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

Abstract

The invention 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 comprises the following steps: creating a sewage treatment model of the sewage treatment plant, marking specification parameters of each treatment component, associating the specification parameters with a chemical analysis program, and generating a sewage reaction model; the method comprises the following steps: determining a target treatment component, acquiring detection information of a plurality of single-source sewage, marking main pollution indexes and non-main pollution indexes in the detection information, and counting sewage quantity, concentration of each pollution index and modulation index value of each single-source sewage; inputting the sewage quantity of each single-source sewage, each pollution index concentration, the modulation index value and the information of a plurality of purification aids into a sewage reaction model, setting a stage effluent standard and an optimization target, and generating a sewage input control program based on a reaction optimization algorithm; inputting the sewage input control program into a controller of the target treatment component to control the target treatment component; according to the invention, the purification effect of multi-source sewage treatment can be optimized.

Description

Technical Field

[0001] The present application relates to the technical field of sewage treatment, and in particular to a method and device for treating multi-source sewage mixture in a sewage treatment plant. Background Art

[0002] A sewage treatment plant is used to carry out a series of purification treatments on the input sewage, so as to purify the sewage until the water quality meets the standard before discharge or other purposes. A built sewage treatment plant has limited sewage treatment capacity, and its treatment efficiency range for various pollutants and modulation indicators is limited, so it is necessary to monitor the water quality entering the sewage treatment plant; however, sewage treatment plants need to receive and treat sewage from a variety of different sources. The sewage from different sources has complex components and different concentrations. Currently, sewage treatment plants usually simply mix sewage from different sources before purifying it. 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 of affecting the sewage purification effect after the mixing of sewage from multiple sources. 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 mixed treatment method and device for a sewage treatment plant.

[0004] The first invention objective of this application is achieved by adopting the following technical solution: Multi-source sewage mixed treatment method used in sewage treatment plants, including: 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 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 has a built-in reaction optimization algorithm; the detection information includes sewage flow, concentrations of several pollution indicators, and modulation index values.

[0005] By adopting the above technical scheme, based on the design drawings of the sewage treatment plant, the specification parameters of each treatment component in the sewage treatment plant are determined to create a sewage treatment model and mark each specification parameter, and the sewage treatment model and the chemical analysis program are associated to generate a sewage reaction model, so as to facilitate the 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, the detection information of several single-source sewage input into the target treatment component is obtained, the main pollution indicators and non-main pollution indicators are determined according to the detection information, and the sewage volume, concentration of various pollution indicators and modulation index values ​​of each single-source sewage are counted, so as to facilitate the determination of several single-source sewage input into the target treatment component. The type and degree of water pollution; the sewage volume of each single-source sewage, the concentration of each pollution index, the modulation index value and several purification aids information are input into the sewage reaction model in order to obtain the sewage input situation and available purification aids of the target treatment component, set the stage effluent standard and optimization target, and use the reaction optimization algorithm to analyze the optimal unit time input amount and input sequence of various single-source sewage and purification aids based on the stage effluent standard and optimization target, so as to generate a sewage input control program; the sewage input control program is input into the controller of the target treatment component to control the unit time input amount and input sequence of the easy-to-dry single-source sewage and purification aids corresponding to the target treatment component, thereby improving the purification effect of multi-source sewage treatment through computer optimization algorithm.

[0006] In a preferred example of the present application, the acquisition of detection information of a plurality of 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 including 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 purification components for cleaning.

[0007] By adopting the above technical scheme, the sewage flow, pollution index concentration, modulation index value and sampling time of the single-source sewage are obtained based on the detection frequency, so as to record the change of the properties of the single-source sewage input to the target treatment component over time and input it into the data sampling form; when a sudden change in the index is detected, it means that the properties of the input single-source sewage have changed significantly, and a sensor purification instruction is generated and sent to the purification component corresponding to the sensor that detected the sudden change in the index, 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 properties of the water quality detected by the sensor change significantly, thereby improving the accuracy of the detection information; the detection information of the single-source sewage is generated based on the data sampling form, so as to subsequently determine the pollution type and degree of pollution of several single-source sewages input to the target treatment component.

