Multi-source sewage mixing treatment method and device for sewage treatment plant

Abstract

The present application relates to the technical field of sewage treatment, and discloses a multi-source sewage mixing treatment method and device for a sewage treatment plant. The method includes creating a sewage treatment model of the sewage treatment plant, marking the specification parameters of each treatment component and associating them with a chemical analysis program to generate a sewage reaction model; determining the target treatment component, obtaining the detection information of several single-source sewage, marking the main pollution indicators and non-main pollution indicators in the detection information, and statistically calculating the sewage volume, the concentration of each pollution indicator and the modulation index value of each single-source sewage; inputting the sewage volume, the concentration of each pollution indicator, the modulation index value and the information of several purification aids of each single-source sewage into the sewage reaction model, setting the stage effluent standard and the optimization goal, and generating a sewage input control program based on the reaction optimization algorithm; inputting the sewage input control program into the controller of the target treatment component to control the target treatment component; the present application can optimize the purification effect of multi-source sewage treatment.

Description

Technical Field

[0001] The present application relates to the technical field of sewage treatment, and in particular to a multi-source sewage mixing treatment method and device for sewage treatment plants. Background Technique

[0002] Sewage treatment plants are used to perform a series of purification treatments on the input sewage to purify the sewage to meet the water quality standards for discharge or other uses. A built sewage treatment plant has limited sewage treatment capacity, and its treatment efficiency range for various pollutants and modulation indicators is limited. Therefore, it is necessary to monitor the water quality of the sewage entering the sewage treatment plant; however, sewage treatment plants need to receive and treat sewage from multiple different sources, and the sewage from different sources has complex components and different concentrations. Currently, sewage treatment plants usually simply mix the sewage from different sources and then perform purification treatment. However, when different sewage is mixed, physical, chemical, and biological reactions may occur between different pollutants in the sewage. Therefore, the above-mentioned related technologies have the problem that the mixing of multi-source sewage affects the sewage purification effect. Summary of the Invention

[0003] In order to optimize the purification effect of multi-source sewage treatment, the present application provides a multi-source sewage mixing treatment method and device for sewage treatment plants.

[0004] The first invention object of the present application is achieved by the following technical solutions:

[0005] A multi-source sewage mixing treatment method for a sewage treatment plant, comprising:

[0006] Based on the design drawings of the sewage treatment plant, create a sewage treatment model, mark the specification parameters of each treatment component in the sewage treatment model, and associate the sewage treatment model with a chemical analysis program to generate a sewage reaction model;

[0007] Determine the target treatment component, obtain the detection information of several single-source sewage, mark the main pollution indicators and non-main pollution indicators in the detection information, and count the sewage volume, the concentration of each pollution indicator, and the modulation index value of each single-source sewage;

[0008] Input the sewage volume, the concentration of each pollution indicator, the modulation index value, and the information of several purification aids of each single-source sewage into the sewage reaction model, set the stage effluent standard and the optimization target, and generate a sewage input control program based on the reaction optimization algorithm;

[0009] Input the sewage input control program into the controller of the target treatment component to control the unit time input volume and input order of several single-source sewage and purification aids corresponding to the target treatment component;

[0010] The sewage treatment plant is provided with a number of treatment components, which include an inlet pipe for receiving single-source sewage, an outlet pipe for discharging single-source sewage, a water storage function pool, and a purification function pool. The water storage function pool is provided with a number of water storage units for storing single-source sewage. Each treatment component is provided with an inlet sensor, an outlet sensor, and a purification tank sensor; the sewage reaction model is built-in with a reaction optimization algorithm; the detection information includes sewage flow rate, concentrations of several pollution indicators, and modulation index values.

[0011] By adopting the above technical solution, based on the design drawings of the sewage treatment plant, determine the specification parameters of each treatment component in the sewage treatment plant to create a sewage treatment model and mark each specification parameter, and associate the sewage treatment model with a chemical analysis program to generate a sewage reaction model, which is convenient for subsequent computer simulation of the reaction of multi-source sewage input into the sewage treatment component and the sewage purification process in combination with the specification parameters of each sewage treatment component; after determining the target treatment component one by one, obtain the detection information of several single-source sewage input corresponding to the target treatment component, determine the main pollution indicators and non-main pollution indicators according to the detection information, and count the sewage volume, concentrations of various pollution indicators, and modulation index values of each single-source sewage, which is convenient for determining the pollution type and pollution degree of several single-source sewage input into the target treatment component; input the sewage volume, concentrations of various pollution indicators, modulation index values, and information of several purification aids of each single-source sewage into the sewage reaction model to know the sewage input situation and available purification aid situation of the target treatment component, set the stage effluent standard and optimization goal, and analyze the optimal unit time input volume and input order of various single-source sewage and purification aids based on the stage effluent standard and optimization goal by using the reaction optimization algorithm, so as to generate a sewage input control program; input the sewage input control program into the controller of the target treatment component to control the unit time input volume and input order of the corresponding single-source sewage and purification aids of the target treatment component, thereby improving the purification effect of multi-source sewage treatment through the computer optimization algorithm.

[0012] In a preferred example of the present application: The obtaining of the detection information of several single-source sewage includes:

[0013] Obtain the sewage flow rate, pollution indicator concentration, modulation index value, and sampling time of the single-source sewage based on a preset detection frequency and input them into a data sampling form;

[0014] When an index mutation is detected, generate a sensor purification instruction and send it to the corresponding purification component to purify the corresponding sensor;

[0015] Generate detection information based on the data sampling form;

[0016] The indicator mutation refers to the phenomenon that the detected value of any one of the sewage flow rate, the concentration of pollution indicators, and the modulation index value shows a numerical mutation; the influent sensor, the effluent sensor, and the purification tank sensor are all provided with purification components for cleaning.

[0017] By adopting the above technical solution, based on the detection frequency, the sewage flow rate, the concentration of pollution indicators, the modulation index value, and the sampling time of the single-source sewage are obtained, so as to record the change of the attributes of the single-source sewage input to the target treatment component over time, and input it into the data sampling form; when an indicator mutation is detected, it indicates that there has been a significant change in the attributes of the input single-source sewage, and a sensor purification instruction is generated and sent to the purification component corresponding to the sensor where the indicator mutation is detected, so as to control the purification component to purify the sensor, thereby reducing the residual effect of the pollution indicator concentration and the modulation index value data when the attributes of the water quality detected by the sensor change significantly, and improving the accuracy of the detection information; based on the data sampling form, the detection information of the single-source sewage is generated, so as to determine the pollution type and pollution degree of several single-source sewage input to the target treatment component subsequently.

