An anaerobic bacteria-based sewage treatment method and system

Abstract

The application relates to the technical field of sewage treatment, and discloses a sewage treatment method and system based on anaerobic bacteria, which comprises the following steps: obtaining the suspended matter concentration of each sewage detection area, comparing the suspended matter concentration with a standard suspended matter concentration, determining the initial dosage of the anaerobic bacteria according to the comparison result, comparing a characteristic parameter sequence with a standard characteristic parameter sequence, judging whether the initial dosage needs to be adjusted according to the comparison result, when it is judged that the initial dosage needs to be adjusted, establishing a dosage correlation model according to environmental data sets, determining a dosage prediction adjustment factor based on the environmental characteristic parameters with differences and the dosage correlation model, adjusting the initial dosage according to the dosage target adjustment factor, and adding the sewage pool according to the adjusted initial dosage to complete sewage treatment. The application effectively controls the dosage of the anaerobic bacteria and adapts to the sewage environment, and improves the efficiency of the sewage treatment.

Description

TECHNICAL FIELD

[0001] The present application relates to the sewage treatment technical field, and in particular, relates to a sewage treatment method and system based on anaerobic bacteria. BACKGROUND

[0002] With the acceleration of industrialization and urbanization, the amount of sewage discharge is increasing, and sewage treatment has become a key link in the field of environmental protection, and anaerobic bacteria can convert sewage into certain biogas, thereby realizing the treatment and utilization of sewage resources. At present, in the process of sewage treatment, the addition of anaerobic bacteria has certain limitations. On the one hand, the addition of anaerobic bacteria mainly depends on manual addition, which is easily affected by the experience, operation habit and working state of the operator, and it is difficult to effectively control the addition amount of anaerobic bacteria, thereby affecting the stability and treatment efficiency of sewage treatment. On the other hand, the addition amount cannot effectively adapt to the sewage environment, and when the environmental parameters such as flow rate and temperature change, the addition amount set by human beings cannot effectively degrade the pollutants in the sewage, thereby causing sludge bulking and reducing the efficiency of sewage treatment.

[0003] Therefore, it is necessary to design a sewage treatment method and system based on anaerobic bacteria to solve the problems in the prior art. SUMMARY

[0004] Therefore, the present application provides a sewage treatment method and system based on anaerobic bacteria, which aims to solve the problems that the addition of anaerobic bacteria mainly depends on manual addition, is easily affected by the experience, operation habit and working state of the operator, and it is difficult to effectively control the addition amount of anaerobic bacteria, and the addition amount cannot effectively adapt to the sewage environment, and the addition amount set by human beings cannot effectively degrade the pollutants in the sewage.

[0005] In one aspect, the present application provides a sewage treatment method based on anaerobic bacteria, comprising:

[0006] dividing the sewage pool into a plurality of sewage detection areas, obtaining the suspended matter concentration of each sewage detection area, comparing the suspended matter concentration with the standard suspended matter concentration, and determining the initial addition amount of anaerobic bacteria according to the comparison result;

[0007] obtaining the environmental characteristic parameters of the sewage pool and constructing a characteristic parameter sequence, comparing the characteristic parameter sequence with a standard characteristic parameter sequence, and judging whether to adjust the initial addition amount according to the comparison result;

[0008] When it is determined that the initial dosage is adjusted, a dosage correlation model is established according to an environmental data set, and an environmental characteristic parameter with a difference is extracted, a dosage prediction adjustment factor is determined based on the environmental characteristic parameter with the difference and the dosage correlation model, and the dosage prediction adjustment factor is compared with a historical data set, a dosage target adjustment factor is determined according to a comparison result, and the initial dosage is adjusted according to the dosage target adjustment factor to complete sewage treatment by adjusting the initial dosage.

[0009] According to the dosage target adjustment factor, the initial dosage is adjusted, and the sewage tank is dosed according to the adjusted initial dosage to complete sewage treatment.

[0010] Further, when the suspended solids concentration is compared with the standard suspended solids concentration, and the initial dosage of anaerobic bacteria is determined according to a comparison result, it includes:

[0011] A first processing mark is established for a sewage detection area with a suspended solids concentration less than the standard suspended solids concentration, a second processing mark is established for a sewage detection area with a suspended solids concentration equal to the standard suspended solids concentration, and a third processing mark is established for a sewage detection area with a suspended solids concentration greater than the standard suspended solids concentration.

[0012] An average suspended solids concentration of all sewage detection areas with the second processing mark is obtained.

[0013] The initial dosage is determined according to the suspended solids concentration with the first processing mark, the suspended solids concentration with the third processing mark, and the average suspended solids concentration.

[0014] Further, when the initial dosage is determined according to the suspended solids concentration with the first processing mark, the suspended solids concentration with the third processing mark, and the average suspended solids concentration, it includes:

[0015] The suspended solids concentrations of all sewage detection areas with the first processing mark are constructed as a first concentration set, and the suspended solids concentrations of all sewage detection areas with the third processing mark are constructed as a third concentration set.

[0016] A first median and a first average of the first concentration set are determined, and a third median and a third average of the third concentration set are determined.

[0017] The suspended solids concentrations greater than the first median in the first concentration set are extracted and constructed as a first concentration value set, and the suspended solids concentrations greater than the first average in the first concentration set are extracted and constructed as a second concentration value set.

[0018] The suspended solids concentrations greater than the third median in the third concentration set are extracted and constructed as a third concentration value set, and the suspended solids concentrations greater than the third average in the third concentration set are extracted and constructed as a fourth concentration value set.