[0008] In a preferred example of the present application: 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: Inputting the first sampling value, the second sampling value and the third sampling value of the numerical mutation corresponding to the sudden change of the indicator into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value; The second sampling value, the third sampling value and the subsequent correction number of sampling values ​​are set as the data to be corrected, and the regression sampling number of 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.

[0009] By adopting the above technical solution, numerical mutation refers to the phenomenon that among the 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 greater than the corresponding preset indicator deviation threshold value, so as to reduce the possibility of misjudging data fluctuations as numerical mutation phenomena; the first sampling value, the second sampling value and the third sampling value corresponding to the numerical mutation of the indicator mutation are input into the preset correction quantity calculation formula to calculate the correction quantity of the sampling value, and the correction quantity calculation formula includes the deviation degree term and the deviation correction term of finding the difference between the first sampling value and the average value of the second sampling value and the third sampling value and multiplying it by the first coefficient. When the degree of deviation between the first sampling value and the second sampling value and the third sampling value is greater, the degree of numerical mutation phenomenon is greater, and the range of sampling values ​​that need to be corrected is larger, and in the deviation correction term, the difference between the second sampling value and the third sampling value is greater than the difference between the second sampling value and the third sampling value. The degree of deviation is negatively correlated with the value of the deviation correction item and the minimum value of the deviation correction item 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 may be numerical fluctuation, and the range of the corrected sampling value needs to be reduced, otherwise vice versa; the second sampling value, the third sampling value and the subsequent correction number of sampling values ​​are set as the data to be corrected, and the preset regression sampling number of sampling values ​​sorted after the data to be corrected are taken and set as the regression analysis data, so as to correct the data to be corrected based on the processing of the regression analysis data; a regression prediction curve is generated based on several regression analysis data, and the correction value corresponding to the sampling time of each data to be corrected is predicted based on the regression prediction curve to determine the corrected data corresponding to each data to be corrected, and the data sampling form is adjusted based on each corrected data, thereby improving the accuracy of the detection information.

[0010] In a preferred example of the present application, 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.

[0011] By adopting the above technical scheme, each single-source sewage and purification aid is sorted and processed as an element to generate all feasible release sequences, and the release interval time of each element in the release sequence is determined based on the number of elements and the available processing time of the purification stage, so as to preliminarily set the feasible release sequence; various release sequences are simulated based on the sewage reaction model to obtain the corresponding sewage treatment results, and based on several optimization objectives, several release sequences are sorted according to different optimization objectives, thereby obtaining several optimization effect sorting forms. An optimization effect sorting form refers to a form that arranges several release sequences from high to low according to the optimization effect for one optimization objective.

[0012] In a preferred example of the present application: the setting of the effluent standard and optimization target in the stage, generating the sewage input control program based on the reaction optimization algorithm, also includes: 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.

[0013] By adopting the above technical scheme, the set stage effluent standard and the selected optimization target are introduced into the reaction optimization algorithm, and the known sewage volume of each single source sewage, the concentration of each pollution index, the modulation index value and several purification auxiliary agent information are combined to set the starting conditions, effluent standards and boundary conditions of the sewage reaction, and the current sewage input situation, the available purification auxiliary agent situation, the sewage treatment demand, and the constraints of the hardware facilities of the sewage treatment plant are set to improve the reliability of subsequent optimization analysis; based on the optimization target, the corresponding optimization effect ranking form is retrieved, and a number of delivery sequences that meet the optimization target and are ranked first are retrieved, and the specific number can be determined according to the performance of the computer equipment running the reaction optimization algorithm or the actual needs. The retrieved delivery sequence is analyzed by genetic algorithm, so as to optimize and analyze according to the set starting conditions, effluent standards and boundary conditions to obtain the optimal delivery method of each single source sewage and purification auxiliary, including the delivery order, the delivery amount per unit time, the total delivery amount, etc., so as to generate a sewage input control program according to the optimization result.

[0014] The second invention objective of this application is achieved by the following technical solution: A multi-source sewage mixing treatment device for a sewage treatment plant, applied to any of the multi-source sewage mixing treatment methods for a sewage treatment plant described above, 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 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 has a built-in reaction optimization algorithm; the detection information includes sewage flow, concentrations of several pollution indicators, and modulation index values.