[0018] In a preferred example of the present application: the numerical mutation refers to the phenomenon that among three sampling values with adjacent time, the absolute values of the deviation rates of the second sampling value and the third sampling value relative to the first sampling value are both greater than the corresponding preset indicator deviation threshold;

[0019] After generating a sensor purification instruction and sending it to the corresponding purification component to purify the corresponding sensor when an indicator mutation is detected, it further includes:

[0020] Input the first sampling value, the second sampling value, and the third sampling value corresponding to the indicator mutation to the preset correction quantity calculation formula to calculate the correction quantity of the sampling value;

[0021] Set the second sampling value, the third sampling value, and the subsequent correction quantity of sampling values as the data to be corrected, and take the preset regression sampling quantity of sampling values sorted after the data to be corrected and set them as the regression analysis data;

[0022] Generate a regression prediction curve based on several regression analysis data, predict the correction values of each data to be corrected based on the regression prediction curve to determine the corrected data corresponding to each data to be corrected, and adjust the data sampling form based on each corrected data;

[0023] Among them, the correction quantity calculation formula is:

[0024] ;

[0025] ;

[0026] is the correction quantity, is the first sampling value, is the second sampling value, is the third sampling value, is the first coefficient, is the deviation correction term, is the second coefficient, is the deviation correction reference parameter.

[0027] By adopting the above technical solution, numerical mutation refers to the phenomenon that, among three sampling values with adjacent time, the absolute values of the deviation rates of the second sampling value and the third sampling value relative to the first sampling value are both greater than the corresponding preset index deviation threshold, so as to reduce the possibility of misjudging data fluctuations as numerical mutation phenomena; input the first sampling value, the second sampling value, and the third sampling value corresponding to the index mutation into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value. The correction quantity calculation formula includes a deviation degree term that subtracts the average value of the second sampling value and the third sampling value from the first sampling value and multiplies by the first coefficient, and a deviation correction term. The greater the deviation degree between the first sampling value and the second sampling value and the third sampling value, the greater the degree of the numerical mutation phenomenon, and the larger the range of sampling values that need to be corrected. In the deviation correction term, the deviation degree between the second sampling value and the third sampling value is negatively correlated with the value of the deviation correction term, and the minimum value of the value of the deviation correction term is 0. When the deviation between the second sampling value and the third sampling value is greater, it is considered that the type of numerical mutation that occurs may be numerical fluctuation, and the range of sampling values that need to be corrected needs to be reduced, otherwise vice versa; set the second sampling value, the third sampling value, and the subsequent correction quantity of sampling values as the data to be corrected, and take the preset number of regression sampling values sorted after the data to be corrected and set them as regression analysis data, so as to correct the data to be corrected based on the processing of the regression analysis data; generate a regression prediction curve based on a number of regression analysis data, predict the correction value corresponding to the sampling time of each data to be corrected based on the regression prediction curve to determine the corrected data corresponding to each data to be corrected, and adjust the data sampling form based on each corrected data, thereby improving the accuracy of the detection information.

[0028] In a preferred example of the present application: after inputting the sewage volume, various pollution index concentrations, modulation index values, and information of several purification aids of each single-source sewage into the sewage reaction model, it includes:

[0029] Perform element sorting processing based on each single-source sewage and purification aids to generate several dosing sequences, and determine the dosing intervals of each element in the dosing sequence based on the number of elements and the stage processing time;

[0030] Simulate the processing results of each dosing sequence based on the sewage reaction model, and perform optimization effect ranking on several dosing sequences respectively based on a preset number of optimization objectives to obtain several optimization effect ranking forms;

[0031] The optimization objectives include purification effect, purification efficiency, cost efficiency, and environmental protection efficiency.

[0032] By adopting the above technical solution, each single-source sewage and purification aid are sorted as elements to generate all feasible dosing sequences. The dosing interval time of each element in the dosing sequence is determined based on the number of elements and the available treatment time at this purification stage, so as to preliminarily set the feasible dosing sequences; various dosing sequences are simulated based on the sewage reaction model to obtain the corresponding sewage treatment results. Based on several optimization objectives, several dosing sequences are sorted according to different optimization objectives to obtain several optimization effect ranking forms. An optimization effect ranking form refers to a form in which several dosing sequences are arranged from high to low according to the optimization effect for one optimization objective.

[0033] In a preferred example of this application: the effluent standard and optimization objectives of the setting stage are used to generate a sewage input control program based on the reaction optimization algorithm, and it further includes:

[0034] The set effluent standard and optimization objectives are imported into the reaction optimization algorithm, and combined with the sewage volume, various pollution index concentrations, modulation index values of each single-source sewage, and information on several purification aids to set the starting conditions, effluent standard, and boundary conditions of the sewage reaction;

[0035] Based on the optimization objective, the corresponding optimization effect ranking form is retrieved, and several dosing sequences that meet the optimization objective and are ranked in the front are retrieved from it for genetic algorithm analysis, so as to optimize the dosing methods of each single-source sewage and purification aid according to the set starting conditions, effluent standard, and boundary conditions, and generate a sewage input control program.

[0036] By adopting the above technical solution, the set effluent standard of the stage and the selected optimization objective are imported into the reaction optimization algorithm, and combined with the known sewage volume, various pollution index concentrations, modulation index values of each single-source sewage, and information on several purification aids to set the starting conditions, effluent standard, and boundary conditions of the sewage reaction. The current sewage input situation, available purification aid situation, sewage treatment requirements, and constraints of the hardware facilities of the sewage treatment plant are set to improve the reliability of subsequent optimization analysis; based on the optimization objective, the corresponding optimization effect ranking form is retrieved, and several dosing sequences that meet the optimization objective and are ranked in the front are retrieved from it. The specific number can be determined according to the performance of the computer device running the reaction optimization algorithm or actual requirements. The retrieved dosing sequences are analyzed by the genetic algorithm to optimize and analyze to obtain the optimal dosing methods of each single-source sewage and purification aid, including dosing order, dosing amount per unit time during dosing, total dosing amount, etc., so as to generate a sewage input control program according to the optimization results.