[0019] The initial dosage is determined based on the first set of concentration values, the second set of concentration values, the third set of concentration values, the fourth set of concentration values, and the average suspended solids concentration.

[0020] Furthermore, when determining the initial dosage based on the first set of concentration values, the second set of concentration values, the third set of concentration values, the fourth set of concentration values, and the average suspended solids concentration, the following steps are included:

[0021] Determine whether there is an intersection between the first set of concentration values ​​and the second set of concentration values, and whether there is an intersection between the third set of concentration values ​​and the fourth set of concentration values;

[0022] If so, construct a set of suspended solids concentrations based on the intersection values, determine the average concentration of the set of suspended solids concentrations, and determine the average concentration of the average concentration and the average of the average suspended solids concentrations as the target suspended solids concentration;

[0023] If not, merge the first concentration value set and the second concentration value set to construct the fifth concentration value set, and merge the third concentration value set and the fourth concentration value set to construct the sixth concentration value set. Obtain the first average concentration value of the fifth concentration value set and the second average concentration value of the sixth concentration value set, and determine the average of the first average concentration value, the second average concentration value, and the average of the average suspended solids concentration as the target suspended solids concentration.

[0024] The initial dosage is determined based on the target suspended solids concentration.

[0025] Furthermore, when determining the initial dosage based on the target suspended solids concentration, the following steps are included:

[0026] A first preset target suspended solids concentration and a second preset target suspended solids concentration are preset, wherein the first preset target suspended solids concentration is greater than the second preset target suspended solids concentration;

[0027] A first preset initial dosage, a second preset initial dosage, and a third preset initial dosage are preset, wherein the first preset initial dosage is greater than the second preset initial dosage, and the second preset initial dosage is greater than the third preset initial dosage;

[0028] When the target suspended solids concentration is greater than the first preset target suspended solids concentration, the first preset initial dosage is determined as the initial dosage.

[0029] determining the second preset initial dosing amount as the initial dosing amount when the target suspended substance concentration is less than or equal to the first preset target suspended substance concentration and greater than or equal to the second preset target suspended substance concentration;

[0030] determining the third preset initial dosing amount as the initial dosing amount when the target suspended substance concentration is less than the second preset target suspended substance concentration.

[0031] Further, when the environmental characteristic parameters of the sewage pool are acquired and the characteristic parameter sequence is constructed, the characteristic parameter sequence and the standard characteristic parameter sequence are compared, and whether to adjust the initial dosing amount is determined according to the comparison result, comprising:

[0032] acquiring the standard characteristic parameter sequence corresponding to the characteristic parameter sequence;

[0033] when the environmental characteristic parameters in the characteristic parameter sequence are all equal to the standard environmental characteristic parameters in the standard characteristic parameter sequence, it is determined that the initial dosing amount is not adjusted, and the initial dosing amount is used to complete sewage treatment by dosing the sewage pool, otherwise, it is determined that the initial dosing amount is adjusted.

[0034] Further, when the dosing correlation model is established according to the environmental data set, and the environmental characteristic parameters with differences are extracted, the dosing prediction adjustment factor is determined based on the environmental characteristic parameters with differences and the dosing correlation model, comprising:

[0035] extracting the environmental characteristic parameters in the characteristic parameter sequence that are not equal to the standard environmental characteristic parameters, and recording them as a difference characteristic parameter set;

[0036] dividing the environmental data set into a training set and a test set, using grid search to find the establishment parameters of the model, and establishing a random forest model;

[0037] training the random forest model using the training set, and substituting the test set into the trained random forest model to determine the accuracy rate of model prediction, when the accuracy rate reaches an accuracy rate threshold, the trained random forest model is determined as the dosing correlation model, otherwise, the random forest model is continuously trained until the accuracy rate threshold is reached;

[0038] substituting the difference characteristic parameter set into the dosing correlation model to determine the dosing prediction adjustment factor.

[0039] Further, when the dosing prediction adjustment factor is compared with the historical data set, and the dosing target adjustment factor is determined according to the comparison result, comprising:

[0040] The historical data set comprises a plurality of historical difference characteristic parameter sets and a plurality of historical dosing prediction adjustment factors, each historical difference characteristic parameter set corresponds to a historical dosing prediction adjustment factor;

[0041] When the historical data set has a historical difference characteristic parameter set consistent with the difference characteristic parameter set, the historical dosing prediction adjustment factor corresponding to the historical difference characteristic parameter set is obtained, if the corresponding historical dosing prediction adjustment factor is equal to the dosing prediction adjustment factor, the dosing prediction adjustment factor is determined as the dosing target adjustment factor, otherwise, the historical data set and the difference characteristic parameter set are clustered to determine a clustered data set, and the mean value of the historical dosing prediction adjustment factors in the clustered data set is determined as the dosing target adjustment factor;

[0042] When the historical data set has no historical difference characteristic parameter set consistent with the difference characteristic parameter set, the dosing prediction adjustment factor is determined as the dosing target adjustment factor.

[0043] Further, when the initial dosing amount is adjusted according to the dosing target adjustment factor, it comprises:

[0044] The initial dosing amount and the dosing target adjustment factor are in a proportional relationship.