[0015] In a preferred example of the present application: 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 including 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 purification components for cleaning.

[0016] In a preferred example of the present application: the sensor purification submodule includes: A correction quantity calculation submodule, used for inputting the first sampling value, the second sampling value and the third sampling value of the numerical mutation corresponding to the indicator mutation into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value; The to-be-corrected data setting submodule is used to set the second sampling value, the third sampling value and the subsequent correction number sampling values ​​as the to-be-corrected data, and take the preset regression sampling number sampling values ​​sorted after the to-be-corrected data and set them 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.

[0017] The third invention objective of this application is achieved by the following technical solution: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the multi-source sewage mixing treatment method for a sewage treatment plant when executing the computer program.

[0018] The fourth invention objective of this application is achieved by the following technical solution: A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the multi-source sewage mixing treatment method for a sewage treatment plant.

[0019] In summary, the present application includes at least one of the following beneficial technical effects: 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, associate the sewage treatment model with the chemical analysis program to generate a sewage reaction model, so as to facilitate the 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 into the target treatment component, determine the main pollution indicators and non-main pollution indicators according to the detection information, and count the sewage volume, concentration of various pollution indicators and modulation index values ​​of each single-source sewage, so as to facilitate the determination of the pollution type of several single-source sewage input into the target treatment component type and pollution degree; input the sewage volume of each single-source sewage, the concentration of each pollution index, the modulation index value and several purification aids information into the sewage reaction model, so as to know the sewage input situation and available purification aids of the target treatment component, set the stage effluent standard and optimization target, and use the reaction optimization algorithm to analyze the optimal unit time input amount and input sequence of various single-source sewage and purification aids based on the stage effluent standard and optimization target, 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 amount and input sequence of the easy-to-dry single-source sewage and purification aids corresponding to the target treatment component, thereby improving the purification effect of multi-source sewage treatment through the computer optimization algorithm.

[0020] 2. Based on the detection frequency, the sewage flow, pollution index concentration, modulation index value and sampling time of the single-source sewage are obtained to record the changes in the properties of the single-source sewage input to the target treatment component over time, and input them into the data sampling form; when a sudden change in the index is detected, it means that the properties of the input single-source sewage have changed significantly, and a sensor purification instruction is generated and sent to the purification component corresponding to the sensor that detected the sudden change in the index, 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 properties of the water quality detected by the sensor change significantly, thereby improving the accuracy of the detection information; based on the data sampling form, the detection information of the single-source sewage is generated to subsequently determine the pollution type and degree of pollution of several single-source sewages input to the target treatment component.

[0021] 3. Numerical mutation refers to the phenomenon that among the 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 greater than the corresponding preset indicator deviation threshold value, so as to reduce the possibility of misjudging data fluctuations as numerical mutation phenomena; the first sampling value, the second sampling value and the third sampling value corresponding to the numerical mutation of the indicator mutation are input into the preset correction quantity calculation formula to calculate the correction quantity of the sampling value. The correction quantity calculation formula includes the deviation degree term and the deviation correction term of finding the difference between the first sampling value and the average value of the second sampling value and the third sampling value and multiplying it by the first coefficient. 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 It is negatively correlated with the value of the deviation correction item and the minimum value of the deviation correction item 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 may be numerical fluctuation, and the range of the corrected sampling value needs to be reduced, otherwise vice versa; the second sampling value, the third sampling value and the subsequent correction number of sampling values ​​are set as the data to be corrected, and the preset regression sampling number of sampling values ​​sorted after the data to be corrected are taken and set as the regression analysis data, so as to correct the data to be corrected based on the processing of the regression analysis data; a regression prediction curve is generated based on several regression analysis data, and the correction value corresponding to the sampling time of each data to be corrected is predicted based on the regression prediction curve to determine the corrected data corresponding to each data to be corrected, and the data sampling form is adjusted based on each corrected data, thereby improving the accuracy of the detection information. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of the multi-source sewage mixing treatment method used in a sewage treatment plant in Example 1 of the present application.

[0023] Figure 2 It is a principle block diagram of a multi-source sewage mixing treatment device used in a sewage treatment plant in Example 2 of the present application.