[0037] The second inventive object of the present application is achieved by the following technical solutions:

[0038] A multi-source sewage mixing treatment device for a sewage treatment plant, which is applied to the multi-source sewage mixing treatment method for a sewage treatment plant described in any one of the above, includes:

[0039] A sewage reaction model generation module, which is used to create a sewage treatment model based on the design drawings of the sewage treatment plant, mark the specification parameters of each treatment component in the sewage treatment model, associate the sewage treatment model with a chemical analysis program, and generate a sewage reaction model;

[0040] A single-source sewage detection and analysis module, which is used to determine the target treatment component, obtain the detection information of several single-source sewage, mark the main pollution indicators and non-main pollution indicators in the detection information, and count the sewage volume, the concentration of each pollution indicator and the modulation index value of each single-source sewage;

[0041] A sewage input control and analysis module, which is used to input the sewage volume, the concentration of each pollution indicator, the modulation index value and several purification aid information of each single-source sewage into the sewage reaction model, set the stage effluent standard and optimization goal, and generate a sewage input control program based on the reaction optimization algorithm;

[0042] A sewage input control execution module, which is used to input the sewage input control program into the controller of the target treatment component to control the unit time input volume and input sequence of several single-source sewage and purification aids corresponding to the target treatment component;

[0043] The sewage treatment plant is provided with several treatment components. The treatment components include an inlet pipe for receiving single-source sewage, an outlet pipe for discharging single-source sewage, a water storage function pool and a purification function pool. The water storage function pool is provided with several water storage units for storing single-source sewage. Each treatment component is provided with an inlet sensor, an outlet sensor and a purification pool sensor; the sewage reaction model is built-in with a reaction optimization algorithm; the detection information includes sewage flow, the concentration of several pollution indicators, and the modulation index value.

[0044] In a preferred example of the present application: the single-source sewage detection and analysis module includes:

[0045] A data sampling sub-module, which is used to obtain the sewage flow, the pollution indicator concentration, the modulation index value and the sampling time of the single-source sewage based on a preset detection frequency and input them into a data sampling form;

[0046] A sensor purification sub-module, which is used to generate a sensor purification instruction and send it to the corresponding purification component to purify the corresponding sensor when an index mutation is detected;

[0047] A detection information generation sub-module, which is used to generate detection information based on the data sampling form;

[0048] The said index mutation refers to the phenomenon that the detected value of any one of the sewage flow rate, the concentration of pollution index, and the value of modulation index has a numerical mutation; the inlet sensor, the outlet sensor, and the purification tank sensor are all provided with purification components for cleaning.

[0049] In a preferred example of the present application: the sensor purification sub-module includes:

[0050] A correction quantity calculation sub-module, which is used to input the first sampling value, the second sampling value, and the third sampling value corresponding to the numerical mutation of the index mutation into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value;

[0051] A data to be corrected setting sub-module, which is used to set the second sampling value, the third sampling value, and the subsequent correction quantity of sampling values as the data to be corrected, and take the preset regression sampling quantity of sampling values sorted after the data to be corrected and set them as regression analysis data;

[0052] A regression analysis correction sub-module, which is used to generate a regression prediction curve based on a number of regression analysis data, predict the correction value of each data to be corrected based on the regression prediction curve to determine the corrected data corresponding to each data to be corrected, and adjust the data sampling form based on each corrected data;

[0053] The said numerical mutation refers to the phenomenon that among three sampling values adjacent in time, the absolute values of the deviation rates of the second sampling value and the third sampling value relative to the first sampling value are both greater than the corresponding preset index deviation threshold;

[0054] Among them, the correction quantity calculation formula is:

[0055] ;

[0056] ;

[0057] is the correction quantity, is the first sampling value, is the second sampling value, is the third sampling value, is the first coefficient, is the deviation correction term, is the second coefficient, is the deviation correction reference parameter.

[0058] The third object of the invention of the present application is achieved by the following technical solution:

[0059] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned multi-source sewage mixing treatment method for sewage treatment plants are implemented.

[0060] The fourth inventive object of this application is achieved by the following technical solution:

[0061] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the above-mentioned multi-source sewage mixing treatment method for sewage treatment plants are implemented.

[0062] In summary, this application includes at least one of the following beneficial technical effects:

[0063] 1. Based on the design drawings of the sewage treatment plant, determine the specification parameters of each treatment component in the sewage treatment plant to create a sewage treatment model and mark each specification parameter, and associate the sewage treatment model with a chemical analysis program to generate a sewage reaction model, which is convenient for subsequent computer simulation of the reaction and sewage purification process of multi-source sewage input into the sewage treatment component in combination with the specification parameters of each sewage treatment component; after determining the target treatment component one by one, obtain the detection information of several single-source sewage corresponding to the target treatment component, determine the main pollution indicators and non-main pollution indicators according to the detection information, and count the sewage volume, various pollution indicator concentrations and modulation indicator values of each single-source sewage, which is convenient for determining the pollution type and degree of several single-source sewage input into the target treatment component; input the sewage volume, various pollution indicator concentrations, modulation indicator values and information of several purification aids of each single-source sewage into the sewage reaction model to know the sewage input situation and available purification aid situation of the target treatment component, set the stage effluent standard and optimization goal, and analyze the optimal unit time input volume and input order of various single-source sewage and purification aids based on the stage effluent standard and optimization goal using a reaction optimization algorithm, so as to generate a sewage input control program; input the sewage input control program into the controller of the target treatment component to control the unit time input volume and input order of the corresponding single-source sewage and purification aids of the target treatment component, thereby improving the purification effect of multi-source sewage treatment through a computer optimization algorithm.

[0064] 2. Obtain the sewage flow rate, pollution index concentration, modulation index value, and sampling time of single-source sewage based on the detection frequency, so as to record the change of the attributes of the single-source sewage input to the target processing component over time and input it into the data sampling form; when an index mutation is detected, it indicates that there has been a significant change in the attributes of the input single-source sewage, generate a sensor purification instruction and send it to the purification component corresponding to the sensor where the index mutation is detected, so as to control the purification component to purify the sensor, thereby reducing the residual effect of the pollution index concentration and modulation index value data when the attributes of the water quality detected by the sensor change significantly, and improving the accuracy of the detection information; generate the detection information of the single-source sewage based on the data sampling form, so as to subsequently determine the pollution type and pollution degree of several single-source sewage input to the target processing component.