[0045] Compared with the prior art, the beneficial effects of the present application are that the sewage pool is divided into a plurality of sewage detection areas, the initial dosing amount of anaerobic bacteria is determined by obtaining the suspended matter concentration of each sewage detection area and comparing it with the standard suspended matter concentration, avoiding the judgment of human experience, combining the environmental characteristic parameters of the sewage pool to construct a characteristic parameter sequence, and comparing it with the standard characteristic parameter sequence to determine whether to adjust the initial dosing amount, avoiding the risk that the dosing amount does not match the actual sewage environment due to environmental changes, ensuring the stability of the sewage treatment process, effectively avoiding the fluctuation of the treatment effect caused by excessive or insufficient dosing amount, determining the dosing prediction adjustment factor by establishing a dosing correlation model, comparing it with the historical data set to obtain the dosing target adjustment factor, dynamically adjusting the initial dosing amount of anaerobic bacteria, ensuring effective degradation of pollutants in sewage under different environmental conditions, and improving the efficiency of sewage treatment.

[0046] On the other hand, the present application also provides a sewage treatment system based on anaerobic bacteria, which is used for applying the above-mentioned sewage treatment method based on anaerobic bacteria, comprising:

[0047] The first processing module is configured to divide the sewage pool into a plurality of sewage detection areas, obtain the suspended matter concentration of each sewage detection area, compare the suspended matter concentration with the standard suspended matter concentration, and determine the initial dosing amount of anaerobic bacteria according to the comparison result;

[0048] The second processing module is configured to acquire an environmental characteristic parameter of the sewage tank and construct a characteristic parameter sequence, compare the characteristic parameter sequence with a standard characteristic parameter sequence, and determine whether to adjust the initial dosing amount according to a comparison result.

[0049] The dosing determination module is configured to, when it is determined to adjust the initial dosing amount, establish a dosing correlation model according to an environmental data set, extract an environmental characteristic parameter with a difference, determine a dosing prediction adjustment factor based on the environmental characteristic parameter with the difference and the dosing correlation model, compare the dosing prediction adjustment factor with a historical data set, and determine a dosing target adjustment factor according to a comparison result.

[0050] The dosing adjustment module is configured to adjust the initial dosing amount according to the dosing target adjustment factor, complete sewage treatment by dosing the sewage tank according to the adjusted initial dosing amount.

[0051] It can be understood that the above-mentioned sewage treatment method and system based on anaerobic bacteria have the same beneficial effects, which will not be described here. BRIEF DESCRIPTION OF DRAWINGS

[0052] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The accompanying drawings are included to provide a description of preferred embodiments and are not meant to limit the present application. Furthermore, the same reference numerals are used throughout the several views to denote the same or similar parts. In the drawings:

[0053] Figure 1 A flowchart of a sewage treatment method based on anaerobic bacteria provided for an embodiment of the present application;

[0054] Figure 2 A functional block diagram of a sewage treatment system based on anaerobic bacteria provided for an embodiment of the present application. DETAILED DESCRIPTION

[0055] Exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be accurately conveyed to those skilled in the art. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0056] In some embodiments of the present application, referring to Figure 1 A sewage treatment method based on anaerobic bacteria, as shown in the drawings, comprises:

[0057] S100: divide the sewage pool into a plurality of sewage detection areas, obtain the suspended matter concentration of each sewage detection area, compare the suspended matter concentration with the standard suspended matter concentration, and determine the initial dosage of anaerobic bacteria according to the comparison result.

[0058] S200: obtain the environmental characteristic parameters of the sewage pool and construct a characteristic parameter sequence, compare the characteristic parameter sequence with a standard characteristic parameter sequence, and determine whether to adjust the initial dosage according to the comparison result.

[0059] S300: when it is determined to adjust the initial dosage, establish a dosage correlation model according to the environmental data set, extract the environmental characteristic parameters that have differences, determine a dosage prediction adjustment factor based on the environmental characteristic parameters that have differences and the dosage correlation model, compare the dosage prediction adjustment factor with a historical data set, and determine a dosage target adjustment factor according to the comparison result.

[0060] S400: adjust the initial dosage according to the dosage target adjustment factor, and complete the sewage treatment by dosing the sewage pool according to the adjusted initial dosage.

[0061] Specifically, the sewage pool is divided into a plurality of sewage detection areas, and the specific number is uniformly divided according to the actual size of the sewage pool. The composition and concentration of sewage at different positions in the sewage pool are not uniformly distributed. By obtaining the suspended matter concentration of each sewage detection area, the distribution of pollutants in the sewage pool can be accurately understood. Comparing it with the standard suspended matter concentration, the standard suspended matter concentration represents the pollutant content under the ideal treatment state of sewage. The standard suspended matter concentration is determined according to the “Technical Specification for Operation Supervision and Management of Urban Sewage Treatment Plant”. If the suspended matter concentration is higher than the standard suspended matter concentration, it means that there are more pollutants in the sewage, and more dosage is needed. Conversely, it is appropriate to reduce. The initial dosage thus determined is a preliminary setting based on the pollutant content of the sewage itself. Environmental characteristic parameters (such as flow rate, temperature, pH value, etc.) have a certain influence on the activity and treatment efficiency of anaerobic bacteria. The environmental characteristic parameters are constructed as a characteristic parameter sequence and compared with a standard characteristic parameter sequence. The standard characteristic parameter sequence is determined according to the ideal treatment environment of anaerobic bacteria and reflects the ideal environmental conditions for anaerobic bacteria to exert treatment effect. When there are differences between the characteristic parameter sequence and the standard characteristic parameter sequence, it indicates that the current environment of the sewage pool may not be conducive to the normal work of anaerobic bacteria, and the initial dosage needs to be adjusted to compensate for the influence of environmental factors on the treatment effect.