[0024] Figure 3 It is a schematic diagram of the equipment in Example 3 of the present application. DETAILED DESCRIPTION

[0025] The following is combined with Figures 1 to 3 This application is described in further detail.

[0026] Embodiment 1

[0027] Reference Figure 1 The present application discloses a method for treating mixed sewage from multiple sources in a sewage treatment plant, which specifically comprises the following steps: 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.

[0028] In this embodiment, the sewage treatment plant is provided with several processing components, and a processing component refers to a functional module composed of several devices, equipment, and components used for performing a sewage purification stage in the sewage treatment plant, and its specification parameters include the size, volume, specific heat capacity, thermal conductivity correlation coefficient, etc. of each device, equipment, and component; the processing component includes 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, wherein the outlet function pool can be a dedicated water storage pool / container, and other types of pools / containers with water storage functions can also 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 consistent or inconsistent, and one single-source sewage can be stored in multiple water storage units; each processing component is provided with an inlet sensor, an outlet sensor, and a purification pool sensor, and each sensor is provided with flow detection, and detection sensors for pollution indicators and modulation indicators are set as needed, and the sewage reaction model has a built-in reaction optimization algorithm.

[0029] Specifically, based on the design drawings of the sewage treatment plant, the specification parameters of each treatment component in the sewage treatment plant are determined to create a sewage treatment model and mark each specification parameter. The sewage treatment model and the chemical analysis program are associated 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.

[0030] 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, concentration of various pollution indicators and modulation index values ​​of each single-source sewage.

[0031] In this embodiment, pollution index refers to the index of pollutants, and there is a corresponding relationship between the pollution index and data such as pollution index concentration and pollution index quantity; modulation index refers to the index of physical, chemical and biological properties of sewage, such as temperature, pH value, chemical oxygen demand, biological oxygen demand and other indicators, and there is a corresponding relationship between the modulation index and data such as modulation index quantity; main pollution index refers to the index that needs to be included in the pollutant analysis, and 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 is not detected; detection information includes sewage flow, concentrations of several pollution indicators, and modulation index values.

[0032] Specifically, after determining the target treatment components one by one, the detection information of several single-source sewages corresponding to the input target treatment components is obtained, the main pollution indicators and non-main pollution indicators are determined according to the detection information, and the sewage volume, pollution indicator concentration and modulation index value of each single-source sewage are counted, so as to facilitate the determination of the pollution type and pollution degree of several single-source sewages input into the target treatment components.

[0033] Wherein, in the step of S20: obtaining detection information of a plurality of single-source sewage, it includes: S21: 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.

[0034] Specifically, the sewage flow, pollution index concentration, modulation index value and sampling time of the single-source sewage are obtained based on the detection frequency, so as to record the changes in the properties of the single-source sewage input into the target treatment component over time and input them into the data sampling form.

[0035] S22: When a sudden change in the indicator is detected, a sensor purification instruction is generated and sent to a corresponding purification component to purify the corresponding sensor.

[0036] In this embodiment, 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 sudden change in value 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 in three adjacent sampling values ​​in time are both greater than the corresponding preset index deviation threshold value, and the index deviation threshold value can be set according to actual needs. Preferably, the index deviation threshold value can be set to 3%. The sudden change in value 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 in three adjacent sampling values ​​in time are both greater than the corresponding preset index deviation threshold value, so as to reduce the possibility of misjudging data fluctuations as sudden changes in value.

[0037] The water inlet sensor, the water outlet sensor and the purification tank sensor are all provided with a purification component for cleaning. Preferably, the purification component is a device with a water spray cleaning function.

[0038] Specifically, when a sudden change in the indicator is detected, it means that the properties of the input single-source sewage have changed significantly. A sensor purification instruction is generated and sent to the purification component corresponding to the sensor that detected the sudden change in the indicator, so as 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 properties of the water quality detected by the sensor change significantly, thereby improving the accuracy of the detection information.

[0039] S23: Generate detection information based on the data sampling form.

[0040] Specifically, detection information of single-source sewage is generated based on the data sampling form, so as to subsequently determine the pollution type and pollution degree of several single-source sewages input into the target treatment component.