[0065] 3. Numerical mutation refers to the phenomenon that the absolute values of the deviation rates of the second sampling value and the third sampling value relative to the first sampling value are both greater than the corresponding preset index deviation threshold among three sampling values with adjacent time, in order to reduce the possibility of misjudging data fluctuations as numerical mutation phenomena; input the first sampling value, second sampling value, and third sampling value corresponding to the index mutation as numerical mutation into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value. The correction quantity calculation formula includes a deviation degree term that calculates the difference between the first sampling value and the average of the second sampling value and the third sampling value and multiplies it by the first coefficient, and a deviation correction term. The greater the deviation degree between the first sampling value and the second sampling value and the third sampling value, the greater the degree of the numerical mutation phenomenon, and the larger the range of sampling values that need to be corrected. In the deviation correction term, the deviation degree between the second sampling value and the third sampling value is negatively correlated with the value of the deviation correction term, and the minimum value of the deviation correction term is 0. When the deviation between the second sampling value and the third sampling value is larger, it is considered that the type of numerical mutation that occurs may be numerical fluctuation, and the range of sampling values to be corrected needs to be reduced, otherwise vice versa; set the second sampling value, the third sampling value, and the subsequent correction quantity of sampling values as data to be corrected, and take the preset regression sampling quantity of sampling values sorted after the data to be corrected and set them as regression analysis data, so as to correct the data to be corrected based on the processing of the regression analysis data; generate a regression prediction curve based on several regression analysis data, predict the correction value corresponding to the sampling time of each data to be corrected based on the regression prediction curve, determine the corrected data corresponding to each data to be corrected, and adjust the data sampling form based on each corrected data, thereby improving the accuracy of the detection information. Description of the Drawings

[0066] Figure 1 is the flowchart of the multi-source sewage mixing treatment method for the sewage treatment plant in Embodiment 1 of the present application.

[0067] Figure 2 is a principle block diagram of the multi-source sewage mixing treatment device for the sewage treatment plant in Embodiment 2 of the present application.

[0068] Figure 3 It is a schematic diagram of the device in Embodiment 3 of the present application. Detailed implementation manners

[0069] The following further elaborates on the present application Figures 1 to 3 in conjunction with the accompanying drawings.

[0070] Embodiment 1

[0071] Referring to Figure 1 , the present application discloses a multi-source sewage mixing treatment method for a sewage treatment plant, which specifically includes the following steps:

[0072] S10: Based on the design drawings of the sewage treatment plant, create a sewage treatment model, mark the specification parameters of each treatment component in the sewage treatment model, and associate the sewage treatment model with a chemical analysis program to generate a sewage reaction model.

[0073] In this embodiment, the sewage treatment plant is provided with several treatment components. A treatment component refers to a functional module composed of several devices, equipment, and components used for a sewage purification stage treatment in the sewage treatment plant. Its specification parameters include the dimensions, volumes, specific heat capacities, heat conduction correlation coefficients, etc. of each device, equipment, and component; the treatment components include an inlet pipe for receiving single-source sewage, an outlet pipe for discharging single-source sewage, a water storage function pool, and a purification function pool. Among them, the outlet function pool can be a dedicated water storage tank / container, or other types of pools / containers with water storage functions can be used according to actual needs; the water storage function pool is provided with several water storage units for storing single-source sewage, and the sizes of each water storage unit can be the same or different. One type of single-source sewage can be stored in multiple water storage units; each treatment component is provided with an inlet sensor, an outlet sensor, and a purification pool sensor. Each sensor is provided with a flow rate detection, and a detection sensor for pollution indicators and modulation indicators as required. The sewage reaction model is built-in with a reaction optimization algorithm.

[0074] Specifically, based on the design drawings of the sewage treatment plant, determine the specification parameters of each treatment component in the sewage treatment plant to create a sewage treatment model and mark each specification parameter, and associate the sewage treatment model with a chemical analysis program to generate a sewage reaction model, so as to facilitate subsequent computer simulation of the reaction of multi-source sewage input into the sewage treatment component and the sewage purification process in combination with the specification parameters of each sewage treatment component.

[0075] S20: Determine the target treatment component, obtain the detection information of several single-source sewage, mark the main pollution indicators and non-main pollution indicators in the detection information, and count the sewage volume, the concentration of each pollution indicator, and the modulation indicator value of each single-source sewage.

[0076] In this embodiment, the pollution index refers to the index of pollutants, and there is a corresponding relationship between the pollution index and data such as the pollution index concentration and the pollution index quantity; the modulation index refers to the index of the physical, chemical, and biological properties of the sewage, such as temperature, pH value, chemical oxygen demand, biological oxygen demand, etc. There is a corresponding relationship between the modulation index and data such as the modulation index quantity; the main pollution index refers to the index that needs to be included in the pollutant analysis, and the non-main pollution index refers to the index that does not need to be included in the pollutant analysis because the pollutant concentration is lower than the corresponding specific threshold or not detected; the detection information includes the sewage flow rate, the concentrations of several pollution indexes, and the modulation index values.

[0077] Specifically, after determining the target treatment component one by one, obtain the detection information of several single-source sewage input to the corresponding target treatment component, determine the main pollution index and the non-main pollution index according to the detection information, and count the sewage volume, the concentrations of various pollution indexes, and the modulation index values of each single-source sewage, so as to determine the pollution type and pollution degree of the several single-source sewage input to the target treatment component.

[0078] Among them, in step S20: obtaining the detection information of several single-source sewage, it includes:

[0079] S21: Obtain the sewage flow rate, pollution index concentration, modulation index value, and sampling time of the single-source sewage based on the preset detection frequency and input them into the data sampling form.

[0080] Specifically, obtain the sewage flow rate, pollution index concentration, modulation index value, and sampling time of the single-source sewage based on the detection frequency, so as to record the change of the attributes of the single-source sewage input to the target treatment component over time, and input them into the data sampling form.