[0062] It can be understood that when it is determined that the initial dosage needs to be adjusted, a dosage correlation model is established according to the environmental data set. The model mines the potential relationship between the environmental characteristic parameters and the dosage of anaerobic bacteria through analysis and learning of a large amount of environmental data. After the environmental characteristic parameters with differences are extracted, a dosage prediction adjustment factor is calculated by using the dosage correlation model. The prediction adjustment factor is an estimate of the adjustment of the dosage based on the current environmental differences of the sewage tank. The prediction adjustment factor is compared with the historical data set, which records the adjustment of the initial dosage under different environmental differences in the past. Through comparison, accurate adjustment basis can be obtained from historical experience, so as to determine the dosage target adjustment factor, so that the adjusted initial dosage can meet the needs of actual sewage treatment, and ensure that the dosage of anaerobic bacteria matches the sewage conditions and environmental conditions. Compared with the traditional judgment of artificial experience, the data-driven method can mine potential rules and relationships, providing a reliable basis for the final dosage, so as to realize stable sewage treatment.

[0063] In some embodiments of the present application, when the suspended solids concentration is compared with the standard suspended solids concentration, and the initial dosage of anaerobic bacteria is determined according to the comparison result, the method comprises: establishing a first processing mark for the sewage detection area with a suspended solids concentration less than the standard suspended solids concentration, establishing a second processing mark for the sewage detection area with a suspended solids concentration equal to the standard suspended solids concentration, establishing a third processing mark for the sewage detection area with a suspended solids concentration greater than the standard suspended solids concentration, obtaining the average suspended solids concentration of all sewage detection areas with the second processing mark, and determining the initial dosage according to the suspended solids concentration with the first processing mark, the suspended solids concentration with the third processing mark, and the average suspended solids concentration.

[0064] Specifically, the sewage detection area is marked according to the relationship between the suspended solids concentration and the standard suspended solids concentration, which is a further refinement of the sewage conditions in the sewage tank. The sewage detection area with the first processing mark indicates that the pollutant load is low and the demand for anaerobic bacteria is relatively small. The suspended solids concentration in the sewage detection area with the second processing mark is equal to the standard suspended solids concentration, which means that the pollutant content is in an ideal state. The sewage detection area with the third processing mark indicates that the pollutant load is high and more anaerobic bacteria are needed for treatment. The average suspended solids concentration of the second processing mark area is obtained to obtain a reference value. On this basis, the low suspended solids concentration of the first processing mark and the high suspended solids concentration of the third processing mark are combined to comprehensively consider the pollutant conditions of different sewage detection areas in the sewage tank. By analyzing the suspended solids concentration of the three types of processing marks, an initial dosage that balances the treatment needs of each area is determined, which avoids resource waste or insufficient treatment caused by "one-size-fits-all" dosage, and effectively improves the adaptability and stability of sewage treatment.

[0065] In some embodiments of the present application, when determining the initial dosing amount according to the suspended solids concentration of the first treatment marker, the suspended solids concentration of the third treatment marker, and the average suspended solids concentration, the following steps are included: constructing the suspended solids concentrations of all wastewater detection areas of the first treatment marker into a first concentration set, and constructing the suspended solids concentrations of all wastewater detection areas of the third treatment marker into a third concentration set; determining the first median and the first average of the first concentration set, and determining the third median and the third average of the third concentration set; extracting the suspended solids concentrations greater than the first median from the first concentration set and constructing a first concentration value set, extracting the suspended solids concentrations greater than the first average from the first concentration set and constructing a second concentration value set, extracting the suspended solids concentrations greater than the third median from the third concentration set and constructing a third concentration value set, and extracting the suspended solids concentrations greater than the third average from the third concentration set and constructing a fourth concentration value set; and determining the initial dosing amount according to the first concentration value set, the second concentration value set, the third concentration value set, the fourth concentration value set, and the average suspended solids concentration.

[0066] Specifically, after constructing the suspended solids concentrations of different treatment markers into corresponding concentration sets, the corresponding median and average are determined to ensure that the characteristics of the concentration distribution are grasped from the two dimensions of the whole and the middle level, and the suspended solids concentrations greater than the corresponding median and average are extracted from each concentration set, which can focus on the part of the suspended solids concentration in each concentration set that is relatively high. These data can better reflect the pollution situation of the wastewater detection areas of different treatment markers. For example, the first concentration set represents 80 mg / L, 100 mg / L, 120 mg / L, 130 mg / L, and 140 mg / L, the first median represents 120 mg / L, and the first average represents 114 mg / L. Therefore, the first concentration value set represents 130 mg / L and 140 mg / L, and the second concentration value set represents 120 mg / L, 130 mg / L, and 140 mg / L. The first and second concentration value sets represent the higher concentration of lower pollutants of the treatment marker, and the third and fourth concentration value sets represent the higher concentration of higher pollutants of the treatment marker. In combination with the average suspended solids concentration, the concentration distribution of the pollutants in different wastewater detection areas can be fully considered, the limitations of a single data index are avoided, the concentration data is analyzed from multiple dimensions, and the initial dosing amount can adapt to the real pollution situation of each wastewater detection area.

[0067] In some embodiments of the present application, in determining the initial dosage according to the first concentration value set, the second concentration value set, the third concentration value set, the fourth concentration value set and the average suspended matter concentration, it includes: judging whether there is an intersection between the first concentration value set and the second concentration value set, and whether there is an intersection between the third concentration value set and the fourth concentration value set, if yes, constructing a suspended matter concentration set according to the intersection value, determining the average concentration of the suspended matter concentration set, and determining the average of the average suspended matter concentration as the target suspended matter concentration, if no, merging the first concentration value set and the second concentration value set to construct a fifth concentration value set, and merging the third concentration value set and the fourth concentration value set to construct a sixth concentration value set, obtaining the first concentration value average of the fifth concentration value set and the second concentration value average of the sixth concentration value set, and determining the first concentration value average, the second concentration value average and the average of the average suspended matter concentration as the target suspended matter concentration, and determining the initial dosage according to the target suspended matter concentration.