[0041] Wherein, in step S22, it includes: S221: Inputting the first sampling value, the second sampling value and the third sampling value of the numerical mutation corresponding to the indicator mutation into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value.

[0042] In this embodiment, the correction quantity calculation formula 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, is the deviation correction benchmark parameter; the first coefficient, the second coefficient and the deviation correction benchmark parameter can be set and adjusted according to actual needs to adapt to actual needs.

[0043] Specifically, the first sampling value, the second sampling value and the third sampling value of the numerical mutation corresponding to the indicator mutation are input into the preset correction quantity calculation formula to calculate the correction quantity of the sampling value. The correction quantity calculation formula includes the deviation degree term and the deviation correction term of taking the difference between the first sampling value and the average value of the second sampling value and the third sampling value and multiplying it by the first coefficient. The greater the deviation 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 may be numerical fluctuation, and the range of corrected sampling values ​​needs to be reduced, otherwise vice versa.

[0044] S222: setting the second sampling value, the third sampling value and the subsequent correction number of sampling values ​​as the data to be corrected, taking the preset regression sampling number of sampling values ​​sorted after the data to be corrected and setting them as the regression analysis data.

[0045] Specifically, the second sampling value, the third sampling value and the subsequent correction number sampling values ​​are set as the data to be corrected, and the regression sampling number sampling values ​​preset after the data to be corrected are taken and set as the regression analysis data, so as to correct the data to be corrected based on the processing of the regression analysis data.

[0046] S223: 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.

[0047] Specifically, a regression prediction curve is generated based on a number of regression analysis data, and the correction value corresponding to the sampling time of each data to be corrected is predicted based on the regression prediction curve to determine the corrected data corresponding to each data to be corrected, and the data sampling form is adjusted based on each corrected data, thereby improving the accuracy of the detection information.

[0048] S30: Input the sewage volume of each single source sewage, the concentration of each pollution index, the modulation index value and a number of purification aid information into the sewage reaction model, set the stage effluent standard and optimization target, and generate a sewage input control program based on the reaction optimization algorithm.

[0049] In this embodiment, the purification agent information includes model information, parameter information, cost information, environmental assessment value information, etc., which is convenient for subsequent evaluation of its purification function, cost and environmental protection status; the stage effluent standard includes various pollution index quantities and modulation index values ​​of the sewage produced in the current stage.

[0050] Specifically, the sewage volume of each single-source sewage, the concentration of various pollution indicators, the modulation index value and several purification aid information are input into the sewage reaction model in order to obtain the sewage input situation and available purification aid situation of the target treatment component, set the stage effluent standard and optimization target, and use the reaction optimization algorithm to analyze the optimal unit time input amount and input sequence of various types of single-source sewage and purification aids based on the stage effluent standard and optimization target, so as to generate a sewage input control program.

[0051] Wherein, after the step of S30: inputting 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 into the sewage reaction model, it includes: S31: Element sorting is performed based on each single-source sewage and purification aid to generate a number of 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.

[0052] In this embodiment, the number of elements refers to the number of types of single-source sewage and purification aids.

[0053] Specifically, each single-source sewage and purification aid is sorted and processed as an element to generate all feasible delivery sequences, and the delivery interval of each element in the delivery sequence is determined based on the number of elements and the available processing time of the purification stage, so as to preliminarily set the feasible delivery sequence.

[0054] S32: simulating the treatment results of each delivery sequence based on the sewage reaction model, and ranking the optimization effects of several delivery sequences based on several preset optimization objectives to obtain several optimization effect ranking tables.

[0055] In this embodiment, the preset optimization goals include purification effect, purification efficiency, cost efficiency, and environmental protection efficiency.

[0056] Specifically, various types of delivery sequences are simulated based on the sewage reaction model to obtain corresponding sewage treatment results, and several delivery sequences are ranked according to different optimization objectives based on several optimization objectives, thereby obtaining several optimization effect ranking forms. An optimization effect ranking form refers to a form that arranges several delivery sequences from high to low according to the optimization effect for one optimization objective.

[0057] Among them, in S30: setting the stage effluent standard and optimization target, the step of generating the sewage input control program based on the reaction optimization algorithm includes: S33: The set stage effluent standards and optimization targets are imported 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 aids are combined to set the starting conditions, effluent standards and boundary conditions of the sewage reaction.