[0081] S22: When an index mutation is detected, generate a sensor purification instruction and send it to the corresponding purification component to purify the corresponding sensor.

[0082] In this embodiment, an index mutation refers to a phenomenon in which the detected value of any one of the sewage flow rate, pollution index concentration, and modulation index value shows a numerical mutation; a numerical mutation refers to a phenomenon in which, among three sampling values adjacent in time, the absolute values of the deviation rates of the second sampling value and the third sampling value relative to the first sampling value are both greater than the corresponding preset index deviation threshold. The index deviation threshold can be set according to actual needs. Preferably, the index deviation threshold can be set to 3%. A numerical mutation refers to a phenomenon in which, among three sampling values adjacent in time, the absolute values of the deviation rates of the second sampling value and the third sampling value relative to the first sampling value are both greater than the corresponding preset index deviation threshold, so as to reduce the possibility of misjudging data fluctuations as numerical mutation phenomena.

[0083] The inlet sensor, the outlet sensor, and the purification tank sensor are all provided with purification components for cleaning. Preferably, the purification component is a device with a water spraying and cleaning function.

[0084] Specifically, when an index mutation is detected, it indicates that there has been a significant change in the attributes of the input single-source sewage. A sensor purification instruction is generated and sent to the purification component corresponding to the sensor that detected the index mutation to control the purification component to purify the sensor, thereby reducing the residual effect of the pollution index concentration and the modulation index value data when the attributes of the water quality detected by the sensor change significantly, and improving the accuracy of the detection information.

[0085] S23: Generate detection information based on the data sampling form.

[0086] Specifically, generate the detection information of the single-source sewage based on the data sampling form, so as to determine the pollution type and pollution degree of several single-source sewage input into the target processing component later.

[0087] Among them, in step S22, it includes:

[0088] S221: Input the first sampling value, the second sampling value, and the third sampling value corresponding to the numerical mutation of the index mutation into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value.

[0089] In this embodiment, the correction quantity calculation formula is:

[0090] ;

[0091] ;

[0092] is the correction quantity, is the first sampling value, is the second sampling value, is the third sampling value, is the first coefficient, is the deviation correction term, is the second coefficient, is the deviation correction reference parameter; the first coefficient, the second coefficient, and the deviation correction reference parameter can be set and adjusted according to actual needs to meet the actual needs.

[0093] Specifically, input the first sampling value, the second sampling value, and the third sampling value corresponding to the index mutation and the numerical mutation into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value. The correction quantity calculation formula includes a deviation degree term that calculates the difference between the first sampling value and the average of the second sampling value and the third sampling value and multiplies it by a first coefficient, and a deviation correction term. The greater the deviation degree between the first sampling value and the second sampling value and the third sampling value, the greater the degree of numerical mutation phenomenon, and the larger the range of sampling values that need to be corrected. In the deviation correction term, the deviation degree between the second sampling value and the third sampling value is negatively correlated with the value of the deviation correction term, and the minimum value of the deviation correction term is 0. When the deviation between the second sampling value and the third sampling value is larger, it is considered that the type of numerical mutation that occurs may be numerical fluctuation, and the range of sampling values that need to be corrected needs to be reduced, otherwise vice versa.

[0094] S222: Set the second sampling value, the third sampling value, and the subsequent correction quantity of sampling values as the data to be corrected, and take the preset regression sampling quantity of sampling values sorted after the data to be corrected and set them as the regression analysis data.

[0095] Specifically, set the second sampling value, the third sampling value, and the subsequent correction quantity of sampling values as the data to be corrected, and take the preset regression sampling quantity of sampling values sorted after the data to be corrected and set them as the regression analysis data, so as to correct the data to be corrected based on the processing of the regression analysis data.

[0096] S223: Generate a regression prediction curve based on a number of regression analysis data, predict the correction values of each data to be corrected based on the regression prediction curve to determine the corrected data corresponding to each data to be corrected, and adjust the data sampling form based on each corrected data.

[0097] Specifically, generate a regression prediction curve based on a number of regression analysis data, predict the correction values corresponding to the sampling times of each data to be corrected based on the regression prediction curve to determine the corrected data corresponding to each data to be corrected, and adjust the data sampling form based on each corrected data, thereby improving the accuracy of the detection information.

[0098] S30: Input the sewage volume of each single-source sewage, the concentration of each pollution index, the modulation index value, and the information of a number of purification aids into the sewage reaction model, set the stage effluent standard and the optimization goal, and generate a sewage input control program based on the reaction optimization algorithm.

[0099] In this embodiment, the purification aid information includes model information, parameter information, cost information, environmental protection evaluation value information, etc., which is convenient for subsequent evaluation of its purification function, cost, and environmental protection situation; the stage effluent standard includes the amounts of various pollution indexes and the modulation index value of the sewage produced in the current stage.

[0100] Specifically, input the sewage volume, the concentration of various pollution indicators, the modulation index value, and the information of several purification aids of each single-source sewage into the sewage reaction model, so as to obtain the sewage input situation and the available purification aids situation of the target treatment component, set the stage effluent standard and the optimization goal, and analyze the optimal input volume per unit time and the input sequence of various single-source sewage and purification aids based on the stage effluent standard and the optimization goal by using the reaction optimization algorithm, so as to generate a sewage input control program.

[0101] Among them, after step S30: input the sewage volume, the concentration of various pollution indicators, the modulation index value, and the information of several purification aids of each single-source sewage into the sewage reaction model, it includes:

[0102] S31: Perform element sorting processing based on each single-source sewage and purification aids to generate several dosing sequences, and determine the dosing interval of each element in the dosing sequence based on the number of elements and the stage treatment time.

[0103] In this embodiment, the number of elements refers to the number of types of single-source sewage and purification aids.

[0104] Specifically, sort each single-source sewage and purification aids as elements to generate all feasible dosing sequences, and determine the dosing interval time of each element in the dosing sequence based on the number of elements and the available treatment time of this purification stage, so as to make a preliminary setting for the feasible dosing sequences.

[0105] S32: Simulate the treatment results of each dosing sequence based on the sewage reaction model, and perform optimization effect ranking on several dosing sequences respectively based on several preset optimization goals to obtain several optimization effect ranking forms.