[0068] Specifically, judging the intersection between each concentration value set is to explore the potential association between different dimensional concentration data. If there is an intersection, it means that the higher concentration data filtered under different calculation dimensions have overlapping parts, and these overlapping data are more representative. Constructing them as a suspended matter concentration set and calculating the average can accurately reflect the more prominent pollution situation in different sewage detection areas. Combined with the average suspended matter concentration, the target suspended matter concentration is determined, so that the result fits the actual sewage treatment demand. If there is no intersection, the different concentration value sets are merged and calculated respectively to obtain the corresponding average values, which is to integrate the higher concentration data in different dimensions as a whole. By comprehensively considering these average values and the average suspended matter concentration, the pollution situation of each area can also be comprehensively considered. For example, the first concentration value average is 90 mg / L, the second concentration value average is 130 mg / L, and the average suspended matter concentration is 100 mg / L. Then the average value of them is 106.67 mg / L. Therefore, 106.67 mg / L is determined as the target suspended matter concentration. Whether based on intersection data or comprehensive integration when there is no intersection, it ensures that the target suspended matter concentration can reflect the actual pollution condition of sewage, and lays a reliable data foundation for determining the initial dosage.

[0069] In some embodiments of the present application, when the initial dosage is determined according to the target suspended solids concentration, the first preset target suspended solids concentration and the second preset target suspended solids concentration are preset, the first preset target suspended solids concentration is greater than the second preset target suspended solids concentration, the first preset initial dosage, the second preset initial dosage and the third preset initial dosage are preset, the first preset initial dosage is greater than the second preset initial dosage, and the second preset initial dosage is greater than the third preset initial dosage. When the target suspended solids concentration is greater than the first preset target suspended solids concentration, the first preset initial dosage is determined as the initial dosage; when the target suspended solids concentration is less than or equal to the first preset target suspended solids concentration and greater than or equal to the second preset target suspended solids concentration, the second preset initial dosage is determined as the initial dosage; and when the target suspended solids concentration is less than the second preset target suspended solids concentration, the third preset initial dosage is determined as the initial dosage.

[0070] Specifically, different gradient target suspended solids concentrations (first preset target suspended solids concentration, second preset target suspended solids concentration) and preset initial dosages (first preset initial dosage, second preset initial dosage, third preset initial dosage) are preset to form a target suspended solids concentration-dosage corresponding rule. After the calculated target suspended solids concentration is determined, it is compared with the preset target suspended solids concentration, and the corresponding preset initial dosage is dynamically selected. The dependence on human experience is reduced, the error of human judgment is avoided, the initial dosage is matched with the degree of sewage pollution, the sewage treatment efficiency is improved, and the treatment effect fluctuation and resource waste caused by improper dosage are reduced.

[0071] In some embodiments of the present application, when the environmental characteristic parameters of the sewage tank are obtained and the characteristic parameter sequence is constructed, the characteristic parameter sequence and the standard characteristic parameter sequence are compared, and whether the initial dosage is adjusted is determined according to the comparison result, including: obtaining the standard characteristic parameter sequence corresponding to the characteristic parameter sequence; when the environmental characteristic parameters in the characteristic parameter sequence are equal to the standard environmental characteristic parameters in the standard characteristic parameter sequence, it is determined that the initial dosage is not adjusted, and the initial dosage is added to the sewage tank to complete the sewage treatment; otherwise, it is determined that the initial dosage is adjusted.

[0072] Specifically, the environmental characteristic parameters (such as temperature, flow rate, pH value, etc.) of the sewage tank are acquired, each environmental characteristic parameter corresponds to a numerical value, and a characteristic parameter sequence constructed comprehensively reflects the characteristics of the overall data of the current sewage tank environment, which is compared with a standard characteristic parameter sequence, wherein the standard environmental characteristic parameters in the standard characteristic parameter sequence correspond one-to-one with the environmental characteristic parameters in the characteristic parameter sequence. When all the environmental characteristic parameters in the characteristic parameter sequence are completely equal to all the standard environmental characteristic parameters in the standard characteristic parameter sequence, it means that the current sewage tank environment is in an ideal state, and the anaerobic bacteria can achieve good treatment effect under the initial dosage, without the need to adjust the initial dosage, and the initial dosage can be directly added. If there is a situation that the environmental characteristic parameters and the standard environmental characteristic parameters are not equal, it indicates that the environment has changed, which may affect the activity and treatment efficiency of the anaerobic bacteria, and the initial dosage needs to be adjusted to ensure the sewage treatment effect and ensure that the anaerobic bacteria are in a relatively suitable environment, thereby effectively improving the stability and reliability of the sewage treatment.

[0073] In some embodiments of the present application, when the dosage correlation model is established according to the environmental data set, the environmental characteristic parameters with differences are extracted, and the dosage prediction adjustment factor is determined based on the environmental characteristic parameters with differences and the dosage correlation model, including: extracting the environmental characteristic parameters in the characteristic parameter sequence that are not equal to the standard environmental characteristic parameters, and recording them as a difference characteristic parameter set; dividing the environmental data set into a training set and a test set; using grid search to find the establishment parameters of the model; establishing a random forest model; training the random forest model using the training set; and substituting the test set into the trained random forest model to determine the accuracy rate of the model prediction. When the accuracy rate reaches an accuracy rate threshold, the trained random forest model is determined as the dosage correlation model, otherwise, the random forest model is continuously trained until the accuracy rate threshold is reached. The difference characteristic parameter set is substituted into the dosage correlation model to determine the dosage prediction adjustment factor.