[0058] In this embodiment, the optimization target is set according to the current demand; when the sewage inlet flow 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 target; when the sewage inlet flow rate is 70%-100% of the upper limit of the sewage treatment flow rate of the target treatment component, the optimization target is set to achieve the optimization of cost efficiency or environmental protection efficiency under the premise of being able to process the current sewage inlet flow rate; when the sewage inlet flow rate is greater than the upper limit of the sewage treatment flow rate of the target treatment component, the optimization target is set to the optimization of purification efficiency.

[0059] Specifically, the set stage effluent standards and the selected optimization objectives are imported into the reaction optimization algorithm, combined with the known sewage volume of each single source sewage, the concentration of various pollution indicators, the modulation index value and several purification agent information to set the starting conditions, effluent standards and boundary conditions of the sewage reaction, and set the current sewage input situation, available purification agent situation, sewage treatment demand, and the constraints of the sewage treatment plant hardware facilities to improve the reliability of subsequent optimization analysis.

[0060] S34: Based on the optimization target, the corresponding optimization effect ranking form is retrieved, and 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.

[0061] Specifically, based on the optimization target, the corresponding optimization effect ranking form is retrieved, and a number of delivery sequences that meet the optimization target and are ranked first are retrieved. The specific number can be determined according to the performance of the computer equipment running the reaction optimization algorithm or the actual needs. The retrieved delivery sequence is analyzed by genetic algorithm, so as to optimize and analyze according to the set starting conditions, effluent standards and boundary conditions to obtain the optimal delivery method of each single source sewage and purification aid, including the delivery order, the delivery amount per unit time, the total delivery amount, etc., so as to generate a sewage input control program according to the optimization results.

[0062] S40: Inputting the sewage input control program into the controller of the target treatment component to control the input amount per unit time and the input sequence of a plurality of single-source sewage and purification aids corresponding to the target treatment component.

[0063] Specifically, the sewage input control program is input into the controller of the target treatment component to control the unit time input amount and input sequence of the easy-to-dry single-source sewage and purification aids corresponding to the target treatment component, thereby improving the purification effect of multi-source sewage treatment through computer optimization algorithms.

[0064] It should be understood that the serial numbers of the steps in the above embodiments do not imply a sequence of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0065] Embodiment 2 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.

[0066] like Figure 2 As shown, a multi-source sewage mixed 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 description of each functional module is as follows: 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; 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 amount and input sequence of a number of single-source sewage and purification aids corresponding to the target treatment component.

[0067] Among them, the single-source sewage detection and analysis module also 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; The detection information generation submodule is used to generate detection information based on the data sampling form.

[0068] Among them, the sensor purification submodule also includes: A correction quantity calculation submodule, used for inputting the first sampling value, the second sampling value and the third sampling value of the numerical mutation corresponding to the indicator mutation into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value; The to-be-corrected data setting submodule is used to set the second sampling value, the third sampling value and the subsequent correction number sampling values ​​as the to-be-corrected data, and take the preset regression sampling number sampling values ​​sorted after the to-be-corrected data and set them as the regression analysis data; The 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 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.

[0069] Among them, the sewage input control analysis module also includes: The delivery sequence generation submodule is used to perform element sorting processing based on each single-source sewage and purification aid, generate several delivery sequences, and determine the delivery interval of each element in the delivery sequence based on the number of elements and stage processing time; The optimization effect ranking form generation submodule is used to simulate the treatment results of each delivery sequence based on the sewage reaction model, and to rank the optimization effects of several delivery sequences based on several preset optimization objectives to obtain several optimization effect ranking forms.

[0070] Also includes: The condition setting submodule is used to import the set stage effluent standards and optimization targets into the reaction optimization algorithm, and combine the sewage volume of each single source sewage, the concentration of various pollution indicators, the modulation index value and some purification auxiliary information to set the starting conditions, effluent standards and boundary conditions of the sewage reaction; The sewage input control program generation submodule is used to retrieve the corresponding optimization effect ranking form based on the optimization target, and retrieve several delivery sequences that meet the optimization target and are ranked first 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.