[0106] In this embodiment, the preset optimization goals include purification effect, purification efficiency, cost efficiency, and environmental protection efficiency.

[0107] Specifically, simulate various dosing sequences based on the sewage reaction model to obtain the corresponding sewage treatment results, perform optimization effect ranking on several dosing sequences respectively according to different optimization goals based on several optimization goals, so as to obtain several optimization effect ranking forms. An optimization effect ranking form refers to a form in which several dosing sequences are arranged in descending order of optimization effect for one optimization goal.

[0108] Among them, in step S30: set the stage effluent standard and the optimization goal, and generate a sewage input control program based on the reaction optimization algorithm, it includes:

[0109] S33: Import the set stage effluent standard and optimization goal into the reaction optimization algorithm, and combine the sewage volume, the concentration of various pollution indicators, the modulation index value, and the information of several purification aids of each single-source sewage to set the initial conditions, effluent standard, and boundary conditions of the sewage reaction.

[0110] In this embodiment, the optimization objective is set according to the current demand; when the sewage inflow rate is less than 70% of the upper limit of the sewage treatment flow rate of the target treatment component, the purification effect, cost efficiency, or environmental protection efficiency is set as the optimization objective; when the sewage inflow rate is 70%-100% of the upper limit of the sewage treatment flow rate of the target treatment component, the optimization objective is set to optimize the cost efficiency or environmental protection efficiency on the premise of being able to treat the current sewage inflow rate; when the sewage inflow rate is greater than the upper limit of the sewage treatment flow rate of the target treatment component, the optimization objective is set to optimize the purification efficiency.

[0111] Specifically, the set stage effluent standard and the selected optimization objective are imported into the reaction optimization algorithm. Combining the known sewage volume, various pollution index concentrations, modulation index values, and information on clean purification aids of each single-source sewage, the starting conditions, effluent standard, and boundary conditions of the set sewage reaction are used to set the current sewage input situation, available purification aid situation, sewage treatment requirements, and constraints of the sewage treatment plant's hardware facilities, so as to improve the reliability of subsequent optimization analysis.

[0112] S34: Based on the optimization objective, retrieve the corresponding optimization effect ranking form, and retrieve several input sequences that meet the optimization objective and are ranked at the top from it for genetic algorithm analysis, so as to optimize the input methods of each single-source sewage and purification aids according to the set starting conditions, effluent standard, and boundary conditions, and generate a sewage input control program.

[0113] Specifically, based on the optimization objective, retrieve the corresponding optimization effect ranking form, and retrieve several input sequences that meet the optimization objective and are ranked at the top. The specific number can be determined according to the performance of the computer device running the reaction optimization algorithm or actual requirements. Conduct genetic algorithm analysis on the retrieved input sequences, so as to optimize and analyze according to the set starting conditions, effluent standard, and boundary conditions to obtain the optimal input methods of each single-source sewage and purification aids, including input order, unit time input volume during input, total input volume, etc., and thus generate a sewage input control program according to the optimization results.

[0114] S40: Input the sewage input control program into the controller of the target treatment component to control the unit time input volume and input order of the corresponding several single-source sewage and purification aids of the target treatment component.

[0115] Specifically, input the sewage input control program into the controller of the target treatment component to control the unit time input volume and input order of the corresponding single-source sewage and purification aids that are easy to dry of the target treatment component, thereby improving the purification effect of multi-source sewage treatment through computer optimization algorithms.

[0116] It should be understood that the sequence numbers of the steps in the above embodiments do not indicate the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0117] Embodiment 2

[0118] A multi-source sewage mixing treatment device for a sewage treatment plant, which corresponds to the multi-source sewage mixing treatment method for a sewage treatment plant in the above embodiment.

[0119] As Figure 2 shown, the multi-source sewage mixing treatment device for a sewage treatment plant includes a sewage reaction model generation module, a single-source sewage detection and analysis module, a sewage input control analysis module, and a sewage input control execution module. The detailed descriptions of each functional module are as follows:

[0120] The sewage reaction model generation module is used to create a sewage treatment model based on the design drawings of the sewage treatment plant, mark the specification parameters of each treatment component in the sewage treatment model, associate the sewage treatment model with a chemical analysis program, and generate a sewage reaction model;

[0121] The single-source sewage detection and analysis module is used to determine the target treatment component, obtain the detection information of several single-source sewage, mark the main pollution indicators and non-main pollution indicators in the detection information, and count the sewage volume, the concentration of each pollution indicator, and the modulation index value of each single-source sewage;

[0122] The sewage input control analysis module is used to input the sewage volume, the concentration of each pollution indicator, the modulation index value, and the information of several purification aids of each single-source sewage into the sewage reaction model, set the stage effluent standard and the optimization goal, and generate a sewage input control program based on the reaction optimization algorithm;

[0123] The sewage input control execution module is used to input the sewage input control program into the controller of the target treatment component to control the unit time input volume and input order of several single-source sewage and purification aids corresponding to the target treatment component.

[0124] Among them, the single-source sewage detection and analysis module further includes:

[0125] The data sampling sub-module is used to obtain the sewage flow rate, pollution indicator concentration, modulation index value, and sampling time of the single-source sewage based on a preset detection frequency and input them into the data sampling form;

[0126] The sensor purification sub-module is used to generate a sensor purification instruction and send it to the corresponding purification component when an index mutation is detected to purify the corresponding sensor;

[0127] A detection information generation sub-module, which is used to generate detection information based on a data sampling form.

[0128] Among them, the sensor purification sub-module further includes:

[0129] A correction quantity calculation sub-module, which is used to input the first sampling value, the second sampling value, and the third sampling value corresponding to the numerical mutation of the index mutation into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value;

[0130] A data to be corrected setting sub-module, which is used to set the second sampling value, the third sampling value, and the subsequent correction quantity of sampling values as the data to be corrected, and take the preset regression sampling quantity of sampling values sorted after the data to be corrected and set them as regression analysis data;

[0131] A regression analysis correction sub-module, which is used to generate a regression prediction curve based on a number of regression analysis data, predict the correction value of each data to be corrected based on the regression prediction curve to determine the corrected data corresponding to each data to be corrected, and adjust the data sampling form based on each corrected data.