[0074] Specifically, the environmental data set contains environmental characteristic parameters of the sewage pool at different periods, and corresponding sample values, anaerobic bacteria activity and other data. The environmental data set is divided into a training set and a test set. The division ratio is usually 7:3, and the training set and the test set both contain multiple data to improve the generalization ability of the model. Grid search establishes parameters such as the number of trees and the maximum depth of the tree by exhaustive search in the parameter space. The random forest model is trained using the training set data. The random forest improves the accuracy and stability of the model by integrating multiple decision trees and averaging the prediction results of multiple trees. During the training process, the model attempts to learn the patterns and relationships between data to improve the prediction or classification ability. The test set is input into the trained random forest model to calculate the accuracy of the model. The accuracy reflects the performance of the model on unknown data and is an important indicator for evaluating the performance of the model. When the model reaches the preset accuracy threshold, it is considered that the model has been able to stably approach the global optimal solution. Therefore, the trained random forest model is determined as the dosing correlation model, and the difference characteristic parameter set is input into the dosing correlation model to determine the dosing prediction adjustment factor. When the model cannot reach the preset accuracy threshold, the random forest model is continuously trained until the accuracy threshold is reached, avoiding the risk of model prediction error, so that the dosing amount can be matched with the environment of the sewage pool, and the efficiency of sewage treatment is improved.

[0075] In some embodiments of the present application, when the dosing prediction adjustment factor is compared with the historical data set, and the dosing target adjustment factor is determined according to the comparison result, the historical data set includes a plurality of historical difference characteristic parameter sets and a plurality of historical dosing prediction adjustment factors. Each historical difference characteristic parameter set corresponds to a historical dosing prediction adjustment factor. When there is a historical difference characteristic parameter set consistent with the difference characteristic parameter set in the historical data set, the historical dosing prediction adjustment factor corresponding to the historical difference characteristic parameter set is obtained. If the corresponding historical dosing prediction adjustment factor is equal to the dosing prediction adjustment factor, the dosing prediction adjustment factor is determined as the dosing target adjustment factor. Otherwise, the historical data set and the difference characteristic parameter set are clustered to determine a clustered data set, and the mean value of the historical dosing prediction adjustment factors in the clustered data set is determined as the dosing target adjustment factor. When there is no historical difference characteristic parameter set consistent with the difference characteristic parameter set in the historical data set, the dosing prediction adjustment factor is determined as the dosing target adjustment factor.

[0076] Specifically, the historical data set forms a data reserve, and a matching search is performed in the historical data set. If a completely consistent historical difference characteristic parameter set is found, it means that the current environmental situation has a trace in history. At this time, the historical prediction adjustment factor and the prediction adjustment factor are compared. If they are equal, it means that the current result is consistent with historical experience, and the historical prediction adjustment factor can be directly determined as the target adjustment factor. If they are not equal, the historical data set and the difference characteristic parameter set are subjected to cluster analysis. The mean value of the historical prediction adjustment factor in the clustered data set is taken as the target adjustment factor. The cluster analysis algorithm includes K-Means algorithm, hierarchical clustering algorithm and density clustering algorithm. One of them can be selected. Here, the K-Means algorithm is taken as an example. The difference characteristic parameter set and the historical data set are taken as the data set to be clustered. The historical prediction adjustment factor corresponding to each data set in the data set to be clustered is extracted. The expected cluster number k is determined as 2, and the parameters of the Gaussian distribution are initialized. The probability of each data set in the data set to be clustered belonging to each Gaussian distribution is calculated to obtain the responsibility value. The cluster data set corresponding to the difference characteristic parameter set is obtained according to the responsibility value. If no matching historical difference characteristic parameter set is found, it means that the difference characteristic parameter set is special. Therefore, the prediction adjustment factor is taken as the target adjustment factor, which ensures the timeliness of the processing strategy and provides a basis for the accumulation of subsequent data while ensuring the processing efficiency.

[0077] In some embodiments of the present application, when the initial dosage is adjusted according to the target adjustment factor, the initial dosage and the target adjustment factor are in a proportional relationship.

[0078] Specifically, the initial dosage is adjusted according to the target adjustment factor. Assuming that the initial dosage is L and the target adjustment factor is P, the adjusted initial dosage is L*P. When a higher initial dosage is needed, the proportional relationship between the initial dosage and the target adjustment factor is used to achieve accurate control of the initial dosage in the sewage treatment process, thereby improving the efficiency of sewage treatment.

[0079] In summary, the present application has the beneficial effects that: the sewage pool is divided into several sewage detection areas, the initial dosing amount of anaerobic bacteria is determined by obtaining the suspended matter concentration of each sewage detection area and comparing it with the standard suspended matter concentration, avoiding the judgment of human experience, combining the environmental characteristic parameters of the sewage pool to construct a characteristic parameter sequence, and comparing it with the standard characteristic parameter sequence to determine whether to adjust the initial dosing amount, avoiding the risk that the dosing amount does not match the actual sewage environment due to environmental changes, ensuring the stability of the sewage treatment process, effectively avoiding the fluctuation of the treatment effect caused by excessive or insufficient dosing amount, determining the dosing prediction adjustment factor by establishing a dosing correlation model, comparing it with the historical data set to obtain the dosing target adjustment factor, which can dynamically adjust the initial dosing amount of anaerobic bacteria, ensure effective degradation of pollutants in sewage under different environmental conditions, and improve the efficiency of sewage treatment.

