutant concentration in the purified water is greater than a preset second variance.

7. The low-temperature water treatment decomposition system based on a deep learning model according to claim 6, characterized in that, The control module is connected to the electric valve and is used to reduce the output rate of the purified water when the variance of the pollutant concentration in the purified water only meets the second variance condition. The reduced output rate is determined by the difference between the variance of the pollutant concentration in the purified water and the preset second variance.

8. The low-temperature water treatment decomposition system based on a deep learning model according to claim 7, characterized in that, The control module is connected to the high performance liquid chromatograph and is used to make a secondary determination that the mixing effectiveness of the source water and the treatment agent does not meet the requirements when the average concentration difference of the treatment agent in the purified water meets the first difference condition or the second difference condition; and to make a preliminary determination that the heating effect does not meet the requirements when the average concentration difference of the treatment agent in the purified water only meets the second difference condition, and to make a secondary determination of the heating effect based on the temperature rise rate of the mixture. The control module is connected to the stirring assembly and is used to reduce the vertical height of the stirring paddle when the average concentration difference of the treatment agent in the purified water only meets the first difference condition. Wherein, the first difference condition is that the average concentration difference of the treatment agent in the purified water is greater than a preset first difference and less than or equal to a preset second difference; the second difference condition is that the average concentration difference of the treatment agent in the purified water is greater than a preset second difference.

9. The low-temperature water treatment decomposition system based on a deep learning model according to claim 7, characterized in that, The adjustment range of the vertical height of the agitator is determined by the difference between the average concentration difference of the treatment agent in the purified water and a preset first difference.

10. The low-temperature water treatment decomposition system based on a deep learning model according to claim 9, characterized in that, The control module is connected to the temperature sensor and is used to determine that the heating effect does not meet the requirements when the temperature rise rate of the mixture is greater than the preset rise rate, and to increase the interval between the heating time and the cooling time. The increased interval between heating and cooling times is determined by the difference between the temperature rise rate of the mixture and the preset rise rate.

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