[0132] Among them, the sewage input control analysis module further includes:

[0133] A dosing sequence generation sub-module, which is used to perform element sorting processing based on each single-source sewage and purification aids to generate a number of dosing sequences, and determine the dosing interval of each element in the dosing sequence based on the element quantity and the stage processing time;

[0134] An optimization effect ranking form generation sub-module, which is used to simulate the processing results of each dosing sequence based on a sewage reaction model, and perform optimization effect ranking on a number of dosing sequences respectively based on a number of preset optimization objectives to obtain a number of optimization effect ranking forms.

[0135] It further includes:

[0136] A condition setting sub-module, which is used to import the set stage effluent standard and optimization objective into a reaction optimization algorithm, and combine the sewage volume, various pollution index concentrations, modulation index values of each single-source sewage, and information of a number of purification aids to set the starting conditions, effluent standard, and boundary conditions of the sewage reaction;

[0137] A sewage input control program generation sub-module, which is used to retrieve the corresponding optimization effect ranking form based on the optimization objective, retrieve a number of dosing sequences that meet the optimization objective and are ranked in the front from it for genetic algorithm analysis, so as to optimize the dosing methods of each single-source sewage and purification aids according to the set starting conditions, effluent standard, and boundary conditions, and generate a sewage input control program.

[0138] For the specific limitations of the multi-source sewage mixing treatment device for sewage treatment plants, reference can be made to the limitations of the multi-source sewage mixing treatment method for sewage treatment plants in the above text, which will not be elaborated here; each module in the above multi-source sewage mixing treatment device for sewage treatment plants can be implemented in whole or in part by software, hardware, and their combinations; the above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0139] Embodiment III

[0140] A computer device, which can be a server, and its internal structure diagram can be as Figure 3 shown. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as design drawings of sewage treatment plants, sewage treatment models, specification parameters, chemical analysis programs, sewage reaction models, detection information, main pollution indicators, non-main pollution indicators, sewage volume, concentrations of various pollution indicators, modulation index values, purification aid information, stage effluent standards, optimization objectives, reaction optimization algorithms, sewage input control programs, etc. The network interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it realizes the multi-source sewage mixing treatment method for sewage treatment plants.

[0141] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are realized:

[0142] S10: Based on the design drawings of the sewage treatment plant, create a sewage treatment model, mark the specification parameters of each treatment component in the sewage treatment model, associate the sewage treatment model with the chemical analysis program, and generate a sewage reaction model;

[0143] S20: Determine the target treatment component, obtain the detection information of several single-source sewage, mark the main pollution indicators and non-main pollution indicators in the detection information, and count the sewage volume, concentrations of various pollution indicators, and modulation index values of each single-source sewage;

[0144] S30: Input the sewage volume, concentrations of various pollution indicators, modulation index values, and information on several purification aids of each single-source sewage into the sewage reaction model, set the stage effluent standard and optimization goal, and generate a sewage input control program based on the reaction optimization algorithm;

[0145] S40: Input the sewage input control program into the controller of the target treatment component to control the unit time input volume and input sequence of several single-source sewage and purification aids corresponding to the target treatment component.

[0146] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0147] S10: Create a sewage treatment model based on the design drawings of the sewage treatment plant, mark the specification parameters of each treatment component in the sewage treatment model, and associate the sewage treatment model with a chemical analysis program to generate a sewage reaction model;

[0148] S20: Determine the target treatment component, obtain the detection information of several single-source sewage, mark the main pollution indicators and non-main pollution indicators in the detection information, and count the sewage volume, concentrations of various pollution indicators, and modulation index values of each single-source sewage;

[0149] S30: Input the sewage volume, concentrations of various pollution indicators, modulation index values, and information on several purification aids of each single-source sewage into the sewage reaction model, set the stage effluent standard and optimization goal, and generate a sewage input control program based on the reaction optimization algorithm;

[0150] S40: Input the sewage input control program into the controller of the target treatment component to control the unit time input volume and input sequence of several single-source sewage and purification aids corresponding to the target treatment component.

[0151] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0152] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0153] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for treating mixed sewage from multiple sources in a sewage treatment plant, characterized in that: include: Based on the design drawings of the sewage treatment plant, create a sewage treatment model, mark the specification parameters of each treatment component in the sewage treatment model, associate the sewage treatment model with the chemical analysis program, and generate a sewage reaction model; Determine the target treatment component, obtain the detection information of several single-source sewage, mark the main pollution indicators and non-main pollution indicators in the detection information, and count the sewage volume, concentration of various pollution indicators and modulation index values ​​of each single-source sewage; Input the sewage volume, concentration of various pollution indicators, modulation index value and several purification aid information of each single source sewage into the sewage reaction model, set the stage effluent standard and optimization target, and generate the sewage input control program based on the reaction optimization algorithm; Inputting the sewage input control program into the controller of the target treatment component to control the input amount and input sequence of a plurality of single-source sewage and purification aids corresponding to the target treatment component per unit time; The sewage treatment plant is provided with several processing components, the processing components include an inlet pipe for receiving single-source sewage, an outlet pipe for discharging single-source sewage, a water storage function pool and a purification function pool, the water storage function pool is provided with several water storage units for storing single-source sewage, and each processing component is provided with an inlet sensor, an outlet sensor and a purification tank sensor; the sewage reaction model is built with a reaction optimization algorithm; the detection information includes sewage flow, several pollution index concentrations, and modulation index values; Wherein, the obtaining of detection information of several single-source sewage includes: Based on the preset detection frequency, the sewage flow, pollution index concentration, modulation index value and sampling time of the single-source sewage are obtained and input into the data sampling form; When a sudden change in the indicator is detected, a sensor purification instruction is generated and sent to the corresponding purification component to purify the corresponding sensor; Generate detection information based on data sampling form; The index mutation refers to the phenomenon that the detection value of any one of the indicators of sewage flow, pollution index concentration and modulation index value has a sudden change in value; the water inlet sensor, water outlet sensor and purification tank sensor are all provided with a purification component for cleaning; The sudden change in value refers to the phenomenon that among three sampling values ​​adjacent in time, the absolute values ​​of the deviation rates of the second sampling value and the third sampling value relative to the first sampling value are both greater than the corresponding preset indicator deviation threshold; After the above-mentioned generating a sensor purification instruction and sending it to the corresponding purification component to purify the corresponding sensor when a sudden change in the indicator is detected, the following is also included: The first sampling value, the second sampling value and the third sampling value of the index mutation corresponding to the numerical mutation are input into the preset correction quantity calculation formula to calculate the correction quantity of the sampling value. ; The second sample value, the third sample value and the subsequent The sampling values ​​are set as the data to be corrected, and the regression sampling quantity sampling values ​​preset after the data to be corrected are taken and set as the regression analysis data; Generate a regression prediction curve based on a number of regression analysis data, predict the correction value of each to-be-corrected data based on the regression prediction curve to determine the corrected data corresponding to each to-be-corrected data, and adjust the data sampling form based on each corrected data; The calculation formula for the corrected quantity is: ； ； To correct the quantity, is the first sampling value, is the second sampling value, is the third sampling value, is the first coefficient, is the bias correction term, is the second coefficient, Correct the baseline parameters for deviations.