[0080] In another preferred mode based on the above embodiment, referring to Figure 2 The present embodiment provides an anaerobic bacteria-based sewage treatment system for applying the above-mentioned anaerobic bacteria-based sewage treatment method, which comprises:

[0081] The first processing module is configured to divide the sewage pool into several sewage detection areas, obtain the suspended matter concentration of each sewage detection area, compare the suspended matter concentration with the standard suspended matter concentration, and determine the initial dosing amount of anaerobic bacteria according to the comparison result.

[0082] The second processing module is configured to obtain the environmental characteristic parameters of the sewage pool and construct a characteristic parameter sequence, compare the characteristic parameter sequence with the standard characteristic parameter sequence, and determine whether to adjust the initial dosing amount according to the comparison result.

[0083] The dosing determination module is configured to, when it is determined that the initial dosing amount is adjusted, establish a dosing correlation model according to the environmental data set, extract the environmental characteristic parameters that have differences, determine the dosing prediction adjustment factor based on the environmental characteristic parameters that have differences and the dosing correlation model, and compare the dosing prediction adjustment factor with the historical data set to determine the dosing target adjustment factor.

[0084] The dosing adjustment module is configured to adjust the initial dosing amount according to the dosing target adjustment factor, and complete the sewage treatment by dosing the sewage pool according to the adjusted initial dosing amount.

[0085] Those skilled in the art will appreciate that embodiments of the application can be readily used as software, hardware, and / or embodied as computer program products. Accordingly, embodiments of the application can be implemented in a completely hardware embodiment, a completely software embodiment or an embodiment containing both software and hardware aspects. Furthermore, embodiments of the application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code.

[0086] The present application is described in reference to the flowchart and / or block diagrams of the methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart and / or block diagrams, and combinations of blocks in the flowchart and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0087] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0088] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0089] Finally, it should be noted that the above-mentioned embodiments are merely intended for describing and illustrating, not limiting, the technical solutions of the present application. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that the specific embodiments of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the present application, and any modification or equivalent replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. A wastewater treatment method based on anaerobic bacteria, characterized in that, include: The wastewater tank is divided into several wastewater testing areas. The suspended solids concentration in each wastewater testing area is obtained. The suspended solids concentration is compared with the standard suspended solids concentration. The initial dosage of anaerobic bacteria is determined based on the comparison results. The environmental characteristic parameters of the wastewater pond are obtained and a characteristic parameter series is constructed. The characteristic parameter series is compared with the standard characteristic parameter series. Based on the comparison results, it is determined whether the initial dosage should be adjusted. The environmental characteristic parameters include temperature and pH. When it is determined that the initial dosage should be adjusted, a dosage correlation model is established based on the environmental dataset, and environmental feature parameters that differ are extracted. Based on the environmental feature parameters that differ and the dosage correlation model, a dosage prediction adjustment factor is determined, and the dosage prediction adjustment factor is compared with the historical dataset. Based on the comparison results, a dosage target adjustment factor is determined. The initial dosage is adjusted according to the dosage target adjustment factor, and the wastewater is treated by adding the wastewater to the wastewater tank according to the adjusted initial dosage. When comparing the suspended solids concentration with the standard suspended solids concentration and determining the initial dosage of anaerobic bacteria based on the comparison results, the following steps are included: A first treatment mark is established for wastewater detection areas with suspended solids concentrations lower than the standard suspended solids concentration; a second treatment mark is established for wastewater detection areas with suspended solids concentrations equal to the standard suspended solids concentration; and a third treatment mark is established for wastewater detection areas with suspended solids concentrations greater than the standard suspended solids concentration. Obtain the average suspended solids concentration in all wastewater monitoring areas where a second treatment marker has been established; The initial dosage is determined based on the suspended solids concentration at the first treatment marker, the suspended solids concentration at the third treatment marker, and the average suspended solids concentration. When determining the initial dosage based on the suspended solids concentration at the first treatment marker, the suspended solids concentration at the third treatment marker, and the average suspended solids concentration, the following steps are included: The suspended solids concentrations of all wastewater detection areas with the first treatment mark are constructed into a first concentration set, and the suspended solids concentrations of all wastewater detection areas with the third treatment mark are constructed into a third concentration set; Determine the first median and the first mean of the first concentration set, and determine the third median and the third mean of the third concentration set; Extract the suspended solids concentrations greater than the first median from the first concentration set and construct a first concentration value set; extract the suspended solids concentrations greater than the first average value from the first concentration set and construct a second concentration value set. Extract the suspended solids concentrations greater than the third median from the third concentration set and construct a third concentration value set; extract the suspended solids concentrations greater than the third average value from the third concentration set and construct a fourth concentration value set. The initial dosage is determined based on the first set of concentration values, the second set of concentration values, the third set of concentration values, the fourth set of concentration values, and the average suspended solids concentration. When establishing an application correlation model based on an environmental dataset, extracting differentiated environmental feature parameters, and determining the application prediction adjustment factor based on the differentiated environmental feature parameters and the application correlation model, the process includes: Extract environmental feature parameters from the feature parameter sequence that are not equal to the standard environmental feature parameters in the standard feature parameter sequence, and denote them as the differential feature parameter set; The environmental dataset is divided into a training set and a test set. A grid search is used to find the parameters for building the model, and a random forest model is built. The training set is used to train the random forest model, and the test set is substituted into the trained random forest model to determine the accuracy of the model prediction. When the accuracy reaches the accuracy threshold, the trained random forest model is determined as the addition association model; otherwise, the random forest model is trained until the accuracy threshold is reached. The differential feature parameter set is substituted into the dosage association model to determine the dosage prediction adjustment factor.