[0071] For the specific limitations on the multi-source sewage mixing treatment device for a sewage treatment plant, please refer to the limitations on the multi-source sewage mixing treatment method for a sewage treatment plant mentioned above, which will not be repeated here; the various modules in the above-mentioned multi-source sewage mixing treatment device for a sewage treatment plant can be fully or partially implemented by software, hardware and a combination thereof; the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of the above modules.

[0072] Embodiment 3 A computer device, which may be a server, may have an internal structure as shown in Figure 3 As 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, 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 targets, reaction optimization algorithms, sewage input control programs, etc. of a sewage treatment plant. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a multi-source sewage mixing treatment method for a sewage treatment plant is implemented.

[0073] 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, wherein the processor implements the following steps when executing the computer program: 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; S20: determining a target treatment component, obtaining detection information of several single-source sewage, marking major pollution indicators and non-major pollution indicators in the detection information, and counting the sewage volume, concentration of various pollution indicators and modulation index values ​​of each single-source sewage; S30: Inputting the sewage volume of each single-source sewage, the concentration of each pollution index, the modulation index value and a number of purification aid information into the sewage reaction model, setting the stage effluent standard and optimization target, and generating a sewage input control program based on the reaction optimization algorithm; S40: Inputting the sewage input control program into the controller of the target treatment component to control the input amount per unit time and the input sequence of a plurality of single-source sewage and purification aids corresponding to the target treatment component.

[0074] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: 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; S20: determining a target treatment component, obtaining detection information of several single-source sewage, marking major pollution indicators and non-major pollution indicators in the detection information, and counting the sewage volume, concentration of various pollution indicators and modulation index values ​​of each single-source sewage; S30: Inputting the sewage volume of each single-source sewage, the concentration of each pollution index, the modulation index value and a number of purification aid information into the sewage reaction model, setting the stage effluent standard and optimization target, and generating a sewage input control program based on the reaction optimization algorithm; S40: Inputting the sewage input control program into the controller of the target treatment component to control the input amount per unit time and the input sequence of a plurality of single-source sewage and purification aids corresponding to the target treatment component.

[0075] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink), DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0076] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by 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.

[0077] The embodiments described above 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 aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions 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 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 has a built-in reaction optimization algorithm; the detection information includes sewage flow, concentrations of several pollution indicators, and modulation index values.

2. The multi-source sewage mixed treatment method for a sewage treatment plant according to claim 1, characterized in that: The obtaining of detection information of a plurality of 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 forms; The index mutation refers to the phenomenon that the detection value of any one of the indicators including 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 purification components for cleaning.

3. The multi-source sewage mixed treatment method for a sewage treatment plant according to claim 2 is characterized in that: 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: Inputting the first sampling value, the second sampling value and the third sampling value of the numerical mutation corresponding to the sudden change of the indicator into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value; The second sampling value, the third sampling value and the subsequent correction number of sampling values ​​are set as the data to be corrected, and the regression sampling number of 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.

4. 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.

5. The multi-source sewage mixed treatment method for a sewage treatment plant according to claim 1, characterized in that: The setting of the effluent standard and optimization target in the stage, generating the sewage input control program based on the reaction optimization algorithm, also includes: 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.

6. 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 5 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 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 has a built-in reaction optimization algorithm; the detection information includes sewage flow, concentrations of several pollution indicators, and modulation index values.

7. The multi-source sewage mixing treatment device for a sewage treatment plant according to claim 6 is characterized in that: 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 including 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 purification components for cleaning.

8. The multi-source sewage mixing treatment device for a sewage treatment plant according to claim 7 is characterized in that: The sensor purification submodule comprises: A correction quantity calculation submodule, used for inputting the first sampling value, the second sampling value and the third sampling value of the numerical mutation corresponding to the indicator mutation into a preset correction quantity calculation formula to calculate the correction quantity of the sampling value; The to-be-corrected data setting submodule is used to set the second sampling value, the third sampling value and the subsequent correction number sampling values ​​as the to-be-corrected data, and take the preset regression sampling number sampling values ​​sorted after the to-be-corrected data and set them 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.

9. 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 are implemented as described in any one of claims 1 to 5.

10. 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 5 are implemented.

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