2. The multi-source sewage mixed treatment method for a sewage treatment plant according to claim 1, characterized in that: After the sewage volume of each single source sewage, the concentration of each pollution index, the modulation index value and the information of several purification aids are input into the sewage reaction model, it includes: Based on each single-source sewage and purification aid, the elements are sorted and processed to generate several delivery sequences, and the delivery interval of each element in the delivery sequence is determined based on the number of elements and the stage processing time; Based on the sewage reaction model, the treatment results of each delivery sequence are simulated, and the optimization effects of several delivery sequences are sorted based on several preset optimization objectives to obtain several optimization effect sorting tables; The optimization objectives include purification effect, purification efficiency, cost efficiency and environmental protection efficiency.

3. The multi-source sewage mixed treatment method for a sewage treatment plant according to claim 2 is characterized in that: The setting stage effluent standard and optimization target, and the generation of sewage input control program based on the reaction optimization algorithm, include: The set stage effluent standards and optimization targets are introduced into the reaction optimization algorithm, and the sewage volume of each single source sewage, the concentration of each pollution index, the modulation index value and the information of several purification additives are combined to set the starting conditions, effluent standards and boundary conditions of the sewage reaction; Based on the optimization target, the corresponding optimization effect ranking form is retrieved, from which several delivery sequences that meet the optimization target and are ranked first are retrieved for genetic algorithm analysis, so as to optimize the delivery method of each single source sewage and purification aid according to the set starting conditions, effluent standards and boundary conditions, and generate a sewage input control program.

4. A multi-source sewage mixing treatment device for a sewage treatment plant, characterized in that: The multi-source sewage mixed treatment method for a sewage treatment plant as claimed in any one of claims 1 to 3 comprises: A sewage reaction model generation module is used to create a sewage treatment model based on the design drawings of the sewage treatment plant, mark the specification parameters of each treatment component in the sewage treatment model, associate the sewage treatment model with the chemical analysis program, and generate a sewage reaction model; The single-source sewage detection and analysis module is used to determine the target treatment component, obtain the detection information of several single-source sewage, mark the main pollution indicators and non-main pollution indicators in the detection information, and count the sewage volume, concentration of various pollution indicators and modulation index values ​​of each single-source sewage; The sewage input control analysis module is used to input the sewage volume of each single source sewage, the concentration of each pollution index, the modulation index value and a number of purification aids information into the sewage reaction model, set the stage effluent standard and optimization target, and generate the sewage input control program based on the reaction optimization algorithm; A sewage input control execution module, used to input the sewage input control program into the controller of the target treatment component to control the unit time input amount and input sequence of a plurality of single-source sewage and purification aids corresponding to the target treatment component; The sewage treatment plant is provided with several processing components, the processing components include an inlet pipe for receiving single-source sewage, an outlet pipe for discharging single-source sewage, a water storage function pool and a purification function pool, the water storage function pool is provided with several water storage units for storing single-source sewage, and each processing component is provided with an inlet sensor, an outlet sensor and a purification tank sensor; the sewage reaction model is built with a reaction optimization algorithm; the detection information includes sewage flow, several pollution index concentrations, and modulation index values; Wherein, the single-source sewage detection and analysis module includes: A data sampling submodule, for obtaining the sewage flow, pollution index concentration, modulation index value and sampling time of the single-source sewage based on a preset detection frequency and inputting them into a data sampling form; The sensor purification submodule is used to generate a sensor purification instruction and send it to the corresponding purification component to purify the corresponding sensor when a sudden change in the indicator is detected; A detection information generation submodule, used to generate detection information based on a data sampling form; The index mutation refers to the phenomenon that the detection value of any one of the indicators of sewage flow, pollution index concentration and modulation index value has a sudden change in value; the water inlet sensor, water outlet sensor and purification tank sensor are all provided with a purification component for cleaning; Wherein, the sensor purification submodule includes: The correction quantity calculation submodule is used to input the first sampling value, the second sampling value and the third sampling value of the numerical mutation corresponding to the index mutation into the preset correction quantity calculation formula to calculate the correction quantity of the sampling value ; The data to be corrected setting submodule is used to set the second sampling value, the third sampling value and the subsequent The sampling values ​​are set as the data to be corrected, and the regression sampling quantity sampling values ​​preset after the data to be corrected are taken and set as the regression analysis data; A regression analysis correction submodule is used to generate a regression prediction curve based on a number of regression analysis data, predict the correction value of each to-be-corrected data based on the regression prediction curve, so as to determine the corrected data corresponding to each to-be-corrected data, and adjust the data sampling form based on each corrected data; The sudden change in value refers to the phenomenon that among three sampling values ​​adjacent in time, the absolute values ​​of the deviation rates of the second sampling value and the third sampling value relative to the first sampling value are both greater than the corresponding preset indicator deviation threshold; The calculation formula for the corrected quantity is: ； ； To correct the quantity, is the first sampling value, is the second sampling value, is the third sampling value, is the first coefficient, is the bias correction term, is the second coefficient, Correct the baseline parameters for deviations.

5. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the multi-source sewage mixing treatment method for a sewage treatment plant as described in any one of claims 1 to 3 are implemented.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the multi-source sewage mixing treatment method for a sewage treatment plant as described in any one of claims 1 to 3 are implemented.

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