2. The wastewater treatment method based on anaerobic bacteria according to claim 1, characterized in that, When determining the initial dosage based on the first set of concentration values, the second set of concentration values, the third set of concentration values, the fourth set of concentration values, and the average suspended solids concentration, the following steps are included: Determine whether there is an intersection between the first set of concentration values ​​and the second set of concentration values, and whether there is an intersection between the third set of concentration values ​​and the fourth set of concentration values; If so, construct a set of suspended solids concentrations based on the intersection values, determine the average concentration of the set of suspended solids concentrations, and determine the average concentration of the average concentration and the average of the average suspended solids concentrations as the target suspended solids concentration; If not, merge the first concentration value set and the second concentration value set to construct the fifth concentration value set, and merge the third concentration value set and the fourth concentration value set to construct the sixth concentration value set. Obtain the first average concentration value of the fifth concentration value set and the second average concentration value of the sixth concentration value set, and determine the average of the first average concentration value, the second average concentration value, and the average of the average suspended solids concentration as the target suspended solids concentration. The initial dosage is determined based on the target suspended solids concentration.

3. The wastewater treatment method based on anaerobic bacteria according to claim 2, characterized in that, Determining the initial dosage based on the target suspended solids concentration includes: A first preset target suspended solids concentration and a second preset target suspended solids concentration are preset, wherein the first preset target suspended solids concentration is greater than the second preset target suspended solids concentration; A first preset initial dosage, a second preset initial dosage, and a third preset initial dosage are preset, wherein the first preset initial dosage is greater than the second preset initial dosage, and the second preset initial dosage is greater than the third preset initial dosage; When the target suspended solids concentration is greater than the first preset target suspended solids concentration, the first preset initial dosage is determined as the initial dosage. When the target suspended solids concentration is less than or equal to the first preset target suspended solids concentration and greater than or equal to the second preset target suspended solids concentration, the second preset initial dosage is determined as the initial dosage. When the target suspended solids concentration is less than the second preset target suspended solids concentration, the third preset initial dosage is determined as the initial dosage.

4. The wastewater treatment method based on anaerobic bacteria according to claim 3, characterized in that, When acquiring environmental characteristic parameters of the wastewater pond and constructing a characteristic parameter series, comparing the characteristic parameter series with a standard characteristic parameter series, and determining whether to adjust the initial dosage based on the comparison results, the process includes: Obtain the standard feature parameter sequence corresponding to the feature parameter sequence; When all environmental characteristic parameters in the characteristic parameter sequence are equal to the standard environmental characteristic parameters in the standard characteristic parameter sequence, it is determined that the initial dosage should not be adjusted, and the wastewater treatment is completed by adding the initial dosage to the wastewater tank; otherwise, it is determined that the initial dosage should be adjusted.

5. The wastewater treatment method based on anaerobic bacteria according to claim 4, characterized in that, When comparing the predicted dosing adjustment factor with historical datasets and determining the dosing target adjustment factor based on the comparison results, the following steps are included: The historical dataset includes several sets of historical difference feature parameters and several historical injection prediction adjustment factors, with each set of historical difference feature parameters corresponding to a historical injection prediction adjustment factor. When a historical differential feature parameter set exists in the historical dataset that is consistent with the differential feature parameter set, the historical injection prediction adjustment factor corresponding to the historical differential feature parameter set is obtained. If the corresponding historical injection prediction adjustment factor is equal to the injection prediction adjustment factor, the injection prediction adjustment factor is determined as the injection target adjustment factor. Otherwise, the historical dataset and the differential feature parameter set are clustered to determine a cluster dataset, and the mean of the historical injection prediction adjustment factors in the cluster dataset is determined as the injection target adjustment factor. When there is no historical difference feature parameter set in the historical dataset that matches the difference feature parameter set, the addition prediction adjustment factor is determined as the addition target adjustment factor.

6. The wastewater treatment method based on anaerobic bacteria according to claim 5, characterized in that, When adjusting the initial dosage based on the dosage target adjustment factor, the following is included: The adjusted initial dosage is the product of the initial dosage and the dosage target adjustment factor.

7. A wastewater treatment system based on anaerobic bacteria, used for applying the wastewater treatment method based on anaerobic bacteria as described in any one of claims 1-6, characterized in that, include: The first processing module is configured to divide the sewage tank into several sewage detection areas, obtain the suspended solids concentration of each sewage detection area, compare the suspended solids concentration with the standard suspended solids concentration, and determine the initial dosage of anaerobic bacteria based on the comparison results. The second processing module is configured to acquire environmental characteristic parameters of the sewage tank and construct a characteristic parameter series, compare the characteristic parameter series with a standard characteristic parameter series, and determine whether to adjust the initial dosage based on the comparison result. The dosing determination module is configured to, when it is determined that the initial dosing amount should be adjusted, establish a dosing association model based on the environmental dataset, extract the environmental feature parameters that are different, determine the dosing prediction adjustment factor based on the environmental feature parameters that are different and the dosing association model, compare the dosing prediction adjustment factor with the historical dataset, and determine the dosing target adjustment factor based on the comparison result. The dosing adjustment module is configured to adjust the initial dosing amount according to the dosing target adjustment factor, and then add the wastewater to the wastewater tank according to the adjusted initial dosing amount to complete the wastewater treatment.

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